Research On Challenge And Countermeasures Of Renewable Energy Integration

After large-scale new energy power generation is connected to the power grid,due to its inherent volatility and randomness,the number and depth of adjustments of conventional units are greatly increased,which will bring voltage peaking,active imbalance,power flow randomness to the power system and other adverse effects.Therefore,the grid needs to have more flexibility to match the grid connection of new energy generation.If the traditional power supply cannot follow the load change,it is necessary to discard the wind or cut the load to ensure the safe and stable operation of the power system.However,abandoning the wind and abandoning the light is not in line with the vision of the whole society to vigorously develop new energy.The load shedding will bring adverse effects and economic losses to the society.Therefore,more acceptance of new energy generation and grid connection,improving new energy consumption capacity,and building a clean power system are of great significance to the development of China's power grid.Studying the impact of new energy generation on the grid and how to deal with the challenge is an issue of current importance.In this context,this paper discusses the challenges and countermeasures brought by the integration of new energy into the power system,and focuses on the optimization model and scheduling method of the unit combination problem of the wind-fire combined power generation system.First of all,this paper analyzes the wind power output and photovoltaic power output characteristics.Subsequently,the challenges brought by wind power grid-connected and photovoltaic grid-connected power systems were summarized,and two common power optimization schemes for improving new energy consumption capacity were summarized:wind-fired combined power generation optimization dispatching,wind-light storage joint optimization dispatching,The article mainly studies the wind-fire combined bundling power generation.The paper establishes a mathematical model of unit combination optimization including wind power,including three objective functions of economy,environmental protection and wind power consumption capacity,and considers the positive and negative rotation reserve constraints established by making up for the randomness of wind power.The discrete particle swarm optimization(DPSO)-quadratic programming(QP)hybrid intelligent algorithm is used to decompose the unit optimization scheduling problem into two internal and outer sub-problems for analysis and solution.The outer layer uses the discrete particle swarm optimization algorithm to optimize the start-stop state of the unit,and determines the start-stop scheme under the optimal output.The inner layer uses the quadratic programming method to optimally process the output of the starting unit to obtain the optimal solution.Through 10 thermal power units and 2 wind farm system examples,PSO and DPSO-QP were used to solve the problem of unit start-stop combination and load optimization distribution of wind farms connected to the grid and compare the results.The simulation results show that the algorithm can realize the optimization operation of combined unit scheduling of wind-fire combined system under the influence of wind power fluctuation and randomness.It satisfies the economics of power production while taking into account the economics of the system,showing the effectiveness and feasibility of the algorithm.In short,based on the in-depth understanding of the new energy output characteristics,analyzing the challenges brought by the new energy grid connection to the power grid,researching the power supply optimization with new energy has certain theoretical and practical significance for improving the new energy consumption capacity.