A Modeling Method For Smart Distribution Network Optimization Problem Based On Conic Programming

With wide application of distribution generation(DG), soft normally open point(SNOP), energy storage system(ESS), and demand response, distribution network has transformed into a new type of power supply system with functions of electric energy collection, transmission, storage and distribution, which is also the core of smart grid technology. Due to the variety of DG technologies, different operation strategies should be considered in compliance with their control modes and technical features. Therefore, the planning of DG play a significant role to the reliability and economics of the distribution system it integrated. In the intelligent development mode, distribution network will actively invoke some technologies, such as DG, SNOP, ESS, smart terminal as well as reactive power compensation. Consequently, it will realize the effective management of power flow and operation optimization. Therefore, smart distribution network optimization problem can be divided into two stages- planning and operation optimization, and these two stages interact to each other. Mathematical modeling and calculation solving will be more complicated when a large number of new equipment start to participate into distribution network regulation. There is no doubt that this exploration should be based on efficient modeling and simulation methods. In this paper, intelligent distribution network optimization problem is taken to research. The main work is summarized as follows:Proceeding from distribution network steady-state modeling aspect, power conversion(PC) elements, power delivery(PD) elements, and control elements are modeled respectively. PC elements are modeled as Norton equivalent circuits. PD elements are represented by admittance matrix. Control elements don't belong to electrical components and thus don't need to participate in formatting system equations.A modeling method based on conic programming(CP) for smart distribution network optimization is proposed in this paper while taking DG allocation, SNOP and ESS as the optimizing technologies. The theory foundations of conic optimization are represented, including standard model, duality, complementarity and smooth reconstruction method. With constraints boundary of DG allocation, SNOP and ESS set up, a conic optimization model of distribution network optimization is built through objective function linearization and constraint transformation.The optimal capacities of DG under different penetrations and different power factors levels are analyzed. Operation optimization for distribution network based on SNOP is analyzed. The potential advantages of SNOP are verified compared with network reconfiguration from static and dynamic power flow optimization respectively. Moreover, operation optimization of distribution network with ESS participating is analyzed. The optimization scheme of ESS is contrasted with relationship between the power supply and demand. Results verified that the energy storage system is efficient to smooth the fluctuation of renewable energy resources and optimize the power flow. In addition, numerical studies are also validating the effectiveness and out-performance of the proposed CP method.