考虑不确定性成本的含风电场群电力系统短期优化调度  

Short-term optimal dispatch considering uncertainty cost for power system with wind farms

作　　者：曲正伟[1] 王京波[2] 张坤[1] 王云静[1] 郑磊[1] 

机构地区：[1]燕山大学电力电子节能与传动控制河北省重点实验室,河北秦皇岛066004 [2]国网湖北省电力公司检修公司,湖北武汉430000

出　　处：《电力自动化设备》2016年第4期137-144,共8页Electric Power Automation Equipment

基　　金：国家自然科学基金资助项目(51107109);秦皇岛科学技术研究与发展计划项目(201302A022)~~

摘　　要：提出一种考虑系统不确定性成本和运行风险约束的含风电场群电力系统短期优化调度方法。针对多维风速联合概率分布函数不易构造的问题,采用Copula函数描述其时空分布特性并生成多维风速的场景空间。定义电力系统风险指标,建立一种考虑系统不确定性成本和运行风险约束的含风电场群电力系统动态经济调度模型,协调了系统经济性和安全性的之间的矛盾。提出基于场景运算的风险指标评估方法,并结合改进的量子粒子群优化算法用于模型求解,提高了模型求解速度,直观地反映出系统的风险程度,并得到系统最佳置信水平。以含2个邻近风电场的IEEE 30节点系统为算例,验证了模型及算法的合理性和有效性。A short-term optimal dispatch considering the uncertainty cost and operational risk constraint is proposed for the power system with wind farms. Since the joint probability distribution function of multidimensional wind speed is not easy to construct,the Copula function is adopted to describe its temporal and spatial distribution and generate its scenic space. A risk index is defined for power system and a dynamic economic dispatch model of power system with wind farms is built,which considers the system uncertainty cost and operational risk constraint to coordinate the system economy with its safety. An assessment method based on scene computation is proposed for the risk index and the improved quantum particle swarm optimization method is combined to solve the model,which improves the solving speed,directly reflects the system risk degree and calculates the optimal system confidence level. IEEE 30-bus system with two adjacent wind farms is taken as an example to verify the rationality and effectiveness of the proposed model and algorithm.

关 键 词：优化调度 风电场 不确定性成本 场景运算 量子粒子群优化算法 

分 类 号：TM614[电气工程—电力系统及自动化]