摘要
针对风电功率预测偏差影响电力系统发电计划准确性的问题,提出了一种超短期内风电时序动态修正的实时调度模型.该模型采用马尔科夫链时序预测方法,以5~15min为周期动态修正风电超短期预测功率的时间序列,并以煤耗增量最小和弃风最小为双重优化目标,同步修正风电场及常规机组的发电计划,最后将模型转化为凸二次规划及其拉格朗日对偶问题,并基于原-对偶内点法构建求解算法.通过对含风电场的10机组系统的仿真分析表明：所提模型在日内调度过程中进一步优化了系统的运行成本,同时提高了系统跟踪风电功率波动和消纳风电的能力,所采用的求解算法收敛迅速、鲁棒性强,可适应于实时调度的计算需要.
Since wind power predictive deviation will directly impact the accuracy of system generation dispatch,a real-time generation dispatch model taking wind power time series dynamic rectification into account was proposed.The suggested model,adopting Markov forecasting method to carry out the rolling rectification for wind power time series,with dual goals of minimizing wind spillage and incremental total coal consumption,could synchronously correct the wind power and conventional unit′s schedule outputs.With regard to the model solution,it could be considered as convex quadratic and its Lagrangian dual problems,and the solution algorithm could be achieved based on prime-dual affine scaling interior point method.According to the simulation study of a 10units system with a wind farm,it shows that the proposed dispatch model is utilized,and consequently the system operational cost can be optimized more effectively during the intra-day scheduling process,and the capacity of the system absorbing the wind power can be enhanced to a certain degree.Besides,the applied solution algorithm has a rapid convergence and a great robustness,which can satisfy the computation requirement of real-time generation dispatch.
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2014年第3期73-77,共5页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家科技支撑计划资助项目(2013BAA02B02)
关键词
风力发电
电力系统
实时调度
马尔科夫链模型
原对偶内点法
wind power generation
power systems
real-time generation dispatch
Markov chain model
prime-dual affine scaling interior point method
