Research On Distributed Generation Planning Based On DENPC

Distributed technology with clean energy is the development trend of the future electrical power system.Interconnection of Distributed Generation(DG)can significantly enhance the sufficiency of energy utilization and electrical stability.DG planning problem is an optimization problem,and the corresponding mathematical model can be solved by applying novel intelligence algorithms.However,the configuration of distribution network is becoming more and more complex,this kind of problem can hardly be tackled by traditional mathematical techniques.Differential Evolution(DE)is a effective,simple,robust and easily applicable intelligence algorithm,can be easily applied to the DG planning in distributed network.Here in this paper,we introduce a novel adaptive DE variants,named DENPC(Differential Evolution with Novel Parameter Control),for DG disposition.The main work of this paper can be summarized as follow:1)There are many different types of DG which have different output characteristics.In view of the different output characteristics,we present the simplified mathematical model of three typical kinds of DG,including photovoltaic power generation,wind power generation and fuel cell,for load flow calculation.2)DE algorithm is investigated intensively in this paper.Although DE has show excellent performance in tackling different optimization problems,there still are some weaknesses in DE algorithm.The classical DE with fixed parameter values is easily trapped into local optimization,and some adaptive DE variants rely too much on the fitness difference.In order to overcome the drawbacks mentioned above,we proposed a novel location information based parameter control strategy in DENPC.The location information of the population is utilized to guide the generation of future parameter values,and promising optimization property can also be obtained by employing the novel parameter adapting strategy.3)Benchmarks from CEC2013 test suit are employed to verify the validity of the proposed DENPC algorithm.Experiments are conduced under 30 and 50 dimension,and the experimental results show that the novel DENPC algorithm outperforms other DE variants in both optimization precision and convergence speed.4)The objective function in this thesis has three goals,including construction cost of grid and the network loss cost are minimum,the environmental value is maximum.The 33 IEEE node distribution system is employed to verify the validity of the proposed method.The proposed optimization approach is compared with partial swarm optimization(PSO)and classical DE algorithm under the DG planning model.The experiment results shows that the promising performance can be obtained by our approach.Besides,The voltage stability and the loss of network can be clearly improved by adding DG into the power grid.