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Review
Chemistry, Physical
Long Phan Van et al.
Summary: With the development of renewable energy sources, integrating energy storage systems within microgrids has become a focus of attention. Hydrogen systems are considered a promising energy storage option that utilizes electrolysers to produce and store hydrogen, which can be supplied back to microgrids using fuel cells. Designing an energy management system is crucial for controlling the energy flow within hybrid energy systems and optimizing the operation of microgrids. This study provides a comprehensive review and analysis of energy management systems for hydrogen technologies-based microgrids, including objectives, constraints, techniques, optimization methods, and simulation tools, as well as discussing challenges and future research directions.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2023)
Article
Green & Sustainable Science & Technology
Hassan Yousif Ahmed et al.
Summary: This paper proposes a multi-objective planning framework for EV charging stations in power networks that move towards green transportation electrification. The model combines the planning models of renewable energy systems, energy storage systems, thyristor-controlled series compensators, and transmission lines. The objectives include maximizing EVs' penetration, reducing carbon dioxide emissions, and meeting financial requirements. The proposed model is solved using the multi-objective version of the Gazelle optimization algorithm. The results demonstrate the superiority of the MGOA in solving multi-objective optimization problems and the importance of energy storage systems in improving the EV's hosting capacity.
Article
Energy & Fuels
Zhouquan Wu et al.
Summary: This paper addresses the estimation of the charging power demand of extreme fast charging (XFC) stations and the design of multiple XFC stations with renewable energy resources in distribution networks. By using a Monte Carlo simulation tool, realistic estimations of the charging power demand are obtained considering various impact factors. The optimal energy capacity of the energy storage system (ESS), ESS rated power, and size of photovoltaic (PV) panels for multiple XFC stations in a distribution network are determined using an optimal power flow technique. Simulation results show that the presented simulation method can estimate approximate real-world XFC charging demand and the optimized ESS and PV units can reduce costs and improve network performance.
Review
Energy & Fuels
Suresh Panchanathan et al.
Summary: There has been a growing interest in the transition from gasoline-powered cars to electric vehicles in the past decade. The electric vehicle-grid (V2G) technology allows the battery of an electric vehicle to function as an energy source that can store or release energy as needed, enabling energy exchange between the grid and EV batteries. This article reviews different bidirectional converter topologies used in the V2G system and discusses their benefits, including cost reduction for electric utilities and increased profits for EV owners.
Article
Energy & Fuels
Nandini K. Krishnamurthy et al.
Summary: In this study, a DC microgrid consisting of a solar photovoltaic, wind power system, and fuel cells is interconnected with the utility grid. The optimal sizing and positioning of electric vehicle charging stations and renewable energy sources are simultaneously determined to minimize their negative impact on the distribution network's operational parameters. The location problem is presented as a multi-objective optimization, considering voltage stability, reliability, power loss index, and cost as objective functions. The effectiveness of the proposed algorithm is demonstrated through simulations on modified IEEE 33 and 123-bus radial distribution systems.
Article
Thermodynamics
Zhonghao Zhao et al.
Summary: This study addresses the optimal deployment of electric vehicle charging stations in the transportation and power distribution networks, which is a critical issue for the mass adoption of EVs. A finite-discrete Markov decision process formulation is proposed in a reinforcement learning framework to solve the curse of dimensionality problem. The proposed approach, which utilizes a LSTM-based recurrent neural network with an attention mechanism, outperforms other baseline approaches in terms of solution quality and computational time.
Article
Thermodynamics
Mohammad Shafiei et al.
Summary: This paper aims to design a fast-charging station that considers parameters such as solar panel capacity, storage systems, wind turbine, Demand Response (DR) program, and stochastic model of Renewable Energy Sources (RESs). The findings revealed that using load management at the charging station increases profitability and reduces initial capital investment. A hybrid algorithm is proposed to forecast wind speed changes. The total 10-year cost is reduced by 17.85% and 3.31% in the presence of Demand Response (DR) for the first and second ownerships, respectively.
Article
Mathematics
Nahar F. Alshammari et al.
