基于改进动态惯性权重粒子群算法的冷热电联供型微网运行优化

通过多种能源优势互补的冷热电联供型微网,能够促进可再生能源的使用,实现资源的阶梯利用。针对区域内由电、热、冷多种能源耦合形成的微网系统运行优化问题,基于不同季节典型日风光出力和负荷需求特性曲线,构建了含燃气轮机、余热锅炉、吸收式制冷机等机组设备,采用改进的动态惯性权重粒子群算法(particle swarm algorithm, PSO)求解方法,综合考虑系统的燃料成本、环境治理成本、电网交互成本和运行维护成本进行优化求解。最后,通过算例分析验证本模型和方法的有效性。研究成果为冷热电联供型微网系统的规划设计提供参考和依据。

Operation Optimization of Combined Cooling, Heating and Power Microgrid Based on Improved Dynamic Inertia Weighted Particle Swarm Algorithm

A cooling, heating and power microgrid with multiple energy sources complementing each other can promote the use of renewable energy and realize the ladder utilization of resources. For the optimization of the operation of the microgrid system formed by the coupling of electricity, heat and cold in the region, this paper based on the typical daily wind, photovoltaic output and load demand characteristic curves in different seasons, it is constructed with gas turbine, waste heat boiler, absorption chiller and other unit equipment, and uses an improved dynamic inertia weight particle swarm algorithm to solve the problem, taking into account the fuel cost, environmental management cost, grid interaction cost and operation and maintenance cost of the system. The optimized solution is carried out by considering the fuel cost, environmental management cost, grid interaction cost and operation and maintenance cost of the system. Finally, the validity of the model and method is verified through case analysis, which provides a reference and basis for the planning and design of the combined cooling, heating and power microgrid system.