Optimal design and three-level stochastic energy management for an interconnected microgrid with hydrogen production and storage for fuel cell electric vehicle refueling stations

被引：22
作者：
Nagem, Nadia A. [1 ]
Ebeed, Mohamed [2 ,3 ]
Alqahtani, Dokhyl [4 ]
Jurado, Francisco [3 ]
Khan, Noor Habib [5 ]
Hafez, Wessam A. [6 ]
机构：
[1] Menoufia Univ, Fac Engn, Elect Engn Dept, Menoufia, Egypt
[2] Sohag Univ, Fac Engn, Dept Elect Engn, Sohag 82524, Egypt
[3] Univ Jaen, Dept Elect Engn, EPS Linares, Jaen 23700, Spain
[4] Prince Sattam bin Abdulaziz Univ, Elect Engn Dept, Al Kharj, Saudi Arabia
[5] North China Elect Power Univ, Dept New Energy, Beijing 102206, Peoples R China
[6] Sohag Univ, Fac Technol & Educ, Elect Dept, Sohag, Egypt
来源：
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY | 2024年 / 87卷
关键词：
Energy management; Microgrid; Uncertainty; Renewable energy resources; Fuel cell electric vehicles; Demand side response; HYBRID AC/DC MICROGRIDS; OPTIMAL OPERATION; SYSTEM; POWER; PV; OPTIMIZATION; UNCERTAINTY; ALGORITHM; UNITS; WIND;
D O I：
10.1016/j.ijhydene.2024.08.415
中图分类号：
O64 [物理化学（理论化学）、化学物理学];
学科分类号：
070304 ; 081704 ;
摘要：
A new trend in the transportation sector globally can be observed in a shift away from gasoline-powered vehicles to Hydrogen-based fuel-cell electric vehicles (FCEVs), aimed at reducing harmful emissions. However, there are challenges in producing hydrogen for vehicle stations related to microgrid design and energy management under uncertain conditions. This research sought to identify the optimum design of an electric microgrid to provide the required energy for electric loads, together with a hydrogen refueling station. The microgrid under study consists of various renewable energy resources (RERs), such as photovoltaic (PV) devices, wind power systems, and hydrogen storage systems. The energy management strategy (EMS) aims to reduce the total costs (investment, operation, replacement, procurement energy costs) considering four uncertain parameters associated with PV panels, FCEVs, wind turbines, and power demand. A three-level EMS is proposed based on testing various solutions: without RERs or a hydrogen energy storage system (Level 1); with RERs and a hydrogen energy storage system (Level 2), with RERs and hydrogen energy storage that includes demand side response (DSR) (Level 3). The results indicate annual cost savings of 1.946 E+06 $ for Level 2 and 2.001 E+06 $ for Level 3, compared to Level 1.
引用
收藏
页码：574 / 587
页数：14
相关论文
共 73 条
[1]   Integration of cascaded coordinated rolling horizon control for output power smoothing in islanded wind-solar microgrid with multiple hydrogen storage tanks [J].
Abdelghany, Muhammad Bakr ;
Al-Durra, Ahmed ;
Zeineldin, Hatem ;
Hu, Jiefeng .
ENERGY, 2024, 291
[2]   Optimizing Two-stage Energy Management in renewable-based Multi-Microgrid using a Modified Student Psychology-Based Optimization with Demand Response and Hydrogen Storage [J].
Alamir, Nehmedo ;
Kamel, Salah ;
Hashim, Fatma A. ;
Bouaouda, Anas ;
Safaraliev, Murodbek ;
Abdelkader, Sobhy M. .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2024, 63 :696-719
[3]   Fuel cell cars in a microgrid for synergies between hydrogen and electricity networks [J].
Alavi, Farid ;
Lee, Esther Park ;
van de Wouw, Nathan ;
De Schutter, Bart ;
Lukszo, Zofia .
APPLIED ENERGY, 2017, 192 :296-304
[4]   Optimal Placement and Sizing of Uncertain PVs Considering Stochastic Nature of PEVs [J].
Ali, Abdelfatah ;
Raisz, David ;
Mahmoud, Karar ;
Lehtonen, Matti .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2020, 11 (03) :1647-1656
[5]   Determining the Peer-to-Peer electricity trading price and strategy for energy prosumers and consumers within a microgrid [J].
An, Jongbaek ;
Lee, Minhyun ;
Yeom, Seungkeun ;
Hong, Taehoon .
APPLIED ENERGY, 2020, 261
[6]   Energy-based stochastic MPC for integrated electricity-hydrogen VPP in real-time markets [J].
Appino, Riccardo R. ;
Wang, Han ;
Ordiano, Jorge Angel Gonzalez ;
Faulwasser, Timm ;
Mikut, Ralf ;
Hagenmeyer, Veit ;
Mancarella, Pierluigi .
ELECTRIC POWER SYSTEMS RESEARCH, 2021, 195
[7]   Genetic-Algorithm-Based Optimization Approach for Energy Management [J].
Arabali, A. ;
Ghofrani, M. ;
Etezadi-Amoli, M. ;
Fadali, M. S. ;
Baghzouz, Y. .
IEEE TRANSACTIONS ON POWER DELIVERY, 2013, 28 (01) :162-170
[8]   Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization [J].
Atwa, Y. M. ;
El-Saadany, E. F. ;
Salama, M. M. A. ;
Seethapathy, R. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2010, 25 (01) :360-370
[9]  
Avila E, 2017, 2017 IEEE SOUTHERN POWER ELECTRONICS CONFERENCE (SPEC), P501
[10]  
Behera S., 2023, e-Prime-advances in Electrical Engineering, Electronics and Energy, V3, DOI [10.1016/j.prime.2023.100108, DOI 10.1016/J.PRIME.2023.100108]
12345678