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Economical Dispatch For Microgrid Based On Quantum Behaved Particle Swarm Optimization Algorithm

Posted on:2017-07-22Degree:MasterType:Thesis
Country:ChinaCandidate:Y YangFull Text:PDF
GTID:2322330482987037Subject:Control Engineering
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In the development and utilization of new energy and renewable energy,the high penetration rate and the random fluctuation nature of distributed generations(DGs)will cause a huge impact to the traditional distribution network safety operation.As a typical application of distributed generations,microgrids have been got more and more attention since it can coordinate the contradiction between DGs and the distribution network,and maximize the advantages of DGs in economical efficiency,energy saving and the environment protection.The economic dispatch of microgridshave provided a strongly support for economic operation of DGs.Considering the controllable generation,storage capacity and the load,the day-ahead economic dispatch problems of the micro grid which including photovoltaic power generation,wind power generation,diesel generator and battery energy storage systemat grid connecting and islanding mode are established,then quantum-behaved particle swarm optimization algorithm was adopted to find the optimal economic results in this paper.On the basis of deeply analyzing optimal scheduling mechanism and research method of current microgrids,the mathematical models has been built on the base of the characteristics about the sources,stored energy and load in the system that includes photovoltaic power generation,wind power generation,diesel generator and battery energy storage.Then establish day-ahead optimal scheduling model in grid connecting and islanding modeaccording to the characteristics of the built mathematical models,choosing the output power of battery and diesel as optimal variables when the system is in grid connecting mode,and the output power of battery as optimal variableswhen in island mode,and use quantum behaved particle swarm optimization algorithmto solve the optimization scheduling problem.Because of battery capacity causing significant influence to the economic scheduling optimization of microgrids,the study of different battery capacity to the optimal scheduling in grid connecting and islanding mode under the optimal objective of economic operating costs.Simulation results show that increasing battery capacity can effectively reduce the system operating costs in the grid connecting and islanding mode,and the start-stop frequency of diesel generator will obviously decrease in islanding mode,and the diesel generator will completely stop running when the battery capacity reaches a certain capacity.Gnerally,microgrid closed to big market and the neighborhoods that centralized power supply,which including a lot of shitftable and schedulable load,it will save economic costs if considering shitftable and schedulable load indemand side response.this paper selected the number of shitftable load such as disinfection cabinets,washing machines and electric water heaters and the setting temperature of schedulable load,the air conditions in the one disptach time scale as optimal parameters,established the optimal object which is make full use of photovoltaic power and wind power generation in the grid connecting mode,and use the disesel generater as less as posssible in the islanding mode.Then use the quantum behaved particle swarm algorithm to solve it.Base on the new load results,the day-ahead economic dispatch problems which only consider the controllable DGs and the battery capacity were solved.Compared with the results of optimized dispatching without the consideration of demand side response,more economic costs of Microgrid has been saved;the renewable energy's renewable ability of micro grid has been promoted,when connected to grid.The frequency of diesel engine start-stop in island has obviously declined,which verified the necessity and effectiveness of source,storage and load synchronous optimization.
Keywords/Search Tags:Microgrid, Quantum-behaved Particle Swarm Algorithm, Optimal operation, Demand response
PDF Full Text Request
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