Multiobjective Dynamic Optimal Power Flow Considering Fuzzy-Based Smart Utilization of Mobile Electric Vehicles
Multiobjective Dynamic Optimal Power Flow Considering Fuzzy-Based Smart Utilization of Mobile Electric Vehicles
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DOI：
10.1109/tii.2016.2518484
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发表时间：
2016-01
影响因子：
12.3
通讯作者：
R. Azizipanah‐Abarghooee;V. Terzija;F. Golestaneh;A. Roosta
中科院分区：
文献类型：
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作者：
R. Azizipanah‐Abarghooee;V. Terzija;F. Golestaneh;A. Roosta
针对插电式电动汽车（pev）的充放电（C/D）节点，设计了一种高效智能的模糊逻辑控制器（FLC）。所设计的控制器控制由这些节点补偿的功率量，以满足所需的削峰和电压平坦。本研究的主要重点是在多目标安全约束的动态最优潮流（OPF）问题中实际协调移动pev，该问题的目标是在24小时时间范围内同时最小化运行成本和排放。在问题的表述中，还考虑了阀点效应、多燃料选择、禁区和交流潮流方程的非光滑、非凸和非线性性质。这一复杂问题需要一种鲁棒、快速、强大的优化算法，该算法能够提取出pareto最优曲面（POS）。为此，提出了一种新的改进黑洞（IBH）算法，该算法采用新的粒子更新公式，可以更大程度地探索和合理利用搜索空间。将该框架应用于包含多个聚合pev的IEEE 118总线测试系统，验证了该框架的有效性和能力。
In this study, an efficient and smart fuzzy logic controller (FLC) is designed for charging/discharging (C/D) nodes of plug-in electric vehicles (PEVs). The designed controller controls the amount of power to be compensated by these nodes in order to meet the required peak shaving and voltage flattening. The main focus of this work is to practically coordinate the mobile PEVs in a multiobjective security constrained dynamic optimal power flow (OPF) problem that aims at simultaneously minimizing the operation cost and emission over 24-h time horizons. In the formulation of the problem, nonsmooth, nonconvex, and nonlinear natures of valve-point effects, multifuel options, prohibited zones, and ac power flow equations are also considered. This complex problem needs a robust, fast, and powerful optimization algorithm, which is able to extract the Pareto-optimal surface (POS). Hence, a new improved black hole (IBH) algorithm is proposed with a new formulation for updating particles to allow a greater exploration and appropriate exploitation of the search space. The proposed framework is applied on IEEE 118-bus test system incorporating several aggregated PEVs to show its efficiency and ability.