Videos and presentation materials from other INI events are also available.
Event  When  Speaker  Title  Presentation Material 

MESW01 
7th January 2019 11:30 to 12:30 
Warren Powell 
A Unified Framework for Stochastic Optimization in Energy
A Unified Framework for Stochastic Optimization in Energy Warren B. Powell Dept. of Operations Research and Financial Engineering Princeton University Energy systems offer a variety of forms of uncertainty that have to be accommodated to ensure a reliable source of power. The modeling of these sequential decision problems under uncertainty has lacked the kind of canonical framework long enjoyed by deterministic problems. I will introduce a modeling framework that is completely general, which involves three mathematical challenges: 1) machine learning (there are up to five classes of learning problems), 2) uncertainty modeling, and 3) designing policies, which are functions for making decisions. There are two fundamental strategies for creating policies, each of which further divides into two subclasses, creating four classes of policies. These four (meta)classes of policies are universal, in that any method used to solve a sequential decision problem will be drawn from this set. The four classes are illustrated in the context of several applications in energy systems. An energy storage application is then used to demonstrate that each of the four classes of policies might be best depending on the characteristics of the data. 

MESW01 
7th January 2019 13:30 to 14:30 
Andrew Haslett 
Creating user value through mathematics – the challenge of hidden states
Energy systems are large complex, and expensive, often significantly regulated and delivered through policy interventions. They are paid for through user charges, supported by taxation. Moving away from fossil fuels creates new systems challenges to meet user needs. Understanding these needs is an important element in meeting them, as the supply paradigm changes.Energy use is incidental to daily life – visiting friends, going to work, eating, keeping clean and comfortable etc are the things that matter to users. Control has a critical part to play in managing large loads such as vehicle charging or space heating. How do we understand the user intent behind the energy use and represent it in our mathematics?There are two kinds of hidden states in energy use systems – physical and psychological states. Control systems have direct impact on physical states, and psychological states through the user experience. This talk considers the functional needs of the user, their need for agency and the transaction cost from their perspective of engaging with the control systems for their house or car. It does not consider consumer segmentations on functional, affective and symbolic dimensions. Although in principle, hidden physical states can be discovered by measurement, often this is not practical.Control of heating systems and vehicle charging should aim to deliver satisfied users at lowest system cost. Although the talk will not cover in detail how to estimate current supply side state and forecast its coevolution with aggregate demand over the control period, it will consider in general terms how this might interact with user needs and willingness to pay.The talk will not cover mathematical solutions to the challenges. It is intended to illuminate the realworld problems that will require advanced mathematics to deliver effective solutions.


MESW01 
7th January 2019 14:30 to 15:30 
Patrick Panciatici 
(R)evolution of large electrical systems: Needs and Challenges
Historical power systems are emblematic examples of system of systems. Now, we are living a major evolution and perhaps a revolution in electrical grids. The term “smart grid” is used everywhere without a very precise definition. The concept of cyberphysical System of Systems seems a good framework to capture the essence of this (r)evolution. The “cyber” layer is going to play a key role in the system reliability. Indeed, more and more controls are embedded in subsystems which become “intelligent” and partially autonomous. The system behavior will be imposed by the interactions between these “intelligent” agents driven by local pieces of software rather than by physical laws. Different examples showing this trend will be presented from synchronization of inverters to aggregated game for demand response management. We must pay attention; possible negative impacts could occur when a certain critical level of penetration of new devices and processes will be reached. It is not easy, we must review our historical approach in order to specify behaviors which were yesterday imposed by physical laws and didn’t need any specification and which will be tomorrow defined by software in local controls. 

MESW01 
7th January 2019 16:00 to 17:00 
Hungpo Chao 
Electricity market reform to enhance the energy market pricing mechanism: observations from PJM
Electricity market reform to enhance the energy and reserve pricing mechanism: Observations from PJM by Hungpo Chao Abstract For more than 20 years, the PJM wholesale markets have successfully worked to promote competition, produce stable energy prices and attract competitive resource investments to ensure efficient and reliable operations. However, in recent years, the PJM markets have been undergoing a significant transition. While such transitions have also occurred elsewhere, each has resulted in some unique challenges. This paper examines issues regarding efficient price formation in the energy and reserve markets under nonconvex. In principle, with nonconvexity, no market clearing prices exist without side payments. In a poolbased wholesale electricity market, one of the greatest challenges unmatched in scale and complexity is that in the dayahead and realtime markets, after running a mixed integer programming model for solving a security constrained economic commitment and dispatch problem to determine the market allocations, a pricing model is employed to determine the market clearing prices and side payments in ways that must promote economic efficiency, consistent incentives and revenue sufficiency. One of the most severe limitations of the current pricing mechanism (locational marginal pricing or LMP) is that LMP is not incentive compatible. This limitation has caused adverse effects in operations and investments. Building on the classic Lagrangian dual formulation, this paper extends the existing pricing method in a way that is dominant strategy incentive compatible in a competitive market with a large number of independent suppliers, and like a VickeryClarkGrove mechanism, truthful revelation would become a dominant strategy. The convex hull pricing method or called the extended LMP, is a wellknown case which yields the minimum uplift. Moreover, integer relaxation is a computationally practical implementation that ensures incentive compatibility producing generally good, and often exact, approximations to ELMP solutions if the cost functions are homogeneous of degree one. As market continues to evolve with flattening demand growth, flattening supply curves with low marginal costs and penetration of renewable resources with zero marginal cost, nonconvex conditions will become growingly important. A key advantage of enhanced pricing mechanism is that it would form price signals in ways that would foster economic efficiency in operations and investments, demand participation and market innovation. 

MESW01 
8th January 2019 09:00 to 10:00 
Ben Godfrey  Market design for flexible distribution networks  
MESW01 
8th January 2019 10:00 to 11:00 
Gilles Louppe  Automated parameter inference and data modelling with deep learning  
MESW01 
8th January 2019 11:30 to 12:30 
Javad Lavaei 
Computational Methods for Nonlinear Power Operational Problems: Convex Reformulations and NearLinear Time Algorithms
Coauthors: Somayeh Sojoudi (UC Berkeley), Richard Zhang (UC Berkeley), Salar Fattahi (UC Berkeley), Igor Molybog (UC Berkeley), Ming Jin (UC Berkeley), SangWoo Park (UC Berkeley)In this talk, we will study a set of nonlinear power optimization and decisionmaking problems, namely power flow, optimal power flow, state estimation and topology error detection. We will propose different conic relaxation and approximation techniques to solve these nonconvex problems. We will prove that such conic problems could be solved in near linear time due to intrinsic properties of realworld power networks. We will offer case studies on systems with as high as 14,000 nodes.


MESW01 
8th January 2019 13:30 to 14:30 
Juan Miguel Morales González 
Electricity demand forecasting and bidding via datadriven inverse optimization
A method to predict the aggregate demand of a cluster of priceresponsive consumers of electricity is discussed in this presentation. The priceresponse of the aggregation is modelled by an optimization problem whose defining parameters represent a series of marginal utility curves, and minimum and maximum consumption limits. These parameters are, in turn, estimated from observational data using an approach inspired from duality theory. The resulting estimation problem is nonconvex, which makes it very hard to solve. In order to obtain good parameter estimates in a reasonable amount of time, we divide the estimation problem into a feasibility problem and an optimality problem. Furthermore, the feasibility problem includes a penalty term that is statistically adjusted by cross validation. The proposed methodology is datadriven and leverages information from regressors, such as time and weather variables, to account for changes in the parameter estimates. The estimated priceresponse model is used to forecast the power load of a group of heating, ventilation and air conditioning systems, with positive results. We also show how this method can be easily extended to be used for demandside bidding in electricity markets.


MESW01 
8th January 2019 14:30 to 15:30 
Anna Scaglione 
On modeling dispatchable loads in grid operation: the good, the bad and the ugly
The past ten years of research had produced a variety of models for managing flexible loads, paving the way for addressing congestion in the grid by enabling a more efficient dynamic pricing of electricity. However, real change has been hard to come by in practice. The goal of this talk is to review such models, highlighting the difference between distributed algorithms, that seek to decompose the problem, and aggregate representations that map large populations of flexible loads onto spinning reserves. The objective is to highlight the challenges that exist in transforming and remaining compatible with established retail and wholesale market practices and legacy systems and how new abstractions may be necessary to rip the benefits of flexible load.


