Article
Energy & Fuels
Mohammad Esmaeil Hassanzadeh, Majid Nayeripour, Saeed Hasanvand, Eberhard Waffenschmidt
Summary: This paper proposes an optimal control strategy based on fuzzy logic control to support frequency regulation in microgrids. The strategy includes supplementary control units to protect the battery and manage the state of charge. Simulation results demonstrate the effectiveness of the proposed control strategy.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Zhongjie Guo, Wei Wei, Jiayu Bai, Shengwei Mei
Summary: This paper investigates the operation of renewable-dominated isolated microgrids integrated with hybrid seasonal-battery storage and proposes a data-driven scheduling-correction framework. The method eliminates the need for long-term renewable power forecasts and has been shown to outperform existing approaches in terms of economy, power supply reliability, and renewable energy utilization.
Article
Computer Science, Information Systems
Kun-Yik Jo, Seok-Il Go
Summary: This paper presents an operation method for PV-battery hybrid systems by estimating PV generation. The method aims to reduce peak load by predicting the maximum PV generation on a clear day and determining the charge and discharge set points of the battery. The effectiveness of the operation method was validated through simulation studies, showing a 30% reduction in peak load using the proposed algorithm.
Article
Energy & Fuels
R. S. Sreelekshmi, Rishika Lakshmi, Manjula G. Nair
Summary: The inevitability of energy storage has become apparent due to the rapid increase in global energy demand and integration of renewable energy with the main grid. This study explores the feasibility of battery storage and management systems for microgrids with renewable energy sources, and develops a control algorithm for battery power flow management.
Article
Green & Sustainable Science & Technology
Jiyoung Eum, Yongki Kim
Summary: The integration of residential battery energy storage systems (BESS) with balcony photovoltaic systems (PV) can address the drawbacks of renewable energy systems and reduce household electricity bills. By optimizing the charging and discharging of the battery, residential BESS can effectively manage power consumption and increase energy utilization efficiency in apartment households.
Article
Energy & Fuels
Kotb M. Kotb, Mahmoud F. Elmorshedy, Hossam S. Salama, Andras Dan
Summary: Utilizing robustly-controlled energy storage technologies can improve the stability of standalone microgrids in terms of voltages and powers. The study focuses on integrating energy storage systems like SMES within DC-bus microgrids and implementing fuzzy logic control for both batteries and SMES to enhance stability and power quality under extreme conditions. The proposed fuzzy logic control approaches show effective performance in regulating energy interchange and mitigating voltage fluctuations.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Engineering, Electrical & Electronic
Anagha Bhattacharya, Debashis Chatterjee, Swapan Kumar Goswami
Summary: A modified power sharing methodology with improved fuzzy based control is proposed for hybrid islanded micro grid system in this paper. The proposed technique takes into account the fluctuation in the input power and improves voltage and frequency regulation. A model based technique is employed using a storage unit for adjustment of the active and reactive power sharing. The effectiveness of the proposed method is evaluated through simulation and experimental verifications on a practical microgrid prototype.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Thermodynamics
Adel Merabet, Ahmed Al-Durra, Ehab F. El-Saadany
Summary: The paper introduces an improved energy management system to reduce energy costs and increase battery lifespan in a hybrid solar and wind microgrid. By analyzing different contribution factor profiles and implementing load shifting mechanism, the system shows superiority in reducing costs and improving battery degradation compared to conventional systems. Linear contribution factor and load shifting result in daily costs of $68.27 for energy and $0.81 for degradation, representing significant decreases compared to traditional systems.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Engineering, Electrical & Electronic
Xue Zhang, Wei Pei, Chunxiao Mei, Wei Deng, Jianxin Tan, Qingqing Zhang
Summary: Hydrogen refueling stations are essential for the development of hydrogen-powered vehicles, with electric-hydrogen hybrid refueling stations being a promising solution. A fuzzy power allocation strategy and control method are proposed to address power distribution and coordinated operation issues in DC microgrid-based hydrogen energy storage systems.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Computer Science, Information Systems
Mohammadreza Gholami, Soad Abokhamis Mousavi, S. M. Muyeen
Summary: This study aims to improve the reliability of microgrids by finding the optimal size and type of battery energy storage systems (BESSs). Various factors of the BESS, such as rated power, power cost, discharge time, efficiency, and life cycle, as well as power exchange limitations with the main grid, are considered. The results show that utilizing BESS can significantly improve the expected energy not supplied (EENS) of both islanded and grid-connected microgrids with power exchange limitations.
