Research On Optimal Operation Of Wind Power-Hydropower Based On Improved Biogeography-Based Optimization Algorithm

As the most rapidly developing renewable energy source in recent years,wind power becomes an important distributed and auxiliary power source.Due to the random fluctuation of the output power of the wind farm,wind power integration can affect the safe and stable operation of the power system,thus restricting the ability of the grid to absorb wind power.In the power system composed of thermal power,wind power and hydropower,hydropower and wind power have good complementarities,and the flexible adjustment capability of hydropower can become an important means to balance and absorb wind power.Based on this,this paper mainly focuses on the randomness of wind power and studies the optimal operation of wind power and hydropower.Firstly,on the basis of analyzing the characteristics of wind power and hydropower,the complementarities between wind power and hydropower in terms of seasonality,technical characteristics,and volatility cycle is studied.Given the randomness of wind power,it is difficult to achieve ideal optimization results by using traditional deterministic methods to establish optimal models.Therefore,this paper introduces chance constraint to describe wind power output in the form of probability.Based on the study of wind power output characteristics and the operating characteristics of cascaded hydropower station,the wind power output is regarded as a random variable.From the perspective of taking into account the reliability and economy of wind power-hydropower optimal operation,and ensuring subsequent power generation capacity of hydropower,a wind power-hydropower multi-objective stochastic optimization model based on chance constraint is established,and the wind power output constrain is established at a certain confidence level,which fully considers the influence of wind power randomness.In order to solve the optimization model,Biogeography-Based Optimization algorithm is introduced in view of the limitations of the traditional optimization algorithm.In view of the strong exploitation ability and weak exploration ability of the algorithm,the cosine migration model,the mutation operation of differential evolution algorithm and the dynamic non-uniform mutation operator are used to improve the algorithm.Improved Biogeography-Based Optimization algorithm is used to solve the optimization model and stochastic simulation technique is used to process the constraints and solve the chance constraint.Taking the optimal operation of wind power and hydropower in the thermal power-wind power-hydroelectric hybrid power system as an example,the simulation results show that the stochastic optimization model considering wind power randomness is superior to the deterministic model,and it verifies that the proposed model and the improved algorithm are feasible and effective.Finally,on the basis of using Improved Biogeography-Based Optimization algorithm to solve stochastic optimization model,the problem that the deviation of wind power-hydropower optimization result from the system's equivalent load in the later period of operation becomes larger.The use of wind power forecasting accuracy has the characteristics of gradually increasing with the reduction of time scale,and it proposes time-division rolling decision.The decision method is to minimize the difference between wind power-hydropower output and equivalent load,and reduce the hydropower deviation at the end of the operation period.According to the new forecast information and the current operating status,the subsequent optimization results of wind power-hydropower are revised.The example simulation shows that this decision method can effectively reduce the deviation between wind power-hydropower output and equivalent load,further reduce the impact of wind power randomness on the optimal operation of wind power-hydropower,and improve the reliability and economy of optimal operation.