Article
Thermodynamics
Yi Ge, Jitian Han, Qingzhao Ma, Jiahui Feng
Summary: A solar-assisted natural gas distributed energy system with energy storage is proposed to determine the optimal configuration of the system. A mixed-integer nonlinear programming model is established considering the part-load performances of devices and the total cost as objective. The study analyzes different scenarios of the system and evaluates the impact of energy price changes.
Article
Engineering, Electrical & Electronic
Jiayue Zhao, Wei Wang, Chuangxin Guo
Summary: This paper proposes an optimal configuration method for a multi-energy microgrid system in the context of the electricity market. By establishing a hierarchical collaborative optimization configuration framework and a dynamic electricity price model, it enables the collaborative operation and economic cost minimization of microgrids.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Energy & Fuels
Bishwajit Dey, Sourav Basak, Arnab Pal
Summary: This paper proposes a novel hybrid algorithm to minimize the overall cost of a microgrid system with demand-side management. Numerical results show that the algorithm outperforms existing algorithms in terms of overall generation cost reduction.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Thermodynamics
Da Xu, Zhe-Li Yuan, Ziyi Bai, Zhibin Wu, Shuangyin Chen, Ming Zhou
Summary: This paper proposes a geothermal-solar-wind renewable energy hub framework for community multi-energy supplies. The framework explores the complementarities of geothermal-solar-wind hybrid renewable energy based on the electrolytic thermo-electrochemical effects of geothermal-to-hydrogen (GTH), integrated with multi-energy conversion and storage devices. A multi-energy coupling matrix is formulated to model the production, conversion, storage, and consumption of electricity, hydrogen, and heating energy within the hub. A multi-energy operation scheme is developed to dispatch the energy flows for cost-effective accommodation of community renewables. Case studies verify the effectiveness and superiority of the proposed methodology, showing improved solar-wind accommodation and lower system operating costs.
Article
Engineering, Electrical & Electronic
Bin Li, Jianing Zhao, Yangyang Zhang, Xiaoqing Bai
Summary: This study proposes a solution to the electricity tension in agriculture by establishing a small pumped storage power station that combines wind power, photovoltaic power, and the technology of pumped storage. The system meets the irrigation demand and takes into account the fluctuation smoothing. Simulation results validate the feasibility of the system and its ability to address the water and electricity consumption issue in mountainous regions for agricultural irrigation.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2023)
Article
Thermodynamics
Peng Li, Zixuan Wang, Haitao Liu, Jiahao Wang, Tianyu Guo, Yunxing Yin
Summary: This paper proposes a bi-level optimal configuration strategy for a community integrated energy system (CIES) based on energy supply-demand responses and robustness adjustable scenarios. Through case studies and simulation results, the effectiveness and advantage of the proposed strategy are demonstrated in designing an efficient and flexible CIES.
Article
Energy & Fuels
R. Seshu Kumar, L. Phani Raghav, D. Koteswara Raju, Arvind R. Singh
Summary: This paper introduces various demand-side management strategies into microgrid energy management. A stochastic EMS framework is developed to implement flexible load shaping, price-based, and incentive-based demand response programs in the presence of non-dispatchable energy resources. The study utilizes a novel metaheuristic algorithm to enhance energy efficiency and optimize energy utilization in a modified IEEE-34 node distribution feeder-based MG network.
Article
Energy & Fuels
Bishwajit Dey, Srikant Misra, Fausto Pedro Garcia Marquez
Summary: The primary goal of this paper is to provide a demand-response (DR) model that maximizes the benefits of energy retailers, specifically microgrid customers. The model takes into account the different behaviors of customers during peak and valley periods and uses an exhaustive optimization process to calculate the optimal incentive value. The results show that the use of a DR-based energy management microgrid system significantly reduces overall generating costs and pollutants released, while also lowering the peak demand.
Article
Thermodynamics
Mohammad MansourLakouraj, Majid Shahabi, Miadreza Shafie-khah, Joao P. S. Catalao
Summary: This paper discusses the optimal operation of a microgrid in the electricity market and the communication between the distribution market operator and microgrid operator. Through effective short-term scheduling and a risk based stochastic model, the optimal operation of the microgrid is achieved, demonstrating the significant role of demand response in reducing operating costs.
Review
Computer Science, Information Systems
Guolong Ma, Jianing Li, Xiao-Ping Zhang
Summary: Microgrid is an effective solution to integrate distributed renewable energy into power system, but it faces technical challenges such as multi-vector energy system migration, increasing renewable energy penetration, and uncertainty modeling. Multi-microgrid improves system stability, reliability, economy, and energy efficiency through autonomous management and coordinated control, but also faces challenges in uncertainty modeling.
Review
Green & Sustainable Science & Technology
Lisa Gerlach, Thilo Bocklisch, Marco Verweij
Summary: The changing landscape of energy supply systems has necessitated new approaches for energy management in distribution grids, particularly with the dissemination of energy storage systems. However, a lack of coherence in agent-based systems research poses challenges to the field's advancement. This article provides a conceptual framework based on plural rationality theory to analyze and classify multiagent-based energy management, highlighting strengths and weaknesses in the literature and the underrepresentation of community-based approaches.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Green & Sustainable Science & Technology
S. K. Rai, H. D. Mathur, Ramesh C. Bansal
Summary: This paper presents an optimal energy management approach using a battery storage system (BSS) with optimum sizing to minimize the total operating cost of a nanogrid. Five different operating modes are tested to find the optimal mode on an hourly basis. Linear programming (LP) is used for objective functions with non-integer variables, while mixed-integer linear programming (MILP) is used for objective functions with an integer variable. The proposed hourly-based optimal operating mode results in 17.8-94.5% savings in day operating costs compared to the best individual operating mode. The optimal capacity of BSS is derived considering the day operating cost and adjusted with investment cost and interest paid during the lifespan, suggesting a capacity range of 4-19 kWh for this nanogrid.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2023)
Article
Computer Science, Information Systems
Zetong Fan, Ziruo Wan, Liansheng Gao, Yongkang Xiong, Guanhong Song
Summary: This paper proposes a multi-objective optimal configuration method for renewable energy generation units and battery energy storage systems in zero-carbon microgrids from the perspective of microgrid operation. The method aims to minimize the life cycle cost of the system and renewable curtailment. By using actual wind and solar power output and load data, the multi-objective problem is solved to obtain the configuration results. The validation study proves that the proposed method can promote the cooperation between generation equipment and battery energy storage system, making the microgrid more economical, and the model is stable for load changes as demonstrated by sensitivity analysis.
Article
Thermodynamics
Alireza Rahnama, Hossein Shayeghi, Abdolmajid Dejamkhooy, Nicu Bizon
Summary: This paper investigates optimal energy management in a distribution network consisting of multiple microgrids. A cooperative game method is used to find the best coalitions, and a fair profit-sharing procedure based on individual contribution value is proposed. The maximum voltage deviation in each game is used as an economic indicator to allocate rewards. The study shows that forming alliances and adopting proper profit allocation procedures can reduce system costs and increase network flexibility.
Article
Energy & Fuels
Gurkan Soykan, Gulfem Er, Ethem Canakoglu
Summary: This study determines the optimal configuration of an isolated microgrid system with renewable sources and energy storage systems using a two-stage stochastic programming-based multi-objective optimization model. The effects of different electric vehicle roles and configurations, as well as charger size, on the sizing of the microgrid are simulated and analyzed.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
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.
