Battery energy storage with renewable energy sources integration in unbalanced distribution network considering time of use pricing

被引:0
|
作者
Ray, Sigma [1 ]
Kasturi, Kumari [1 ]
Patnaik, Samarjit [2 ]
Nayak, Manas Ranjan [3 ]
机构
[1] Siksha O Anusandhan Univ, Dept Elect Engg, Bhubaneswar 751030, Odisha, India
[2] Odisha Univ Technol & Res, Sch Elect Sci, Bhubaneswar 751029, Odisha, India
[3] Biju Patnaik Univ Technol, Dept Elect Engn, Rourkela 769015, India
关键词
Renewable energy; Battery energy storage; Unbalanced distribution system; Pelican optimization; Voltage unbalance factor;
D O I
10.1016/j.ref.2024.100630
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The increasing demand for sustainable energy solutions and the escalating energy demand have facilitated the emergence of renewable energy sources (RES), such as photovoltaic (PV) sources. Combining RES with battery energy storage system (BESS) technology reduces peak hour demand and allows for economical charging and discharging for time-based energy pricing. Integrating PV and BESS in an unbalanced system with multiple RES sources is a challenging task. It requires a robust algorithm to minimise power loss in the distribution system and decrease the voltage unbalance factor (VUF). This paper presents a new multi-objective Pelican optimisation algorithm (MOPOA) for the optimal allocation of PV and BESS. The MOPOA helps find the best placement of PV and BESS in an IEEE-33 bus unbalanced radial distribution system (URDS). The proposed algorithm combines multiple benefits from a lower net present cost (NPC) and a higher voltage profile enhancement index (VPEI). The case studies and simulation results show that the proposed method places PV and BESS in IEEE 33-bus URDS optimally, satisfying all of the system's requirements. The results indicate an improvement in the minimum VUF factor of 4.4% in a winter day and 4.3% in a summer day; a reduction in active power loss of 16% in a winter day and 7.1% in a summer day; and a reduction in reactive power loss of 7.5% in a winter day and 7.2% in a summer day. Thus, the recommended strategy effortlessly accelerates to a suboptimal solution.
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收藏
页数:15
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