摘要
近年来,由于风电渗透率持续增加而电网消纳能力有限,造成风机产能过剩,"弃风"现象开始凸显。为保证电力系统的稳定运行,要求风电场主动参与系统调频,根据电网调度部门指令控制其功率输出。将风速预测信息与尾流效应模型结合起来,预测场内每台机组的最大出力。在此基础上,以提高风电场效益为目标,建立了限电情况下风电场内机组组合问题的数学模型,并利用改进的粒子群算法进行优化研究,得到限电情况下风电场内机组最优组合方案。最后通过实际算例进行仿真分析,验证了所提出方法的可行性和优越性。
In recent years, penetration of wind power continuously increases but wind power can not be completely consumed by the grid, it leads to energy waste in a large scale and wind curtailment becomes prominent. To insure the grid＇ s stability, wind farms must actively take on the task of frequency modulation and control the power outputs in keeping with requests from power grid dispatch center. This paper predicts the maximum power output of each turbine by the wind speed forecasting information and wake model then presents a mathematical model and adopt a modified particle swarm optimization algorithm to solve the unit commitment problem for the benefit of the wind farm. The actual case examination is carried out and the result testing result indicates the feasibility and advancement of the proposed method.
出处
《可再生能源》
CAS
北大核心
2014年第9期1319-1326,共8页
Renewable Energy Resources
基金
中丹国际科技合作专项项目(2014DFG62530)
教育部留学回国人员科研启动基金(2012-940)
关键词
风电场
弃风
风速预测
机组组合
粒子群算法
wind farm
wind curtailment
wind speed forecast
unit commitment
particle swarm optimization algorithm
