Article
Green & Sustainable Science & Technology
Mingyang Zhang, Yinliang Xu, Hongbin Sun
Summary: This paper proposes a collaborative operation model for multiple virtual power plants (VPPs) in an active distribution network (ADN) to improve the efficiency of renewable energy utilization. In this model, the distribution system operator (DSO) organizes a joint energy-reserve market, and minimizes the total operational cost of the ADN to determine the energy and reserve prices for trading with VPPs, considering the network technical constraints and load shaping performance. VPPs aim to maximize profits by adjusting bidding quantities according to the prices issued by the DSO. The proposed bilevel model is transformed into a tractable single-level optimization problem using the Karush-Kuhn-Tucker optimality conditions and analytical methods are designed to calculate potential losses. Simulation results demonstrate the effectiveness and superiority of this approach in load shaping and system operational economy.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Engineering, Electrical & Electronic
Seyed-Mohammad Razavi, Hamid-Reza Momeni, Mahmoud-Reza Haghifam, Sadegh Bolouki
Summary: This paper presents a comprehensive approach to improve the performance of an active distribution network (ADN) with renewable resources and responsive loads. Distribution network reconfiguration (DNR) is used to optimize active losses, voltage profile, reliability, and operation costs. The approach considers the probability of renewable resource failure, solar radiation variations, and the impact of renewable resource performance. Stochastic DNR and a self-adaptive modified crow search algorithm are employed to find the optimal reconfiguration scenario.
IEEE TRANSACTIONS ON POWER DELIVERY
(2022)
Article
Engineering, Electrical & Electronic
Farid Hamzeh Aghdam, Mohammad Sadegh Javadi, Joao P. S. Catalao
Summary: This paper proposes an optimization method for the optimal operation of technical virtual power plants in a reconfigurable network to resolve potential contingency problems. The virtual power plant includes combined heat and power, renewable DGs, dispatchable DGs, thermal and electrical storage systems and loads. The uncertainties of renewable DGs and demand levels are handled using chance constrained programming to ensure the security of the system.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Engineering, Civil
Lei Yu, Xiufeng Wu, Shiqiang Wu, Benyou Jia, Guoyi Han, Peng Xu, Jiangyu Dai, Yu Zhang, Fangfang Wang, Qianqian Yang, Zehui Zhou
Summary: Maintaining ecological flow and mitigating impacts on river health are essential for sustainable hydropower development. Research on the Yalong River in China demonstrates clear tradeoffs between cascade power generation and ecological flow assurance under different environmental conditions, providing crucial evidence for stakeholder dialogue and decision-making in hydropower operation modes.
JOURNAL OF HYDROLOGY
(2021)
Article
Chemistry, Analytical
Li Gong, Xianpei Wang, Meng Tian, Hongtai Yao, Jiachuan Long
Summary: This paper addresses the issue of the distribution network in smart grid relying on cyber systems to achieve active control with high penetration of photovoltaic (PV) generator. It proposes a modeling and optimization approach to minimize cost and maximize stability, aiming to mitigate the impact of PV power and line-switch state uncertainties on the distribution network.
Article
Computer Science, Information Systems
Libo Fan, Weiguo Si, Yi Xuan, Zhiqing Sun, Jian Zhao, Bin Xu, Qiuhan Gu
Summary: The distribution network of prosumer group is equipped with switches for topological adjustment after faults occur, improving reliability and reducing fault handling time. Multi-objective optimization is achieved through minimizing costs and maximizing income.
Article
Thermodynamics
Zhiguang Hua, Tianhong Wang, Xianglong Li, Dongdong Zhao, Yuanlin Wang, Manfeng Dou
Summary: This research introduces a multi-objective comprehensive optimization power distribution strategy specifically designed for a hybrid electric vehicle that utilizes both fuel cell and battery technology. The strategy focuses on optimizing the operational cost and service life of the fuel cell stack, as well as the energy storage system's lifetime loss and state of charge (SOC) fluctuation. Furthermore, the research aims to enhance fuel efficiency by optimizing the hydrogen consumption of the system. The proposed strategy has been validated using hardware-in-the-loop (HIL) bench, showing advantages over other benchmark power distribution strategies.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Thermodynamics
Abdullah M. Shaheen, Ragab A. El-Sehiemy, Mosleh M. Alharthi, Sherif S. M. Ghoneim, Ahmed R. Ginidi
Summary: The article introduces an enhanced multi-objective Quasi-Reflected Jellyfish Search Optimizer (MOQRJFS) for solving multi-dimensional Optimal Power Flow (MDOPF) issue. With two modifications to strengthen the searching capability of JFS algorithm, the MOQRJFS is applied to various systems and proven to be superior.
