Article
Energy & Fuels
Hao Tian, Keqing Wang, Xiufeng Cui, Zexi Chen, Ergang Zhao, Sara Saeedi
Summary: This research focuses on the optimal planning of microgrids by incorporating renewable energy sources and conventional units. A multi-objective model is used to consider economic factors and energy management, while accounting for limitations and different energy sources for a more realistic approach. The model takes into account the uncertainty in production capacity of wind turbines and photovoltaics, and incorporates load uncertainty, price, and renewable energy production. Through a demand response program with incentives, the model aims to maximize profitability and minimize costs. To solve the conflicting objectives, a developed optimization algorithm based on teaching-learning and fuzzy theory is proposed.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Green & Sustainable Science & Technology
Daniel Akinyele, Abraham Amole, Elijah Olabode, Ayobami Olusesi, Titus Ajewole
Summary: Energy systems modelling and design play a crucial role in planning and development, requiring the integration of key dimensions to achieve sustainable energy supply. This paper focuses on simulation and analysis approaches for sustainable planning, design, and development of microgrids based on clean energy resources.
Article
Thermodynamics
Felipe Verastegui, Alvaro Lorca, Daniel Olivares, Matias Negrete-Pincetic
Summary: Several countries are adopting plans to reduce contaminant emissions from the energy sector through renewable energy integration and restrictions on fossil fuel generation. This study develops a planning model that includes an effective representation of the system's operational aspects to understand the key role of flexible resources in highly renewable power systems undergoing strong decarbonization. The results show that highly renewable generation mixes are feasible with an effective balance of flexibility attributes like ramping, storage, and transmission capacities.
Review
Green & Sustainable Science & Technology
Troy Malatesta, Gregory M. Morrison, Jessica K. Breadsell, Christine Eon
Summary: The development of renewable energy systems is a potential solution for residential energy consumption, but these systems face barriers and challenges due to the nature of home energy demand and household behaviors. A systematic literature review highlights gaps in the research and shows the limitations of integrating renewable energy systems into everyday lives. Personal and social barriers inhibit behavior change and limit the adoption of renewable systems. The review emphasizes the need for technology, consumers, and policies to interact in creating a sustainable energy solution to address the climate emergency, including reevaluating home automation and energy management system designs.
Article
Green & Sustainable Science & Technology
Daniel J. Sambor, Samantha C. M. Bishop, Aaron Dotson, Srijan Aggarwal, Mark Z. Jacobson
Summary: Reliance on imported diesel fuel and high transportation costs have made power and water treatment expensive in remote diesel microgrids in the Arctic; attempts to implement piped water in these areas have proven difficult; a modular Water Reuse system provides affordable, distributed water service but still consumes substantial electricity.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Thermodynamics
I. L. R. Gomes, R. Melicio, V. M. F. Mendes
Summary: This paper presents a microgrid support management system based on a stochastic mixed-integer linear programming problem, managed and operated by a new electricity market agent, the microgrid aggregator. Plausible scenarios are computed using Kernel Density Estimation to characterize random variables, and a scenario reduction is carried out with a two-tier procedure involving K-means clustering technique and a fast backward scenario reduction method. Case studies demonstrate the performance of the microgrid and validate the methodology proposed for the microgrid support management system.
Article
Computer Science, Information Systems
Muaiz Ali, Mohamed A. A. Abdulgalil, Ibrahim Habiballah, Muhammad Khalid
Summary: A new method has been developed to minimize the operating cost in microgrids integrated with renewables and energy storage systems (ESSs) through demand response. By shifting some of the load from high-price periods to low-price periods, the operating cost is reduced for operators and bill prices decrease for consumers. The optimization problem is solved using mixed integer quadratically constrained programming (MIQCP) in the General Algebraic Modeling System (GAMS) with the CPLEX solver.
