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Search Results (811)

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Keywords = electrical power system microgrid

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19 pages, 1020 KiB  
Article
Optimizing Power Sharing and Demand Reduction in Distributed Energy Resources for Apartments Through Tenant Incentivization
by Janak Nambiar, Samson Yu, Jag Makam and Hieu Trinh
Energies 2025, 18(15), 4073; https://doi.org/10.3390/en18154073 (registering DOI) - 31 Jul 2025
Abstract
The increasing demand for electricity in multi-tenanted residential areas has placed unforeseen strain on sub-transformers, particularly in dense urban environments. This strain compromises overall grid performance and challenges utilities with shifting and rising peak demand periods. This study presents a novel approach to [...] Read more.
The increasing demand for electricity in multi-tenanted residential areas has placed unforeseen strain on sub-transformers, particularly in dense urban environments. This strain compromises overall grid performance and challenges utilities with shifting and rising peak demand periods. This study presents a novel approach to enhance the operation of a virtual power plant (VPP) comprising a microgrid (MG) integrated with renewable energy sources (RESs) and energy storage systems (ESSs). By employing an advanced monitoring and control system, the proposed topology enables efficient energy management and demand-side control within apartment complexes. The system supports controlled electricity distribution, reducing the likelihood of unpredictable demand spikes and alleviating stress on local infrastructure during peak periods. Additionally, the model capitalizes on the large number of tenancies to distribute electricity effectively, leveraging locally available RESs and ESSs behind the sub-transformer. The proposed research provides a systematic framework for managing electricity demand and optimizing resource utilization, contributing to grid reliability and a transition toward a more sustainable, decentralized energy system. Full article
42 pages, 4775 KiB  
Article
Optimal Sizing of Battery Energy Storage System for Implicit Flexibility in Multi-Energy Microgrids
by Andrea Scrocca, Maurizio Delfanti and Filippo Bovera
Appl. Sci. 2025, 15(15), 8529; https://doi.org/10.3390/app15158529 (registering DOI) - 31 Jul 2025
Abstract
In the context of urban decarbonization, multi-energy microgrids (MEMGs) are gaining increasing relevance due to their ability to enhance synergies across multiple energy vectors. This study presents a block-based MILP framework developed to optimize the operations of a real MEMG, with a particular [...] Read more.
In the context of urban decarbonization, multi-energy microgrids (MEMGs) are gaining increasing relevance due to their ability to enhance synergies across multiple energy vectors. This study presents a block-based MILP framework developed to optimize the operations of a real MEMG, with a particular focus on accurately modeling the structure of electricity and natural gas bills. The objective is to assess the added economic value of integrating a battery energy storage system (BESS) under the assumption it is employed to provide implicit flexibility—namely, bill management, energy arbitrage, and peak shaving. Results show that under assumed market conditions, tariff schemes, and BESS costs, none of the analyzed BESS configurations achieve a positive net present value. However, a 2 MW/4 MWh BESS yields a 3.8% reduction in annual operating costs compared to the base case without storage, driven by increased self-consumption (+2.8%), reduced thermal energy waste (–6.4%), and a substantial decrease in power-based electricity charges (–77.9%). The performed sensitivity analyses indicate that even with a significantly higher day-ahead market price spread, the BESS is not sufficiently incentivized to perform pure energy arbitrage and that the effectiveness of a time-of-use power-based tariff depends not only on the level of price differentiation but also on the BESS size. Overall, this study provides insights into the role of BESS in MEMGs and highlights the need for electricity bill designs that better reward the provision of implicit flexibility by storage systems. Full article
(This article belongs to the Special Issue Innovative Approaches to Optimize Future Multi-Energy Systems)
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22 pages, 3051 KiB  
Article
Novel Gaussian-Decrement-Based Particle Swarm Optimization with Time-Varying Parameters for Economic Dispatch in Renewable-Integrated Microgrids
by Yuan Wang, Wangjia Lu, Wenjun Du and Changyin Dong
Mathematics 2025, 13(15), 2440; https://doi.org/10.3390/math13152440 - 29 Jul 2025
Viewed by 96
Abstract
Background: To address the uncertainties of renewable energy power generation, the disorderly charging characteristics of electric vehicles, and the high electricity cost of the power grid in expressway service areas, a method of economic dispatch optimization based on the improved particle swarm optimization [...] Read more.
