Coordinately Optimal Operation Of Smart Active Distribution Grid

With the world increasingly environmental issues and energy crisis, distributed generation and related technologies are becoming the key research direction of domestic and overseas and get great development:renewable energy power generation technologies, such as wind power, solar power, biomass and waste to energy and so on, become mature and have been promoting around the world.Faced with the diversification and large-scale access of DG, smart active distribution grid (SADG) which is based on advanced automation technology and intelligent communication technology realizes the intelligent integration of traditional distribution network and meets the demand for power supply reliability of distribution system and grid-connected requirement of diverse DGs. In view of the optimal operation problem of SADG, this paper proposes and builds SADG day-ahead with real-time optimal scheduling model, the main work includes the following aspects:(1) Based on the review and study of SADG optimal operation, the integration patterns and operating characteristics of SADG are analyzed:first, analyze the physical structure and explicit the internal structure module and corresponding function of SADG; subsequently, the operation and control mode of main scheduling objects of SADG are analyzed and the scheduling mode is cleared.(2) Considering the diversification and the gradual expansion of DG, the SADG day-ahead with real-time optimal scheduling method based on multi-agent system is proposed, then the SADG day-ahead with real-time optimal scheduling model is built, realizing the decoupling control the scheduling problem of SADG in time and physical level as well as improving the usefulness of the model.(3) Aiming at the solving problem of SADG day-ahead with real-time optimal scheduling model, differential evolution algorithm (DE) is used to solve the day-ahead optimal scheduling model and interior-point method is used to solve the real-time optimal scheduling model, ensuring the global optimality of day-ahead scheduling and rapidity of real-time scheduling. The validation and practicability of the proposed model is verified by the simulation analysis on the IEEE33 node model.