A Costs-Emissions Bi-objective Optimization of Virtual Power Plant Operation in Hongfeng Eco-town

This paper addresses the optimal operation issues for virtual power plant (VPP). Two conflicting objectives are considered and a bi-objective problem is formulated mathematically. The first objective (economical performance) contains cost of fuel consumption and cost of power purchased from grid. The second objective (environmental performance) takes account of several pollutant emissions. Multi-objective particle swarm optimization (MOPSO) is applied to derive the Pareto frontier which is a set of noninferior solutions. A realistic case study is performed on Hongfeng Eco-town as a model of VPP, which includes various distributed energy resources (DER) such as hydropower units, wind turbines, photovoltaic panels, combined cooling heating and power units (CCHP) and storage devices. Simulation concentrates on three strategies: 1) money-oriented, 2) environment-only, 3) Pareto-optimal. Comparison of simulation results reveals that Pareto-optimal strategy can better compromise costs and emissions. Further, system operators could choose noninferior solutions from Pareto frontier according to their specific preference.