考虑风电和光伏发电影响的电力系统最优旋转备用容量确定  

Determination of Optimal Spinning Reserve Capacity of Power System Considering Wind and Photovoltaic Power Affects

作　　者：殷桂梁[1] 张雪[1] 操丹丹[1] 刘静文[1] 

机构地区：[1]燕山大学电气工程学院,河北省秦皇岛市066004

出　　处：《电网技术》2015年第12期3497-3504,共8页Power System Technology

摘　　要：随着风电和光伏发电并网规模的不断增大,传统旋转备用容量的确定方法已不能满足电力系统安全运行的要求。为此,建立了计及系统可靠性和经济性的机组组合优化模型,同时充分考虑了负荷、风电和光伏发电输出功率的预测误差以及常规机组的故障停运。采用序列运算理论对这些不确定因素进行处理,将不确定性以概率的形式综合考量,并将其引入到目标函数的计算中,能够直观体现系统运行的风险程度,从而联合优化了发电机组的出力计划和旋转备用容量。提出了采用基于离散粒子群和细菌群体趋药性的混合智能算法对模型进行求解,结合序列运算,提高了模型的求解速度和解的最优性。最后,以加入风电场和光伏电站的IEEE 10机39节点系统为算例进行仿真研究,结果验证了所提优化模型及算法的正确性和有效性。With continuous increase of wind and photovoltaic powers in power system, traditional method determining spinning reserve capacity can＇t meet safe operation requirement of power system. A unit commitment model is proposed considering reliability and economy of system. Forecast error of load, wind and photovoltaic power generation and conventional unit fault outage are also fully considered in the model. Using sequence operation theory to deal with these uncertainties introduced into objective function calculation can directly reflect risk degree in system operation. Optimal allocation results of generation unit output and spinning reserve capacity can also be obtained. Hybrid intelligent algorithm based on discrete particle swarm optimization（DPSO） and bacterial colony chemotaxis（BCC） combined with sequence operation are applied to solve the model with significant optimality. Finally, case studies are carried out on IEEE 10-unit 30-bus system as benchmark, and simulation results demonstrate validity and effectiveness of the proposed model and method.

关 键 词：旋转备用 风电 光伏发电 机组组合 序列运算 离散粒子群 细菌群体趋药性 

分 类 号：TM721[电气工程—电力系统及自动化]