文档介绍：摘要I 微网多目标优化运行研究摘要为有效解决日益严重的能源枯竭与环境污染问题,分布式发电技术近年来快速发展,并在全世界得到了广泛推广和应用,微电网由此应运而生。而如何在微网安全稳定可靠运行的前提下,减少其运行成本和污染气体排放以提高其经济性和环保性,俨然已发展成为微网的热门研究方向。实际上微网优化运行是一个多目标优化问题,若只单纯的考虑发电成本或环境效益都不能完整的描述微网的运行情况。为此,本位将对微网的多目标优化运行展开研究,建立该问题的数学模型,并探索其有效的求解方法。本文首先给出了各分布式发电(Distributed Generation,DG)的能耗和出力模型,然后根据微网的运行原理,提出了以其运行成本最小和二氧化碳排放最低为优化指标的多目标优化运行模型,这是一个复杂的带多种等式约束和不等式约束条件的多目标优化问题,采用常规的多目标优化算法解决该类问题存在几点不足:一是传统的约束处理方法在处理多约束问题时难度较大且效率不高;二是基于单一算法的种群多样性不高且容易早熟。因此,本文提出一种新型的α约束支配排序混合进化算法(α-Constraint Dominant Sorting Hybrid Evolution Algorithm,α-CDSHEA)求解模型。该算法通过采用α约束支配排序机制,将所有约束条件统一处理为α约束水平度,并将其作为进化选择指标以控制所有个体快速转化为可行解,可显著提高约束处理效率;同时提出一种基于非劣排序的混合多目标进化算法,有效融合了微分进化算法与分布估计算法各自的优点,克服单一算法种群多样性不足和易早熟的缺陷。此外,通过分类逼近理想解的排序方法实现多属性决策,以获得最优折中解。最后,用一个微网算例对以上内容进行仿真测试,并与采用常规罚函数约束处理的非劣排序微分进化算法以及单目标遗传算法工具箱进行了对比,算例结果显示本文算法在收敛速度、解集质量与运算时间上都明显优于另外两者。且相比于单目标优化模型,采用多目标优化模型更符合实际的微网运行状态,能更好的体现微网在经济性和环保性两方面的综合效益。关键词:微网;多目标优化;α约束支配排序;混合进化算法;多属性决策目录II The Study of Microgrid Multi-objective Optimization Operation ABSTRACT To effectively solve the increasingly serious energy depletion and environmental pollution problems, distributed power generation technology rapidly developments and widely spreads all over the world in recent years, microgrid thus arises at the historic moment. And how to optimize the allocation of resources, reduce the running cost and pollution emissions in work under the premise of safe and reliable operation also e one of the hot topics in the study of work operation, in order to improve the micro economy and environmental protection of work operation. Actually microgrid optimal operation is a multi-objective optimization problem. Simply considering the operation cost environmental benefits pletely describe the microgrid running status. Therefore, this paper will study microgrid multi-objective optimization operation, establish its mathematical model and explore its effective solving method. At first, this paper gives the energy consumption and output model of distributed generations, and the