Optimal Charging Control of Energy Storage and Electric Vehicle of an Individual in the Internet of Energy With Energy Trading

Abstract

Developing green energy to be applied in green cities has received much attention. The Internet of energy (IoE) effectively improves networking of distributed green energies through extending smart grids with bidirectional transmission of energy and distributed renewable energy facilities. Previous works on the IoE focused on decisions of IoE operators or optimization of the whole system. However, few considered optimal decisions of a single end user in the IoE. Therefore, this work creates a mixed-integer linear programming (MILP) model for a single end user that considers green energy generation, an energy storage, an electric vehicle, and an IoE-based energy trading platform to reduce energy waste. This model considers a complete system of charging control of multiple facilities of a single end user in the IoE, and allows the end user to purchase energy and sell green energy through the IoE, in which the energy prices of the electrical grid and the IoE platform are set by the power company and the energy market, respectively. Because MILP is NP complete and the proposed model involves a large number of variables and constraints, this paper further proposes a genetic algorithm for this problem, in which a repairing scheme is proposed to handle solution infeasibility of all constraints. By simulation, the proposed algorithm is verified to effectively reduce energy waste.