Game-Theory Modeling for Social Welfare Maximization in Smart Grids

Abstract

In this paper, we study the Stackelberg game-based evolutionary game with two players, generators and energy users (EUs), for monetary profit maximization in real-time price (RTP) demand response (DR) systems. We propose two energy strategies, generator’s best-pricing and power-generation strategy and demand’s best electricity-usage strategy, which maximize the profit of generators and EUs, respectively, rather than maximizing the conventional unified profit of the generator and EUs. As a win–win strategy to reach the social-welfare maximization, the generators acquire the optimal power consumption calculated by the EUs, and the EUs obtain the optimal electricity price calculated by the generators to update their own energy parameters to achieve profit maximization over time, whenever the generators and the EUs execute their energy strategy in the proposed Stackelberg game structure. In the problem formulation, we newly formulate a generator profit function containing the additional parameter of the electricity usage of EUs to reflect the influence by the parameter. The simulation results show that the proposed energy strategies can effectively improve the profit of the generators to 45% compared to the beseline scheme, and reduce the electricity charge of the EUs by 15.6% on average. Furthermore, we confirmed the proposed algorithm can contribute to stabilization of power generation and peak-to-average ratio (PAR) reduction, which is one of the goals of DR.

Scenario Selection for Iterative Stochastic Transmission Expansion Planning

“…Social welfare is a commonly used objective for transmission planning [39][40][41][42][43][44][45]. We measure the quality of selected scenarios based on the similarity between social welfare distributions resulting from the selected and whole set of scenarios, rather than the similarity of the elements of the scenarios.…”

New Methods for Improved Prosumer Trading and Energy Poverty Mitigation in Microgrids using Crowdsourcing Concepts and Blockchain Technologies

“…The same first author considers that in a microgrid the energy flows in a transactive way and the transactions are based on bilateral contracts between peers [33]. Another concept of prosumer surplus trading based on the transactive energy concept is proposed in the literature [34][35][36][37]. Paper [34] uses a Stackelberg game-based method for solving the transactive energy problem, in which the DNO and the SSRES aggregators are able to participate simultaneously in the Local Electricity Market (LEM) and Wholesale Electricity Market (WEM).…”

“…A comprehensive costbenefit model for prosumer load sharing has been proposed in [35], using the game theory and considering non-cooperative game models of the microgrids for prosumers energy surplus. In the same context, a particular social welfare-based concept on transactive energy or demand response (DR) is applied in [36,37] using negotiated prices.…”

“…In addition, the last column considers the type of settlement used in the market. [24,25], [44], [49] No No No Yes No Negotiated [26,27] Yes No No Yes No Negotiated [30][31][32], [35], [38], [42] No Yes No No No Negotiated, MCP [33,34], [36,37], [43], [45] Our vision is to enable an overlay social network of smart devices that facilitates communication and trading process between players from LEM, prosumers, consumers and microgrid. Indubitably in microgrid communities the peers might be from different geographical locations (and bounded by, for example, the DSO).…”

A Real-Time Pricing Scheme for Energy Management in Integrated Energy Systems: A Stackelberg Game Approach

“…Additionally, a flexible management strategy of wind power heating is proposed in [19] to facilitate the consumption of curtailed wind based on game theory. In [20], two energy strategies are proposed to maximize the social welfare of generators and energy consumers in the smart grid based on a Stackelberg game.…”