To improve the utilization efficiency of biomass energy in rural areas of China, by virtue of the advantages of the high energy efficiency of a Combined Heat and Power (CHP) system, an optimization strategy for economic operation of such a system considering biomass energy is proposed. Given the constraints of operating power and capacity, the operational costs of biomass gas power and photovoltaic power generation and an energy storage battery are modeled and analyzed. The operational economy optimization of a CHP system is transformed into solving the minimum system operation cost problem. To improve the efficiency of a traditional Particle Swarm Optimization (PSO), the Gray Wolf Particle Swarm Optimization (GW-PSO) algorithm is used to reduce the probability of falling into a local optimum and improve the running speed of the algorithm. The simulation results show that the proposed GW-PSO algorithm has faster convergence, and can improve the energy efficiency of a CHP system with biomass energy. It can effectively reduce energy consumption in rural areas. This could promote the popularization and application of biomass energy. This work is supported by the National Natural Science Foundation of China (No. 51806242) and the Science and Technology Project of State Grid Hebei Electric Power Co., Ltd. (No. B104DY200299).