Parameter Identification Of Governing System Of Pumped Storage Unit Based On ISSA And IAHA Algorithms

Pumped storage technology is an important peak shaving technology for renewable energy power generation.It can balance the difference between the load and power supply of the power grid by storing water energy,and is one of the means to improve the stability and reliability of the power grid.However,in actual operation,the dynamic characteristics of the governing system of pumped storage units are influenced by various factors.For example,water level changes,load fluctuations,and water pump turbine fault and other factors will lead to changes in system parameters,affecting the performance and stability of the system.Therefore,it is necessary to identify the parameters of the governing system of pumped storage units.The main research contents of this thesis are as follows:(1)The four modular governor(PID controller and electro hydraulic servo system),pressure diversion system(rigid and elastic water hammer model),pump turbine,generator and load of the governing system of pumped storage unit are derived in detail,and their respective transfer functions and mathematical models are established.And a mathematical model for the governing system of pumped storage units is established,which provides a theoretical basis for subsequent parameter identification.(2)Linear parameter identification for the governing system of pumped storage units.Firstly,an improved salpa swarm optimization algorithm(ISSA)is proposed by integrating Piecewise mapping initialization,sine and cosine strategy to update the leader and elite pool strategy to update the follower strategy.Secondly,the principle of parameter identification is introduced,and three intelligent optimization algorithms are employed to verify the effectiveness of the parameter identification method.Finally,the parameter identification of the linear model of the governing system is analyzed under frequency disturbances of 4%,7%,and 10%.The experimental results show that the parameter identification system is in good agreement with the actual system.(3)Improved artificial hummingbird algorithm(AHA).Two strategies are adopted to improve the artificial hummingbird algorithm: firstly,the Chebyshev chaotic mapping was added to the initialization of artificial hummingbird to increase the diversity of the population;Secondly,the Levy flight was added into the foraging strategy to increase the search space of artificial hummingbirds.Based on the above improved strategy,an improved artificial hummingbird algorithm(IAHA)is proposed,which is applied IAHA to the identification of nonlinear model parameters for the governing system of pumped storage units.Then,under the frequency and load disturbance conditions of 5%,10% and 15%,the nonlinear governing system is analyzed experimentally.The results show that,compared with particle swarm optimization algorithm,ant lion optimization algorithm,gravity search algorithm and artificial hummingbird algorithm,the dynamic response curve of IAHA is the most consistent with the actual curve,with the smallest error of 0.0204,0.0182,0.0128,0.0668,0.0981,and 0.0791.Therefore,the identification of IAHA is the most accurate.