Demand Response Strategy Based On Supply Function In Smart Grid

Traditional power grids have been jeopardized as a growing number of issues occur when operating. Along with challenges for optimizing power grids by regulating the structure of energy, attentions have been focused on general solutions to these matters by researchers. As a result, smart grids emerge as a suggested construction for future scenarios. The future smart grid is envisioned as a large-scale cyber-physical system encompassing advanced power, communications, control, and computing technologies. This heterogeneous nature of the smart grid motivates the adoption of advanced techniques for overcoming the various technical challenges at different levels such as design, control, and implementation. Demand response can be defined as the changes in electricity usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity over time. Demand response has been proposed since it is able to reflect consumers’ willingness to reduce electricity consumption at high wholesale prices or when the reliability of the power grid is endangered. Meanwhile, demand response is capable to improve the resource-efficiency of electricity production.According to the researches of smart grid and demand response in recently years, the main contents of this paper are as follow:1. Summarize the architecture of demand response. By generalizing the practice and academic research of demand response at home and abroad, this paper starts with the definition the demand response. Followed by highlighting different DR programs, potential benefits and cost savings related to different market components will be discussed. Brief introduction on the technical support will be demonstrated.2. This paper proposes a parameterized supply function considering the situation to match the power supply deficit. We characterize the resulting Nash equilibria in competitive and oligopolistic markets and show that the equilibrium in competitive market maximizes social welfare.3. This paper proposes an iterative distributed algorithm for the demand response to achieve the equilibria by solving corresponding convex optimization problem.4. Simulation results confirm that by using the proposed iterative distributed algorithm. The price, supply function parameters and amount of load shedding approach the market equilibrium quickly.