基于多目标双重动态遗传算法的含分布式电源冷热电联供型综合能源运行优化

Optimization of Integrated Energy System Combined Cooling Heating and Distributed Power Based on Dual Dynamic Genetic Algorithm

综合能源系统优化运行对提高综合能源利用、消纳可再生资源具有重要作用。为了使系统中各设备的出力得到进一步优化以及解决系统污染的环境问题,构建了一种含有分布式电源、燃气锅炉、电制冷机、储能等机组的冷热电多能源联供系统的优化模型,并以系统总成本、运行成本及环境成本为优化目标,求解模型的优化配置;提出一种双重动态遗传算法,提高求解的收敛精度、收敛速度及稳定性;最后利用算例进行结构分析。结果表明双重动态遗传算法相比于标准粒子群算法及标准遗传算法提高了系统的经济效益和环保效益,并且在全局寻优和搜索精度等方面更具优势。

The optimization of the integrated energy system plays an important role in improving the integrated energy utilization and the consumption of renewable resources.In order to optimize the output of each equipment in the system further and solve environmental problems caused by system pollution,an optimization model for a multi energy cogeneration system consisting of distributed power sources,gas boilers,electric refrigerators,energy storage units,and other units is constructed.The optimal configuration of the model is solved with the total system cost,operating cost and environmental cost as the optimization objectives.A dual dynamic genetic algorithm is proposed to improve the convergence accuracy,the convergence speed and the stability of solution,and a structural analysis is conducted finally through the examples.The results are indicated that the dual dynamic genetic algorithm improves the economic and environmental benefits of the system compared with the standard particle swarm algorithm and standard genetic algorithm,and has more advantages in global optimization and search accuracy.