摘要
风电的大量接入产生复杂的互联电网运行特性,这需要电网AGC能及时响应能源与负荷的快速、大范围的变化,并根据AGC机组的动态特性发布有效指令,既能进行多时段连续的协调控制,又能保证电网运行的经济性。为此,论文建立了考虑AGC机组动态特性,又考虑风电快速、大范围波动情况下的AGC动态优化控制策略模型。该模型权衡动态优化过程中经济性和指标性的比重,兼顾CPS评价标准,综合发布多时段连续的协调指令。该控制策略模型是一个多约束,大规模,多时段的复杂优化问题,因此采用PSO算法求解运算,结合运行的实际特征,对越限的粒子进行有效处理。通过对某区域AGC策略计算,验证了本控制策略无论是AGC调节费用,还是电网频率或CPS指标等均优于传统的控制策略。
The extensive penetration of the wind power leads to the complicated operating characteristics of the interconnected grid.The automatic generation control(AGC)is required to respond to the large-scale,fast variations of the power and load.In addition,the AGC needs to release the effective instructions according to the dynamic unit characteristics,and achieve the continuous multi-period coordination control while addressing the economic issues of the power grid operation.A dynamic model of the optimal AGC control strategy for interconnected power grids is established considering the dynamic AGC unit characteristics,and the large-scale,fast variations of the wind power investigated.The proposed model weighs the proportion of the economic factors and the indicative targetsin the process of dynamic optimization,takes into account the CPS evaluation criteria,and comprehensively releases multi-period continuous coordination instructions.As the proposed model formulates a large-scale,multi-period optimization problem with multiple constraints,particle swarm optimization(PSO)is adopted to solve it.The particles that violate the constraints are effectively accommodated based on the actual operating characteristics.By simulation,the proposed control strategy is verified to has advantages over the traditional control strategy in both AGC regulation expanse and the power grid frequency/CPS indicator.
作者
许榅增
刘禾
XU Wenzeng;LIU He(Guangzhou Metro Design & Research Institute Co Ltd,Guangzhou 510010,China;School of Control and Computer Engineering,North China Electric Power University,Beijing 102206,China)
出处
《现代电力》
北大核心
2018年第6期33-38,共6页
Modern Electric Power
关键词
动态优化
CPS
机组特性
PSO算法
dynamic optimization
CPS
units’ characteristics
PSO algorithm
