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Multi Objective Optimization Scheduling Of Microgrid Based On Heuristic Rules And Particle Swarm Optimization

Posted on:2018-10-23Degree:MasterType:Thesis
Country:ChinaCandidate:S M ZhangFull Text:PDF
GTID:2322330518459991Subject:Power system and its automation
Abstract/Summary:PDF Full Text Request
To reduce the use of fossil fuels and the emission of harmful gas DG(distributed generation)taking advantage of environmentally friendly energy has become the focus of the study in the word including China who has also put development of renewable energy in the extremely important position.Given distributed generation has the characteristics of intermittency and volatility,utilizing microgrid technology to manage distributed generation has been widely recognized at home and abroad.DG and microgrid technology not only is a way to efficiently utilize renewable energy,but also has some other characteristics: making realization of remote region's electrification more economical;providing energy supplement weak areas of the large grid,even in some cases providing standby power for the large grid and so on.Microgrid at the same time providing the active and reactive power is put forward and the multi-objective optimal operation problem putting the power generation cost,environmental cost and voltage fluctuation amplitude as the optimization goal,based on fuzzy optimization theory is translated into a nonlinear single objective optimization problem,which can be solved by improved particle swarm algorithm.Compared with the traditional model the innovation of this paper lies in introducing the voltage fluctuation function and analyzing whether in the premise of minimizing the voltage fluctuation amplitude the satisfaction of other objective functions keep in an acceptable range,So as to find a good balance between economic and voltage quality satisfaction.Microgrid is an effective way to connect distributed generation.In recent years,it has been widely studied,and the optimal operation of microgrid has become one of the important topics in the research of microgrid.Model of optimal operation of microgrid considering the economic cost,environmental cost,network loss and node voltage fluctuation balances the interests of various stakeholders.In the aspect of algorithm,the elite reverse learning strategy and the worst particle exclusion method are brought into particle swarm optimization algorithm(Particle Swarm Optimization,PSO),which can be used to solve the multi-objective and multi-constraint optimal operation of microgrid.In the process of searching,to enhance the local search ability,chaotic disturbance help the particle to jump out of local optimal solution.The same conditions were established when the optimized operation of the microgrid is solved by using the improved algorithm and the former algorithm Respectively.The superiority of the improved algorithm is verified by comparing the optimization results.
Keywords/Search Tags:microgrid, multi-objective optimization, voltage fluctuation, improved particle swarm algorithm, elite anti learning strategy, the worst particle exclusion, chaotic disturbance
PDF Full Text Request
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