Article
Engineering, Electrical & Electronic
Tianwei Zhong, Hai-Tao Zhang, Yuanzheng Li, Lan Liu, Renzhi Lu
Summary: This article proposes a scheme to address the reconfiguration problem of DPN with high wind power penetrations, balancing voltage stability and wind energy absorption rate. A multi-objective optimization problem is formulated with a curtailment strategy to maximize wind power absorption and improve voltage stability. A modified multi-objective evolutionary algorithm and TOPSIS method are applied to find a tradeoff solution, with numerical case studies on an IEEE-33 bus system verifying the scheme's effectiveness.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Environmental Sciences
Yang Song, Chunqi Shen, Ying Wang
Summary: By coupling the non-dominated sorting genetic algorithm-II (NSGA-II) model and the General Lake Model-Aquatic EcoDynamics library (GLM-AED) model, reservoir operation strategies (ROSs) can effectively control algal blooms. In the case of Zipingpu Reservoir, the peak of outflow discharge can be reduced by 19%, total power generation can be increased by 8%, and the peak of chlorophyll a concentration can be decreased by 36% compared to the original reservoir operation. Balancing the objectives of algal bloom control, flood prevention, and power generation is crucial in reservoir operations.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
C. G. Marcelino, G. M. C. Leite, C. A. D. M. Delgado, L. B. de Oliveira, E. F. Wanner, S. Jimenez-Fernandez, S. Salcedo-Sanz
Summary: This paper addresses the short-term hydro-power unit commitment problem in a multi-reservoir system using a new mathematical modeling approach and the MESH algorithm. The results show that MESH outperforms other evolutionary algorithms in terms of efficiency and accuracy, providing significant profit in a realistic hydro-power energy system scenario.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Hongjun Gao, Wang Ma, Yingmeng Xiang, Zao Tang, Xiandong Xu, Hongjin Pan, Fan Zhang, Junyong Liu
Summary: This paper proposes a multi-objective dynamic reconfiguration optimization model to address the unbalanced load demands in an urban distribution network. The model utilizes multi-level switching modes and a load balancing index to quantify the global load balancing degree. Stochastic programming and fuzzy c-means clustering are used to handle the uncertainties of photovoltaic generators and loads. The modified binary particle swarm optimization and Cplex solver are employed to solve the optimization problem of the proposed model.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2022)
Article
Energy & Fuels
Kyeongseon Park, Dongyeong Lee, Gilsoo Jang
Summary: In recent years, there have been significant changes in power systems known as energy transitions, that involve the replacement of synchronous generators with power electronics-based generation. Due to this replacement, the voltage stability of power systems has become a major concern. This study proposes a multi-objective optimization approach using the non-dominated sorting genetic algorithm III to improve the voltage stability of the overall system by optimizing reactive power reserve procurement.
Article
Green & Sustainable Science & Technology
Alper Cicek
Summary: Nowadays, renewable energy sources (RESs) are becoming increasingly important in meeting the energy demand of residential and transportation sectors due to environmental concerns and the need for energy reliability. This study proposes a multi-objective stochastic optimum energy management model for a renewable-supported hydrogen-based community. The model utilizes a hydrogen energy system (HES) consisting of an electrolyzer, hydrogen tank, and fuel cell to provide energy to the community and fuel support for hydrogen fuel cell electric vehicles (HFCEVs). The effectiveness of the model is demonstrated through various case studies using real data from Spain, showing a 58.67% reduction in community cost.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2023)
Article
Computer Science, Information Systems
Li Tong, Shen Zhao, Hang Jiang, Jinhui Zhou, Bin Xu
Summary: This paper introduces a distribution network optimal scheduling model based on mobile energy storage system, which solves the overvoltage issue caused by distributed power sources and household electric vehicles through multi-scenario multi-objective collaborative optimization.