Background: To address the uncertainties of renewable energy power generation, the disorderly charging characteristics of electric vehicles, and the high electricity cost of the power grid in expressway service areas, a method of economic dispatch optimization based on the improved particle swarm optimization algorithm is proposed in this study. Methods: Mathematical models of photovoltaic power generation, energy storage systems, and electric vehicles were established, thereby constructing the microgrid system model of the power load in the expressway service area. Taking the economic cost of electricity consumption in the service area as the objective function and simultaneously meeting constraints such as power balance, power grid interactions, and energy storage systems, a microgrid economy dispatch model is constructed. An improved particle swarm optimization algorithm with time-varying parameters of the inertia weight and learning factor was designed to solve the optimal dispatching strategy. The inertia weight was improved by adopting the Gaussian decreasing method, and the asymmetric dynamic learning factor was adjusted simultaneously. Findings: Field case studies demonstrate that, compared to other algorithms, the improved Particle Swarm Optimization algorithm effectively reduces the operational costs of microgrid systems while exhibiting accelerated convergence speed and enhanced robustness. Value: This study provides a theoretical mathematical reference for the economic dispatch optimization of microgrids in renewable-integrated transportation systems. Full article
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21 pages, 5953 KiB  
Article
Enhanced Singular Value Decomposition Modulation Technique to Improve Matrix Converter Input Reactive Power Control
by Luis Ramon Merchan-Villalba, José Merced Lozano-García, Alejandro Pizano-Martínez and Iván Abel Hernández-Robles
Energies 2025, 18(15), 3995; https://doi.org/10.3390/en18153995 - 27 Jul 2025
Viewed by 147
Abstract
Matrix converters (MC) offer a compact, bidirectional solution for power conversion; however, achieving precise reactive power control at the input terminals remains challenging under varying operating conditions. This paper presents an enhanced Singular Value Decomposition modulation technique (e-SVD) as a solution tailored to [...] Read more.
Matrix converters (MC) offer a compact, bidirectional solution for power conversion; however, achieving precise reactive power control at the input terminals remains challenging under varying operating conditions. This paper presents an enhanced Singular Value Decomposition modulation technique (e-SVD) as a solution tailored to optimize reactive power management on the MC input side, enabling both active and reactive power control regardless of the power factor. The proposed method achieves input reactive power control based on a reactive power gain, a quantity derived from the apparent output power and defined by a mathematical expression involving electrical parameters and control variables. Experimental tests carried out on a low-power MC prototype to validate the proposal show that the measured reactive power gain closely aligns with theoretical predictions from the mathematical expressions. Overall, the proposed e-SVD modulation technique lays the foundation for more reliable reactive power regulation in applications such as microgrids and distributed generation systems, contributing to the development of smarter and more resilient energy infrastructures. Full article
(This article belongs to the Special Issue Energy, Electrical and Power Engineering: 4th Edition)
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38 pages, 2182 KiB  
Article
Smart Grid Strategies for Tackling the Duck Curve: A Qualitative Assessment of Digitalization, Battery Energy Storage, and Managed Rebound Effects Benefits
by Joseph Nyangon
Energies 2025, 18(15), 3988; https://doi.org/10.3390/en18153988 - 25 Jul 2025
Viewed by 335
Abstract
Modern utilities face unprecedented pressures as trends in digital transformation and democratized energy choice empower consumers to engage in peak shaving, flexible load management, and adopt grid automation and intelligence solutions. A powerful confluence of architectural, technological, and socio-economic forces is transforming the [...] Read more.
