Real-time pricing for smart grid considering energy complementarity of a microgrid interacting with the large grid

Abstract

Currently, generating electricity relies primarily on fossil energy, which is not only limited in resources but also harmful to the environment as it emits carbon dioxide and other gases. For contributing to carbon peaking and carbon neutrality, building a resource-saving and environment-friendly society, clean energy should be used for generating electricity as much as possible. Additionally, the overproduction of electricity by suppliers and the instability of power grids, which are caused by the information asymmetry between customers and power suppliers, can be solved by the smart grid based on smart meters. Motivated by the two aspects, a smart power system combining a microgrid system based on clean energy generation with a supplier based on fossil energy generation is considered. For pursuing maximal social welfare under joint power supply, a real-time pricing model is established. This model, which is convex, does not explicitly contain the electricity price variable such that the optimal Lagrange multiplier of its Karush–Kuhn–Tucker condition, i.e., shadow price, is taken as the optimal electricity price. For solving the Karush–Kuhn–Tucker system, the smooth Levenberg–Marquardt algorithm is used to solve its approximate smooth system of equations. The simulation results demonstrate that the proposed pricing model, joint supply mechanism and the smooth Levenberg–Marquardt algorithm are reasonable, feasible and effective.