Optimal allocation of electric vehicle charging stations and renewable distributed generation with battery energy storage in radial distribution system considering time sequence characteristics of generation and load demand

被引:77
作者
Balu, Korra [1 ]
Mukherjee, V. [1 ]
机构
[1] Indian Sch Mines, Indian Inst Technol, Dept Elect Engn, Dhanbad, Jharkhand, India
关键词
Benchmark test functions; Chaotic maps; Distributed generation; Electric vehicle charging stations; Radial distribution system; Student psychology based optimization; MULTIOBJECTIVE OPTIMAL ALLOCATION; NETWORK RECONFIGURATION; OPTIMIZATION; PLACEMENT; ALGORITHM;
D O I
10.1016/j.est.2022.106533
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 addition of electric vehicle (EV) charging station (EVCS)/EV battery swapping stations (EVBSSs) in radial distribution system (RDS) draws extra real power from the distribution substation. This paper proffers a novel strategy for obtaining the best location of EVCS/EVBSSs in the RDS. Further, the EV charger has been modeled as constant current load and the influence of EVCS/EVBSSs demand on the voltage profile, real power loss, total voltage deviation, energy loss cost and overall operating cost of the RDS have been investigated considering constant power (CP), industrial (IL), residential (RES) and commercial (COM) load models. In order to make the network more self-sustainable and reliable, it is obligatory to assimilate the distributed generations (DGs) of optimal size and at proper location in the RDS to diminish the impact of EVCS/EVBSS(s) load. In addition, non-dispatchable solar photovoltaic (SPV) and wind turbine (WT) units are converted into a dispactable SPV and WT units with a combination of battery energy storage (BES) (i.e., SPV-BES and WT-BES). This research work sug-gests a novel chaotic student psychology based optimization (SPBO) (CSPBO) algorithm to acquire the optimal size and site of SPV-BES, WT-BES and biomass in IEEE 33-bus and practical Brazil 136-bus RDS for CP, IL, RES and COM load models considering the average hourly load demand profile and the average hourly variation in generation profile of SPV and WT. The obtained results based on benchmark test problems reveals that chaotic maps are proficient to enhance the performance of the SPBO algorithm significantly in terms of local optima circumvention and faster convergence mobility. The obtained outcomes show that the attained size and site of renewable DGs in the RDS may be feasible ones. The attained outcomes of the proffered CSPBO algorithm are contrasted to SPBO and Harris hawk's optimization algorithm. The yielded results will definitely help the EV and distribution industry in improving the reliability and the efficiency of the system.
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页数:29
相关论文
共 70 条
[1]   An optimization planning framework for allocating multiple distributed energy resources and electric vehicle charging stations in distribution networks [J].
Adetunji, Kayode E. ;
Hofsajer, Ivan W. ;
Abu-Mahfouz, Adnan M. ;
Cheng, Ling .
APPLIED ENERGY, 2022, 322
[2]   Multi-Objective Allocation of EV Charging Stations and RESs in Distribution Systems Considering Advanced Control Schemes [J].
Ali, Abdelfatah ;
Shaaban, Mostafa F. ;
Awad, Ahmed S. A. ;
Azzouz, Maher A. ;
Lehtonen, Matti ;
Mahmoud, Karar .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2023, 72 (03) :3146-3160
[3]   An improved wild horse optimization algorithm for reliability based optimal DG planning of radial distribution networks [J].
Ali, Mohammed Hamouda ;
Kamel, Salah ;
Hassan, Mohamed H. ;
Tostado-Veliz, Marcos ;
Zawbaa, Hossam M. .
ENERGY REPORTS, 2022, 8 :582-604
[4]   Dynamic Joint Allocation of EV Charging Stations and DGs in Spatio-Temporal Expanding Grids [J].
Atat, Rachad ;
Ismail, Muhammad ;
Serpedin, Erchin ;
Overbye, Thomas .
IEEE ACCESS, 2020, 8 :7280-7294
[5]   Optimal planning of electric vehicle charging station at the distribution system using hybrid optimization algorithm [J].
Awasthi, Abhishek ;
Venkitusamy, Karthikeyan ;
Padmanaban, Sanjeevikumar ;
Selvamuthukumaran, Rajasekar ;
Blaabjerg, Frede ;
Singh, Asheesh K. .
ENERGY, 2017, 133 :70-78
[6]  
Babu PVK, 2020, INT J RENEW ENERGY R, V10, P366
[7]   Optimal siting and sizing of distributed generation in radial distribution system using a novel student psychology-based optimization algorithm [J].
Balu, Korra ;
Mukherjee, V .
NEURAL COMPUTING & APPLICATIONS, 2021, 33 (22) :15639-15667
[8]   NETWORK RECONFIGURATION IN DISTRIBUTION-SYSTEMS FOR LOSS REDUCTION AND LOAD BALANCING [J].
BARAN, ME ;
WU, FF .
IEEE TRANSACTIONS ON POWER DELIVERY, 1989, 4 (02) :1401-1407
[9]   Modified Student Psychology Based Optimization Algorithm for Economic Dispatch Problems [J].
Basu, Subhamay ;
Basu, Mousumi .
APPLIED ARTIFICIAL INTELLIGENCE, 2021, 35 (15) :1508-1528
[10]   Grid congestion mitigation in the era of shared electric vehicles [J].
Brinkel, Nico ;
AlSkaif, Tarek ;
van Sark, Wilfried .
JOURNAL OF ENERGY STORAGE, 2022, 48