Article
Thermodynamics
Daniele Colarossi, Paolo Principi
Summary: Traditional cold ironing allows ships to be powered by an on-shore power supply during berthing, reducing pressure on the national grid. This paper presents an optimization model for a combined photovoltaic/energy storage/cold ironing system, with the ferry traffic of the port of Ancona used as a case study. Results show that the optimal configurations can achieve significant CO2 reduction.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Energy & Fuels
Nikolaos Sifakis, Emmanouil Vichos, Angelos Smaragdakis, Emmanouil Zoulias, Theocharis Tsoutsos
Summary: This study conducted a technoeconomic analysis comparing a hybrid renewable energy power plant with a hydrogen energy storage system to the cold-ironing technique. The results show that hydrogen storage systems have lower costs for larger infrastructures. Additionally, these hybrid systems significantly reduce energy costs and carbon footprint, contributing to the development of nearly Zero Energy Ports.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Kyaw Hein, Yan Xu, Gary Wilson, Amit K. Gupta
Summary: The research focuses on the coordination of AES and HESS for optimal voyage planning and multi-objective energy management to optimize vessel route, operation cost, emission, and ESS degradation.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Energy & Fuels
Nur Najihah Abu Bakar, Najmeh Bazmohammadi, Halil Cimen, Tayfun Uyanik, Juan C. Vasquez, Josep M. Guerrero
Summary: This paper proposes a data-driven approach for forecasting the berthing duration of ships undergoing cold ironing using various models. The artificial neural network outperforms other models in handling complex forecasting problems and provides accurate predictions. This information is vital for port operators.
Article
Energy & Fuels
Hamid Zakernezhad, Mehrdad Setayesh Nazar, Miadreza Shafie-khah, Joao P. S. Catalao
Summary: This paper presents a two-level optimization model for the optimal scheduling of an active distribution system in day-ahead and real-time market horizons. The proposed framework considers the arbitrage strategy of different stakeholders and uses robust and lexicographic ordering optimization methods.
Article
Thermodynamics
Peng Gao, Hao Hu, Shengxiang Jin, Shu Wang, Yanlin Chen, Weidong Wu, Qiguo Yang, Fangqi Zhu, Liwei Wang
Summary: This paper proposes a solar-driven refrigeration/cold energy storage system that can effectively solve the problem of delayed precooling of freshly harvested fruits and vegetables in rural regions. It shows high energy efficiency and adaptability.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Thermodynamics
Alicia Crespo, Daniel Gibert, Alvaro de Gracia, Cesar Fernandez
Summary: This study applies deep reinforcement learning (DRL) to control a solar-driven seasonal sorption thermal energy storage (TES) system for the first time and compares it with a traditional optimized rule-based control strategy. The results show that the DRL strategy significantly reduces the operational costs of the system, but performs worse once the sorption TES is fully discharged.
APPLIED THERMAL ENGINEERING
(2024)
Article
Environmental Studies
Xiaohan Liu, Xiaoyue Cathy Liu, Zhengke Liu, Ruifeng Shi, Xiaolei Ma
Summary: This study investigates the location problem of solar-powered bus charging infrastructure by considering photovoltaic and energy storage system (PESS). A two-stage robust optimization model is formulated to handle the uncertainty of charging service degradation. The results of a case study using a sub-network of Beijing public transport show that PESS can lower the daily bus charging costs and improve the service capacity of passengers when the charging service degrades.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
Article
Engineering, Electrical & Electronic
Kyaw Hein
Summary: A data-driven many-objective voyage and energy management scheduling of all-electric ships (AES) with energy storage systems (ESS) and solar photovoltaic (PV) is proposed to improve operational efficiency. The study demonstrates that non-dominated sorting algorithms and an LSTM-based PV forecast model can efficiently identify optimal operating points that meet all constraints and objectives within 300 iterations.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Energy & Fuels
Ramesh Gugulothu, Bhookya Nagu, Deepak Pullaguram, B. Chitti Babu
Summary: Energy management strategy (EMS) is proposed to optimize the flow rate, discharge, and charge cycles of battery energy storage systems (BESS) by coordinating supercapacitors (SC) and photovoltaic systems (PV). The proposed EMS reduces the impact of high charge/discharge currents on the BESS and extends its life by using SC to handle transient energy mismatches. Simulation and hardware validation show improved performance of BESS and SC with the proposed EMS compared to conventional charge and discharge methods for hybrid energy storage systems (HESS). Economic analysis demonstrates the cost-effectiveness and economy of standalone PV and HESS systems with the proposed EMS over PV and BESS systems beyond 6 years of operation.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Thermodynamics
Jingze Yang, Zhen Yang, Yuanyuan Duan
Summary: The study proposed a hybrid renewable energy system with the optimal combination obtained through a multi-objective optimization algorithm. It was found that the combination of CSP plant and PV plant is an effective way to improve power generation reliability. The recommendation is to use power cycle to supplement power shortages.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Thermodynamics
Yi He, Su Guo, Jianxu Zhou, Feng Wu, Jing Huang, Huanjin Pei
Summary: The proposed wind-photovoltaic-thermal energy storage-electric heater cogeneration system effectively addresses the fluctuating wind and photovoltaic output, and optimizes objectives, capacity optimization problem, and the performance comparison of many-objective algorithms. The system is feasible and cost-effective for practical applications.
