Charging Scheduling of Electric Vehicle Incorporating Grid-to-Vehicle and Vehicle-to-Grid Technology Considering in Smart Grid

Das, Sourav; Acharjee, Parimal; Bhattacharya, Aniruddha

doi:10.1109/tia.2020.3041808

Cited by 116 publications

(28 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Objective Formulation: The objective of the proposed method is less, voltage deviation [27,28] and cost minimization. So, to obtain the objective function in this article, the hybrid GJO-RFA approach is proposed.…”

Section: Load Modelingmentioning

confidence: 99%

A Hybrid Technique for Optimal Placement of Fast‐Charging Stations of Electric Vehicles for the Reliability of Distribution Network

Ranjith Kumar,

Vallimurugan

2023

Energy Tech

View full text Add to dashboard Cite

Proper planning for electric vehicle (EV) charging stations, as well as the necessary network development, is critical for the continued growth of EVs and conventional loads. This article proposes a hybrid method for the allocation of fast‐charging stations (FCSs) and photovoltaic (PV) with battery energy storage (BES) and scheduling. The proposed hybrid technique is the wrapper of golden jackal optimization (GJO) and random forest algorithms (RFA), commonly named the GJO–RFA technique. Using the GJO approach, the allocation and EV assignment problems are resolved. RFA is used to address EV, traffic flow, and PV‐related uncertainties. The objective of the proposed approach is to minimize the loss of energy, investments, index of voltage deviation, and operation and maintenance costs of FCS, PV, and BES. The associated important factors are also assessed, including the number of charging ports, FCS capacity, and EV flow caught using a FCS. As a test example, a 33‐node radial distribution network with the appropriate traffic network is used. For the final problem, the proposed approach to minimal energy loss is 2622.7270 kWh. By then, the performance of the proposed approach is executed in MATLAB, and it is contrasted with other existing techniques. The result shows that the proposed method‐related energy loss is less than existing approaches.

show abstract

Section: Load Modelingmentioning

confidence: 99%

A Hybrid Technique for Optimal Placement of Fast‐Charging Stations of Electric Vehicles for the Reliability of Distribution Network

Ranjith Kumar,

Vallimurugan

2023

Energy Tech

View full text Add to dashboard Cite

show abstract

“…The linear programming problem (ILPP) is formulated by an assignment matrix ( , ℎ) (Das et al 2020) where ℎ >> and each EV is assigned to a PFCS. This matrix is grounded on the renowned assignment problem (Aktel et al 2017) with the combination of traffic flow structure (Schrieber et al 2017).…”

Section: ) Assignment Matrix For Ilpmentioning

confidence: 99%

Allocation of EV Public Charging Station in Renewable based Distribution Network using HHO Considering Uncertainties and Traffic Congestion

Pal¹,

Bhattacharya²,

Chakraborty³

2021

Preprint

Self Cite

View full text Add to dashboard Cite

Electric vehicle (EV) is the growing vehicular technology for sustainable development to reduce carbon emission and to save fossil fuel. The charging station (CS) is necessary at appropriate locations to facilitate the EV owners to charge their vehicle as well as to keep the distribution system parameters within permissible limits. Besides that, the selection of a charging station is also a significant task for the EV user to reduce battery energy wastage while reaching the EV charging station. This paper presents a realistic solution for the allocation of public fast-charging stations (PFCS) along with solar distributed generation (SDG). A 33 node radial distribution network is superimposed with the corresponding traffic network to allocate PFCSs and SDGs. Two interconnected stages of optimization are used in this work. The first part deals with the optimization of PFCS’s locations and SDG’s locations with sizes, to minimize the energy loss and to improve voltage profile using harris hawk optimization (HHO) and few other soft computing techniques. The second part handles the proper assignment of EVs to the PFCSs with less consumption of the EV’s energy considering the road distances with traffic congestion using linear programming (LP), where the shortest paths are decided by Dijkstra's algorithm. The 2m point estimation method (2m PEM) is employed to handle the uncertainties associated with EVs and SDGs. The robustness of solutions are tested using wilcoxon signed rank test and quade test.

show abstract

“…An energy-sharing problem [17] considering an energy service provider and PV prosumers is studied using RTP offered by the grid. RTP scheme is extensively used in the analysis of EMP of residential consumers [18]- [20], microgrids [21], an EV charging station operator and EV owners [22], etc. An optimal sizing problem of PV and BESS in a residential household is employed considering TOU, RTP, and Stepwise electricity tariff [23].…”

Section: Related Literature Workmentioning

confidence: 99%

“…The charging/discharging power of SD should be less than the maximum value presented in Eqs. (21,22).…”

Section: Storage Devicementioning

confidence: 99%

Comparative analysis of dynamic pricing schemes in distributed energy management of residential users in smart grid

Gaba

Chanana

2021

Journal of Energy Systems

View full text Add to dashboard Cite

Increasing power demand, greenhouse gas emissions, and the old infrastructure are serious concerns in the existing power system. With the advent of the smart grid, demand response (DR) has emerged as an effective approach to handle these issues. The selection of an appropriate DR program is vital to acquire the maximum benefits for the utility and the consumers. In this context, a distributed energy management scheme for residential consumers is presented and analyzed to observe the impact of different pricing schemes. The three dynamic pricing schemes considered in this work are based on linear function, the logarithmic function, and the penalty-based linear function of aggregated load. A non-cooperative game is used to formulate the energy management problem of the consumers. The Nash equilibrium of the game is obtained using the proximal decomposition algorithm. The results are obtained for different cases based on the presence of a storage device, a dispatchable generation unit, and two different modes of operation of an electric vehicle. The best pricing scheme is chosen based on the minimum cost, the peak-to-average ratio of the system load profile, and consumer comfort.

show abstract

Charging Scheduling of Electric Vehicle Incorporating Grid-to-Vehicle and Vehicle-to-Grid Technology Considering in Smart Grid

Cited by 116 publications

References 29 publications

A Hybrid Technique for Optimal Placement of Fast‐Charging Stations of Electric Vehicles for the Reliability of Distribution Network

A Hybrid Technique for Optimal Placement of Fast‐Charging Stations of Electric Vehicles for the Reliability of Distribution Network

Allocation of EV Public Charging Station in Renewable based Distribution Network using HHO Considering Uncertainties and Traffic Congestion

Comparative analysis of dynamic pricing schemes in distributed energy management of residential users in smart grid

Contact Info

Product

Resources

About