Article
Chemistry, Physical
Bei Li, Jiangchen Li
Summary: This paper proposes a three-stage algorithm to coordinate grouped hybrid storage systems: first, using multi-criteria decision making to allocate expected power to each hybrid storage system; second, employing model predictive control with support vector machine to dispatch the allocated power; third, utilizing a PID controller for reference tracking. Simulation results indicate that prediction errors in MPC lead to increased operation cost and system degradation index. The combination of fuzzy membership and MPC-Kalman filter algorithm shows better performance in reducing operation cost. The PID controller demonstrates good ability in tracking reference signals.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2021)
Article
Engineering, Electrical & Electronic
Yi Dong, Zhen Dong, Tianqiao Zhao, Zhengtao Ding
Summary: The study formulates the BESS bidding problem as a Markov Decision Process to maximize profit, introducing function approximation technology to handle massive bidding scales and avoid dimension curse. Several case studies demonstrate the effectiveness of the proposed algorithm.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Faa-Jeng Lin, Kuang-Hsiung Tan, Chao-Fu Chang, Meng-Yang Li, Tzu-Yu Tseng
Summary: This article develops an online trained intelligent voltage controller to improve the transient responses and achieve fast load shedding in a microgrid with droop control. The proposed controller, a Petri probabilistic wavelet fuzzy neural network, replaces the traditional proportional-integral controller in a battery energy storage system to enhance power sharing and load shedding.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2022)
Article
Energy & Fuels
Ariana Ramos, Markku Tuovinen, Mia Ala-Juusela
Summary: Battery Energy Storage Systems (BESS) can serve as a service for final customers, microgrids, and external actors like DSOs and TSOs. Ownership of BESS can vary between the final consumer or a third party, and the key enablers for the service model are regulatory framework that allows stacked revenues and technological interoperability.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Md. Mahadi Hasan, Abdul Hasib Chowdhury
Summary: This paper proposes a simple improved adaptive Fuzzy-ANFIS hybrid algorithm-based BESS controller, which can emulate virtual inertia by controlling the active power flow to improve frequency stability. Through different case studies and comparative analysis, the controller has demonstrated its potential to improve frequency nadir by 0.43% for sudden load variation and 0.61% for transient short circuit fault. The promising performance of the controller suggests its utility for better grid inertial support to a low inertia grid.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Akhtar Hussain, Petr Musilek
Summary: The use of electric vehicles to provide different grid services is possible due to increased penetration levels, mileage efficiencies, and usable battery sizes of EVs. This study analyzes the suitability of using EVs to provide reliability-as-a-service for different types of buildings and finds that mixed buildings are the most suitable, while commercial/industrial buildings are the least suitable. The study also proposes an index to determine the desired ratio of EVs to be contracted from homes and workplaces for mixed buildings.
Article
Engineering, Electrical & Electronic
Asfand Yar Ali, Akhtar Hussain, Ju-Won Baek, Hak Man-Kim
Summary: Improvements in the field of electric vehicles and the increasing number of catastrophic events have resulted in researchers exploring the use of stored energy in EVs to enhance the flexibility of power systems. Microgrids are seen as a potential solution to address these issues. This article proposes a revenue-driven acquisition and flexibility enhancement strategy using existing EVs in a microgrid parking lot with minimal additional capital expenditure. The viability of the proposed scheme is demonstrated through simulations.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2022)
Article
Construction & Building Technology
Akhtar Hussain, Petr Musilek
Summary: This study analyzes the resilience of power systems and electric vehicles (EVs), discussing the use of EVs as a resilience resource and strategies for enhancing EV resilience. The study also highlights the challenges and research gaps in this area.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Green & Sustainable Science & Technology
Akhtar Hussain, Petr Musilek
Summary: This study proposes an optimization method based on modified division rules to maximize utilitarianism and fairness in allocating energy to electric vehicles during outages. The concept of essential energy demand is introduced, and an EV ranking mechanism is devised to prioritize EVs based on their energy demands and urgency. The proposed method outperforms existing division rules in both utilitarianism and fairness for essential energy demand. Sensitivity analysis is also conducted to analyze the performance of the proposed method under various conditions.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Engineering, Electrical & Electronic
Akhtar Hussain, Van-Hai Bui, Hak-Man Kim
Summary: The deployment of fast charging stations is important for promoting the widespread adoption of electric vehicles, but it may overload the power system. To avoid system overload, a deep reinforcement learning-based method is proposed to operate fast charging stations with battery energy storage systems (BESS) under uncertainties. The trained model successfully reduces the peak load of the charging stations by optimizing the operation of the BESS.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Van-Hai Bui, Akhtar Hussain, Wencong Su
