Optimization Allocation Of Distributed Generations In Distribution Network

With the rapid development of economy in China, power demand is increasing quickly and the construction scale of power grids also keep expanding. However, the growth pattern of traditional power is limited by the depletion of nonrenewable energy resources and environmental problems. The distributed generation (DG) is becoming a new research hotspot, which has advantages in terms of making full use of renewable energy, reducing environment pollutants and realizing economic benefits. Nevertheless, DGs connected to the power network have a great influenced on the distribution power flow, power quality, power system protection and other aspects. Rational allocation of DGs not only can reduce the power loss and the reconfiguration of power system protection as well as improve the voltage, supply quality and enhance the security and reliability of power grid, but also improve power supply capacity for feeder lines and delay the upgrade investment. Therefore, this thesis mainly aims to study the location and capacity allocation of distributed generations connected to network.The analysis of power flow calculated method and its mathematic model for distribution networks containing DGs are described in detail. The optimal allocation model is established based on the following conditions. Among them, the objective function is to minimize the power loss of the distributed network and the operation cost of distributed generation, respectively. For the constraint conditions, the node voltage, transmission capability and single and the whole DGs’capacity are both considered in this paper the penalty function method is used to deal with the constraints mentioned above. On the basis of genetic algorithm and colony algorithm, a new hybrid algorithm that mixes genetic algorithm and colony algorithm is proposed and the deep study on its parameter settings of the new algorithm and its application to the optimization allocation of DGs in distribution network is performed.MATLAB7.11programming software is considered as the simulation platform and IEEE33nodes network is used to optimize the location and capacity of DGs. The simulation results demonstrate a good performance of the proposed algorithm both in search speed and in accuracy. The result indicates that optimal configuration of DGs takes effect on reducing network loss, improving the voltage of load and the load capacity of feeder and achieving satisfactory economic benefits.