Technoeconomic Analysis of Fuel Cell Vehicle‐to‐Grid (FCV2G) System Supported by Photovoltaic Energy

İnci, Mustafa

doi:10.1002/ente.202201162

Cited by 25 publications

(5 citation statements)

References 45 publications

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“…7. Compared to many researches, the hydrogen production is efficient, particularly hydrogen production with electricity/renewable energy [28].…”

Section: ) Load Profilementioning

confidence: 99%

Momentum Search Algorithm for Analysis of Fuel Cell Vehicle-to-Grid System with Large-Scale Buildings

Sivalingam,

Gurusamy

2024

Prot. Control Mod. Power Syst.

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The design and analysis of a fuel cell vehicle-to-grid (FCV2G) system with a high voltage conversion interface is proposed. The system aims to maximize the utilization of fuel cell vehicles (FCVs) as distributed energy resources, allowing them to actively participate in the energy market. The proposed FCV2G system has FCVs, power electronics interfaces, and the electrical grid. The power electronics interfaces are responsible for converting the low-voltage output of the fuel cell stack into high-voltage DC power, and ensuring efficient power transfer between the FCVs and the grid. To optimize the operation of the FCV2G system, the momentum search algorithm (MSA) is employed. By applying MSA, the FCV2G system can achieve optimal power dispatch, considering factors such as energy efficiency, grid stability, and economic feasibility. The proposed method is tested in MATLAB. The best MSA and dynamic load profile solutions are run for 24 h and the results show that 100% import of FCVs 51.0% more than 100% electric vehicle. Peak-cutting and vehicle-to-grid service revenue are 30.5% and 95.0% greater, respectively. Low discharge loss, high capacity, and high discharge power are the main advantages of FCVs. The benchmark FCVs ratio of 15% is used for sensitivity analysis. The findings reveal that the overall advantages of FCV2G are improved.

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“…7. Compared to many researches, the hydrogen production is efficient, particularly hydrogen production with electricity/renewable energy [28].…”

Section: ) Load Profilementioning

confidence: 99%

Momentum Search Algorithm for Analysis of Fuel Cell Vehicle-to-Grid System with Large-Scale Buildings

Sivalingam,

Gurusamy

2024

Prot. Control Mod. Power Syst.

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“…Abid et al [60] attempted to iterate real-world parameters such as energy consumption, heterogenous fleets, and infrastructure data in order to minimize the total number of vehicles used, distance traveled, travel time, and energy consumption. In addition, several studies have been conducted on EVs and energy consumption [61][62][63][64].…”

Section: Literature Reviewmentioning

confidence: 99%

A Sustainable Multi-Objective Model for Capacitated-Electric-Vehicle-Routing-Problem Considering Hard and Soft Time Windows as Well as Partial Recharging

Azadi,

Khalilzadeh,

Antucheviciene

et al. 2024

Biomimetics

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Due to the high pollution of the transportation sector, nowadays the role of electric vehicles has been noticed more and more by governments, organizations, and environmentally friendly people. On the other hand, the problem of electric vehicle routing (EVRP) has been widely studied in recent years. This paper deals with an extended version of EVRP, in which electric vehicles (EVs) deliver goods to customers. The limited battery capacity of EVs causes their operational domains to be less than those of gasoline vehicles. For this purpose, several charging stations are considered in this study for EVs. In addition, depending on the operational domain, a full charge may not be needed, which reduces the operation time. Therefore, partial recharging is also taken into account in the present research. This problem is formulated as a multi-objective integer linear programming model, whose objective functions include economic, environmental, and social aspects. Then, the preemptive fuzzy goal programming method (PFGP) is exploited as an exact method to solve small-sized problems. Also, two hybrid meta-heuristic algorithms inspired by nature, including MOSA, MOGWO, MOPSO, and NSGAII_TLBO, are utilized to solve large-sized problems. The results obtained from solving the numerous test problems demonstrate that the hybrid meta-heuristic algorithm can provide efficient solutions in terms of quality and non-dominated solutions in all test problems. In addition, the performance of the algorithms was compared in terms of four indexes: time, MID, MOCV, and HV. Moreover, statistical analysis is performed to investigate whether there is a significant difference between the performance of the algorithms. The results indicate that the MOSA algorithm performs better in terms of the time index. On the other hand, the NSGA-II-TLBO algorithm outperforms in terms of the MID, MOCV, and HV indexes.

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“…A technique has been developed in [17] to enhance renewable energy systems' efficiency by perturbing and observing maximum power point tracking (MPPT) during both grid connections and failures. The potential cost reductions associated with fuel cell vehicles connected to the grid (FCV2G) are currently being investigated [18]. Using photovoltaic power as the source of FCV2G, test results are verified under dynamic loads.…”

Section: Literature Reviewmentioning

confidence: 99%

“…As shown, the decision vector X includes five parts. The first part, as expressed in (18), specifies the installation position of the sectionalizing switch. The second part, as defined in (19), indicates the open/closed state of the tie-switches.…”

Section: Decision Variablesmentioning

confidence: 99%

Multi-Objective Framework for Optimal Placement of Distributed Generations and Switches in Reconfigurable Distribution Networks: An Improved Particle Swarm Optimization Approach

Alanazi

2023

Sustainability

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Distribution network operators and planners face a significant challenge in optimizing planning and scheduling strategies to enhance distribution network efficiency. Using improved particle swarm optimization (IPSO), this paper presents an effective method for improving distribution system performance by concurrently deploying remote-controlled sectionalized switches, distributed generation (DG), and optimal network reconfiguration. The proposed optimization problem’s main objectives are to reduce switch costs, maximize reliability, reduce power losses, and enhance voltage profiles. An analytical reliability evaluation is proposed for DG-enhanced reconfigurable distribution systems, considering both switching-only and repairs and switching interruptions. The problem is formulated in the form of a mixed integer nonlinear programming problem, which is known as an NP-hard problem. To solve the problem effectively while improving conventional particle swarm optimization (PSO) exploration and exploitation capabilities, a novel chaotic inertia weight and crossover operation mechanism is developed here. It is demonstrated that IPSO can be applied to both single- and multi-objective optimization problems, where distribution systems’ optimization strategies are considered sequentially and simultaneously. Furthermore, IPSO’s effectiveness is validated and evaluated against well-known state-of-the-art metaheuristic techniques for optimizing IEEE 69-node distribution systems.

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Technoeconomic Analysis of Fuel Cell Vehicle‐to‐Grid (FCV2G) System Supported by Photovoltaic Energy

Cited by 25 publications

References 45 publications

Momentum Search Algorithm for Analysis of Fuel Cell Vehicle-to-Grid System with Large-Scale Buildings

Momentum Search Algorithm for Analysis of Fuel Cell Vehicle-to-Grid System with Large-Scale Buildings

A Sustainable Multi-Objective Model for Capacitated-Electric-Vehicle-Routing-Problem Considering Hard and Soft Time Windows as Well as Partial Recharging

Multi-Objective Framework for Optimal Placement of Distributed Generations and Switches in Reconfigurable Distribution Networks: An Improved Particle Swarm Optimization Approach

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