Distribution network reinforcement planning for high penetration level of distributed generation

Abstract

High penetration levels of distributed generation (DG) significantly affect the operations of distribution networks that they are connected. Different network reinforcement alternatives that provide different levels of improvements to fit with special requirements of individual utility are available. From a cost-benefit point of view, an optimal investment strategy is necessary for network reinforcements in a cost-effective manner. This paper aims presenting a methodology for optimal planning of network reinforcements to accommodate increased connection of DG to distribution networks. An objective function, which contains three objectives including investment cost, customer interruption cost, and network losses conversion cost, is minimized subject to system operation constraints. A multi-stage approach based on genetic algorithms (GAs) is then used to derive long-term investment planning and network configurations in the planning period. Test results of a practical distribution feeder system connected to wind power generations is selected for computer simulation in order to ensure and demonstrate performance of the proposed method.