Modeling And Operation Optimization Of Wind-Solar-Water-Storage Multi-Energy Complementary System

Now the effective method to alleviate the energy crisis is building a new power system with new energy as the main body.It is significant to construct new power systems that using new energy such as solar energy,wind energy,and hydro energy to explore the wind-solar-water-storage multi-energy complementary development model.What’s more,small hydropower,wind power and photovoltaics are unstable and hard to meet the system stability conditions.By controlling the charging and discharging of the energy storage battery,the problem of output fluctuation can be effectively solved,and the safety and stability of the power system can be ensured.The main subjects of current research is effectively reducing the instability of complementary output of new energy sources such as wind and solar and optimizing the operation and scheduling mode of multi-energy complementary systems,so as to improve the efficiency of new energy utilization.Firstly,establishing a multi-energy complementary simulation model of wind,photovoltaic and water storage including small hydropower system by combining numerical simulation and physical model,this thesis verifies the reliability of the simulation model through the experimental data of the physical model.Then,the optimal scheduling model of wind,solar and water storage is established based on the fluctuation and economy of the system output and the constraints of load balance.According to the wind,light and load forecast values combined with the power supply constraints,the optimization algorithm is used to solve the scheduling model,so as to obtain the optimal scheduling scheme for the economy of the multi-energy complementary system.The specific work steps are as follows:(1)Establish a windsolar-water-storage multi-energy complementary simulation model containing small hydropower,and carry out numerical simulation calculation of the output data in the simulation model according to different working conditions.Through the verification of simulation data and experimental data,it is shown that each part of the simulation model has a good complementary performance,and the simulation can be carried out for different environments and working conditions.(2)Compared with the LSTM model,the artificial fish swarm algorithm with higher prediction accuracy was selected to optimize the generalized regression neural network prediction model.After calculation,the wind,light and load output prediction works best when the optimal smoothing factor was calculated to be 0.2.(3)Taking both the load forecast data and all constraints into consideration,the optimal scheduling model of the wind-solar-waterstorage complementary system is constructed with the fluctuation and economy of the system output.Compared with the mopso algorithm,the NSGA-Ⅱ algorithm owns the characters of faster convergence speed and higher accuracy when solving the optimal scheduling model.When only wind and light are connected to the system,the NSGA-Ⅱ algorithm improves the solving effect by 8% compared with mopso.The advantage is most obvious in the combined wind-water storage system,and the optimization effect is increased by 15%.It effectively reduces the output instability of small hydropower,wind-photovoltaic and photovoltaic complementary systems that add energy storage batteries to the windsolar-water-water complementary system to construct a wind-solar-water-storage complementary system.When wind power or photovoltaic power is supplied independently,the mean square deviation of the output fluctuation of the system reached 21.18;when the wind and solar power are jointly powered,the mean square deviation of the system output fluctuation of the system is reduced to 13.8;when the wind and solar complementary system is introduced into the hydropower and energy storage part to form a wind-solar water storage complementary system,the deviation is reduced to 9.5.Using the NSGA-Ⅱ optimization algorithm to optimize the scheduling of the wind-solar-water-storage complementary system,the most economical cost is21320.53 RMB per day,which reduces the operating cost by 79 RMB a day compared with the use of mopso algorithm,which effectively increases the utilization rate of wind and solar energy and improves the operating economy of the system.