基于NSGA-Ⅱ的新型混合电力系统优化规划方法

New hybrid power system optimization planning method based on NSGA-II

迄今为止,风能、太阳能等新能源作为可再生能源,在生成电能方面是清洁无污染的,但在电网运行过程中却与温室气体(GHG)的排放息息相关。因此,介绍了一种新型的独立混合新能源-电池系统尺寸优化方法,最大限度地降低了平准化能源成本(LCOE)、能源损耗率(LPSP)和等效二氧化碳(CO_(2))排放量。以预期光伏峰值功率、风力发电机输出功率、电池能量容量为决策变量,以单位用电量所含二氧化碳为约束,采用精英非主导排序遗传算法(NSGA-II)求解了这一约束性非线性多目标优化问题,并对系统的不同组合进行优化和比较,以确定经济高效、可靠环保的最佳架构。最后,对所提出的算法进行了灵敏度分析,仿真结果验证了所提方法在实现经济、能源和环境目标方面的有效性。

So far,new energy sources such as wind and solar,as renewable energy sources,are clean and pollution-free in generating electricity,but they are closely related to greenhouse gas(GHG)emissions in the process of power grid operation.Therefore,this paper introduces a novel independent hybrid new energy-battery system size optimization method,which minimizes the normalized energy cost(LCOE),energy loss rate(LPSP)and equivalent carbon dioxide(CO_(2))emissions.Based on the expected peak power photovoltaic,wind generator output power,battery energy capacity of decision variables,unit power consumption contains carbon dioxide as constraint,using the non-dominant elite sorting genetic algorithm(NSGA II)solving the nonlinear multiobjective optimization problem of the binding,and different combination of system optimization and comparison,To determine the best cost-effective,reliable and environmentally friendly framework.Finally,the sensitivity analysis of the proposed algorithm is carried out,and the simulation results demonstrate the effectiveness of the proposed method in achieving economic,energy and environmental objectives.