Coordinated Allocation Of Distributed Generation And Controllable Switches In Distribution Systems

It is a new challenge for distribution network planning with a large scale peneation of distributed wind power. It is a significant problem for improving the efficiency of the use of wind power and holding the economical cost and reliability of the distruted systems by considering how to deal with a coordination of the source-network-load planning. Current research literatures are mainly focused on the coordinated planning of the new energy and controllable distributed generators, but haven’t fully considered the coordination of switches and controllable load. Based on the above problems, this paper is proposed a study on the source-network-load the coordination of planning model and algorithm for the three aspects of the wind power and switch, energy storage power and switch and controllable DG/controllable load and switching coordinated planning respectively. Thus, the main innovative studies are as follows:① A method considering the coordination planning of the controllable switch and DWG was developed. The decision variables of this model are the capacity and position of distributed wind power and the position of the switch, the objective function are three goals including switch and distributed wind power investment and operation cost minimum, reliability and best environmental benefits. The constraint equations include network security constraints and the constraints of wind power high penetration. For connected wind power that has contributed to the reliability of distribution system in this model, the method proposed an estimation method for connected wind power system on the yearly supplied power shortage. In view of the mixed integer programming and multi-objective problems, the coordinated planning of DWG and switch with inferior sorting multi-objective genetic algorithm(ga) is proposed. The simulation results of two IEEE example systems verified the effectiveness of the proposed model and algorithm.② A model for coordinated allocation of BESS and controllable switches is developed in the distribution network. The decision variables of this model are the energy storage system capacity and switch position. The objective functions are the minimum comprehensive investment and operation cost of switch and energy storage system and the minimum loss power energy of system. The constraint equations consider the charge and discharge characteristic of the energy storage system constraints and network security constraints. For the influence of island stroke/storage system on the operation reliability of distribution network, the method proposed an estimation method for the wind/storage distribution system on the yearly supplied power shortage. In view of the mixed integer programming and multi-objective problem, a multi-objective hybrid intelligent algorithm using the decomposition strategy for the discrete variable and continuous variable is proposed. The simulation results of two IEEE example systems verified the effectiveness of the proposed model and algorithm.③ A coordinated allocation model for controllable distribution generation and switchers considering the impact of demand response and wind power generators is proposed. The decision variables of the model are controllable capacity of DG, switch position and power regulation of controllable load. The objective functions include the integrated minimum investment operation cost of the controllable DG and switch considering the impact of demand response and the minimum loss energy of system. Constraint equations are the network security constraints and operation constraints of demand response. For the influence of demand response on the wind power grid controllable DG island system, this method proposed an estimation method for distribution system with controllable distribution generation and demand response on the yearly supplied power shortage. In view of the mixed integer programming and multi-objective problem, a multi-objective hybrid intelligent algorithm using the decomposition strategy for the discrete variable and continuous variable is proposed. The simulation results of two IEEE example systems verified the effectiveness of the proposed model and algorithm.