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Ancillary service to the grid from deferrable loads: the case for intelligent pool pumps in Florida

Presented by: 
S Meyn University of Illinois
Date: 
Wednesday 14th August 2013 - 13:30 to 14:15
Venue: 
INI Seminar Room 1
Abstract: 
Renewable energy sources such as wind and solar power have a high degree of unpredictability and time-variation, which makes balancing demand and supply challenging. One possible way to address this challenge is to harness the inherent flexibility in demand of many types of loads. We focus on pool pumps, and how they can be used to provide ancillary service to the grid for maintaining demand-supply balance.

The control solution is based on the following steps: 1. A Markov Decision Process (MDP) model is introduced for an individual pool pump. 2. Using the Todorov's formulation, a randomized control architecture is proposed, motivated by the need for decentralized decision making, and the need to avoid synchronization that can lead to large and detrimental spikes in demand. 3. An aggregate model for a large number of pools is obtained from a mean field limit. 4. A linearization of the eigenvector problem in (2) provides an LTI-system approximation of the aggregate nonlinear model, with a scalar signal as the input and a measure of the aggregate demand as the output.

The final approximation is convenient for control design at the grid level. Simulations are provided to illustrate the accuracy of the models and effectiveness of the proposed control approach.

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University of Cambridge Research Councils UK
    Clay Mathematics Institute The Leverhulme Trust London Mathematical Society Microsoft Research NM Rothschild and Sons