摘要
含分布式新能源配电网规划均采用被动、保守接入分布式新能源的规划方法,固然保证了配电网安全,但并没有反映分布式新能源的出力特征,因而造成不必要的配电网建设投资。为了解决这一问题,采用基于随机机会约束规划的有源配电网规划方法,将有源配电网规划中必须满足的硬性约束条件转变为较高置信度的软约束形式,同时,在模型中引入反映经济效益的投资成本、网络损耗以及反映配电网供电安全性的电压偏移度这3个目标函数作为优化对象,形成了有源配电网规划的多目标随机机会约束规划模型。采用结合量子法改进的非支配排序多目标优化遗传算法(non-dominated sorting genetic algorithm2,NSGA-2)求解获得非劣解帕累托前沿,在此基础上,运用逼近理想解排序法(technique for order preference by similarity to ideal solution,TOPSIS)对非劣解排序得到最优方案。最后,以57节点的配电网网络为算例,验证了方法的可行性、有效性。
Most of the typical distribution network programmings with distributed newenergy utilize passive,conservative programming method to access distributed newenergy,which indeed secure the safe of distribution network,but cannot reflect the output characteristics of distributed newenergy and cause unnecessary investment on distribution network construction. To solve this problem,this paper proposed active power distribution network programming method based on random chance constrained programming. Firstly,the hard constraint conditions in active power distribution network programming were transformed into soft ones with higher confidence level. Meanwhile,three independent objective functions including the investment cost reflecting the economic benefit,the power loss and the voltage deviation degree reflecting the distribution network power supply security were set to form the multiple-objective active power distribution network planning model based on random chance constrained programming. Then,the model was solved to obtain noninferior solution Pareto frontier by the improved NSGA-2（ non-dominated sorting genetic algorithm2） combined with the quantum method. On this basis,the TOPSIS（ technique for order preference by similarity to ideal solution） was used to sort the non-inferior solution,in order to obtain the optimal solution. Finally,a distribution network with 57 nodes was used as example to verify the feasibility and availability of the proposed method.
出处
《电力建设》
北大核心
2015年第11期10-16,共7页
Electric Power Construction
基金
国网宁夏电力公司科技项目(5229JY1307G6)
关键词
随机机会约束
分布式电源
时序特性
有源配电网规划
改进NSGA-2
random chance constraint
distributed generation
time sequential characteristics
active power distribution network planning
improved NSGA-2