Summary: In this study, a novel two-step optimization model is developed to maximize the internal power trading in a distribution network comprising multiple microgrids. The proposed model combines soft actor-critic method with entropy-regularized reinforcement learning to handle large state and action spaces. Experimental results demonstrate the superiority of the proposed model in increasing internal power trading and improving retailer's profit.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Energy & Fuels
Asfand Yar Ali, Akhtar Hussain, Ju-Won Baek, Hak-Man Kim
Summary: This study proposes a trade-off scheme between resilience and peak shaving, utilizing a local static battery energy storage system (BESS) in charging stations to address the challenges posed by electric vehicles (EVs) to the power network. An optimal window size for storing energy in the BESS is determined to ensure EV resilience during contingencies while prioritizing either peak shaving or resilience based on the time of day. An optimization algorithm is developed to minimize system costs while maintaining resilience and maximizing peak shaving. Simulation results demonstrate the effectiveness of the proposed scheme, achieving additional 3.9% peak shaving and 3.41% reduction in operational costs. Sensitivity analysis is also conducted to consider factors that may impact the optimal size of the resilience window, such as market price, EV fleet size, and BESS size.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Computer Science, Artificial Intelligence
Van-Vinh Nguyen, Nhat-Tung Nguyen, Quang-Thuan Nguyen, Van-Hai Bui, Wencong Su
Summary: This study develops a multi-objective genetic algorithm-based optimization model to identify the optimal parameters for hybrid direct current circuit breakers (HCBs). The proposed algorithm is verified with a novel HCB topology, and simulation results show that the optimal parameter design significantly reduces the magnitude of the peak fault current and operating time, ensuring the safe and stable operation of the entire system.
Article
Chemistry, Inorganic & Nuclear
Azeem Ghulam Nabi, Aman Ur-Rehman, Nabia Zainab, Muhammad Hamza Akhlaq, Nisar Ahmed, Akhtar Hussain
Summary: The present research systematically studies the influence of Mn doping on the structural, electronic, and optical properties of ZnTe nanoclusters. The calculations reveal the structures and spectra of pure and Mn-doped ZnTe molecules with different numbers of atoms, and identify different modes. The results demonstrate that the wavelength of absorption peaks shifts gradually towards red due to quantum size effects.
JOURNAL OF CLUSTER SCIENCE
(2023)
Review
Computer Science, Artificial Intelligence
Ahmed Al Amin, Junho Hong, Van-Hai Bui, Wencong Su
Summary: This article provides a comprehensive review of the utilization of emerging 6G wireless communication for smart grid applications. It focuses on massive connectivity and monitoring, secured communication for operation and resource management, and time-critical operations. The article introduces the fundamentals of smart cities, smart grids, and 6G wireless communication, and explains the motivations to integrate 6G with the smart grid system. It fills the research gap by providing a literature overview and describing the novel technologies of 6G wireless communication that improve key performance indicators. The article also discusses the anticipated challenges and future research pathways.
Article
Energy & Fuels
Akhtar Hussain, Van-Hai Bui, Petr Musilek
Summary: This study proposes a welfare maximization-based soft actor critic (SAC) model to manage the demand of electric vehicle charging stations and mitigate transformer overload in distribution systems. By optimizing the welfare of EV owners and training a pricing strategy using deep reinforcement learning, real-time demand management is achieved.
Proceedings Paper
Energy & Fuels
Sina Zarrabian, Van-Hai Bui, Thai-Thanh Nguyen
Summary: This paper models and analyzes the new SUNY-Maritime College's National Security Multi-Mission Vessel (NSMV). The shipboard power system is investigated and modified by integrating battery energy storage systems (BESS) for improved performance. The results validate the effectiveness of integrated energy storage systems in shipboard power systems.
2023 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, PESGM
(2023)
Proceedings Paper
Energy & Fuels
Van -Hai Bu, Sina Zarrabian, Wencong Su
Summary: This study proposes a deep reinforcement learning-based optimization model for the operation of distribution systems. The model consists of a surrogate model and an optimization model, where the surrogate model is trained to accelerate the learning process and the optimization model utilizes deep Q learning to determine the set-points for generators, ensuring optimal power flow in the distribution network.
2023 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, PESGM
(2023)
Proceedings Paper
Energy & Fuels
Van-Hai Bui, Akhtar Hussain, Wencong Su
2023 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, PESGM
(2023)
Article
Computer Science, Information Systems
Van-Hai Bui, Fangyuan Chang, Wencong Su, Mengqi Wang, Yi Lu Murphey, Felipe Leno Da Silva, Can Huang, Lingxiao Xue, Ruben Glatt
Summary: This paper proposes a deep reinforcement learning-based optimization algorithm for power converter design parameters. By using surrogate models and optimization models, the power efficiency can be estimated quickly, and optimal design parameters can be determined. The proposed algorithm can handle large state and action spaces, and can accelerate and stabilize the learning process.
