Optimal Planning of Battery-Powered Electric Vehicle Charging Station Networks

Hayajneh, Hassan S.; Salim, Muath Naser Bani; Bashetty, Srikanth; Zhang, Xuewei

doi:10.1109/greentech.2019.8767139

Cited by 17 publications

(15 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The objective of this study is to design a logistics system model for mobile BESSs powered EVCS network, and then examine its performance when applied into a scenario of supply side, energy produced by renewable energy source (wind energy in this case), and demand side, energy consumed by EVs at the EVCSs. The scheme of EVCSs we study in this paper includes 27 charging stations spread in the city of Corpus Christi, Texas, and their locations are known as obtained from our previous study [9]. These EVCSs are projected to serve a population of about ten thousand EVs.…”

Section: Methodsmentioning

confidence: 99%

“…In addition to these issues, the constraint from the power grid to meet the demands of the Electric Vehicle Charging Stations (EVCSs) has also been a main challenge to the EV industry and it might be responsible for negatively impacting EVs' social acceptance [7,8]. To address this, we introduced and have been exploring the idea of developing grid independent EVCS networks in previous works [7,[9][10][11][12]. Essentially, mobile Battery Energy Storage Systems (BESSs) that absorb extra (i.e., would be curtailed otherwise) energy from renewable sources (e.g., a wind farm) and are shipped by Electric Semi-Trucks (ESTs) to the EVCSs power the EVCS networks.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Logistics Design for Mobile Battery Energy Storage Systems

Hayajneh

Zhang

2020

Energies

Self Cite

View full text Add to dashboard Cite

Currently, there are three major barriers toward a greener energy landscape in the future: (a) Curtailed grid integration of energy from renewable sources like wind and solar; (b) The low investment attractiveness of large-scale battery energy storage systems; and, (c) Constraints from the existing electric infrastructure on the development of charging station networks to meet the increasing electrical transportation demands. A new conceptual design of mobile battery energy storage systems has been proposed in recent studies to reduce the curtailment of renewable energy while limiting the public costs of battery energy storage systems. This work designs a logistics system in which electric semi-trucks ship batteries between the battery energy storage system and electric vehicle charging stations, enabling the planning and operation of power grid independent electric vehicle charging station networks. This solution could be viable in many regions in the United States (e.g., Texas) where there are plenty of renewable resources and little congestion pressure on the road networks. With Corpus Christi, Texas and the neighboring Chapman Ranch wind farm as the test case, this work implement such a design and analyze its performance based on the simulation of its operational processes. Further, we formulate an optimization problem to find design parameters that minimize the total costs. The main design parameters include the number of trucks and batteries. The results in this work, although preliminary, will be instrumental for potential stakeholders to make investment or policy decisions.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Logistics Design for Mobile Battery Energy Storage Systems

Hayajneh

Zhang

2020

Energies

Self Cite

View full text Add to dashboard Cite

show abstract

“…The demand profile plotted in Figure 4(c) is used. Note that in a previous work [38], for an EVCS network that serves a population of 10,000 EVs, the total daily demand is estimated to be ~1200 MWh. A random vector with a mean of 50 MWh is generated as the hourly demand profile (ℎ).…”

Section: A Data Inputsmentioning

confidence: 96%

“…b) The region's load demand in 2018 along with 5% monthly peak shaving used for ECA. c) An estimation for the hourly energy demand by the EVCSs which serves a future population of 10k EVs in the region for a typical day[38].…”

mentioning

confidence: 99%

Design of Combined Stationary and Mobile Battery Energy Storage Systems

Hayajneh¹,

Zhang²

2021

Preprint

Self Cite

View full text Add to dashboard Cite

To minimize the curtailment of renewable generation and incentivize grid-scale energy storage deployment, a concept of combining stationary and mobile applications of battery energy storage systems built within renewable energy farms is proposed. A simulation-based optimization model is developed to obtain the optimal design parameters such as battery capacity and power ratings by solving a multi-objective optimization problem that aims to maximize the economic profitability, the energy provided for transportation electrification, the demand peak shaving, and the renewable energy utilized. Two applications considered for the stationary energy storage systems are the end-consumer arbitrage and frequency regulation, while the mobile application envisions a scenario of a grid-independent battery-powered electric vehicle charging station network. The charging stations receive supplies from the energy storage system that absorbs renewable energy, contributing to a sustained DC demand that helps with revenues. Representative results are presented for two operation modes and different sets of weights assigned to the objectives. Substantial improvement in the profitability of combined applications over single stationary applications is shown. Pareto frontier of a reduced dimensional problem is obtained to show the trade-off between design objectives. This work could pave the road for future implementations of the new form of energy storage systems.<br>

show abstract

“…They showed that the EV loss would become the dominant component of the cost if the EVCSs are not located optimally. Further applications of the GA when planning for EVCSs was performed by Hayajneh et al [22]. Starting with initial potential candidates, the main objective function was to obtain the optimum number of EVCSs in terms of locations and configurations with the aim to minimize both the transportation energy losses (TEL) and EVCS investment and operation/maintenance costs.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Electric Vehicle Charging Station Network Planning via a Co-Evolution Approach

Hayajneh

Zhang

2019

Energies

Self Cite

View full text Add to dashboard Cite

The optimal planning of electric vehicle charging infrastructure has attracted extensive research interest in recent years. Most of the optimization problems were formulated by assuming that the configurations will be fixed at the optimal solution while overlooking the fact that the charging stations and the electric vehicles are “evolving” over time and have mutual impacts. On the other hand, little attention has been paid to evaluate the performance of the solutions in such a dynamic environment. Motivated by these gaps, this work develops a simulation model that captures the interactions between charging station configurations and electric vehicle population (and the preference of electric vehicles when choosing charging station). This modeling framework is then implemented to evaluate the performance of planned charging infrastructure in providing services to electric vehicles. Two indicators are calculated, i.e., usage rate and rejection rate. The former measures the “waste” due to abundant facilities installed; the latter measures the inadequacy of planned facilities, especially when the electric vehicle population is larger. The simulation results presented in this work validate the model and show the potential of the model not only to evaluate designs but also to be used for optimal planning in subsequent works.

show abstract

Optimal Planning of Battery-Powered Electric Vehicle Charging Station Networks

Cited by 17 publications

References 6 publications

Logistics Design for Mobile Battery Energy Storage Systems

Logistics Design for Mobile Battery Energy Storage Systems

Design of Combined Stationary and Mobile Battery Energy Storage Systems

Evaluation of Electric Vehicle Charging Station Network Planning via a Co-Evolution Approach

Contact Info

Product

Resources

About