On Distributed Scheduling of Flexible Demand and Nash Equilibria in the Electricity Market

Antonio Paola (), David Angeli () and Goran Strbac ()
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Antonio Paola: Imperial College London
David Angeli: Imperial College London
Goran Strbac: Imperial College London

Dynamic Games and Applications, 2018, vol. 8, issue 4, No 6, 798 pages

Abstract: Abstract This paper presents a novel game theory approach for large-scale deployment of price-responsive electrical appliances. In the proposed distributed control scheme, each appliance independently schedules its power consumption on the basis of a broadcast demand/price signal, aiming to complete its task at minimum cost. The conflicting interactions of the appliances, competing for power consumption at the cheapest hours of the day, are modelled through a differential game with a continuum of players, and efficient deployment of flexible demand is characterized as a Nash equilibrium. A novel approach is adopted to derive necessary and sufficient equilibrium conditions: intrinsic properties of the problem (price monotonicity, unidirectionality of power transfers) are exploited to perform an equilibrium study based on sublevel sets of the considered demand profiles. As a result, it is possible to determine for which penetration levels of flexible demand, types of appliances and inflexible demand profiles it is possible to achieve an equilibrium. Such stable configuration is achieved through the broadcast of a single demand/price signal and does not require iterated exchange of information between devices and coordinator. In addition, the global optimality of the equilibrium is proved, necessary conditions for Pareto optimality are derived, and a preliminary analysis of devices with partial time availability is carried out. The performance of the proposed control strategy is evaluated in simulation, considering realistic future scenarios of the UK power system with large penetration of flexible demand.

Keywords: Smart grid; Distributed algorithms; Price-responsive appliances; Electricity market; Differential games (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s13235-017-0237-3

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