MESW01 
8th January 2019 16:00 to 17:00 
JeanYves Le Boudec 
Realtime operation of microgrids
Coauthors: Paolone, Marione (EPFL), Reyes, Lorenzo (EPFL), Bernstein, Andrey (NREL), Wang, Cong (EPFL) Very large amounts of renewable electricity generation, combined with a large penetration of plugin electric vehicles, may cause considerable stress to electrical grids and to the system of spinning reserves. This problem can be solved by controlling the huge number of electrical resources that are located in distribution grids, such as thermal loads, stationary batteries, charging stations and curtailable power generators. However, this poses a number of new challenges in terms of online computation and scalability. In this talk we discuss how these challenges are solved by COMMELEC, a system of realtime software agents developed at EPFL and deployed in several grids. We also introduce elements of a theory about how uncertainty on power injections affects the controllability of the grid. Slides available at http://icawww1.epfl.ch/PS_files/MESW01LEB2019.pdf 

MESW01 
8th January 2019 17:00 to 18:00 
Poster session  
MESW01 
9th January 2019 09:00 to 10:00 
Rene Aid 
Optimal Electricity Demand Response Contracting
Coauthors: Dylan Possamaï (Columbia University), Nizar Touzi (Ecole Polytechnique)We address the moral hazard underlying demand response contracts in electricity markets, we formulate the interaction problem between producer and the consumer by means of a PrincipalAgent problem. The producer, acting as the Principal, is subject to the generation costs related to the level and the volatility of generation, thus accounting for the limited flexibility of production. Based on the continuoustime consumption of the Agent, representing a single consumer, she sends an incentive compensation in order to encourage him to reduce his average consumption and to improve his responsiveness defined as the volatility of his consumption. We provide closedform expression for the optimal contract that maximizes the utility of the principal in the case of linear energy valuation. We provide rationality for the form of the observed demandresponse contracts, that is a fixed premium for enrolment and a proportional price for the energy consumed. However, we show that the pre mium should be an increasing function of the duration of the demand response event. Further, we show that optimal contracting allows the system to bear more risk as the resulting consumption volatility may increase, but the corresponding risk is now optimally shared between the two actors. We calibrate of our model to publicly available data of the London demandresponse trial, and we infer that a significant increase of responsiveness can be expected by the implementation of the control of the consumption volatility. We find that the responsiveness control would lead a significant increase of the value of the producer. We examine the stability of our explicit optimal contract by performing appropriate sensitivity analysis, and show that the linear approximation of the energy value function of the consumer provides a robust approximation of the optimal contract.


MESW01 
9th January 2019 10:00 to 11:00 
Lang Tong  Towards seemless operation: a new look at interface scheduling and market operation  
MESW01 
9th January 2019 11:30 to 12:30 
Anthony Papavasiliou 
Transmission capacity allocation in zonal electricity markets We propose a novel framework for modelling zonal electricity markets, based on projecting the constraints of the nodal network onto the space of the zonal aggregation of the network. The framework avoids circular definitions and discretionary parameters, which are recurrent in the implementation and study of zonal markets. Using this framework, we model and analyze two zonal market designs currently present in Europe: flowbased market coupling (FBMC) and availabletransfercapacity market coupling (ATCMC). We develop cuttingplane algorithms for simulating FBMC and ATCMC while accounting for robustness of imports/exports to single element failures, and we conduct numerical simulations of FBMC and ATCMC for a realistic instance of the Central Western European system under 768,000 different operating conditions. We find that FBMC and ATCMC are unable to anticipate congestion of branches interconnecting zones and branches within zones, and that both zonal designs achieve similar overall cost efficiencies 0.5% difference in favour of FBMC), while a nodal market design largely outperforms both of them (5.9% better than FBMC). These findings raise the question of whether it is worth for more European countries to switch from ATCMC to FBMC, instead of advancing directly towards a nodal design. 

MESW01 
10th January 2019 09:00 to 10:00 
Florian Doerfler 
Realtime feedback optimization on the power flow manifold
I will focus on online optimization of AC power systems in closed loop. In contrast to the conventional approach where an optimal power flow solution is computed offline and online controllers enforce these setpoints, our objective is to design an adaptive feedback controller that steers the system robustly and in real time to the optimal operating point. Our methodological approach is based on online algorithms for manifold optimization that can be applied in feedback with realtime measurements and actuation. We treat the power flow equations as implicit constraints that are naturally enforced by the physics and hence give rise to the power flow manifold. Based on our theoretical results for this type of optimization problems, we propose a projected gradient descent scheme on the power flow manifold. In detailed simulation case studies we validate the performance of our algorithm and show that it reliably tracks the timevarying optimum of the underlying AC optimal power flow problem. Coauthors: Adrian Hauswirth (ETH Zurich), Saverio Bolognani (ETH Zurich), Gabriela Hug (ETH Zurich) 

MESW01 
10th January 2019 10:00 to 11:00 
Andrea Simonetto 
TimeVarying Optimization: Algorithms and Applications in Power Systems
Continuously varying optimization programs have appeared as a natural extension of timeinvariant ones when the cost function, the constraints, or both, depend on a time parameter and change continuously in time. This setting captures relevant control, signal processing, and machine learning problems. Recently, running and predictioncorrection methods have been put forward to set up iterative algorithms that sample the continuouslyvarying optimization program at discrete time steps track the optimizer(s) trajectory while it evolves in time up to an asymptotical error bound.In this talk, we will review current stateoftheart algorithms in timevarying optimization, with a special emphasis on applications in power grids. We will touch upon timevarying AC optimal power flow problems, realtime optimization of aggregations of distributed energy resources, as well as dynamic distribution state estimation.


MESW01 
10th January 2019 11:30 to 12:30 
Emiliano Dall'anese 
Feedbackbased online algorithms for timevarying optimization: theory and applications in power systems
The talk focuses on the synthesis and analysis of online algorithmic solutions to control systems or networked systems based on performance objectives and engineering constraints that may evolve over time. Particular emphasis is given to applications in power systems operations and control. The timevarying optimization formalism is leveraged to model optimal operational trajectories of the systems, as well as explicit local and networklevel constraints. The design of the algorithms then capitalizes on an online implementation of primaldual projectedgradient methods; the gradient steps are, however, suitably modified to accommodate actionable feedback in the form of measurements from the network  hence, the term feedbackbased online optimization. By virtue of this approach, the resultant running algorithms can cope with model mismatches in the algebraic representation of the system states and outputs, they avoid pervasive measurements of exogenous inputs, and they naturally lend themselves to a distributed implementation. Under suitable assumptions, Qlinear convergence to optimal solutions of a timevarying convex problem is shown. On the other hand, under a generalization of the MangasarianFromovitz constraint qualification, sufficient conditions are derived for the running algorithm to track a KarushKuhnTucker point of a timevarying nonconvex problem. Examples of applications in power systems will be provided. Joint work with: A. Simonetto, Y. Tang, A. Bernstein, and S. Low. 

MESW01 
10th January 2019 13:30 to 14:30 
Andy Sun  A new distributed algorithm for nonconvex network flow problems with convergence guarantees  
MESW01 
10th January 2019 14:30 to 15:30 
Pär Holmberg 
Central versus SelfDispatch in Electricity Markets In centralized markets, producers submit detailed cost data to the dayahead market, and the market operator decides how much should be produced in each plant. This differs from decentralized markets that rely on selfcommitment and where producers send less detailed cost information to the operator of the dayahead market. Ideally centralized electricity markets would be more effective, as they consider more detailed information, such as startup costs and noload costs. On the other hand, the bidding format is rather simplified and does not allow producers to express all details in their costs. Moreover, due to uplift payments, producers have incentives to exaggerate their costs. As of today, US has centralized wholesale electricity markets, while most of Europe has decentralized wholesale electricity markets. The main problem with centralized markets in US is that they do not provide intraday prices which can be used to continuously update the dispatch when the forecast for renewable output changes. Intraday markets are more flexible and better adapted to deal with renewable power in decentralized markets. Iterative intraday trading in a decentralized market can also be used to sort out coordination problems related to nonconvexities in the production. The downside of this is that increased possibilities to coordinate increase the risk of getting collusive outcomes. Decentralized dayahead markets in Europe can mainly be improved by considering network constraints in more detail. 

MESW01 
10th January 2019 16:00 to 17:00 
Sean Meyn 
Irrational Agents and the Power Grid
For decades power systems academics have proclaimed the need for real time prices to create a more efficient grid. The rationale is economics 101: proper price signals will lead to an efficient outcome. In this talk we will review a bit of economics 101; in particular, the definition of efficiency. We will see that the theory supports the realtime price paradigm, provided we impose a particular model of rationality. It is argued however that this standard model of consumer utility does not match reality: the products of interest to the various "agents" are complex functions of time. The product of interest to a typical consumer is only loosely related to electric power  the quantity associated with price signals. There is good news: an efficient outcome is easy to describe, and we have the control technology to achieve it. We need supporting market designs that respect dynamics and the impact of fixed costs that are inherent in power systems engineering, recognizing that we need incentives on many timescales. Most likely the needed economic theory will be based on an emerging theory of efficient and robust contract design.


MESW01 
10th January 2019 17:00 to 18:00 
Orcun Karaca 
CoreSelecting Mechanisms in Electricity Markets
Previous work on electricity market auctions considers the payasbid and the locational marginal pricing (LMP) mechanisms. In both mechanisms, generators can bid strategically to influence their profits since these mechanisms do not incentivize truthful bidding. As an alternative, under the VickreyClarkeGroves mechanism, truthful bidding is the dominantstrategy Nash equilibrium. Despite having this theoretical virtue, coalitions of participants can influence the auction outcome to obtain higher collective profit. In this talk, we characterize the exact class of coalitionproof mechanisms as the coreselecting mechanisms. In addition to being coalitionproof, we show that these mechanisms generalize the economic rationale of the LMP mechanism. Namely, these mechanisms are the exact class of mechanisms that ensure the existence of a competitive equilibrium in linear/nonlinear prices. This implies that the LMP mechanism is also coreselecting, and hence coalitionproof. In contrast to the LMP mechanism, coreselecting mechanisms exist for a broad class of electricity markets, such as ones involving nonconvex costs and nonconvex constraint sets. In addition, they can approximate truthfulness without the pricetaking assumption of the LMP mechanism. Finally, we show that they are also budgetbalanced. Our results are verified with case studies based on optimal power flow test systems and the Swiss reserve market.


MESW01 
11th January 2019 09:00 to 10:00 
Clemence Alasseur 
A meanfield game model for management of distributed storages for the power system
We consider a stylized model for a power network with distributed local power generation and storage. This system is modeled as a network connection of a large number of nodes, where each node is characterized by a local electricity consumption, has a local electricity production (e.g. photovoltaic panels), and manages a local storage device. Depending on its instantaneous consumption and production rate as well as its storage management decision, each node may either buy or sell electricity, impacting the electricity spot price. The objective at each node is to minimize energy and storage costs by optimally controlling the storage device. In a noncooperative game setting, we are led to the analysis of a nonzero sum stochastic game with N players where the interaction takes place through the spot price mechanism. For an infinite number of agents, our model corresponds to an Extended MeanField Game (EMFG). We are able to compare this solution to the optimal strategy of a central planner and in a linear quadratic setting, we obtain and explicit solution to the EMFG and we show that it provides an approximate Nashequilibrium for Nplayer game.


MESW01 
11th January 2019 10:00 to 11:00 
Simon Tindemans 
Optimal dispatch of heterogeneous batteries to maximise security of supply
Coauthors: Michael Evans (Imperial College London), David Angeli (Imperial College London). We consider the problem of dispatching a fleet of heterogeneous batteries (i.e. energyconstrained generators) to prevent or minimise power shortage scenarios. In the general case on which nothing is known about future power requirements, three significant results are derived. First, a greedy policy exists that uniquely maximises the time until the fleet is first unable to supply demand. This policy implicitly establishes a `feasible set’ of power requests that can be satisfied by the fleet. Second, an analytical transformation is presented that expresses this feasible set in a graphical form instead of a procedural form (i.e. by invoking the policy). The graphical representation also provides a measure of the flexibility penalty due to heterogeneity. Third, it is shown that the policy can be extended to handle scenarios with unavoidable power shortages, in which case it minimises the energy not supplied. The fact that the greedy policy results in bestcase securityof supply performance suggests it is suitable to be used as a reference policy for battery dispatch within system adequacy studies. We present a discrete time algorithm that is tailored for this use case and show results for a Great Britain case study.


MESW01 
11th January 2019 11:30 to 12:30 
Meng Wang 
Highdimensional data analytics using lowdimensional models in power systems
Phasor Measurement Units and smart meters provide finegrained measurements to enhance the system visibility to the operators and reduce blackouts. The recent wealth of data is revolutionizing the conventional modelbased power system monitoring and control to a modern datadriven counterpart. One recent research interest is to develop computationally efficient datadriven methods to convert data into information. This first part of the talk discusses our proposed missing data recovery and error correction methods for synchrophasor data. The low data quality currently prevents the implementation of synchrophasordatabased realtime monitoring and control. This second half of the talk discusses our proposed privacypreserving data collection framework for smart meters. We developed load pattern extraction methods from highly noisy and quantized smart meter data such that the estimated load pattern is only accurate for the operator, and the information is obfuscated to a cyber intruder with partial measurements. The common theme of the two projects is to exploit the intrinsic lowdimensional structures in the data to develop fast algorithms for nonconvex problems with analytical performance guarantees. 

MESW01 
11th January 2019 13:30 to 14:30 
Pierre Gaillard 
Bandit algorithms for power consumption control
We are interesting in optimizing price signals sent by an electricity provider to its customers so has to modify their electricity consumption. We formulate this problem as a sequential problem in which the electricity provider send signals and sequentially observes corresponding feedback. The mathematical theory of bandits will be adapted to this exploration  exploitation problem. This is a joint work with Margaux Brégère, Gilles Stoltz and Yannig Goude 

MESW01 
11th January 2019 14:30 to 15:30 
John Moriarty, Ana Busic, Steven Low, Louis Wehenkel, Pierre Pinson  Wrapup discussion session  
OFBW42 
23rd January 2019 10:00 to 10:10 
Jane Leeks, David Abrahams  Welcome and Introduction  
OFBW42 
23rd January 2019 10:10 to 10:20 
John Moriarty  Outline and Summary of INI Research Programme  Mathematics of Energy Systems  
OFBW42 
23rd January 2019 10:20 to 10:55 
Andy Philpott  Planning a 100% Renewable Electricity System  
OFBW42 
23rd January 2019 10:55 to 11:30 
James Cruise  Modelling Flexibility for Future Networks  
OFBW42 
23rd January 2019 11:50 to 12:25 
Damian Giaouris  Decarbonisation, Decentralisation and Digitisation of Energy through Hybrid Storage Systems  
OFBW42 
23rd January 2019 12:25 to 12:30 
Patrick Panciatici  (R)evolution of Large Electrical Systems  
OFBW42 
23rd January 2019 12:30 to 12:35 
Michael Coulon  Wind Park Valuation and Risk Management in Germany  
OFBW42 
23rd January 2019 12:35 to 12:40 
Valentin Courgeau  Continuoustime Modelling of Energy Networks  
OFBW42 
23rd January 2019 12:40 to 12:45 
Paulina Rowinska  Blowing in the Wind  
OFBW42 
23rd January 2019 12:45 to 12:50 
Thomas Marge  Integrated Offshore Wind Farm Design: Optimising Micrositing and Cable Layout Simultaneously  
OFBW42 
23rd January 2019 12:50 to 12:55 
Tommaso Nesti  Emergent Failures and Cascades in Power Grids: A Large Deviations Approach  
OFBW42 
23rd January 2019 14:00 to 14:30 
Cathy McClay  Industry Talk: The Electricity System Operator Perspective  
OFBW42 
23rd January 2019 14:30 to 15:00 
Alastair Davies  Renewable Energy Focus: Calculating the Carbon Content of Power Imports  
OFBW42 
23rd January 2019 15:00 to 15:30 
Jonas Ströjby  An Industry Perspective on Managing Flexibility  
OFBW42 
23rd January 2019 15:50 to 16:20 
Iain Miller  Future Energy Systems Challenges  a Distribution Operator Perspective  
OFBW42 
23rd January 2019 16:20 to 17:00 
David Newbery  Panel Discussion  can we/should we do 100% Renewables?  
MES 
11th February 2019 13:30 to 16:00 
Research Tracks  Pierre Pinson and Yanning Goude  
MES 
20th February 2019 15:00 to 16:00 
Said Hamadene 
Zerosum optimal switching games motivated by energy applications
\author{S.Hamadene, LMM, Le Mans University, France.\\
Jww: R.Martyr (QMUL) and J.Moriary (QMUL).}
\begin{abstract}
In this paper we study continuoustime twoplayer zerosum optimal switching games on a finite horizon. Using the theory of doubly reflected backward stochastic differential equations (DRBSDE) with interconnected barriers, we show that this game has a value and an equilibrium in the players' switching controls.
\end{abstract}


MES 
25th February 2019 09:30 to 12:00 
Stephen Haben  Data Analytics for Short Term Operation  
MES 
25th February 2019 14:00 to 16:00 
Assisting control room operators with artificial intelligence : Antoine Marot  
MES 
26th February 2019 09:30 to 10:30 
Pierre Gaillard  Forecasting electricity consumption by aggregating forecasts  
MES 
26th February 2019 10:40 to 12:00 
Robust and online learning with the BOA algorithm : Olivier Wintenberger  
MES 
27th February 2019 09:30 to 12:00 
Qiwei Yao  Multiple forecasting based on time series PCAs  
MES 
27th February 2019 13:30 to 16:00 
Jethro Browell  Aspect of High Dimensional Energy Modelling and Forecasting  
MES 
28th February 2019 09:30 to 10:30 
Generalised additive models for electricity demand forecasting : Matteo Fasiolo  
MES 
28th February 2019 10:30 to 12:00 
Florian Ziel  Marginal copula scores for multivariate foecasting evaluation  
MES 
28th February 2019 13:30 to 17:00 
Hierarchical probabilistic forecasting of electricity demand with smart meter data : Souhaib Ben Taieb  
MES 
4th March 2019 10:00 to 12:00 
Janusz Bialek  Power System Operation  
MES 
4th March 2019 14:00 to 16:00 
Janusz Bialek  Power System Modeling  
MESW02 
18th March 2019 09:45 to 10:45 
David Newbery 
Market and regulatory design for renewables dominated systems A lowcarbon electricity system has a dominance of plant with high fixed costs and low variable costs, backed up with flexible controllable generation. In a liberalised market all required new investment will need to cover its full cost, necessitating payments for capacity, energy and quality of service to deliver reliability (longterm adequacy) and security of supply (short term resilience to shocks). Their value varies over time and space. Current liberalised markets lack futures markets and proper spatial signals to guide investment. Networks have always had high fixed, very low variable costs and longrun marginal costs well below average costs, creating challenges for setting network tariffs. Consumers need to pay for these generation and network services in ways that are efficient, equitable and acceptable, in a system that offers a greater range of scale and location (voltage level) of options for delivering the three services of capacity, energy and quality of servic e, requiring more careful tariff design than hitherto. ICT can help deliver but cannot avoid the tensions between efficiency, equity and acceptability. The talk will identify the challenges, the theoretical solutions drawing on the mature subject of public economics, and possible solutions. 

