Demand side management of electric vehicles in smart grids: A survey on strategies, challenges, modeling, and optimization

Mohanty, Sarthak; Panda, Subhasis; Rout, Pravat Kumar; Sahu, Binod Kumar; Bajaj, Mohit; Zawbaa, Hossam M.; Kumar, Nallapaneni Manoj; Kamel, Salah

doi:10.1016/j.egyr.2022.09.023

Cited by 92 publications

(32 citation statements)

References 133 publications

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“…However, these bi-directional-based EV technologies currently being implemented have not yet matured. The sudden rising EV integration in grids has caused many serious issues, such as technical, socio-economical, and environmental issues, that must be passed on to optimize the EV integration with grids [82]. According to the available data, an effective G2V and V2G power distribution plan can reduce the demand for further electricity infrastructure investments while minimizing the requirement for new energy.…”

Section: G2v and V2g Issuesmentioning

confidence: 99%

“…Owners must choose whether they want to participate in future contracts. An EV with bidirectional power flow capabilities is significantly expensive have some limitations due to additional technology parts inclusions [82,85,86]. Studies and research are required to close the uncertainty gap and provide manufacturers and customers with a viable option for energy market contributors.…”

Section: G2v and V2g Limitationsmentioning

confidence: 99%

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Grid-Vehicle-Grid (G2V2G) Efficient Power Transmission: An Overview of Concept, Operations, Benefits, Concerns, and Future Challenges

et al. 2023

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Electric vehicles (EVs) are proportionally increasing day-by-day with the inclusion of upgraded technology toward considered zero carbon emission efforts. To mitigate greenhouse gas emissions from the transportation sector, grid-to-vehicle (G2V) and vehicle-to-grid (V2G) technologies are getting significant attention nowadays. EVs equipped with modern technology can help to stabilize the power grids through load-balancing topology during peak hours. The improvement in EVs can support the surroundings in numerous ways, such as power grid voltage and frequency regulations, harmonics distortions, accessible solar energy implemented to the grids, and peak load stabilizations. This literature review analyzes G2V and V2G impacts in more depth, namely opportunities, improvements in strategies, operation, control, issues, and new technology adoptions. This paper emphasizes the possibilities of bringing advancements in EV technology, smooth operations between grids and EVs, fast bidirectional charging and discharging scopes, control of grids and EVs structures, issues, benefits, pitfalls, challenges, and recommendations.

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Section: G2v and V2g Issuesmentioning

confidence: 99%

Section: G2v and V2g Limitationsmentioning

confidence: 99%

Grid-Vehicle-Grid (G2V2G) Efficient Power Transmission: An Overview of Concept, Operations, Benefits, Concerns, and Future Challenges

et al. 2023

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“…In the RL process, the agent interacts with the environment to collect experience data and optimize the policy or value function based on this data Zhang et al (2022). and policy-based methods (such as Policy Gradient and Actor-Critic).…”

Section: Reinforcement Learning (Rl)mentioning

confidence: 99%

Optimizing electric vehicle charging schedules and energy management in smart grids using an integrated GA-GRU-RL approach

Zhao,

Liang

2023

Front. Energy Res.

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Introduction: Smart grid technology is a crucial direction for the future development of power systems, with electric vehicles, especially new energy vehicles, serving as important carriers for smart grids. However, the main challenge faced by smart grids is the efficient scheduling of electric vehicle charging and effective energy management within the grid.Methods: To address this issue, we propose a novel approach for intelligent grid electric vehicle charging scheduling and energy management, integrating three powerful technologies: Genetic Algorithm (GA), Gated Recurrent Unit (GRU) neural network, and Reinforcement Learning (RL) algorithm. This integrated approach enables global search, sequence prediction, and intelligent decision-making to optimize electric vehicle charging scheduling and energy management. Firstly, the Genetic Algorithm optimizes electric vehicle charging demands while minimizing peak grid loads. Secondly, the GRU model accurately predicts electric vehicle charging demands and grid load conditions, facilitating the optimization of electric vehicle charging schedules. Lastly, the Reinforcement Learning algorithm focuses on energy management, aiming to minimize grid energy costs while meeting electric vehicle charging demands.Results and discussion: Experimental results demonstrate that the method achieves prediction accuracy and recall rates of 97.56% and 95.17%, respectively, with parameters (M) and triggers (G) at 210.04 M and 115.65G, significantly outperforming traditional models. The approach significantly reduces peak grid loads and energy costs while ensuring the fulfilment of electric vehicle charging demands and promoting the adoption of green energy in smart city environments.

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“…Bottom-up models are generally based on detailed technological descriptions of the energy system. The purpose of bottom-up modelling is to obtain insight into their technological performance for optimal decision making at the design (Bagheri et al, 2018;Pastore et al, 2022), operations (Mohammadi et al, 2022;Mohanty et al, 2022) and control level (Mohammadi et al, 2022). Thus, the technological characteristics of the system components are modelled endogenously (i.e., are dependant on other variables or parameters in the model).…”

Section: Introductionmentioning

confidence: 99%

Holistic fuzzy logic methodology to assess positive energy district (PathPED)

Castillo-Calzadilla

Garay-Martinez

Martin

2023

Sustainable Cities and Society

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Demand side management of electric vehicles in smart grids: A survey on strategies, challenges, modeling, and optimization

Cited by 92 publications

References 133 publications

Grid-Vehicle-Grid (G2V2G) Efficient Power Transmission: An Overview of Concept, Operations, Benefits, Concerns, and Future Challenges

Grid-Vehicle-Grid (G2V2G) Efficient Power Transmission: An Overview of Concept, Operations, Benefits, Concerns, and Future Challenges

Optimizing electric vehicle charging schedules and energy management in smart grids using an integrated GA-GRU-RL approach

Holistic fuzzy logic methodology to assess positive energy district (PathPED)

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