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State Space Collapse in Resource Allocation for Demand Dispatch

Presented by: 
Sean Meyn
Friday 3rd May 2019 - 13:30 to 14:30
INI Seminar Room 1
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 two-dimensional manifold.
(ii) Marginal cost for each load class evolves in a two-dimensional subspace: spanned by a co-state 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.
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University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons