中文摘要：

针对环境经济发电调度优化问题，提出了一种应用粗糙集理论构建评价函数的多目标优化方法，并提出了基于混沌局部搜索策略的差分进化算法（chaotic local search strategy differential evolution algorithm, CLSDE）的求解算法。应用粗糙集理论确定经济调度和环境调度函数的约束度，以确定各目标函数在优化模型中的权值。采用CLSDE算法求解环境经济调度（environmental economic dispatch，EED）多目标优化模型，该算法只对目标函数中的变量进行编码，约束条件函数中的变量随机产生，每代进化完毕后，对最优个体进行混沌局部搜索，克服了差分进化算法局部搜索能力较弱和惩罚函数方法中惩罚参数选择较难的问题。对IEEE30节点的标准测试系统进行了仿真计算，结果表明CLSDE算法在解决环境经济调度问题时具有可行性和有效性，在不增加污染气体排放量的同时降低燃料费用，使环境经济调度更能兼顾发电调度的经济利益与环境利益。

英文摘要：

In allusion to environmental economic dispatching optimization, a multi-objective optimization method that constructs evaluation function by rough set theory is proposed, and a solving algorithm based on chaotic local search strategy differential evolution （CLSDE） algorithm for the proposed model is put forward. The constraint degrees of economic dispatching and environmental dispatching function are determined by rough set theory to decide the weight values of objective functions in the proposed optimization model. The CLSDE algorithm is used to solve the multi-objective optimization model of environmental economic dispatching （EED） and this algorithm only encodes the variables in the objective functions; the variables in constraint condition functions are produced at random. After the evolution of each generation is completed, the chaotic local searching is performed to optimal individual, thus both the weak local searching ability of differential evolution algorithm and the difficulty of choosing penalty parameters in the penalty function method can be overcome. The standard IEEE 30-bus system is used to test the proposed method and simulation results show that the CLSDE algorithm is feasible and effective for the solution of environmental economic dispatching, using the proposed method the fuel cost can be reduced while the pollution gas emission is not increased, herefore the environmental economic generation dispatchingcan give consideration to both economic benefit and environmental benefit of generation dispatching.