A hybrid technique for grid-connected solar-wind hybrid system with electric vehicles

被引:6
作者
Ponnapalli, Bhanu [1 ,5 ]
Lakshmikhandan, K. [2 ]
Palanisamy, Kannan [3 ]
Sithambaram, Muthukumaran [4 ]
机构
[1] SA Engn Coll, Dept Elect & Elect Engn, Chennai, India
[2] Madanapalle Inst Technol & Sci, Dept Elect & Elect Engn, Madanapalle, India
[3] Vivekanandha Coll Engn Women, Dept Elect & Elect Engn, Tiruchengode, India
[4] PSNA Coll Engn & Technol, Dept Elect & Elect Engn, Dindigul, India
[5] SA Engn Coll, Dept Elect & Elect Engn, Chennai, Tamil Nadu, India
关键词
Electric vehicle; wind turbine; photovoltaic; Mexican axolotl optimization; wild horse optimizer; least levelized cost of electricity; annualized cost of the system; CHARGING STATION; RENEWABLE ENERGY; PHOTOVOLTAIC SYSTEM; BATTERY STORAGE; MODEL; OPTIMIZATION; MANAGEMENT;
D O I
10.1177/0958305X231153933
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This article proposes a hybrid technique for a grid-connected solar-wind hybrid system with electric vehicles. The Mexican Axolotl Optimization and wild horse optimizer are the proposed optimization techniques. The wild horse optimizer improves the axolotl's life behavior. As a result, the proposed scheme is conducted while reducing the annualized cost of the system and utilizing the proposed method. Using modern optimization approaches, the component is sized to achieve the lowest levelized cost of electricity by decreasing the loss of power supply probability. Lastly, the sensitivity analysis is performed to analyze the influence of maximum grid sales and buy capabilities on levelized cost of electricity. The proposed technique's performance is then executed in MATLAB environment and compared to several current methodologies. As a result of the simulation outcomes, the efficiency and performance of the current method are compared to other techniques. According to simulation outcomes, the energy management system (EMS) may lower general expenses by more than 55% and 29% in summer and winter, respectively, while ensuring the satisfaction rate of demand for electric vehicle-charging without knowing the departure times of electric vehicles.
引用
收藏
页码:2753 / 2789
页数:37
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