MESW02 
18th March 2019 11:15 to 12:00 
Natalia Fabra 
Competition among Renewables
We model strategic behavior of renewable suppliers when competing in electricity auctions. We introduce renewables' intermittency by assuming that firms' available capacities are random and private information. In equilibrium, bid functions are a smooth decreasing function of firms' realized capacities. Thus, at times when there is more renewables' availability, supply functions shift outwards and downwards, leading to reductions in the market price. An increase in correlation between firms' available capacities strengthens competition nonmonotonically. Keywords: electricity, competition, auctions.


MESW02 
18th March 2019 12:00 to 12:45 
Bert Willems 
Investments in flexible generation capacity in an energyonly market A decarbonized energy system will require sufficient investments in flexible generation capacity. The goal of this paper is to study how market design affects investments in flexible generation capacity. If markets are perfectly competitive, production costs are convex, and demand is perfectly predictable, then independent energyonly market (one for each hour of operation) will lead to efficient market outcomes both in the shortrun (market operation) and in the longrun (investment levels and levels of flexibility). We will relax the assumption of convex production costs and predictable demand and analyze first whether small competitive investors have the right incentives to invest in flexible generation. In a second step we intend to derive equilibrium investment levels. 

MESW02 
18th March 2019 13:45 to 14:30 
Richard Green 
Optimal storage, investment and management under uncertainty  It is costly to avoid outages!
We show how electricity storage is operated optimally when the load net of renewable output is uncertain. We estimate a diurnal Markovprocess representation of this residual load in Germany in 2011 to 2015 on an hourly basis and design a simple dynamic stochastic electricity system model with nonintermittent generation technologies and storage. We derive the optimal storage, generator output and capacity levels. If storage capacity replaces some generation capacity, the optimal storage strategy must balance arbitrage (between periods of high and low marginal cost) against precautionary storage to ensure energy is available throughout a long peak in net demand. We then solve the model numerically under realistic conditions and compare the results to perfect foresight findings. We show that a perfect foresight model would overestimate the costsaving potential of energy storage by 18%, as it takes up arbitrage opportunities that ignore the need for precautionary storage.


MESW02 
18th March 2019 14:30 to 15:15 
Pär Holmberg 
Capacity mechanisms and the technology mix in competitive electricity markets The paper is coauthored with Robert Ritz at Judge Business School and EPRG, University of Cambridge. 

MESW02 
18th March 2019 15:45 to 16:30 
Eddie Anderson 
The role of submodularity in capacity auctions
We consider a capacity auction in which multiple supplying firms offer bids, and an agent, the buyer, selects which bids to accept. Payments may depend on the set of bids accepted. We consider the role played by a submodularity property for the social welfare function in terms of the set of participating firms. We show how submodularity leads to good properties for the equilibrium. We illustrate this through discussion of a case where the buyer faces uncertain demand and there are separate costs incurred by the suppliers for making capacity available (reservation costs) and for delivering against the required demand (execution costs). We demonstrate that when marginal costs are constant the submodularity property holds, and in equilibrium each supplier makes a profit equal to their marginal contribution and the overall expected welfare is maximized. Eddie Anderson (Lusheng Shao and Bo Cheng)


MESW02 
18th March 2019 16:30 to 17:15 
Hannes Weigt 
Long Term Electricity Market Design: Pricing Quality?
Future electricity market design needs to address a set of challenges to provide for efficient investment, supply and consumption decisions. The objective of this paper is to sketch those problems and challenges embedded along the electricity value chain and identify how they are altered when shifting from a predominantly centralized nuclear and fossil system towards a system with a mix of central and decentralized elements as well as a high share of intermittent renewable generation. Of particular concern is the mismatch of incentive structures (i.e. between highly dynamic wholesale markets setting incentives for large scale investors and average tariff structures on the end user side setting incentives for prosumers) as well as the security of supply dimension (i.e. shifting from a public good character within regulated systems towards a potential private good in a system characterized by smart control structures). Based on those structures we aim to derive potential market and price setting designs suited for a future electricity market. Frank C. Krysiak and Hannes Weigt


MESW02 
19th March 2019 09:00 to 10:00 
Richard O'Neill 
Incentives, Regulation and Analysis for Investments in ISO Markets
The presentation will examine the history of US Independent System Operator (ISO) markets, mistakes that were made and corrected, how they are regulated, and how theoretical sustainable economic efficiency can be achieved. In addition, we examine how efficient transmission planning in theory is achieved and the problems associated with implementing it. Lastly, we will address the critical role optimization software and approximations must play to achieve these objectives.


MESW02 
19th March 2019 10:00 to 10:45 
Sarah Ryan 
Assessing Potential Benefits of Increased GasElectric Coordination by Stochastic Optimization
Natural gas is the single largest fuel source for electricity generation in the US. Its share of electric energy generated is expected to increase through 2050 while the shares attributed to coal and renewable sources approximately swap their values. However, electric power generation accounts for only about a third of gas consumption and this fraction is expected to remain nearly constant. Despite some recent regulatory changes, the markets for gas and electricity are independent and not well coordinated. This lack of coordination combined with uncertainty associated with variable renewable generation creates risks for both the generators that procure gas by interruptible contracts and the system operators charged with maintaining both reliability and low wholesale electricity prices. We formulate stochastic programming models for daily unit commitment and dispatch with uncertain wind generation to represent operation both within the current uncoordinated markets and under a hypothetical integration of the gas and electricity systems. Comparison of cost and reliability metrics across models allows an estimation of the potential benefits of increased coordination between the two systems. Sarah Ryan and Dan Hu 

MESW02 
19th March 2019 11:15 to 12:00 
Ramteen Sioshansi 
Merchant Storage Investment in a Restructured Electricity Industry
Restructuring and liberalisation of the electricity industry creates opportunities for investment in energy storage, which could be undertaken by a profitmaximising merchant storage operator. Because such a firm is concerned solely with maximising its own profit, the resulting storageinvestment decision may be socially suboptimal (or detrimental). This paper develops a bilevel model of an imperfectly competitive electricity market. The modelling framework assumes electricitygeneration and storageoperations decisions at the lower level and storage investment at the upper level. Our analytical results demonstrate that a relatively high (low) amount of market power in the generation sector leads to low (high) storagecapacity investment by the profitmaximising storage operator relative to a welfare maximiser. This can result in net social welfare losses with a profitmaximising storage operator compared to a nostorage case. Moreover, there are guaranteed to be net social welfare losses with a profitmaximising storage operator if the generation sector is sufficiently competitive. Using a charge on generation ramping between off and onpeak periods, we induce the profitmaximising storage operator to invest in the same level of storage capacity as the welfaremaximising firm. Such a ramping charge can increase social welfare above the levels that are attained with a welfaremaximising storage operator. Afzal S. Siddiqui, Ramteen Sioshansid and Antonio J. Conejo 

MESW02 
19th March 2019 12:00 to 12:45 
Ben Hobbs 
Sources and Implications of Inaccuracies in Capacity Credit Calculations: A Static Analysis of Electric Generation Capacity Markets A static (single shot) model of capacity investments for thermal and renewable resources under energy and capacity markets as well as energy price caps is considered. Under assumptions of risk neutrality and continuous capacity investment variables, it is proven that there exists a capacity (in $/MW capacity credit/yr) and a set of capacity credits by generation type (MW credit/MW nameplate capacity) that supports the most efficient mix of capacity types. However, capacity credits are often set for political reasons, fail to reflect dynamics of levels of penetration upon the marginal contribution of capacity to reliability, or are estimated considering inadequate sample sizes of variable energy output. Through market simulations for an ERCOTlike system, the genmix and efficiency impacts of credits deviating from firstbest levels are calculated for various scenarios of erroneous credits. (Coauthor: Cynthia Bothwell, US Dept. Energy, Office of Energy Efficiency & Renewable Energy) 

MESW02 
19th March 2019 13:45 to 14:30 
Claudia Sagastizabal 
A TwoStage Model for Planning Energy Investment under Uncertainty
We consider riskaverse stochastic programming models for the Generation and Expansion Planning(GEP) problem with investment decisions in the first stage and generation variables of recourse, decided in a second stage. The resulting problem is coupled both along scenarios and along power plants. To achieve decomposition, we combine the Progressive Hedging approach in [1] with a suitable duplication of variables [2]. The resulting nonsmooth dual function can then be solved with an inexact dual proximal bundle method, as in [3]. The procedure defines a primaldual sequence that, under reasonable assumptions, is shown to converge to a primaldual solution of the original problem. Claudia Sagastizabal and F. Atenas 

MESW02 
19th March 2019 14:30 to 15:15 
Anthony Papavasiliou 
Market Design Considerations for Scarcity Pricing: A Stochastic Equilibrium Framework
We develop a stochastic equilibrium framework for analyzing variations of twosettlement system in which energy and reserve capacity is traded in a dayahead market followed by a realtime market. The framework is aimed at analyzing the impact of various shortterm market design decisions on the remuneration of reserve capacity under operating reserve demand curves. The proposed framework accounts for risk aversion, realtime uncertainty, and a relaxed representation of unit commitment decisions. The framework can be used for analyzing the implication of various market design choices on the backpropagation of realtime prices. These choices include (i) the presence or absence of a realtime reserve capacity market, (ii) the simultaneous or sequential clearing of reserves and energy in dayahead markets, and (iii) the presence or absence of virtual bidding. We propose a decomposition heuristic for solving the resulting nonconvex equilibrium problem. We apply our framework for the analysis of market design choices on the remuneration of reserves in the Belgian electricity market.


