摘要
分布在相近区域的风电场之间的风速往往具有相关性,采用Copula函数描述多风电场间风速的联合概率分布,进而得到具有相关性的风速分布样本空间。考虑风速的随机性与相关性,应用机会约束规划理论,在满足系统安全可靠运行的前提下,以可调机组的发电成本最小化作为优化目标,建立了含风电场电力系统概率最优潮流模型,并采用一种基于随机模拟技术的粒子群优化算法求解模型。以IEEE30节点测试系统为算例,分析风速相关性和机会约束置信水平对优化结果的影响,结果验证了所提模型与算法的合理性与可行性。
Wind speed always have correlations due to the wind farms close location. This paper uses Copula function to characterize the joint probability distribution of wind speed and to generate correlated wind speed samples. Consider-ing the randomness and correlations of wind speed in wind farms and under the presupposition of satisfying secure oper- ation of power grid, by use of chance constrained programming and taking the minimal cost of the generations as the ob- jective function, a probabilistically optimal power flow model is proposed. To solve the proposed model, a particle swarm optimization algorithm (PSO) based on stochastic simulation technique is given. Taking IEEE 30-bus system as an example, the influence of wind speed correlations and the chance constraint credit level on the results of probabilisti-cally optimal power flow is analyzed, which verifies the rationality and feasibility of the models and algorithms proposed in this paper.
出处
《华北电力大学学报(自然科学版)》
CAS
北大核心
2013年第5期54-59,共6页
Journal of North China Electric Power University:Natural Science Edition
关键词
风电场
相关性
COPULA函数
机会约束规划
随机模拟
粒子群优化
wind farm
correlation
Copula function
chance constrained programming
stochastic simulation
parti-cle swarm optimization (PSO)