摘要
建立了考虑风电出力和负荷不确定性的电力系统有功优化潮流模型。针对传统经验值法确定的系统所需旋转备用容量适应性较差的不足,文中在对风电出力和负荷需求进行区间预测的基础上,采用极限场景理论确定系统的正负旋转备用以协调风电出力和负荷的随机性。针对现有爬坡率约束只考虑单时段机组调节的缺点,为避免系统在风电出力和负荷出现陡峭波动时,机组调节量超过限值,加入多时段耦合约束以平衡系统风电出力和负荷的波动性。最后通过一种改进的粒子群算法对模型求解,并以含风电场的IEEE 30节点系统为算例验证所提模型的正确性与有效性。
An optimal active power flow model, in which the uncertainties of wind power output and load are considered, is established. In allusion to the poor adaptation of spinning reserve capacity determined by traditional experience method, that is needed by power system, based on the interval prediction of wind power output and load demand the positive- and negative-spinning reserve capacity determined by extreme scenario theory is used to coordinate the randomness of wind power output and load. To remedy the defect that in existing unit ramp rate constraint only single single-period unit regulation is considered and to avoid the regulation of units exceeds the limit while abrupt fluctuations of wind power output and load occur, multi-period coupling constraints are added to balance the fluctuation between wind power output and load. An improved particle swarm optimization algorithm is utilized to solve the proposed model and the correctness and effectiveness of the proposed model are verified by simulation results of IEEE 30-bus system with wind farms.
出处
《电网技术》
EI
CSCD
北大核心
2013年第6期1584-1589,共6页
Power System Technology
基金
国家863高技术基金项目(2011AA05A119)
国家自然科学基金项目(51037003)~~
关键词
风电
区间预测
旋转备用
时段耦合约束
优化潮流
wind farm
interval forecast
spinning reserve
multi-period coupling constraints
optimal power flow