Article
Energy & Fuels
Youssef Amry, Elhoussin Elbouchikhi, Franck Le Gall, Mounir Ghogho, Soumia El Hani
Summary: In electric vehicle charging systems, energy storage systems (ESS) are commonly used to supplement solar power and store excess energy. This article explores a hybrid system with a flywheel and PV for an EV workplace charging station. The study investigates the optimal sizing and operational cost of the hybrid system to make it more cost-effective. Comparative studies are carried out for different charging station models in different climate zones to determine the viability and cost-effectiveness of the proposed system.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Engineering, Electrical & Electronic
Yinping Yang, Chao Qin, Yuan Zeng, Chengshan Wang
Summary: The study proposes a cooperative model that combines wind, solar, and pumped-storage technologies, which effectively utilizes the complementary characteristics of wind and solar power. The model includes an optimized bidding strategy and a revenue distribution method, ensuring economic benefits for participating members.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2022)
Article
Thermodynamics
Akhilesh Gandhi, Manali S. Zantye, M. M. Faruque Hasan
Summary: Energy storage is crucial for addressing the challenges of intermittent and variable renewable energy sources. Cryogenic energy storage is a promising approach with high technology readiness level. Researchers have developed a mathematical model to calculate the costs of energy storage under different scenarios and discuss key decision-making questions in energy transition.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Engineering, Multidisciplinary
Yuan Si, Zezhong Wang, Lianguang Liu, Amjad Anvari-Moghaddam
Summary: When geomagnetic disturbances (GMDs) occur, the reactive power loss caused by geomagnetically induced currents flowing through transformers can lead to system instability. This article focuses on the transient stability of a hybrid system based on wind and conventional energy sources, and quantitatively analyzes the influence of GMDs on transient stability under different proportions of wind farm output power. The research results provide a basis for disaster prevention and control of GMDs.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2023)
Article
Engineering, Multidisciplinary
Tong Wang, Xiaotong Wang, Guangmeng Liu, Zengping Wang, Qipeng Xing
Summary: This article introduces the application of Lyapunov functions based on artificial intelligence (AI) method in transient stability assessment and determination of stability region (SR). The characteristics of neural networks as general function approximators are employed to construct the Lyapunov function combined with stochastic gradient descent (SGD). The proposed construction method of Lyapunov functions is validated and proved effective through tests on a IEEE 9-bus 3-machine system.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2023)
Article
Green & Sustainable Science & Technology
Sijia Li, Arman Oshnoei, Frede Blaabjerg, Amjad Anvari-Moghaddam
Summary: Microgrids enable efficient utilization of integrated energy systems with renewable energy sources. Managing fluctuating renewable energy generation and sudden load changes is a major challenge in microgrid control and operation. Hierarchical control techniques have received attention, with machine learning-based approaches showing promising features and performance. This paper reviews the application of classical control and machine learning techniques in hierarchical control systems, comparing their methods, advantages, disadvantages, and implementation across different control levels. The paper highlights the potential of machine learning to enhance control accuracy and address system optimization concerns in microgrid hierarchical control, but challenges such as computational intensity, stability analysis, and experimental validation remain to be addressed.
