多目标微电网鲁棒优化经济调度

Multi-objective Micro-grid Robust Optimization of Economic Dispatching

为了充分考虑在微电网经济调度中,间歇式电源出力波动性的影响,本文在鲁棒优化情况下,建立了基于可再生能源出力的不确定性,以发电成本和污染物排放量最优为目标的多目标方程,采用复合型微分进化算法(CDE)对数学模型进行求解。通过对比分析鲁棒优化和常规优化下的pareto前沿,来研究在不同间歇式电源出力强度下发电成本和污染物排放量的关系,分析结果表明鲁棒优化的经济性更优。在鲁棒优化的条件下,本文选取某一确定强度,对比分析了CDE算法与NSGA-II算法的折中解。结果表明,CDE算法具有更好的寻优效果,而且整体上可以有效降低鲁棒优化下的燃料成本和污染物排放量。

In order to fully consider the randomness and volatility of intermittent power output in the economic dispatching of microgrid,based on the uncertainty of output of renewable energy under the condition of robust optimization,the objective multiobjective equation is presented aiming to minimize the power generation cost and pollutant emissions.And the differential evolution algorithm(CDE)is used to solve the mathematical model.By comparing the pareto fronts under robust optimization and conventional optimization,the relationship between power generation cost and pollutant emissions under different intermittent power output strengths is studied.The results show that robust optimization is more economical.Under the condition of robust optimization,the paper chooses a certain intensity,and compares the compromise between CDE algorithm and NSGA-II algorithm.The results show that the CDE algorithm has a better optimization effect,and can effectively reduce the fuel cost and pollutant emissions under robust optimization as a whole.