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Research On Optimal Capacity Sizing For Stand-alone Wind-PV-Diesel-Battery Microgrid

Posted on:2019-06-05Degree:MasterType:Thesis
Country:ChinaCandidate:J J ZhangFull Text:PDF
GTID:2382330548989311Subject:Power system and its automation
Abstract/Summary:PDF Full Text Request
Optimal capacity sizing is an important part of microgrid design,which tries to obtain the optimal capacity of distribute generations and energy storage device by using optimization method based on the characteristics of load,wind speed,irradiance and other natural resources.The optimal capacity sizing need not only ensure the reliability of power supply in the whole microgrid,but improve the economic efficiency and environmental protection.Scientific and rational configuration scheme is significant for reducing the construction cost of microgrid,increasing the renewable energy consumptive level and decreasing the emissions of polluted gas.In the beginning of this paper,research achievements in related fields at home and abroad are summarized and analyzed,then,the analysis method,objective function establishment and objective function solution of the optimal capacity sizing for microgrid are introduced.On this basis,the problem of the optimal capacity sizing for microgrid capacity is thoroughly studied.Firstly,this paper focuses on the optimal sizing for stand-alone Wind-PV-Diesel-Battery microgrid.Using the reliability of power supply as the constraint condition and the minimum average annual cost after weighting as the objective function,this paper constructs a non-linear integer programming model which takes economy,environmental protection and renewable energy utilization into consideration.Aiming at the local optimal problem caused by directly applying continuous optimization algorithm into integer programming model,an improved binary bat algorithm is proposed to avoid this problem,which adopts mutation,crossover and selection operations from differential evolution to improve the global searching ability of standard binary bat algorithm.In a case study,the proposed algorithm shows better performance by comparing the improved binary bat algorithm with genetic algorithm,particle swarm optimization and differential evolution algorithm.Then,in order to take the operation risk of microgrid caused by the uncertainty of wind and solar resource into consideration,a stochastic optimization model based on conditional value at risk is proposed.First,a large number of data scenarios for wind and solar are generated using Latin Hypercube Sampling method.Scenarios reduction is performed by the K-medoids clustering algorithm to obtain several wind and solar scenarios with distinct characteristics and high probability of occurrence.Second,using the reliability of power supply as the constraint condition and considering the economy index and renewable energy utilization index of microgrid,a stochastic optimization model is proposed based on the conditional value at risk with the objective function of annual comprehensive cost.Finally,binary particle swarm optimization algorithm is used to solve the integer optimization model.Based on the simulation case,the proposed stochastic optimization model shows more rational.
Keywords/Search Tags:stand-alone microgrid, optimal capacity sizing, improved binary bat algorithm, uncertainty of wind and solar resource, conditional value at risk, Stochastic optimization model
PDF Full Text Request
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