Application Of Improved Brain Storm Optimization Algorithm In Off-grid Hybrid Renewable Energy System

The National Energy Administration issued the guidance on the implementation of the 13 th five-year Plan for the Development of Renewable Energy,in which renewable energy technology plays a leading role in the field of power generation in the future.Increase the number of solar panels and fans nationwide,which are vulnerable to weather conditions.Therefore,the Hybrid Renewable Energy System(HRES)can solve this problem.HRES can work independently or in grid-connected mode,and achieve higher efficiency than a single power supply through multi-energy complementary mode.The problems such as the scarcity of conventional energy,the rise of fuel prices,harmful emissions from fossil fuel combustion and the unsustainable development of traditional energy generation have been solved.In the Hybrid Renewable Energy System,optimizing the unit size is the key to realize the efficient utilization of renewable energy.Optimizing the size and number of units not only meets the requirements of system reliability,but also meets the requirements of the lowest net present value cost of the system,so that the system can operate under the best conditions.In this paper,around the off-grid hybrid renewable energy system,on the basis of reading and analyzing a large number of literatures,different hybrid renewable energy system models are sorted out,and different methods for solving hybrid renewable energy systems are classified.As the model of system optimization is a number of contradictory objectives,this paper makes a reasonable tradeoff among multiple objectives,and optimizes the unit size and the number and size of units.The clustering algorithm is added to the initial population strategy,solved by the improved brain storm optimization algorithm,and tested with an actual case.The main contributions are as follows.(1)Design of off-grid hybrid renewable energy system.Because the power of the power grid cannot be obtained in remote areas,the generation output of the off-grid model is modeled accurately.The off-grid hybrid renewable energy system meets the constraints of power demand balance,and the objectives include the minimum cost of the system,power loss probability and total fuel emissions.The improved brainstorming optimization algorithm is used to solve the unit size of the system.(2)Research on brain storm optimization algorithm.Brain storm optimization algorithm is the latest intelligent optimization algorithm,which can find the optimal solution faster than mathematical methods.First of all,this paper introduces the basic brain storm optimization algorithm,which classifies the initial population,which can effectively jump out of the local optimal solution of the problem.Then,in order to measure the advantages and disadvantages of each individual,the comprehensive index is used as the fitness value,and the Euclidean distance is used as the method to calculate the distance between classes.Finally,the non-dominant sorting is used to maintain the number of populations,which makes the solution feasible.(3)The brain storm optimization algorithm is improved to solve the off-grid hybrid renewable energy system.In this paper,based on the background of the northeast region of Zaragoza,Spain,the performance of the proposed algorithm is tested by a real example,and different schemes of the number of units are obtained.Then the genetic algorithm is compared with the improved brain storm optimization algorithm to verify the competitiveness of the proposed algorithm.Finally,experiments on different clustering numbers of brainstorming optimization algorithm are carried out to determine the optimal clustering number to solve the problem.