Article
Energy & Fuels
Ehsan Azad-Farsani, Hamed Zeinoddini-Meymand, Hamed Jafari
Summary: This paper presents a two-stage policy to deal with network configuration and wind power uncertainty. It uses a modified firework algorithm for network reconfiguration and proposes a strategy to minimize the impact of wind power curtailment by changing the network configuration.
ENERGY SCIENCE & ENGINEERING
(2023)
Article
Computer Science, Information Systems
Amir Reza Aqamohammadi, Taher Niknam, Sattar Shojaeiyan, Pierluigi Siano, Moslem Dehghani
Summary: This study proposes a smart fault detection method (FDM) for microgrids (MGs) based on the Hilbert-Huang transform (HHT) and deep neural networks (DNNs). The method aims to rapidly detect fault type, phase, and location data to protect MGs and restore services. The approach preprocesses branch current measurements using HHT and extracts features using singular value decomposition (SVD) for input to DNNs. Compared to previous studies, this method achieves higher fault-type identification accuracy and can determine new fault locations. Evaluation on IEEE 34-bus and MG systems demonstrates its effectiveness in terms of detection precision, computing time, and robustness to measurement uncertainties.
Article
Computer Science, Information Systems
Mohammad Ghiasi, Taher Niknam, Moslem Dehghani, Hamid Reza Baghaee, Zhanle Wang, Mohammad Mehdi Ghanbarian, Frede Blaabjerg, Tomislav Dragicevic
Summary: This article introduces an enhanced control strategy for renewable energy resources connected to microgrids through voltage-sourced converters. The strategy includes various controllers designed using the finite control set-model predictive control (FCS-MPC) strategy. The controllers can be applied in both grid-connected and island operation modes. The proposed method improves the computation power by eightfold and is proven to be superior theoretically. Simulation and hardware experiments validate the efficiency, authenticity, and compatibility of the proposed control strategy.
IEEE SYSTEMS JOURNAL
(2023)
Article
Green & Sustainable Science & Technology
Marzieh Mokarram, Jamshid Aghaei, Mohammad Jafar Mokarram, Goncalo Pinto Mendes, Behnam Mohammadi-Ivatloo
Summary: The study aims to predict solar energy generation in order to ensure the successful operation of solar power plants. Multiple linear regression and feature selection techniques are used to calculate energy generation, while long short-term memory (LSTM) is used to predict energy generation levels based on climate conditions. The results show that temperature, solar radiation, relative humidity, wind speed, wind direction, and vapor pressure deficit are the most significant parameters for predicting energy generation. The LSTM method proves to be highly accurate in predicting fluctuating energy generation patterns.
IET RENEWABLE POWER GENERATION
(2023)
Article
Computer Science, Information Systems
Ahmed Hamed Ahmed Adam, Jiawei Chen, Salah Kamel, Hamed Zeinoddini-Meymand
Summary: This study thoroughly investigates the zero voltage switching (ZVS) operation range and deadband conditions for a bidirectional DC-DC converter with phase shift control and dual H-bridge. The analysis considers the soft switching range of the DAB converter, taking into account the effects of the deadband and ZVS capacitor. By utilizing the circuit's differential equation during the deadband time, sufficient constraints for the input and output bridges can be determined. The findings demonstrate that increasing the phase shift value expands the ZVS range and reduces switching losses, with the minimum required phase shift value decreasing as the output voltage increases. Simulation results and MATLAB/SIMULINK validation are provided for various operating conditions.
JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING
(2023)
Article
Energy & Fuels
Mohammadali Norouzi, Jamshid Aghaei, Taher Niknam, Mohammadali Alipour, Sasan Pirouzi, Matti Lehtonen
Summary: This paper presents a data-driven model, RFEMS, to optimize the operation of MGs based on risk-averse flexi-intelligent energy management system. The proposed model uses a hybrid deep-learning model to forecast uncertain parameters and optimize the MG operation based on the obtained uncertainty forecasting results. The results show improved performance in wind, solar, load, and price forecasting, as well as significant improvements in operating indices in test networks.
Article
Thermodynamics
Mohammad Jafar Mokarram, Reza Rashiditabar, Mohsen Gitizadeh, Jamshid Aghaei
Summary: This paper presents a new framework for forecasting electricity power net-load in renewable energy systems, which is crucial for the economic well-being, stability, and security of power networks. The framework combines deep learning, fuzzy system, and discrete wavelet transforms to achieve high accuracy prediction. The proposed method achieves a forecast accuracy of 97.7% and further improves to 99.5% by incorporating wavelet transforms and fuzzy system simultaneously.