MESW02 
19th March 2019 15:45 to 16:30 
Jong Shi Pang 
Twostage Stochastic Programming with Linearly Biparameterized Quadratic Recourse
This paper studies the class of twostage stochastic programs (SP) with a linearly biparameterized recourse function defined by a convex quadratic program. A distinguishing feature of this new class of stochastic programs is that the objective function in the second stage is linearly parameterized by the firststage decision variable, in addition to the standard linear parameterization in the constraints. Inspired by a recent result that establishes the differenceofconvexity (dc) property of such a recourse function, we analyze the almostsure subsequential convergence of a successive sample average approximation (SAA) approach combined with the differenceofconvex algorithm (DCA) for computing a directional derivative based stationary solution of the overall non convex stochastic program. Under a basic setup, the analysis is divided into two main cases: one, the problem admits an explicit, computationally viable dc decomposition with a differentiable con cave component, based on which the discretized convex subproblems to be solved iteratively can be readily defined; and two, an implicit bivariate convexconcave property can be identified via a certain smoothing of the recourse function. The first case includes a strictly convex secondstage objective and a few special instances where the secondstage recourse is convex but not strictly convex. A general convex secondstage recourse function belongs to the second main case; this case requires the introduction of the notion of a generalized critical point to which the almostsure subsequential convergence of the combined SAA and DCA is established. Overall, this research provides the first step in the investigation of this class of twostage SPs that seemingly has not been, until now, the object of a focused study in the vast literature of computational twostage stochastic programming.


MESW02 
19th March 2019 16:30 to 17:15 
Luiz Augusto Barroso 
Harmonizing energy planning and market mechanisms to ensure supply adequacy in electricity markets
The objective of this talk is twofold: we
first describe multistage stochastic optimization models with a very
detailed representation of the system components that have been used to carry
out realistic generationtransmission planning studies in large systems with
strong renewable penetration. The optimization framework of these models
allows not only to extract meaningful outputs  such as probabilisticreserve
needs, cost of flexibility  as well as they can be used to factor planning
outcomes in auctions for longterm reliability products to ensure supply
adequacy. We will show that attributes of generation plants can be factored
in the procurement process of these products via primal (pricebased) or dual
(quantitybased) outcomes of the optimizationbased framework for the
planning studies.


MESW02 
20th March 2019 09:00 to 10:00 
Sonja Wogrin 
Hierarchical optimisation and equilibrium problems in electricity systems: challenges and status quo
This
talk starts off with a brief introduction to hierarchical optimisation and
equilibrium problems, and continues with a broad overview of different
applications of these types of problems within the electricity system (such
as transmission and generation expansion planning, strategic bidding in
markets and many more). We then establish the status quo of the existing
models and analyse: what level of technical detail existing models cover;
what are corresponding CPU times, model size and complexity; what are the
current methods available to solve the arising problems, and, raise the
discussion of what gets lost in translation. With the former analysis in
mind, we outline the existing lack in the literature, or better yet the
existing need to represent complex technical realities in our models. Complex
realities such as: the AC optimal power flow, or unit commitment constraints.
We then try to establish the link between the technical nature, and the
corresponding arising mathematical difficulties in the hierarchical models,
discussing issues such as nonconvexities and nonexistence of solutions. The
talk concludes by pointing out some of the most recent methodological
advances in these directions, and what still remains to be done.


MESW02 
20th March 2019 10:00 to 10:45 
Chris Dent 
Capacity markets, risk modelling and decision support
This
talk will introduce the mathematical and statistical questions associated
with running a capacity market. It will then summarise recent research on the
modelling of demand and wind generation for capacity adequacy risk assessment
in Great Britain, and on decision criteria for determining the volume to
procure. Finally, it will describe a new theory of how to run a capacity
auction including all resources including storage on a common basis. All
these topics will be illustrated using examples based on the GB system.


MESW02 
20th March 2019 11:15 to 12:00 
SteinErik Fleten 
The Effect of Capacity Payments on Peaking Generator Availability in PJM
We
study the effects of capacity payments on the strategic decisions of plant
managers for peaking units in the PJM Interconnection. We achieve this
through a structural estimation of maintenance and switching costs between
the operational state, the standby state and retirement of generating units,
using annual data from 20012016. The empirical data shows less switching
between states after the introduction of capacity remunerations in 2007. We
find that the role of peaking units has changed, with the units being
dispatched more often. In the counterfactual analysis, we find a clear
connection between the level of capacity payments and switching. We conclude
that the current level of capacity payments in PJM incentivizes peaking units
to stay in the operational state. SteinErik Fleten (with Benjamin Fram, Magne Ledsaak, Sigurd Mehl, Ola Røssum, Carl Ullrich) 

MESW02 
20th March 2019 12:00 to 12:45 
Asgeir Tomasgard 
Analysing effects of short and longterm uncertainty on capacity expansion in European electricity markets
The
EMPIRE model is a European multiscale power market model with investments
towards 2050 as well as representative hours. It is well suited to capture
operational uncertainty in generation from intermittent energy sources like
wind and sun. In the shortrun
horizon, typical uncertainty is
in load, intermittent generation and inflows to hydro reservoirs. Shortrun
sources of flexibility are regulated hydropower, storages, fossil generators
and demand response. In the long run uncertain factors include learning curves, policy uncertainty,
longterm commodity process and demand trends. In this paper we add longterm
uncertainty to the formulation. The resulting models are large scale
stochastic multistage recourse models with hundred of millions of variables.
We present both solution methods and analysis of the most important factors.
In the shortrun horizon, typical
uncertainty is in load, intermittent
generation and inflows to hydro reservoirs. Shortrun sources of flexibility
are regulated hydropower, storages, fossil generators and demand response. In
the long run uncertain factors include
learning curves, policy uncertainty, longterm commodity process and
demand trends. We look at the European level and analyze questions like to what extent the demand response potential
can facilitate an optimal transition to an European low emission power system
and how does longterm uncertainty affect the investments in renewables.


MESW02 
21st March 2019 09:00 to 10:00 
Yves Smeers 
Risk premium and stochastic equilibrium in generation capacity expansion models
Investment
in new capacities is most often based on a Weighted Average Cost of Capital
where the cost of equities is derived from the Capital Asset Pricing Model
(the cost of debt following a different logic). While a single corporate
discount rate was most often used in the past, differentiated discount rates
reflecting elements such as technology and country risks are now more used.
These introduce undesirable arbitrage phenomena in standard capacity
expansion model interpreted as market simulation models. We discuss three
types of differentiated discounting namely the standard (often based on CAPM)
exogenous discount rate, the more general stochastic discount rate and the
endogenous discount rate derived from risk functions possibly with hedging
instruments. The three approaches are cast in a unifying risk premium
equilibrium formulation where arbitrage phenomena are eliminated. The
models are of the complementarity form and can be handled through splitting
algorithms. We report numerical results for medium size problems adequate for
industrial use. Convergence is based on an (often implicit)
assumption of monotonicity that is not necessarily satisfied for endogenous
discount rates. We briefly discuss the different equilibrium that can arise
when this assumption is not satisfied.


MESW02 
21st March 2019 10:00 to 10:45 
Danny Ralph 
Risky Capacity Equilibrium Models for Risk Averse Investment Equilibria with Incomplete Markets
"Risky Capacity Equilibrium Problems” incorporate (i) risk averse investment in power plants, (ii) financial trading to hedge those investments, and (iii) strategic production in a stochastic spot market. These models concatenate shortterm electricity market (perfect competition or Cournot) with longterm investments (risk neutral or risk averse behaviour in different risk trading settings). We focus on incomplete financial markets, when not all risks can be traded, using results on “Risky Design Equilibrium Problems” and standard Nash game techniques to show existence of equilibria. Numerical results show the impact of incompleteness on equilibrium capacity and spot prices.


MESW02 
21st March 2019 11:15 to 12:00 
Michael Ferris 
Modelling 100 percent renewable electricity
Michael Ferris and Andy Philpott 

MESW02 
21st March 2019 12:00 to 12:45 
Gauthier de Maere d'Aertyrcke 
Valuation of floating price contract formulae for financial renewable PPAs
We propose a valuation methodology based on risk measure to compute the risk premium to cover new structure of financial renewable PPA, where as opposed to traditional unit contingent PPA, a part of merchant risk remains in the hand of the asset developer. Those new contract structures are currently emerging on the market: Offtaker are increasingly showing interest to share the market risk, as in systems with high RES share, the PPA might become a very poor hedge of their electricity bill (due to RES cannibalization effect). We specifically focus on contract formulae based on floating price, where the financial transfer to the Offtaker is not based on the price captured by the renewable asset but rather on a floating price, defined as the average of spot prices over a predefined time duration (e.g. yearly, monthly or daily basis). We then assess several risk mitigation strategies to lower the risk premium, namely physical (well balanced portfolio of wind, PV and battery) and/or financial (power derivatives trading).


