Multi-Types Of Distributed Generators Planning Based On Novel Immune Clonal Algorithm

Distributed Generators (DG) has developed rapidly because of its benefits of the flexibility, shorter construction period and environmental friendliness. However, with a large number of DG connecting to the distribution network, it has a great impact on voltage distribution, network loss, system protection and reliability of distribution network. The degree of impact is closely relative with the site and size of DG. Therefore, it is important to perform research on the optimal allocation of DGs to assure the economical operation.Firstly, the significance and current situation of DG are elaborated, and the applications of a variety of distributed generation technologies and their impact on the distribution network are made detailed analysis based on summarizing the status of distributed power planning study. According to the characteristics of instability and load fluctuations of wind power and solar photovoltaic generation, DG planning model considering its timing characteristics is proposed, on the basis of study of output characteristics of multiple DG, energy storage devices applied to the power output fluctuation of wind power and solar photovoltaic generation furthermore this paper establish were used to establish multi-objective programming models which considering the economy and stability of the system operation and environmental factors. and novel immune clonal algorithm (NICA) is used to solve this model. The NICA uses the overall clonal non-dominated ones, non-uniform mutation and removing Pareto-front-intensive solutions to ensure the convergence speed and the uniformity of solution. The NICA is evaluated by using three classic test functions and three performance indicators and is compared with Non-dominated Sorting Genetic Algorithm Ⅱ and Strength Pareto Evolutionary Algorithm 2 which are both classic multi-objective algorithms. Then its superiority is verified.Taking the IEEE33 bus system for example, by comparing and analyzing the results of solving NSGA-Ⅱ and SPEA2, the effectiveness of NICA to solves DG planning model is verified. The planning models established in this paper considered the power output and load instability of some types of multiple DGs. So the planning results are closer to the actual results and have some practical value and significance.