Multi-Objective Distribution Network Expansion Incorporating Electric Vehicle Charging Stations

Xiang, Yue; Yang, Wei; Liu, Junyong; Li, Furong

doi:10.3390/en9110909

Cited by 31 publications

(23 citation statements)

References 22 publications

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“…Several studies proposed placing chargers at parking lots and locating stations by taking the limitations of power systems such as power losses, network reliability, and voltage deviations, into account [22][23][24][25][26]. The study in [22] proposed a resource allocation method of EV parking lots, with the consideration of the network reliability.…”

Section: Related Workmentioning

confidence: 99%

“…Both the benefits of parking lot investor and the network operator were considered. The authors in [25] proposed a multi-objective optimization framework for the siting and the sizing of CSs for the distribution network expansion. Apart from allocating chargers at parking lots, the work in [26] presented methods for optimally placing CSs in the power network to maintain the reliability of the system.…”

Section: Related Workmentioning

confidence: 99%

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A Hierarchical Optimization Model for a Network of Electric Vehicle Charging Stations

et al. 2017

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Abstract:Charging station location decisions are a critical element in mainstream adoption of electric vehicles (EVs). The consumer confidence in EVs can be boosted with the deployment of carefully-planned charging infrastructure that can fuel a fair number of trips. The charging station (CS) location problem is complex and differs considerably from the classical facility location literature, as the decision parameters are additionally linked to a relatively longer charging period, battery parameters, and available grid resources. In this study, we propose a three-layered system model of fast charging stations (FCSs). In the first layer, we solve the flow capturing location problem to identify the locations of the charging stations. In the second layer, we use a queuing model and introduce a resource allocation framework to optimally provision the limited grid resources. In the third layer, we consider the battery charging dynamics and develop a station policy to maximize the profit by setting maximum charging levels. The model is evaluated on the Arizona state highway system and North Dakota state network with a gravity data model, and on the City of Raleigh, North Carolina, using real traffic data. The results show that the proposed hierarchical model improves the system performance, as well as the quality of service (QoS), provided to the customers. The proposed model can efficiently assist city planners for CS location selection and system design.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A Hierarchical Optimization Model for a Network of Electric Vehicle Charging Stations

et al. 2017

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“…Weight coefficient methods, where the multi-objective model is transformed into a single objective model by means of weight coefficients. Several approaches are adopted to determine these weight Energies 2017, 10, 1715 9 of 27 coefficients for each objective, such as user-defined fixed weight [39,65], analytic hierarchy process [57,107], stochastic weights [63], fuzzing mathematics method [83], and bargaining function [85]. These weight coefficient methods with a priori articulation of preferences have the advantages of simplicity and convenience, but have the drawback of subjectivity at the same time.…”

Section: Objectives Of Ads Planning Modelmentioning

confidence: 99%

“…Locations and sizes of new substations [26,29,30,32,36,38,54,55,58,66,80,85,89] Sizes of existing substations for reinforcement [24,26,27,29,32,34,36,38 …”

Section: Traditional Variablesmentioning

confidence: 99%

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A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches

Wang

Chen³

et al. 2017

Energies

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Due to the widespread deployment of distributed energy resources (DERs) and the liberalization of electricity market, traditional distribution networks are undergoing a transition to active distribution systems (ADSs), and the traditional deterministic planning methods have become unsuitable under the high penetration of DERs. Aiming to develop appropriate models and methodologies for the planning of ADSs, the key features of ADS planning problem are analyzed from the different perspectives, such as the allocation of DGs and ESS, coupling of operation and planning, and high-level uncertainties. Based on these analyses, this comprehensive literature review summarizes the latest research and development associated with ADS planning. The planning models and methods proposed in these research works are analyzed and categorized from different perspectives including objectives, decision variables, constraint conditions, and solving algorithms. The key theoretical issues and challenges of ADS planning are extracted and discussed. Meanwhile, emphasis is also given to the suitable suggestions to deal with these abovementioned issues based on the available literature and comparisons between them. Finally, several important research prospects are recommended for further research in ADS planning field, such as planning with multiple micro-grids (MGs), collaborative planning between ADSs and information communication system (ICS), and planning from different perspectives of multi-stakeholders.

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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

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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.

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Multi-Objective Distribution Network Expansion Incorporating Electric Vehicle Charging Stations

Cited by 31 publications

References 22 publications

A Hierarchical Optimization Model for a Network of Electric Vehicle Charging Stations

A Hierarchical Optimization Model for a Network of Electric Vehicle Charging Stations

A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches

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

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