Article
Green & Sustainable Science & Technology
Geremi Gilson Dranka, Paula Ferreira, A. Ismael F. Vaz
Summary: This study examines the integration of demand-side management resources with clean energy supply options and proposes a framework for assessing the co-benefits of energy efficiency and demand-response in renewable-based energy systems. The results show that implementing DSM strategies can reduce new installed capacity, CO2 emissions, and total system costs. The study also suggests that investing in energy efficiency is more economically valuable than investing only in demand-response strategies. These findings have important implications for governments and policymakers in scaling up energy efficiency investments.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Energy & Fuels
M. Elgamal, Nikolay Korovkin, A. Abdel Menaem, Akram Elmitwally
Summary: This paper proposes a new operation management scheme (OMS) for complex power scheduling in a reconfigurable microgrid. The OMS aims to minimize the operation cost, unmet load, and curtailed renewable power, and has been evaluated using a case study system.
Article
Energy & Fuels
Ziad M. Ali, Mujahed Al-Dhaifallah, Salem Alkhalaf, Zuhair Alaas, Farah Jamali
Summary: The study focuses on coordinating electric vehicles and responsive loads in a microgrid to minimize operational costs and emissions while considering the variability of wind and photovoltaic power sources. The proposed approach utilizes electric vehicles for peak shaving and load curve adjustment, and responsive loads to accommodate the instabilities of renewable energy sources. A two-phase framework is developed to minimize production and backup power costs, as well as the costs of adjusting unit schedules in reaction to renewable energy variations. The research demonstrates the superior performance of the modified sparrow search algorithm in optimizing microgrid operation.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Zia Ullah, Shoarong Wang, Guoan Wu, Mengmeng Xiao, Jinmu Lai, Mohamed R. Elkadeem
Summary: This paper introduces an advanced energy management strategy with a real-time monitoring interface for the effective operation and data analysis of a hybrid microgrid. The proposed model provides optimal operation and control in terms of power supply balance, voltage stability, and frequency stability. By optimizing the supply from renewable sources and battery charging status, the best power supply for loads is achieved.
JOURNAL OF ENERGY STORAGE
(2022)
Review
Green & Sustainable Science & Technology
Md Rayid Hasan Mojumder, M. Hasanuzzaman, Erdem Cuce
Summary: Global energy demand is rising and renewable-based microgrid systems have great potential in addressing energy supply and environmental issues. However, due to the characteristics of renewable energy and technical challenges, microgrid systems face various challenges.
CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
(2022)
Article
Green & Sustainable Science & Technology
Kimsrornn Khon, Chhith Chhlonh, Vannak Vai, Marie-Cecile Alvarez-Herault, Bertrand Raison, Long Bun
Summary: DC-powered devices require AC/DC converters to connect to the grid, raising the question of operating part of the grid in DC. This study proposes a low voltage microgrid planning tool for electrification in developing countries, considering AC/DC distribution, optimal topology, and distributed energy resources allocation. The tool is illustrated on a real case study, showing the feasibility and efficiency of the proposed algorithm. The results indicate that a hybrid AC/DC microgrid allows gradual electrification without large initial investments.
Article
Engineering, Multidisciplinary
Zia Ullah, Hasan Saeed Qazi, Ahmad Alferidi, Mohammed Alsolami, Badr Lami, Hany M. Hasanien
Summary: This study presents a novel method for optimizing energy trading within microgrids by using a hybrid of particle swarm optimization and gravitational search algorithms. The proposed approach promotes cooperative energy trading among microgrids and the main grid, considering network constraints and the uncertainty of renewable energy. Simulation results show that this method maximizes renewable energy utilization, reduces load burden on the main grid, and significantly decreases energy costs.
ALEXANDRIA ENGINEERING JOURNAL
(2024)
Article
Green & Sustainable Science & Technology
Isaias Gomes, Rui Melicio, Victor M. F. Mendes
Summary: This paper presents a computer application to assist in decisions about enhancing sustainability by shifting demand to more convenient periods in a microgrid. The proposed approach customizes a stochastic programming problem to manage uncertainties in decision making. Case studies show opportunities for significant profit enhancements through better bidding and energy consumption decisions.
