摘要
随着可再生能源的大规模并网,其间歇和随机特性给电力系统的频率稳定和控制带来巨大挑战。基于现有自动发电控制框架,根据常规发电机组和插电式电动车(PEVs)的互补特性,提出了一个基于模型预测控制(MPC)的优化控制框架。MPC负荷分配器根据常规发电机组和PEVs不同时间尺度的动态和AGC执行周期,在满足调节功率和电能约束的条件下,协调控制来自常规发电机组和PEVs的调节功率,使ACE跟踪误差和调节成本最小。仿真结果证明,提出的方法能够实现AGC性能的改善和调节成本的节约。
With the large-scale interconnection of Renewable Energy Sources （RESs）, their intermittent and stochastic characteristics bring great challenges to the frequency stability and control of the power system. Based on the existing automatic generation control framework, an optimal control framework based on model predictive control （MPC） is proposed according to the complementary characteristics of conventional generators and plug-in electric vehicles （PEVs）. The MPC load distributor can control the regulation power from conventional generator sets and PEVs according to the dynamic and AGC execution cycles of conventional generator sets and the PEVs at different time scales, so that the ACE tracking error and the adjustment cost can be minimized by meeting regulation power and power constraints. Simulation results show that the proposed method can achieve AGC performance improvement and cost saving.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2018年第1期63-70,共8页
Power System Protection and Control
基金
国家自然科学基金项目(50937002)~~