Article
Engineering, Electrical & Electronic
Moslem Dehghani, Taher Niknam, Mina GhasemiGarpachi, Hassan Haes Alhelou, Motahareh Pourbehzadi, Giti Javidi, Ehsan Sheybani
Summary: The purpose of this paper is to analyze cyber security issues in smart grids, including prior cyber-attacks, vulnerability issues, and enhanced security procedures. It is important to consider motivations, obstacles, and socio-economic conditions when designing public policies for smart grids. The paper evaluates a group of policies suggested by stakeholders and assesses their potential for developing cyber security. The study finds that the policies with the most attention are regulatory changes to foster innovation, regulation of new business models, and establishment of a cyber-security governance strategy.
IET GENERATION TRANSMISSION & DISTRIBUTION
(2023)
Article
Environmental Studies
Milad Haghani, Frances Sprei, Khashayar Kazemzadeh, Zahra Shahhoseini, Jamshid Aghaei
Summary: This article provides a comprehensive view of scholarly research on Electric Vehicles (EV) and determines the current research trends based on objective data analysis. The findings indicate that charging infrastructure, EV adoption, thermal management systems, and routing problems have been the major research topics in recent years. Additionally, the research reveals that the frequency of research on hybrid EV has either stabilized or declined in major subfields of EV research.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
Article
Computer Science, Artificial Intelligence
Shahabodin Afrasiabi, Mousa Afrasiabi, Mohammad Amin Jarrahi, Mohammad Mohammadi, Jamshid Aghaei, Mohammad Sadegh Javadi, Miadreza Shafie-Khah, Joao P. S. Catalao
Summary: In this article, a WAMS-based load modeling method is proposed, which combines impedance-current-power and induction motor, and utilizes deep learning techniques to understand the time-varying and complex behavior of the load. The method is shown to be effective and robust in numerical experiments, and outperforms other methods significantly.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Vali Talaeizadeh, Heidarali Shayanfar, Jamshid Aghaei
Summary: This paper proposes mathematical centralized/decentralized optimization frameworks for flexibility market structures, including a transmission-level centralized market, a local distribution-and centralized transmission-level market, a TSO priority market, and a TSO-DSO price equilibrium market. The paper also develops prioritization mechanisms to improve the performance of the real-time flexibility market. The proposed frameworks are evaluated through simulation experiments.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Automation & Control Systems
Mohsen Farbood, Mokhtar Shasadeghi, Taher Niknam, Behrouz Safarinejadian, Afshin Izadian
Summary: The main aim of this article is to propose a MB-based robust model predictive control (MPC) for nonlinear systems, considering the model uncertainties and disturbances based on Takagi-Sugeno fuzzy models. The suggested RMPC consists of an offline part and an online MB-based MPC.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Sobhan Farjam Keleshteri, Taher Niknam, Mohammad Ghiasi, Hossein Chabok
Summary: This paper proposes a new approach for optimal siting and sizing of PEV charging stations in a coupled electrical and transportation network. The Pareto method is used to solve the problem and the Floyd-Warshall method is utilized to determine the shortest travel routes for PEVs. The obtained results confirm the effectiveness of the optimal planning of PEV charging stations.
JOURNAL OF ENGINEERING-JOE
(2023)
Article
Green & Sustainable Science & Technology
Ahmad Nikoobakht, Jamshid Aghaei
Summary: This paper discusses the improvement of energy efficiency in traditional energy systems under extreme natural disasters by integrating information and cyber technologies. It proposes a model of cyber-physical energy systems to model the integration and improve cost-benefit and energy performance under extreme natural disasters.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2023)
Article
Engineering, Electrical & Electronic
Pekka Manner, Ville Tikka, Samuli Honkapuro, Kyoesti Tikkanen, Jamshid Aghaei
Summary: This article proposes and demonstrates a method for home chargers to participate in the fast-reacting ancillary service market with only software modifications. Through laboratory testing and an economic feasibility study, the approach's potential business opportunity is proven.
IET GENERATION TRANSMISSION & DISTRIBUTION
(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)
