This paper addresses a terminal sliding mode control(T-SMC) method for load frequency control(LFC) in renewable power systems with generation rate constraints(GRC).A two-area interconnected power system with wind turb...This paper addresses a terminal sliding mode control(T-SMC) method for load frequency control(LFC) in renewable power systems with generation rate constraints(GRC).A two-area interconnected power system with wind turbines is taken into account for simulation studies. The terminal sliding mode controllers are assigned in each area to achieve the LFC goal. The increasing complexity of the nonlinear power system aggravates the effects of system uncertainties. Radial basis function neural networks(RBF NNs) are designed to approximate the entire uncertainties. The terminal sliding mode controllers and the RBF NNs work in parallel to solve the LFC problem for the renewable power system. Some simulation results illustrate the feasibility and validity of the presented scheme.展开更多
储能技术是构建以新能源为主体的新型电力系统的关键技术和维持微网可靠稳定运行的重要保证。国内外现有理论研究及示范工程主要集中于单级式链式储能系统,功率模块与电池系统之间无源连接,结构简单但控制自由度不高。同时,针对基于链...储能技术是构建以新能源为主体的新型电力系统的关键技术和维持微网可靠稳定运行的重要保证。国内外现有理论研究及示范工程主要集中于单级式链式储能系统,功率模块与电池系统之间无源连接,结构简单但控制自由度不高。同时,针对基于链式储能的电池荷电状态(state of charge,SOC)不均衡问题,现有的相内SOC均衡控制策略存在不同负载率适应性不足、极度不均衡时可能过调制等缺点,为此,文中基于两级式链式储能系统,研究其总体控制策略,对相间、相内SOC均衡策略进行分析,并提出一种自适应的相内SOC均衡策略,详细说明均衡控制参数的设计原则。该策略能有效地改善链式储能系统在轻载、重载等不同工况下的适应性和均衡效果。最终通过仿真验证了所提控制策略的可行性和有效性,从而为工程实施提供理论储备和技术支撑。展开更多
基金supported by National Natural Science Foundation of China(60904008,61273336)the Fundamental Research Funds for the Central Universities(2018MS025)the National Basic Research Program of China(973 Program)(B1320133020)
文摘This paper addresses a terminal sliding mode control(T-SMC) method for load frequency control(LFC) in renewable power systems with generation rate constraints(GRC).A two-area interconnected power system with wind turbines is taken into account for simulation studies. The terminal sliding mode controllers are assigned in each area to achieve the LFC goal. The increasing complexity of the nonlinear power system aggravates the effects of system uncertainties. Radial basis function neural networks(RBF NNs) are designed to approximate the entire uncertainties. The terminal sliding mode controllers and the RBF NNs work in parallel to solve the LFC problem for the renewable power system. Some simulation results illustrate the feasibility and validity of the presented scheme.
文摘利用温控负荷(thermostatically controlled load,TCL)作为调频资源参与电网调频是应对高比例可再生能源发电并网导致电力系统维持频率稳定能力下降的有效手段。文中提出一种基于动态下垂控制的TCL一次调频控制策略,考虑聚合商TCL平均温度状态(state of temperature,SOT)、调频容量和系统频率变化率,构建动态下垂控制模型,实时调整下垂控制系数,改变TCL聚合商调频参与度。当向上调频时,锁定关状态TCL;当向下调频时,锁定开状态TCL,确保频率快速恢复至额定值附近。同时,为确保用户的舒适度,利用TCL的SOT优先级排序列表派遣法,确定TCL参与调频顺序。在Matlab/Simulink平台上进行仿真分析,仿真结果验证了文中所提策略在确保用户舒适度、改善频率质量等方面的有效性。
文摘储能技术是构建以新能源为主体的新型电力系统的关键技术和维持微网可靠稳定运行的重要保证。国内外现有理论研究及示范工程主要集中于单级式链式储能系统,功率模块与电池系统之间无源连接,结构简单但控制自由度不高。同时,针对基于链式储能的电池荷电状态(state of charge,SOC)不均衡问题,现有的相内SOC均衡控制策略存在不同负载率适应性不足、极度不均衡时可能过调制等缺点,为此,文中基于两级式链式储能系统,研究其总体控制策略,对相间、相内SOC均衡策略进行分析,并提出一种自适应的相内SOC均衡策略,详细说明均衡控制参数的设计原则。该策略能有效地改善链式储能系统在轻载、重载等不同工况下的适应性和均衡效果。最终通过仿真验证了所提控制策略的可行性和有效性,从而为工程实施提供理论储备和技术支撑。