Social Profit Optimization With Demand Response Management in Electricity Market: A Multi-Timescale Leader-Following Approach

Abstract

In the electricity market, it is quite common that the market participants make "selfish" strategies to harvest the maximum profits for themselves, which may cause the social benefit loss and impair the sustainability of the market in the long term. Regarding this issue, we will study how the social profit can be improved through strategic demand response management. Specifically, we explore two interaction mechanisms in the market: Nash game and Stackelberg game. At the user side, each user makes the respective energy-purchasing strategy to optimize its own profit. At the utility company side, we consider multiple self-centric utility companies who play games. A social-centric governmental utility company is established as the leader to optimize the social profit of the market through competitions. Then, a multi-timescale leader-following problem of the utility companies is formulated under the coordination of an independent system operator. By our proposed demand function amelioration strategy, the market efficiency is maximized. In addition, by considering some additional constraints of the market, two projection-based algorithms are proposed. The feasibility of the proposed algorithms is verified with an IEEE 9-bus system model in the simulation.

A pricing game strategy with virtual prosumer guidance in community grid

“…Remark In (3), the utility function is set up to break the traditional impression that consumers only buy energy from the lowest price producer, and will instead take into account various factors of the producer, such as price, preferences, and so on. A similar model can be found in references[25, 26]. This setting of the utility function will also motivate consumers to buy energy from different producers, which in turn will lead to internal energy consumption in the P2P market.…”

“…In this simulation, the prosumer utility function is set according to the approach presented in reference [25]. Prior to the operation of the P2P trading market,the energy demand and production of each prosumer are quantified to ascertain the role played by the VP.…”