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Research on multi-objective optimisation coordination for large-scale V2G

机译:大型V2G的多目标优化协调研究

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Vehicle-to-grid (V2G) technology plays an important role in solving the large-scale disordered charging and discharging behaviour of the electric vehicles (EVs). V2G mode based on microgrid is used for multi-objective optimisation coordination between the EVs and the power grid, and a multi-objective optimisation model, in which minimum grid load fluctuation, maximum renewable energy utilisation and maximum benefits for the EV users as the optimisation objectives are established. In order to solve the optimisation model, searching valley scheduling algorithm, variable threshold optimisation algorithm and variable charge/discharge rate optimisation algorithm are proposed successively. In order to verify the control effect, the three proposed algorithms are compared with the without optimisation algorithm. The results show that the three proposed algorithms, in a manner, could improve the imbalance between power supply and demand of the microgrid; increase utilisation of renewable energy; and bring certain benefits to the EV users. By analysis of experimental data, the control effect of variable charge/discharge rate scheduling algorithm is the best in the three scheduling algorithms.
机译:车对网(V2G)技术在解决电动汽车(EV)的大规模无序充电和放电行为中起着重要作用。基于微电网的V2G模式用于电动汽车与电网之间的多目标优化协调,以及一种多目标优化模型,该模型以最小的电网负荷波动,最大的可再生能源利用率和最大的电动汽车用户收益为优化目标目标已经建立。为了求解该优化模型,相继提出了搜索谷调度算法,可变阈值优化算法和可变充放电速率优化算法。为了验证控制效果,将所提出的三种算法与无优化算法进行了比较。结果表明,所提出的三种算法在一定程度上可以改善微电网的供需不平衡。增加可再生能源的利用;并为电动汽车用户带来一定的好处。通过对实验数据的分析,在三种调度算法中,可变充放电速率调度算法的控制效果最佳。

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