Summary: This study proposes a multi-objective optimization approach for designing hybrid renewable energy systems for electric vehicle charging stations, taking into account economic, reliability, and seasonal factors. Four algorithms, MOPSO, NSGA-II, NSGA-III, and MOEA/D, were evaluated for their performance. Unlike previous studies, our approach leads to a more comprehensive and sustainable design for EV charging systems. The findings contribute to the development of efficient and reliable renewable energy systems for urban areas, emphasizing the importance of considering economic and reliability factors in the design process. The study represents a significant advance in the field of hybrid renewable energy systems for EV charging stations.
Article
Social Sciences, Interdisciplinary
Harin M. Mohan et al.
Summary: The increase in Electric vehicle ownership leads to grid outages due to increased charging stations and load demand during peak hours. Microgrids can effectively resolve these issues by implementing an energy management approach. The proposed dynamic control system based on the Fuzzy-Sparrow Search Algorithm provides reliable power balance and outperforms the Particle Swarm Optimization approach in terms of convergence speed and stability.
Article
Energy & Fuels
Waqas Ur Rehman et al.
Summary: This paper presents a mixed integer linear programming approach for determining the optimal sizing of battery energy storage systems (BESS) and solar generation systems in extreme fast charging stations (XFCS) to minimize total costs. The proposed model considers different scenarios and uses an improved probabilistic method to model charging demand. It also takes into account monthly and annual demand charges, as well as BESS life degradation.
Article
Computer Science, Artificial Intelligence
Yan Yan et al.
IEEE Transactions on Intelligent Vehicles
(2022)
Article
Energy & Fuels
Jan Engelhardt et al.
Summary: This paper proposes an energy management system (EMS) for hybrid fast charging stations that combines battery storage and local renewable generation. The EMS is designed to efficiently allocate energy to different components, such as photovoltaic (PV) system, EV fast chargers, and grid-tie inverter, while managing the energy exchange with the distribution grid. The numerical analyses show that the enhanced control of the EMS can increase self-sufficiency and reduce battery cycles.
Article
Thermodynamics
Nicola Bianco et al.
Summary: Latent heat thermal storage based on phase change material (PCM) in shell-and-tube heat exchangers can reduce power consumption of air conditioning systems. By optimizing the charging/discharging time of PCM and the operating conditions of the chiller, better performance can be achieved. Experimental validation shows that the optimal solution leads to a reduction in the inlet temperature by 1.25℃ and a maximum utilization of PCM by 40% of the initial amount. Further optimization results in a shell diameter reduction of 12 cm to exploit 72% of the PCM potential.
APPLIED THERMAL ENGINEERING
(2022)
Article
Chemistry, Physical
Ingrid Delyova et al.
Summary: Genetic algorithms are a robust method for solving a wide range of optimization problems by exploring a large space of design variables to find the best solution. For structural engineers, it is important to determine the form of the objective function and avoid critical states during the solution process.
Article
Green & Sustainable Science & Technology
Munseok Chang et al.
Summary: This study introduces a methodology to analyze and forecast aggregated charging power demand from multiple fast-charging stations, proposing a forecasting model based on long short-term memory neural network to address the fluctuation in fast-charging power demand. Results demonstrate the superiority of the proposed model in forecasting fast-charging power demand aggregated by multiple stations.
Review
Green & Sustainable Science & Technology
H. S. Das et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2020)
Article
Energy & Fuels
Chong Cao et al.
Article
Energy & Fuels
Desheng Li et al.
Review
Engineering, Electrical & Electronic
Tianjin Chen et al.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2020)
Article
Energy & Fuels
Hasan Mehrjerdi et al.
JOURNAL OF ENERGY STORAGE
(2019)
Article
Thermodynamics
Fakeha Sehar et al.
Article
Automation & Control Systems
Bing Yan et al.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2017)
Article
Energy & Fuels
Mariz B. Arias et al.
Article
Thermodynamics
Bowen Zhou et al.
Article
Economics
Carlos Madina et al.
Article
Engineering, Civil
Wayes Tushar et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2016)
Article
Computer Science, Artificial Intelligence
Kalyanmoy Deb et al.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2014)
Article
Management
Rene Bohnsack et al.
Article
Computer Science, Artificial Intelligence
K Deb et al.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2002)