Editorial Material
Chemistry, Multidisciplinary
Amjad Anvari-Moghaddam, Pooya Davari, Omar Hegazy
APPLIED SCIENCES-BASEL
(2023)
Article
Energy & Fuels
Hongyu Lin, Xingbang Han, Pengshuo Yu, Qingyou Yan, Shenbo Yang, Mengshu Shi, Amjad Anvari-Moghaddam, Dong Liang
Summary: This paper aims to enhance the utilization rate of renewable energy and reduce carbon emissions by establishing a stable and clean energy supply mode for a charging system and constructing a three-stage optimization and benefit distribution model.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Engineering, Electrical & Electronic
Amirhossein Ahmadi, Saman Taheri, Reza Ghorbani, Vahid Vahidinasab, Behnam Mohammadi-Ivatloo
Summary: This study proposes a new ensemble model for dynamic line rating forecasting of overhead transmission lines. By utilizing multivariate empirical mode decomposition, the proposed ensemble model overcomes the limitations of single models and improves the forecasting performance. The results show that the ensemble model can accurately predict the dynamic line rating and is robust to noisy data.
IEEE TRANSACTIONS ON POWER DELIVERY
(2023)
Article
Green & Sustainable Science & Technology
Mohammadreza Daneshvar, Behnam Mohammadi-ivatloo, Amjad Anvari-Moghaddam
Summary: A comprehensive water-energy nexus model is developed for cooperative prosumers equipped with 100% renewable energy sources in the modern interconnected energy structure. The model utilizes transactive energy technology to enable prosumers to cooperatively share multi-energy in a deregulated environment, ensuring reliable power and water supply. A risk-averse stochastic operational model is proposed to address the high risks associated with renewable energy intermittences.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Energy & Fuels
Mohammad Dehghani Sanij, Ahmad Mirzaei, Amjad Anvari-Moghaddam
Summary: A new model is proposed to coordinate the planning of distribution networks and regional energy networks (RENs) in the presence of responsive loads, in order to overcome the challenges posed by competitive electricity markets and responsive loads participation. The results of numerical studies show that the flexibility of the demand side in the electrical sector leads to an increase in the installation capacity of energy resources and storages.
ENERGY SCIENCE & ENGINEERING
(2023)
Article
Construction & Building Technology
Hongyu Lin, Jialu Dang, Haowei Zheng, Lujin Yao, Qingyou Yan, Shenbo Yang, Hongzhen Guo, Amjad Anvari-Moghaddam
Summary: This paper proposes a two-stage bi-layer game charging optimization model for the coordination problem between a network operator, a distributed generation operator, and a charging agent. The model includes a dynamic virtual price-based demand response model and a bi-layer Stackelberg game strategy. Simulation results show that the model effectively reduces energy abandonment and net load fluctuation and achieves optimal comprehensive benefits. Therefore, the bi-layer Stackelberg game approach realizes multi-dimensional benefits in the multi-participant charging system.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Construction & Building Technology
Shahab Eslami, Younes Noorollahi, Mousa Marzband, Amjad Anvari-Moghaddam
Summary: This study utilizes a geographic information system (GIS) to analyze different layers and identify the most suitable locations for district heating in Gaziantep, Turkey. The study employs a mixed integer linear programming (MILP) approach to model proposed energy systems and achieve optimal operation and planning. Results show that a hybrid energy system with a renewable energy penetration rate of 78% achieves the best levelized cost of energy (LCOE) of 0.0442.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Engineering, Electrical & Electronic
Zekun Li, Yi Sun, Hongyue Yang, Shiwei Wang, Yaqi Shen, Xianchun Wang, Kai Zhang, Amjad Anvari-Moghaddam
Summary: With the increased electrification of transportation sector, electric vehicles (EVs) are deemed to be key players in energy scheduling to achieve more economical operation of distribution networks. This paper proposes a multi-time scale coordinated control and scheduling strategy, taking into account the spatial characteristics of EVs and the transferable charging power. The simulation results demonstrate that the proposed strategy can guide more EVs to be grid-connected, promote multi-time scale economic scheduling, and benefit the EV users.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Computer Science, Information Systems
Hamed Moayyed, Arash Moradzadeh, Amin Mansour-Saatloo, Behnam Mohammadi-Ivatloo, Mehdi Abapour, Zita Vale
Summary: This article presents a novel model for dynamic line rating (DLR) forecasting using a federated learning approach. By generating a global model, the approach accurately predicts the maximum current carrying capacity of transmission lines while ensuring data security and protection from cyberattacks. The proposed model is trained using data from nine different regions in Iran and successfully predicts DLR values for new regions with correlation coefficients of 96%, 94%, and 97% for Boroujen, Nahavand, and Rafsanjan, respectively.