Article
Automation & Control Systems
Noa Zargari, Ron Ofir, Nilanjan Roy Chowdhury, Juri Belikov, Yoash Levron
Summary: This paper proposes an optimal control method for storage systems affected by the power grid's ramp constraints. By applying an ongoing trimming process, the number of computations is reduced, resulting in a lower computational burden and improved efficiency.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Green & Sustainable Science & Technology
Vjatseslav Skiparev, Komeil Nosrati, Aleksei Tepljakov, Eduard Petlenkov, Yoash Levron, Juri Belikov, Josep M. Guerrero
Summary: Reducing system inertia and maintaining frequency at nominal value is crucial for the operation, stability, and resilience of today's and future power systems. We propose a variable fractional-order PID controller for virtual inertia control applications, which is tuned online using a modified neural network-based algorithm. The proposed hybrid algorithm captures all tuning knobs of the discrete type and fully tunable variable FOPID controller, combining classical and advanced techniques. Comparative analysis with standard FOPID and PID controllers demonstrates the effectiveness of the proposed controller under different scenarios involving the connection/disconnection of renewable energy sources and loads.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Energy & Fuels
Aviad Navon, Ran Nitskansky, Eshel Lipman, Juri Belikov, Nurit Gal, Ariel Orda, Yoash Levron
Summary: This paper investigates the impact of electric vehicle charging on congestion in low-voltage networks and the economic feasibility of energy storage as an alternative to conventional network upgrades. Through a graph-based methodology applied to a large-scale GIS dataset, the study provides insights on the most congested networks due to electric vehicle charging, the typical location of overloaded network components, and the profitable scenarios for storage-based network upgrades. The findings highlight the significant cost savings achievable by using energy storage to alleviate congestion, particularly with a reduction in the cost of stationary energy storage.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Automation & Control Systems
Komeil Nosrati, Juri Belikov, Aleksei Tepljakov, Eduard Petlenkov
Summary: Developing accurate and optimum state estimation methods for fractional order systems is crucial due to the importance of memory effects. The Kalman filter (KF) can guarantee optimum estimation for these systems under parameter uncertainties. However, the filter's performance can be degraded when the model is uncertain. In this study, an optimal solution is introduced to filter uncertain fractional order systems, using robust penalty game approach and unified recursive Riccati equation. Stability and convergence analysis of the filter are illustrated based on singular theory conception.
IEEE CONTROL SYSTEMS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Ram Machlev, Michael Perl, Avi Caciularu, Juri Belikov, Kfir Yehuda Levy, Yoash Levron
Summary: Deep learning techniques have achieved excellent performance in Power Quality Disturbance (PQD) classification. However, power system professionals are hesitant to trust these techniques if they cannot understand the reasons behind their decisions. In this paper, a new Explainable Artificial Intelligence (XAI) technique is proposed to improve the explainability of PQD classifiers by projecting the input data into a lower-dimensional latent space.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Construction & Building Technology
Abiodun E. Onile, Juri Belikov, Yoash Levron, Eduard Petlenkov
Summary: This study proposes BESS technologies that are embedded into the grid and enhanced with reinforcement learning control and recommendation system technologies for improving grid reliability, self-consumption, and demand response goals. The results show that using multi-agent reinforcement learning control strategy achieved a maximum peak load reduction of about 24.5% and a 94% improvement in comfort for certain loads.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Multidisciplinary Sciences
Aviad Navon, Juri Belikov, Ron Ofir, Yael Parag, Ariel Orda, Yoash Levron
Summary: Decreasing costs of distributed generation and storage, alongside increasing network charges, create an incentive for consumers to defect from the main grid. This research shows that conflicting interests among consumers can lead to complex dynamics of grid defection and potentially inefficient outcomes of centralized grid design. By incorporating defection considerations into the grid's design, social welfare can be improved.
