中文摘要：

为了有效提高风–光–沼混合可再生能源分布式发电系统的可靠性和经济性,首先研究分析了风、光、沼各发电电源特点以及该分布式发电系统结构特征,并以此为基础建立了其系统电源规划的优化目标函数和约束条件函数等数学模型。由于改进的自适应遗传算法使用最优保存策略进化模型的选择算子、改进的自适应交叉算子和变异算子,来获得较优的全局搜索能力和较强的鲁棒性,所以采用该遗传算法对此分布式发电系统电源规划进行优化运算处理。最后选取某负荷中心的300 kW负荷总量为对象进行风–光–沼混合可再生能源分布式发电系统的电源规划模拟优化求解,算例结果验证了该方法的可行性和有效性,而且对其它类型可再生能源分布式发电系统电源规划有一定的指导意义。

英文摘要：

To effectively improve the reliability and economy of distributed generation system（DGS） composed of renewable energy resources such as wind energy,solar energy and biogas energy,firstly the features of generation systems based on wind energy,solar energy and biogas energy respectively as well as the structural feature of generation system mixed with wind,solar and biogas energy resources were researched and analyzed,on this basis mathematical models of optimized objective functions of DGS composed of renewable energy resources and their constraint conditions were built.Secondly,due to the adoption of the selection operator,the improved adaptive crossover operator and the mutation operator in the elitist strategy of the improved adaptive genetic algorithm（AGA）,to achieve better global search ability and stronger robustness,the improved AGA was utilized to optimize the expansion generation planning for distributed DGS.Finally,taking a load center with load amount of 300kW in Guangdong region,China as experimental platform,the simulation for the optimization and solution of a generation expansion planning of a distributed DGS composed of wind farm,PV generation and biogas generation were performed to determine the optimum configuration of power resources.The effectiveness and effectiveness of the proposed method were verified by simulation results that could be available for reference to the expansion generation planning for DGS composed of other types of renewable energy resources.