Comprehensive benefits analysis of electric vehicle charging station integrated photovoltaic and energy storage

Yang, Meng; Zhang, Lihui; Zhao, Zhenli; Wang, Liwan

doi:10.1016/j.jclepro.2021.126967

Cited by 62 publications

(14 citation statements)

References 30 publications

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“…[ 1 ] Besides providing favorable economic returns, photovoltaic (PV) battery systems at charging stations have also been found to benefit the grid side and provide social benefits. [ 2 ] However, to our knowledge, this has not been shown for Norwegian conditions. The charging mode will also impact the benefits of PV systems at charging stations, as fast‐charging leads to more reliance on utility grid and higher electricity costs.…”

Section: Introductionmentioning

confidence: 78%

“…In another study with significantly larger battery-to-PV-ratio (616 kWh battery and 445 kW PV), an energy management system was developed to benefit from energy arbitrage, and the authors concluded that benefits generated for the grid and society were larger than the economic benefits. [2] As cost-efficiency of batteries is dependent on the peak shaving potential, it is obvious that the FCEV station, with a flat electricity consumption profile (Figure 2), did not include batteries. This analysis has not quantified profit generation from contribution to the electricity reserve markets, nor has a detailed analysis of the electricity price volatility been performed.…”

Section: Load Flexibility and Battery Optimizationmentioning

confidence: 99%

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Hybrid PV Systems and Colocalization of Charging and Filling Stations for Electrification of Road Transport Sector

et al. 2022

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Electrification of the road transport sector likely includes both battery electric (BEV) and hydrogen fuel cell electric vehicles (FCEV). Integration of energy carriers is described as a route forward for efficient integration of renewable energy. The objective of this work is to determine cost‐efficiency improvements with co‐localization of BEV and FCEV stations, and how this impacts optimal sizing of the photovoltaic (PV) production and battery storage. Grid‐connected co‐localized charging/filling stations, situated north of Oslo, Norway, are modeled in HOMER Pro and HOMER Grid. PV production is modeled using PVsyst and a snow loss model to analyze the effect of snow shading on PV production. Demand data for BEV and FCEV are synthesized based on historical traffic data (year 2015–2019) to represent three different cases of BEV/FCEV distribution. Results indicate that co‐localization, i.e., the integration of energy carriers for BEV and FCEV, leads to a marginal cost‐efficiency improvement of 0.1–1.4%, depending on BEV/FCEV distribution and cost assumptions. Co‐localization shows greater benefits for the integration of locally produced renewable power. Due to co‐localization, the cost‐optimal PV capacity is either increased or PV power export is reduced. Stationary batteries are also observed to cost‐efficiently perform peak shaving in a future scenario.

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Section: Introductionmentioning

confidence: 78%

Section: Load Flexibility and Battery Optimizationmentioning

confidence: 99%

Hybrid PV Systems and Colocalization of Charging and Filling Stations for Electrification of Road Transport Sector

et al. 2022

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“…Moreover, charging stations comprise one of the largest surrounding industries of EVs [37,38]. Reliable technology in charging stations is considered to be the major approach to maintaining the sustainable development of the EV industry [39][40][41].…”

Section: Literature Review and Hypothesis Development 21 Production Of Evs And Charging Station Randdmentioning

confidence: 99%

An Empirical Research of the Mechanism from Electric Vehicle Production to Charging Station R&D in China

Zhang

2021

Processes

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Electric vehicles (EVs) are regarded as an effective method for dealing with serious environmental pollution. The Chinese government has implemented a series of incentives to accelerate the promotion of EV. However, the increasing production of EVs gives rise to a greater demand for better quality charging station. This study aimed to certify the impact of the production of EVs on charging station research and development (R&D) in China, with mediating effect methods and a panel fixed effect model. The conclusions derived from the study were: (1) Statistically, the production of EVs positively and significantly impacts charging station R&D; (2) the mediating role of investment in charging stations is verified in the relationship between the production of EVs and charging station R&D; (3) environmental tax can moderate the relationship between the production of EVs and charging station R&D. These results implicate, for the first time, that the production of EVs can enhance charging station R&D through the mediating role of charging station investments and the moderating role of environmental tax.

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“…A chance-constrained programming method is adopted to solve this problem, and the risk that the aggregator cannot meet the power grid demand is reduced. Depending on the CS equipped with the photovoltaic (PV) and the energy storage system (ESS), reference [11] makes full use of the peak-valley tariff mechanism to formulate a CS energy management strategy to promote PV consumption. To maximize the profit of CSs, Nishimwe H. et al [12] present an optimal scheduling method considering intermittent PV generation and the EV arrival mode.…”

Section: Introductionmentioning

confidence: 99%

A Modified Rainbow-Based Deep Reinforcement Learning Method for Optimal Scheduling of Charging Station

et al. 2022

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To improve the operating efficiency and economic benefits, this article proposes a modified rainbow-based deep reinforcement learning (DRL) strategy to realize the charging station (CS) optimal scheduling. As the charging process is a real-time matching between electric vehicles ‘(EVs) charging demand and CS equipment resources, the CS charging scheduling problem is duly formulated as a finite Markov decision process (FMDP). Considering the multi-stakeholder interaction among EVs, CSs, and distribution networks (DNs), a comprehensive information perception model was constructed to extract the environmental state required by the agent. According to the random behavior characteristics of the EV charging arrival and departure times, the startup of the charging pile control module was regarded as the agent’s action space. To tackle this issue, the modified rainbow approach was utilized to develop a time-scale-based CS scheme to compensate for the resource requirements mismatch on the energy scale. Case studies were conducted within a CS integrated with the photovoltaic and energy storage system. The results reveal that the proposed method effectively reduces the CS operating cost and improves the new energy consumption.

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Comprehensive benefits analysis of electric vehicle charging station integrated photovoltaic and energy storage

Cited by 62 publications

References 30 publications

Hybrid PV Systems and Colocalization of Charging and Filling Stations for Electrification of Road Transport Sector

Hybrid PV Systems and Colocalization of Charging and Filling Stations for Electrification of Road Transport Sector

An Empirical Research of the Mechanism from Electric Vehicle Production to Charging Station R&D in China

A Modified Rainbow-Based Deep Reinforcement Learning Method for Optimal Scheduling of Charging Station

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