IEEE SYSTEMS JOURNAL
(2023)
Review
Energy & Fuels
Amirhossein Solat, G. B. Gharehpetian, Mehdi Salay Naderi, Amjad Anvari-Moghaddam
Summary: This paper provides a comprehensive review of control strategies and defense mechanisms against cyber-attacks in microgrids (MGs). It discusses the operational conditions of MGs and presents appropriate control methods to ensure a safer mode. The common MGs communication system and the classification of cyber-attacks in MGs are described. Furthermore, the paper summarizes the existing research on prevention, detection, and isolation of cyber-attacks, as well as the control of MGs against such attacks. Finally, future trends in this field are discussed.
Article
Environmental Sciences
Arash Moradzadeh, Hamed Moayyed, Behnam Mohammadi-Ivatloo, Antonio Pedro Aguiar, Amjad Anvari-Moghaddam, Zulkurnain Abdul-Malek
Summary: This study proposes a global solar radiation forecasting approach based on federated learning and convolutional neural network, which accurately predicts solar irradiance and protects data privacy. The results show that this method performs well in solar radiation prediction in different regions.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Business
Mohammadreza Daneshvar, Behnam Mohammadi-ivatloo, Kazem Zare, Amjad Anvari-Moghaddam
Summary: This article aims to develop a novel framework for achieving techno-economic-environmental goals in the grid modernization process. It explores the optimal utilization of energy hubs equipped with 100% renewables to pursue environmental goals while considering technical and economic constraints. The power-to-gas system enables multienergy interactions between electricity and gas networks. Risk-averse and seeker strategies are developed to deal with uncertain fluctuations, based on robustness and opportunistic modes of the information gap decision theory. The proposed framework provides a rational decision-making model for balancing multienergy in the hybrid energy grid with 100% renewables.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2023)
Article
Green & Sustainable Science & Technology
Seyed Majid Hashemzadeh, Mohammed A. Al-Hitmi, Hadi Aghaei, Vafa Marzang, Atif Iqbal, Ebrahim Babaei, Seyed Hossein Hosseini, Shirazul Islam
Summary: This article proposes an interleaved high step-up DC-DC converter topology with an ultra-high voltage conversion ratio for renewable energy applications. The converter utilizes an interleaved structure to reduce the input source current ripple, which is advantageous for solar PV sources. By employing voltage multiplier cells and coupled inductor techniques, the topology enhances the output voltage. The article provides comprehensive operation modes and steady-state analyses, compares the proposed structure with other similar converter topologies, and validates the mathematical analysis with experimental results.
IET RENEWABLE POWER GENERATION
(2024)
Article
Green & Sustainable Science & Technology
Gang Xu, Zixuan Guo
Summary: This paper proposes a two-stage resilience enhancement strategy for the recovery of critical loads after disasters. The first stage utilizes a heuristic algorithm to determine the post-disaster topology, while the second stage incorporates user demand response to maximize the socio-economic value of the recovery.
IET RENEWABLE POWER GENERATION
(2024)
Article
Green & Sustainable Science & Technology
Faruk Oral
Summary: This study investigates the wind characteristics and electricity generation potential from wind energy in the Bitlis-Rahva region in eastern Turkey. Wind data from the Bitlis meteorological station is analyzed using the WindPRO program to determine the wind speed distribution and predict turbine performance. The results show that the region has low wind energy capacity factor, indicating it is not efficient for wind energy investments. However, it is suggested that higher altitudes in the region may have better wind energy utilization.
IET RENEWABLE POWER GENERATION
(2024)
Article
Green & Sustainable Science & Technology
Yingjie Tang, Zheren Zhang, Zheng Xu
Summary: This paper investigates the modular multilevel matrix converter with symmetrically integrated energy storage for low frequency AC system. An evaluation method for the minimum required number of active submodules is presented, and the influences of operating conditions on the minimum required number of active submodules are studied. Issues about the converter control system are also discussed in this paper.
IET RENEWABLE POWER GENERATION
(2024)