Article
Mathematics, Applied
Komeil Nosrati, Juri Belikov, Aleksei Tepljakov, Eduard Petlenkov
Summary: This paper proposes a state estimation algorithm for the original and non-transformed stochastic nonlinear FOS system. The algorithm utilizes a deterministic data-fitting framework and derives the extended fractional singular KF (EFSKF) as an implementation of the Kalman filter (KF). Through detailed analysis of the filter's performance, it is shown that the algorithm reduces to the nominal nonlinear filters when the system is in its usual state-space form, making it highly flexible. Finally, simulation results confirm that the proposed EFSKF algorithm achieves reasonable performance in the estimation of nonlinear states.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Article
Engineering, Electrical & Electronic
Slava Demin, Moshe Sitbon, Ilan Aharon, Eli Barbi, Ram Machlev, Juri Belikov, Yoash Levron, Dmitry Baimel
Summary: This paper proposes a new resonance-type FCL for DFIG-based wind turbines that overcomes the drawbacks of conventional resonance-based FCLs and improves system stability during faults. The proposed circuit limits fault current independently of the reactor's charging state and reduces turbine torque oscillations. Simulation results demonstrate improved fault current, voltage, active power, reactive power, and torque transients during a three-phase to ground fault.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Qianchao Wang, Itamar Kapuza, Dmitry Baimel, Juri Belikov, Yoash Levron, Ram Machlev
Summary: Deep learning techniques have been successful in classifying Power Quality Disturbance (PQD). However, the complexity of deep neural networks (DNNs) and the trial and error process of their architecture design pose challenges. Neural Architecture Search (NAS) techniques have been developed to efficiently find optimal architectures, and this research aims to use NAS based on an evolutionary algorithm to find optimal PQD classifiers. This method can converge efficiently to an optimal DNN architecture, resulting in high accuracy PQD classification with limited resources and minimal human intervention compared to recently developed classifiers.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Automation & Control Systems
Nilanjan Roy Chowdhury, Dmitry Baimel, Juri Belikov, Yoash Levron
Summary: In this paper, a suboptimal control update is proposed for lossless storage systems, which operates based on the instantaneous value of the load power and generalizes previously suggested solutions for energy management problems. The proposed control update works under uncertain conditions and does not require statistical information about the load profile. The stability properties of the control strategy are investigated using the Lyapunov analysis and it is shown to work for both continuous-time and stochastic load profiles, keeping the stored energy within the capacity bounds by following the optimal path.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Automation & Control Systems
Komeil Nosrati, Juri Belikov, Aleksei Tepljakov, Eduard Petlenkov
Summary: This article investigates the state estimation problem of linear fractional order singular (FOS) systems subject to matrix uncertainties and derives a recursive robust algorithm. By minimizing a completely deterministic regularized residual norm, the proposed robust Kalman-type state estimation algorithm handles the uncertainties at each step over admissible uncertainties. The analysis shows that the algorithm not only covers traditional robust Kalman filters (KFs), but also extends the nominal fractional singular KF (FSKF) when the system is not subject to uncertainties.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Energy & Fuels
Dror Miron, Aviad Navon, Yoash Levron, Juri Belikov, Carmel Rotschild
Summary: This study shows that concentrated solar power (CSP) with thermal storage is an economically viable technology for achieving high levels of solar penetration. By using a net levelized cost of electricity (net-LCOE) framework, the study compares the economics of PV with battery storage to CSP in power systems with high solar penetration. The study also explores the potential benefits of a hybrid PV-CSP configuration. The results demonstrate that CSP with thermal storage becomes cheaper than PV with batteries in power systems with 20%-30% solar penetration, enabling cost savings of up to 16%.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Nilanjan Roy Chowdhury, Juri Belikov, Yuval Beck, Yoash Levron, Dmitry Baimel
Summary: This article addresses the energy management problem of grid-connected storage systems with massive integration of renewable energy sources. An optimal control update is proposed considering the degradation cost of the storage systems. Numerical experiments on the Israel electric grid demonstrate the effectiveness of the proposed approach.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Zhenglong Sun, Machlev Ram, Chao Jiang, Qianchao Wang, Perl Michael, Belikov Juri, Levron Yoash
Summary: This article introduces an open-source package PF-FEDG, which can generate frequency events based on PowerFactory with various types of faults and frequency changes. In addition, the package includes three reference fault detection models based on deep learning techniques, which achieve high performance on the IEEE 39-bus system and IEEE 118-bus system. The package and reference models can serve as benchmarks for research and comparison of fault detection algorithms.
