含风电电网关口外送电交易能力的多智能体粒子群分层优化研究

MIAS-PSO Hierarchical Optimization Research of Gate Trading Capability for Power System with Wind Power

随着风电的大规模发展和跨省跨区交易量的不断增加,研究风电并网对外送电交易能力的影响对保证资源优化、交易双方利益极大化有重要的意义。利用多目标随机相关机会规划理论建立关口交易能力的评估模型,采用分层优化结合随机模拟技术和多智能体粒子群算法求解。第一层以风电并网的电力系统经济运行为前提,第二层在极小化本系统购电成本的基础上,求取关口最大外送电交易能力以及机组的外送电交易能力。通过IEEE30节点系统实验和仿真计算,表明该方法能优化本系统的运行、有效获取关口和各机组外送电交易能力指标。

With the large-scale development of wind power and the increasing power exchange of trans-province and transregion, it is more important to evaluate the influence of wind power on the gate exchange capability for the resource optim-ization and bilateral advantage. This paper uses stochastic chance constrained programming( SCCP) of multi-object to create the mathematical model and MIAS-PSO with the hier-archical optimization and stochastic simulation to solve the calculation of gate exchange capability. Firstly, this paper attains the solution of economical dispatch for the minimum purchasing cost in the wind power integrated system. Secondly,it gets the maximum gate exchange capability and some gen-erators' outward exchange capability based on the economical dispatch. The paper also takes wind speed forecasting, its randomness and limited regularity into consideration. The mathematical model and optimization algorithm are proved effective by the IEEE30 node testing and simulation calculation.