Distributed Generation Planning Considering The Different Investment Subjects

With the continuous consumption of fossil energy and environmental problem becoming increasing serious, distributed generation(DG) has attracted much attention with the characteristics of flexible generation and environment friendly. Under the reasonable planning, the economic and technical performance of distribution network can be promoted by the application of DG. At the same time the relevant state policy of DG develops, the barriers of DG have been reduced. More and more investors will enter the field of DG. In addition, different investor has different intrest of investing DG. With the diversification of investment subject, it is necessary to study DG planning considering different investment subject.The common characteristics of DG and the time characteristics of DG generation and load are introduced. With the distribution company being the investment subject, DG planning model considering time characteristic and renewable energy utilization is proposed. With the independent power suppliers(IPS) being the investment subject, DG planning model considering the benefits of several IPSs is proposed, and the Pareto optimal solution set is obtained by using NSGA-II, and the distribution company is the decision-making subject. Network loss, voltage quality and delayed network renewal are chosen as the decision index. Muti-objective decision making method based on vague set is used to analysis the Pareto solution set and the best DG planning scheme is obtained. With the distribution companies and IPS being the joint investment subjects, two-stage and muti-objective DG planning models are proposed. In the first stage, the model considering renewable energy utilization, voltage quality and delayed network renewal is proposed and solved by NSGA-II. The best DG planning scheme is obtained by using muti-objective decision making method. Based on the best DG planning scheme in stage one, in stage two, DG planning model considering the benefits of several IPSs is solved and the Pareto solution set is also evaluated by muti-objective decision making method. Finally, the model and solving method are verified in planning cases.