MESW02 
21st March 2019 13:45 to 14:30 
Jalal Kazempour 
Distributionally robust chanceconstrained generation expansion planning
This talk addresses a centralized generation expansion planning problem, accounting for both long and shortterm uncertainties. The longterm uncertainty (demand growth) is modeled via a set of scenarios, while the shortterm uncertainty (wind power) is considered using momentbased ambiguity sets. In the expansion stage, the optimal units to be built are selected among discrete options. In the operational stage, a detailed representation of unit commitment constraints is considered. To make this problem tractable, we solve it in linear decision rules, and use a tight relaxation approach to covexify the unit commitment constraints. The resulting model is a distributionally robust chanceconstrained optimization, which eventually recasts as a mixedinteger secondorder cone program. We consider the IEEE 118bus test system as a case study, and explore the performance of the proposed model using an outofsample analysis.


MESW02 
21st March 2019 14:30 to 15:15 
Jacob Mays 
Asymmetric Risk and Fuel Neutrality in Capacity Markets
This paper calls into question the fuel neutrality of capacity mechanisms implemented in liberalized electricity markets. The argument relies on two assumptions likely satisfied in practice, first that investors are risk averse and second that markets in risk are incomplete. For the analysis, we develop a heuristic algorithm to solve largescale stochastic equilibrium models describing a competitive market with incomplete risk trading. Introduction of a capacity mechanism has an asymmetric effect on the risk profile of different generation technologies, tilting the resource mix toward those with lower fixed costs and higher operating costs. One implication of this result is that current market structures may be illsuited to financing lowcarbon resources, the most scalable of which have high fixed costs and nearzero operating costs. Development of new risk trading mechanisms to replace or complement current capacity obligations could lead to more efficient outcomes. Jacob Mays, David Morton and Richard O'Neill 

MESW02 
21st March 2019 15:45 to 16:30 
Golbon Zakeri 
Stochastic auctions to accommodate the future flexigrid
We will
discuss the design and performance of some stochastic auctions designed
to accommodate flexibility and hence penetration of intermittent renewable
energy generation. We will examine these auctions in the context of
competitive markets as well as oligopolies. We will also shed some light on
using such mechanisms in markets where the participants are risk averse. The
talk is based on the following literature.


MESW02 
21st March 2019 16:30 to 17:15 
Michael Hintermüller 
Generalized Nash Equilibrium Problems with Application to Spot Markets with Gas Transport
A class of noncooperative Nash equilibrium problems is presented, in which the feasible set of each player is perturbed by the decisions of their competitors via a convex constraint. In addition, for every vector of decisions, a common “state” variable is given by the solution of an affine linear equation. The resulting problem is therefore a generalized Nash equilibrium problem (GNEP). The existence of an equilibrium for this problem is demonstrated, and firstorder optimality conditions are derived under a constraint qualification. An approximation scheme is proposed, which involves the solution of a parameterdependent sequence of standard Nash equilibrium problems. An associated pathfollowing strategy based on the Nikaido–Isoda function is then proposed. Function space based numerics for parabolic GNEPs and a spotmarket model are developed.


MESW02 
22nd March 2019 09:00 to 10:00 
Andrew Wright 
Societal objectives and their impact on the electricity system of the future
Electricity is an essential to people’s wellbeing and the lifeblood of a modern economy. The societal objectives around electricity reflect the wider values of society, and these values precondition the way the electricity system is structured and governed, both today and in the future. The electricity system is changing rapidly, but societal values are usually more enduring, and will shape the ways in which the system develops. The challenge of the energy system of the future is use technology to meet the goal of decarbonisation, without undermining the reasonable expectations of society for an essential public service. This talk will look at these societal objectives, how they shape the electricity system of today and the risks and opportunities in the transition to a low carbon future.


MESW02 
22nd March 2019 10:00 to 10:45 
Goran Strbac 
Energy system decarbonisation: informing reform of energy market and regulatory framework
There is a growing need and opportunity for new emerging technologies and systems to provide flexibility in supporting a costeffective transition to a lower carbon energy system. Key results of the comprehensive analysis carried out will be presented highlighting the benefits of emerging technologies and system in providing grid support, various balancing services, system security services and option value services to deal with uncertainty. This will underline the barriers related to the present market and regulatory framework that may prevent the realization of the quantified system value of flexibility and thus weaken the business case for investment in corresponding technologies and systems. Developing fully costreflective markets and effective regulatory frameworks will therefore be necessary to ensure that the commercial incentives for investing and operating flexible technologies are aligned with the societal benefits. The importance of the wholesystem approach to future market design, strategic versus incremental investment, consumer participation and decentralisation will be discussed and a roadmap for market evolution will be presented, highlighting the importance of aligning the market design with the decarbonisation objectives.


MESW02 
22nd March 2019 11:15 to 12:00 
Afzal Siddiqui 
Strategic Storage Use in a HydroThermal Power System with Carbon Constraints
The Northeast Power Coordinating Council (NPCC) comprises American states and Canadian provinces marked by a significant penetration of variable renewable energy sources (VRES) and hydropower production. Major demand centres in New England, New York, Ontario, and Québec that are subject to stringent to stringent caps on CO2 emissions are included in the NPCC. For example, the Regional Greenhouse Gas Initiative (RGGI) mandates a 30% reduction in CO2 emissions from power plants by 2030 relative to 2020 levels, which affects generation in New England and New York. Likewise, Québec participates in the Western Climate Initiative (WCI), which aims to reduce CO2 emissions by approximately 40% by 2030 relative to 1990 levels and included Ontario until recently. Both RGGI and WCI create capandtrade (C&T) systems for CO2 emissions in which the shadow price on the binding CO2 emission constraint is the permit price that generators incur as an additional cost for their CO2 emissions. While support schemes such as feedin tariffs and the C&T system have induced an increase in VRES generation, they have also enhanced the role of energy storage, viz., by hydro reservoirs especially in Québec. In a perfectly competitive power system, storage capacity would be deployed in a socially optimal way to smooth out the fluctuations in uncontrollable VRES output. However, given the persistence of market power in the electricity industry, hydro reservoirs may be used in a strategic manner to the benefit of their proprietors. Consequently, incentives for VRES and social welfare may be detrimentally affected by such exertion of market power. In order to investigate the extent of these distortions in the NPCC and to propose policies for their mitigation, we develop a bottomup equilibrium model to quantify the welfare losses from the strategic use of hydropower reservoirs and to assess counterfactual CO2 emission caps. Coauthors: Sébastien Debia and PierreOlivier Pineau 

MESW02 
22nd March 2019 12:00 to 12:45 
Duncan Burt 
Risk and Optimization in Future Network Planning
TThe future of power network use is highly uncertainty, with the arrival of renewables and new patterns of power use, creating large uncertainties, risks and opportunities for the optimisation of future investment and development. National Grid runs an annual Network Options Assessment which applies a riskbased economics approach to optimise which investments are progressed on an annual basis. his involves modelling a complex power grid and the timing and choice of many potential investment options, totalling multiple billions of pounds over the next 30 years, to deliver an efficient and secure network. This talk sets out the challenges and key factors involved in our current optimisation process and seeks views on alternative approaches.


MESW02 
22nd March 2019 13:45 to 14:30 
Amy Wilson 
Accounting for uncertainty when using computer models as decisionsupport tools in energy system planning
Computer
models are widely used as decisionsupport tools for planning energy systems
in both industry and government. These computer models are often
computationally intensive and have highdimensional input spaces, making it
difficult to quantify the impact that different sources of uncertainty have
on model output. Without a complete picture of the effect of these
uncertainties it is difficult to take planning decisions that are robust in
the realworld. This presentation will discuss methodology for accounting for
uncertainties in computationally intensive energy planning models. Both input
uncertainty and uncertainty in the structure of the model itself will be
considered. An emulator, or statistical model of the underlying computer
model, will be used to quantify uncertainty in areas of the input space where
it has not been possible to make model runs. This emulator will be combined
with a description of the uncertainty over the input space and a description
of the structural error to quantify uncertainty in model outputs. Several
realworld examples in energy planning will be discussed, including the
modelling of wholesale electricity prices and making decisions about
renewable support schemes.


MESW02 
22nd March 2019 14:30 to 15:15 
JeanPaul Watson 
On the Rigorous Evaluation of Stochastic Approaches to Power Systems Operations While there is significant recent research on stochastic optimization approaches to power systems operations, e.g., unit commitment and economic dispatch, there are still major impediments to their adoption in practice. In our experience, developed over years of attempting to deploy such approaches, one key issue is accurate evaluation of any proposed approach, relative to existing deterministic operational methodologies. In this talk, we discuss the challenges in such evaluation, and report on a novel methodology addressing what we feel to be deficiencies with current approaches. In the talk, we focus on issues relating to data availability and segmentation, probabilistic scenario generation, and the impact of scenarios on operational performance. 

MESW02 
22nd March 2019 15:45 to 16:30 
Andy Philpott 
Longterm generation capacity expansion models in JuDGE
We
consider a multistage stochastic programming model of capacity expansion for
renewable energy in New Zealand. The model is solved using the JuDGE package
in Julia that exploits a DantzigWolfe decomposition of the problem. Andy Philpott and Anthony Downward 

MES 
9th April 2019 16:00 to 17:00 
Claudia Sagastizabal 
Kirk Fellow Lecture: Three Character Archetypes in Energy Optimisation
The management of energy systems, particularly when
transitioning to sustainable sources of electricity, requires a successful
blending of interdisciplinary work. We discuss how the frontier between pure
and applied maths becomes somewhat artificial when dealing with price signals
in energy optimisation. The presentation is organised as a story with three
main characters, Isaac Newton, JosephLouis Lagrange, and JeanJacques Moreau.


