Research On Microgrid Optimal Dispatch Model With Mobile Power Storages

Developing of Distributed Generation (DG) can effectively address the problem of energy exhaustion and environment pollution. However, the characteristics of DG, i.e. intermittent, diversity and coplextity, become the important factor that obstacle the improment. Microgrid, an entity of various distributed DGs, can become a significant supplement to traditional centralized genearion, and improve electricity supply reliability and energy utilization efficiency. Furthermore, the enormous efforts in the ppursuit of low carbon energy consumption have led to a great boom in the utilization of Electric Vehicles (EVs). However, the integration of EVs into the traditional power distribution networks can bring out technical challenges due to their dynamic behaviors.In this paper, optimal energy management for Microgrid is studied. The main work is presented as follows:1. By adopting the existing a statistical model of driving behaviors of PEV owners as well as Latin Hypercube Sampling (LHS) scenario generation and Simultaneous Backward Reduction technique for the stochastic wind power model, we proposed three coordinated energy dispatching methods, i.e. the valley searching, interruptible and variable-rate dispatching methods, to optimize the utilization efficiency of volatile wind power generation,leverage the power generation and demand in a microgrid environment as well as improve the Average Satisfaction Degree (ASD) of EVs owners.2Considering the characteristic of bidirectional energy flow of EVs, we propose the energy dispatch model and strategies for the combined heat and power microgrid including EVs. In this model, not only the micro sources characteristics of the microgrid are considered, but also the operational constraints of micro sources and the influence of time-of-use price are taken into account. Based on the typical daily load data for a microgird network in different seasons, the optimal output of each micro source with the aims, such as minimization of total costs and pollutant emission, is solved using an Improved Particle Swarm Optimization (IPSO) algorithm. The characteristics of economic operation in microgrid are summarized and the accuracy of the proposed model is verified based on the simulation results. Beside, incorporating EVs within the microgrid with smart charging strategy can not only realize peak clipping and valley filling, but also bring considerable income to the EVs owners.