Evaluation of Demand-Side Management over Pricing Competition of Multiple Suppliers Having Heterogeneous Energy Sources

Abstract

Abstract:This study investigates a demand-side management problem in which multiple suppliers compete with each other to maximize their own revenue. We consider that suppliers have heterogeneous energy sources and individually set the unit price of each energy source. Then, consumers that share a net utility react to the suppliers' decisions on prices by deciding the amount of energy to request, or how to split the consumers' aggregated demand over multiple suppliers. In this case, the consumers need to consider the power loss and the price to pay for procuring electricity. We analyze the economic benefits of such a pricing competition among suppliers (e.g., a demand-side management that considers consumers' reaction). This is achieved by designing a hierarchical decision-making scheme as a multileader-multifollower Stackelberg game. We show that the behaviors of both consumers and suppliers based on well-designed utility functions converge to a unique equilibrium solution. This allows them to maximize the payoff from all participating consumers and suppliers. Accordingly, closed-form expressions are provided for the corresponding strategies of the consumers and the suppliers. Finally, we provide numerical examples to illustrate the effectiveness of the solutions. This game-theoretic study provides an example of incentives and insight for demand-side management in future power grids.

Loss Allocation in Distribution Networks Based on Aumann–Shapley

“…Knowing the locations of the customers who are responsible for the network losses will allow the DSO to apply specific local actions in those customer installations in order to reduce the network losses. These actions can be based on Demand Response strategies [5].…”

Energy Management of Combined Cooling, Heating and Power Micro Energy Grid Based on Leader-Follower Game Theory

“…In the lower electricity price periods (1)(2)(3)(4)(5)(6)(7)(20)(21)(22)(23)(24), the user gives priority to experience of energy usage, so the dissatisfaction drops to lowest. Because the expenditure is within acceptable range, no load needs to be adjusted.…”

“…When P m < P < P M and R m < R < R M , the membership degree is a linear distribution. The two membership degree functions are shown in Equations (23) and (24).…”

“…We can see that the electricity price strategy is closely related to the user load strategy at the game equilibrium point. In the lower load level periods (1)(2)(3)(4)(5)(6)(7)(20)(21)(22)(23)(24), MEG adjusts the price in order to prevent user to reduce the load, so that it could keep the lowest dissatisfaction and ensure the profit. In the higher load level periods (9)(10)(11)(12)(13)(14)(15)(16)(17), MEG raises the price within the user acceptable range in order to maximize the profit.…”

“…When Pm < P < PM and Rm < R < RM, the membership degree is a linear distribution. The two membership degree functions are shown in Equations (23) and (24). The user payment function needs to take into account the user expenditure P and the user dissatisfaction R, which is a bi-objective optimization problem.…”