Optimization Methods to Improve Efficiency and Fairness in Peer-to-Peer Energy Trading

In recent years, many countries have been promoting the distributed energy systems for clean energy utilization. Direct energy trading is an efficient way to trade electricity, but not everyone benefits fairly in the market, since some suppliers have limited capacity of supplying electricity. This occasion leads to a decrease in the consumer's benefit. Existing studies are mainly focused on not the equity of consumer's benefit but the efficiency of resource allocation. This paper proposes a multi-objective optimization problem and single-objective one in order to improve both the equity of consumer's benefit and the efficiency of resource allocation. For solving the problem, our study adopts six Evolutionary Algorithms (EAs) and two single-objective algorithms. Simulation results demonstrate that the selected EAs can optimize both the efficiency of resource allocation and the equity of consumer's benefit.