MES 
24th April 2019 10:00 to 12:00 
Research track on mechanism design at the INI  
MESW03 
29th April 2019 10:00 to 11:00 
Janusz Bialek 
Mathematics for energy systems: an engineer’s view
The presentation will contain a personal view of an engineer on the complex interactions between mathematicians and engineers, exploring the myths, tensions, and modes of collaboration. It will also present a personal view on the trends and themes shaping power system research over the last 40 years and how they involved mathematicians. The presentation will end up by showing an example of unresolved research problems that call for mathematics: making use of wealth of information provided by Phasor Measurement Units.


MESW03 
29th April 2019 11:30 to 12:30 
Adilson Motter 
Power Grids: Failures and Opportunities
A fundamental problem in electrical grids is
that the same connections that give a network its functionality can promote the
spread of failures that would otherwise remain confined. Understanding the
resulting cascading failures has been hindered by the lack of realistic
largescale modeling that can account for variable system conditions. In this
presentation, I will discuss our fullscale modeling of the U.S.South Canada
powergrid network, which allows us to characterize the set of network
components that are vulnerable to cascading failures. I will show that the
vulnerable set consists of a small but topologically central portion of the
network and that large cascades are disproportionately more likely to be
triggered by initial failures close to this set. These results elucidate
aspects of the origins and causes of cascading failures, and point to
opportunities for failure mitigation in connection with grid design and
operation.


MESW03 
29th April 2019 13:30 to 14:30 
Anupama Kowli 
SMART Planning and Operations of Grids With Renewables and Storage a.k.a. SPOReS
This talk will introduce the SPOReS project started under the Mission Innovation Smart Grids challenge in India. The goal of SPOReS is to facilitate planning for reliability and affordability along with balancing of grid supply with storage, flexible loads and power electronic controllers. This talk will present two specific deliverables of SPOReS. On the planning front, a graphbased approach for enhancing the reliability of distribution systems by installing new tielines will be introduced. The problem is cast as an edgeconnectivity augmentation problem. We will discuss the associated solution approaches, ways to factor in practical considerations and metrics based on network topology that capture the reliability impacts of the specific interventions. On the operational front, solutions for load management will be discussed to facilitate demand response and community energy sharing.


MESW03 
29th April 2019 14:30 to 15:30 
Veronika Grimm 
Generation and network investment in electricity markets: using multilevel optimization to assess the role of the market design The talk will present a multilevel optimization approach that allows to analyze the longrun impact of electricity market design on investment and production decisions. The presentation will give an overview over various recent contributions that focus on electricity markets that operate under a zonal pricing market design, as it is established in Europe. We apply the approach to the German electricity market as an example to demonstrate the impact of (i) the establishment of additional price zones, (ii) regionally differentiated network fees (iii) marketdriven RES curtailment on key performance indicators such as welfare, economic rents, generation mix and locations, network investment, or electricity prices in the long run. We also show how the model can be used to endogenously determine an optimal configuration of price zones on a network, or to assess the long run impact of structural (regulatory) uncertainty about the future market design. The talk will present work with various coauthors which will be mentioned along the presentation. 

MESW03 
29th April 2019 16:00 to 17:00 
Eddie Anderson 
Rothschild Lecture: What do we agree on when we disagree? Forward contracts with private forecasts
Forward
contracts are used for hedging purposes when firms operate in a spot market.
What will happen when firms have different views on the future distribution of
prices and are risk averse? We discuss different ways in which two firms may
agree on a bilateral forward contract: either through direct negotiation using
the ideas of a Nash bargaining solution, or through a broker. We discuss a type
of equilibrium in which each firm offers a supply function linking quantities
and prices, and the clearing price and quantity for the forward contracts are
determined from the intersection. Each firm may also be able to use the offer
of the other firm to augment its own information about the future price. 

MESW03 
30th April 2019 09:00 to 10:00 
Shmuel Oren 
Mobilizing Grid Flexibility for Renewables Integration through Topology Control and Dynamic Thermal Ratings
(Joint work with Jiaying Shi) The rapid penetration of renewable resources into the electricity supply mix poses challenges for the efficient dispatch of resources due to the inherent uncertainty and variability of such resources. Hence, in order to accommodate large amounts of renewables in is necessary to account for their output uncertainty and mobilize the flexibility of the system embedded in conventional generation, demand side resources and the transmission grid. In this talk we formulate a stochastic unit commitment optimization in which we expand the traditional recourse actions that are available to mitigate the adverse effect of renewables variability. In particular we include in these recourse action, topology control through transmission switching and dynamic line ratings that account for the heating and cooling of transmission lines. We will demonstrate the potential gains from such recourse actions through test cases and discuss heuristic approaches for alleviating the computational burden resulting from such a formulation. 

MESW03 
30th April 2019 10:00 to 11:00 
John SimpsonPorco 
Optimal SteadyState Control with Application to Secondary Frequency Control of Power Systems
The optimal steadystate control problem is that of designing a feedback controller for a multivariable system which regulates selected system variables to the solution of a constrained optimization problem, despite parametric modelling uncertainty and unmeasured exogenous disturbances. For example, an instance of this problem occurs in the design of secondary frequency control systems, where control resources should be optimally used subject to the elimination of frequency deviations and restoration of interarea tieline flows. We present a constructive design framework that reduces the OSS control problem to a more classical control problem of output regulation (tracking and disturbance rejection). Robustness issues which arise in the constructive procedure are discussed, leading to a solution of the OSS control problem for the case where the plant is LTI with structured parametric uncertainty and unknown disturbances are constant in time. We apply the results to frequency control of power systems show that the OSS control framework recovers several recent decentralized and distributed secondary frequency controllers from the literature. Collaborators: Liam S. P. Lawrence (UWaterloo) and Enrique Mallada (JHU) 

MESW03 
30th April 2019 11:30 to 12:30 
Johanna Mathieu 
Optimal Power Flow with Stochastic Reserves
My research seeks to improve the sustainability of electric power systems by developing methods to support the integration of renewable energy sources while maintaining system reliability. In this talk I will describe our efforts to develop approaches to dispatch power systems with reserves provided by stochastic resources like residential air conditioners. We formulate the problem as a chance constrained optimal power flow problem with uncertainty in renewable energy production, load consumption, the capacity of loadbased reserves. Solving such problems is challenging because we do not have good models of the uncertainties. I will describe our work exploring of a variety of solution approaches including distributionally robust optimization, which gives us reliable but costly solutions. I will also describe a novel distributionally robust approach that allow us to leverage structural information about the uncertainty to reduce the conservatism of standard approaches.


MESW03 
30th April 2019 13:30 to 14:30 
Claudia D’Ambrosio 
Smart Grids Observability using Bilevel Programming
Monitoring an electrical network is an important and challenging task. Phasor measurement units (PMU) are devices that can be used for state estimation of this network. We consider a PMU placement problem and propose two new approaches to model this problem, which take into account a propagation rule based on Ohm’s and Kirchoff’s laws. First, we describe the natural binary linear programming model based on an iterative observability process. Then, we remove the iteration by reformulating its fixed point conditions to a bilevel program. We propose two methods to solve such a problem. The first is based on the observation that the integrality constraint of lower level problem can be relaxed so as to derive a single level reformulation by replacing such a problem with its dual. The second is a tailored cutting plane algorithm. We show through computational results that the tailored cutting plane method is much more effective than the others on a set of instances taken from the literature. Joint work with Sonia Toubaline, PierreLouis Poirion, and Leo Liberti 

MESW03 
30th April 2019 14:30 to 15:30 
Claudia Sagastizabal 
Nonsmooth Optimization put to good use in energy problems
We examine problems in managing a mix of power plants generating electricity, using optimization modeling. The modeling includes definition of goals, such as minimizing carbon footprints, maximizing revenue, or reducing risk of blackouts. We discuss how to exploit structural properties of nonsmooth objective functions.


MESW03 
30th April 2019 16:00 to 17:00 
Marija Ilic 
Dynamic monitoring and decision systems (dymonds) framework for dataenabled integration in complex electric energy systems
In this talk we introduce a unifying Dynamic
Monitoring and Decision Systems (DyMonDS) framework that is based on a multilayered
modeling for aggregation and minimal coordination of interactions between the
layers of complex electric energy systems. Using this approach, distributed
control and optimization problems are formulated so that: (1) the lowlevel
decision makers optimize cost of local interactions while accounting for their
heterogeneous technologies, as well as for their social and risk preferences;
and, (2) the higher layer aggregators and coordinators optimize the cost of all
interactions at their levels to enable cooperative control. The interactions of
each layer are abstracted by using unifying energy state space and the Lagrange
coefficients associated with the general physical laws. This sets the bases for
both nonlinear control of power electronicallyswitched automation and for
market design formulation. Potential benefits (such as enhanced reliability,
resiliency, and efficiency) from integrating flexible technologies, storage,
and control, in particular, are illustrated on simple IEEE test systems.


OFBW47 
1st May 2019 10:00 to 10:10 
Jane Leeks, David Abrahams  Welcome and Introduction  
OFBW47 
1st May 2019 10:10 to 10:20 
Bert Zwart  Outline and Summary of INI Research Programme 'Mathematics of Energy Systems'  
OFBW47 
1st May 2019 10:20 to 10:55 
Florentina Paraschiv  Econometrics of Intraday Electricity Prices  
OFBW47 
1st May 2019 10:55 to 11:30 
Pierre Pinson  Analytics and Forecasting for Renewable Energy Generation  
OFBW47 
1st May 2019 11:50 to 12:25 
James Cruise  Moving Energy through Time: Storage and Demand Side Response  
OFBW47 
1st May 2019 12:25 to 13:00 
John Moriarty, Louis Wehenkel  Towards Optimal Operation and Maintenance of Electric Power Grids under Uncertainties  
OFBW47 
1st May 2019 14:00 to 14:35 
Michael Ferris  Computation in Markets with Risk  
OFBW47 
1st May 2019 14:35 to 15:05 
Shane Slater  Energy Storage and Decarbonised Energy Systems  
OFBW47 
1st May 2019 15:30 to 16:00 
Farina Farrier  Open Networks Project  Laying the foundations of a Smart Grid in GB  
OFBW47 
1st May 2019 16:00 to 16:30 
Carol Choi  The Value of Data  
OFBW47 
1st May 2019 16:20 to 16:45 
Discussion and Questions  
MESW03 
2nd May 2019 09:00 to 10:00 
Mahnoosh Alizadeh 
MobilityAware Load Management Algorithms for Electric Vehicles
In this talk, we will discuss pricing mechanisms and/or routing algorithms that can be used to manage the charging demand of a population of electric vehicles. After presenting an overview of some recent results, two main papers will be discussed. In the first part of the talk, I will present on the design of optimal pricing and routing policies to provide differentiated services in a network of fast charging stations, where customers have different values of time and energy demands. The second part of the talk is focused on residential EV demand management under realtime pricing programs. We will discuss the application of multiarmed bandit based algorithms for price design, where customers' price response is modeled as a stochastic system with unknown parameters. Given the presence of reliability constraints in power systems, we will discuss the application of wellknown bandit heuristics in constrained environments and discuss the effects of reliability constraints on the regret guarantees of the algorithms.


MESW03 
2nd May 2019 10:00 to 11:00 
Na Li 
The Role of Prediction And Realtime Learning in Online Optimization and Control
Uncertainties place a key challenge in transforming the grid into one with a large renewable energy integration and active users' participation. The volatile renewable generation constantly introduces disturbance to the grid operation; while the stochastic user behavior makes it difficult to use demand as a reliable resource for balancing realtime supplydemand. This talk will present two lines of work to address these issues. Firstly, we will study how to use a short term prediction, e.g., renewable energy, to improve the performance for online optimization and control, e.g, economic dispatch with ramping cost. Then, we will study how to use realtime learning to design residential demand response programs for achieving grid reliability while balancing the exploitation and exploration of the uncertain user behavior.


MESW03 
2nd May 2019 11:30 to 12:30 
David Hill 
Exploring fundamental limits in future grids with mathematics, computation and databased methods The talk will present results for computing stability limits using a variety of approaches each with advantages and disadvantages arising from the models used. Mathematics favours simplified equationbased models; computation favours detailed physicsbased models and newer databased methods sometimes claim to be actually ‘modelfree’. As systems become more complex in likely scenarios for grids out to 2050and become more everchanging there should be a new discussion about the merits of the associated methods. Results obtained in future grid and high renewable projects in Sydney and Hong Kong respectively will be used for illustration. 

MESW03 
2nd May 2019 13:30 to 14:30 
Enrique Mallada 
Embracing Low Inertia for Power System Frequency Control: A Dynamic Droop Approach
CoAuthors: Yan Jiang, Richard Pates, and Fernando Paganini Abstract: The transition into renewable energy sources with limited or no inertia is seen as potentially threatening to classical methods for achieving grid synchronization. A widely embraced approach to mitigate this problem is to mimic inertial response using gridconnected inverters. That is, introduce virtual inertia to restore the stiffness that the system used to enjoy. In this talk, we seek to challenge this approach and advocate towards taking advantage of the system’s low inertia to restore frequency steady state without incurring in excessive control efforts. With this aim in mind, we develop an analysis and design framework for inverterbased frequency control. We define several performance metrics of practical relevance for power engineers that contemplate system disturbances and measurement noise, and systematically evaluate the performance of standard control strategies, such as virtual inertia and droop control. Our analysis unveils the relatively limited role of inertia on improving performance as well as the inability of droop control to enhance performance without incurring in considerable steadystate control efforts. To solve this problem, we propose a novel dynamic droop control (iDroop) for gridconnected inverters exploiting classical lead/lag compensation from control theory that can significantly outperform existing solutions with comparable and in many cases significantly smaller control efforts. 

MESW03 
2nd May 2019 14:30 to 15:30 
Ana Busic 
Balancing the Grid through Distributed Control of Flexible Loads
A control scheme that unifies feedforward and feedback
control for a large collection of heterogeneous loads is proposed. The
feedforward part capitalizes on the knowledge of gridevent forecasts, such as
predicted ramps in solar and wind energy and the approximate periodicity of the
demand cycle.
The slower timescale feedforward control strategy
utilizes a model predictive control (MPC) framework designed on the basis of
two pieces of
information: aggregate power consumption from each class
of loads and the state of charge surrogate that is a part of the leaky battery
model. Feedback control is performed at a faster time scale in order to reject
realtime disturbances. The control architecture incorporates the decentralized
loadlevel stochastic control design, which ensures that consumer QoS constraints
are respected.


MESW03 
2nd May 2019 16:00 to 17:00 
Steven Low 
Timevarying nonconvex optimization with application to OPF
Optimal power flow (OPF) problems are fundamental for power system operations. They are nonconvex and, in future applications, timevarying. We present a firstorder proximal primaldual algorithm and a secondorder algorithm for general timevarying nonconvex optimization and bound their tracking performance. We incorporate realtime feedback in our algorithms for applications to timevarying OPF problems, and illustrate their tracking performance numerically. (Joint work with Yujie Tang, Caltech, Emiliano Dall’Anese, U of Colorado, Andrey Berstein, NREL) 

MESW03 
3rd May 2019 09:00 to 10:00 
Laura Diaz Anadon 
Innovation in energy technologies and the role of governments
Over the past 20 years there has been a growing amount of empirical research trying to understand the extent to which technology innovation in energy technologies can contribute to mitigating climate change. This presentation will focus on what we know regarding the role of governments in promoting such innovation in lowcarbon energy technologies, with a particular emphasis on the United States and China, the largest greenhouse gas emitters. She will discuss some of the main challenges of building and resourcing effective, empowered institutions able to tackle climate change more rapidly. Her presentation will also discuss how research could help overcome some of these challenges.


MESW03 
3rd May 2019 10:00 to 11:00 
Chris Dent 
Statistical modelling for planning and policy applications
This presents joint thinking with a number of colleagues, key among them being Amy Wilson, Stan Zachary, Michael Goldstein, Henry Wynn, Jim Smith and Peter Challenor. The contributions of various students and postdocs are also acknowledged, and credited in the presentation where relevant.


MESW03 
3rd May 2019 11:30 to 12:30 
Florian Doerfler 
DataEnabled Predictive Control of Autonomous Energy Systems
We consider the problem of optimal and constrained control for unknown systems. A novel dataenabled predictive control (DeePC) algorithm is presented that computes optimal and safe control policies using realtime feedback driving the unknown system along a desired trajectory while satisfying system constraints. Using a finite number of data samples from the unknown system, our proposed algorithm uses a behavioral systems theory approach to learn a nonparametric system model used to predict future trajectories. We show that, in the case of deterministic linear timeinvariant systems, the DeePC algorithm is equivalent to the widely adopted Model Predictive Control (MPC), but it generally outperforms subsequent system identification and modelbased control. To cope with nonlinear and stochastic systems, we propose salient regularizations to the DeePC algorithm. Using techniques from distributionally robust stochastic optimization, we prove that these regularization indeed robustify DeePC against corrupted data. We illustrate our results with nonlinear and noisy simulation case studies from aerial robotics, power electronics, and power systems.


MESW03 
3rd May 2019 13:30 to 14:30 
Sean Meyn 
State Space Collapse in Resource Allocation for Demand Dispatch
The term demand dispatch refers to the creation of virtual energy storage from deferrable loads. The key to success is automation: an appropriate distributed control architecture ensures that bounds on quality of service (QoS) are met and simultaneously ensures that the loads provide aggregate grid services comparable to a large battery system. A question addressed in our 2018 CDC paper is how to control a large collection of heterogeneous loads. This is in part a resource allocation problem, since different classes of loads are more valuable for different services. The evolution of QoS for each class of loads is modeled via a state of charge surrogate, which is a part of the leaky battery model for the load classes. The goal of this paper is to unveil the structure of the optimal solution and investigate short term market implications. The following conclusions are obtained: (i) Optimal power deviation for each of the M 2 load classes evolves in a twodimensional manifold. (ii) Marginal cost for each load class evolves in a twodimensional subspace: spanned by a costate process and its derivative. (iii) The preceding conclusions are applied to construct a dynamic competitive equilibrium model, in which the consumer utility is the negative of the cost of deviation from ideal QoS. It is found that a competitive equilibrium exists, and that the resulting price signals are very different than what would be obtained based on the standard assumption that the utility is with respect to power consumption. It is argued that price signals are not useful for control of the grid since they are inherently open loop. However, the analysis may inform the creation of heuristics for payments within the context of contracts for services with consumers. 

MESW03 
3rd May 2019 14:30 to 15:30 
Panel 