Modern utilities face unprecedented pressures as trends in digital transformation and democratized energy choice empower consumers to engage in peak shaving, flexible load management, and adopt grid automation and intelligence solutions. A powerful confluence of architectural, technological, and socio-economic forces is transforming the U.S. electricity market, triggering significant changes in electricity production, transmission, and consumption. Utilities are embracing digital twins and repurposed Utility 2.0 concepts—distributed energy resources, microgrids, innovative electricity market designs, real-time automated monitoring, smart meters, machine learning, artificial intelligence, and advanced data and predictive analytics—to foster operational flexibility and market efficiency. This analysis qualitatively evaluates how digitalization, Battery Energy Storage Systems (BESSs), and adaptive strategies to mitigate rebound effects collectively advance smart duck curve management. By leveraging digital platforms for real-time monitoring and predictive analytics, utilities can optimize energy flows and make data-driven decisions. BESS technologies capture surplus renewable energy during off-peak periods and discharge it when demand spikes, thereby smoothing grid fluctuations. This review explores the benefits of targeted digital transformation, BESSs, and managed rebound effects in mitigating the duck curve problem, ensuring that energy efficiency gains translate into actual savings. Furthermore, this integrated approach not only reduces energy wastage and lowers operational costs but also enhances grid resilience, establishing a robust framework for sustainable energy management in an evolving market landscape. Full article
(This article belongs to the Special Issue Policy and Economic Analysis of Energy Systems)
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21 pages, 10456 KiB  
Article
Experimental Validation of a Modular Skid for Hydrogen Production in a Hybrid Microgrid
by Gustavo Teodoro Bustamante, Jamil Haddad, Bruno Pinto Braga Guimaraes, Ronny Francis Ribeiro Junior, Frederico de Oliveira Assuncao, Erik Leandro Bonaldi, Luiz Eduardo Borges-da-Silva, Fabio Monteiro Steiner, Jaime Jose de Oliveira Junior and Claudio Inacio de Almeida Costa
Energies 2025, 18(15), 3910; https://doi.org/10.3390/en18153910 - 22 Jul 2025
Viewed by 228
Abstract
This article presents the development, integration, and experimental validation of a modular microgrid for sustainable hydrogen production, addressing global electricity demand and environmental challenges. The system was designed for initial validation in a thermoelectric power plant environment, with scalability to other applications. Centered [...] Read more.
This article presents the development, integration, and experimental validation of a modular microgrid for sustainable hydrogen production, addressing global electricity demand and environmental challenges. The system was designed for initial validation in a thermoelectric power plant environment, with scalability to other applications. Centered on a six-compartment skid, it integrates photovoltaic generation, battery storage, and a liquefied petroleum gas generator to emulate typical cogeneration conditions, together with a high-purity proton exchange membrane electrolyzer. A supervisory control module ensures real-time monitoring and energy flow management, following international safety standards. The study also explores the incorporation of blockchain technology to certify the renewable origin of hydrogen, enhancing traceability and transparency in the green hydrogen market. The experimental results confirm the system’s technical feasibility, demonstrating stable hydrogen production, efficient energy management, and islanded-mode operation with preserved grid stability. These findings highlight the strategic role of hydrogen as an energy vector in the transition to a cleaner energy matrix and support the proposed architecture as a replicable model for industrial facilities seeking to combine hydrogen production with advanced microgrid technologies. Future work will address large-scale validation and performance optimization, including advanced energy management algorithms to ensure economic viability and sustainability in diverse industrial contexts. Full article
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36 pages, 5532 KiB  
Article
Supporting Sustainable Development Goals with Second-Life Electric Vehicle Battery: A Case Study
by Muhammad Nadeem Akram and Walid Abdul-Kader
Sustainability 2025, 17(14), 6307; https://doi.org/10.3390/su17146307 - 9 Jul 2025
Viewed by 407
Abstract
To alleviate the impact of economic and environmental detriments caused by the increased demands of electric vehicle battery production and disposal, the use of spent batteries in second-life stationary applications such as energy storage for renewable sources or backup power systems, offers many [...] Read more.
To alleviate the impact of economic and environmental detriments caused by the increased demands of electric vehicle battery production and disposal, the use of spent batteries in second-life stationary applications such as energy storage for renewable sources or backup power systems, offers many benefits. This paper focuses on reducing the energy consumption cost and greenhouse gas emissions of Internet-of-Things-enabled campus microgrids by installing solar photovoltaic panels on rooftops alongside energy storage systems that leverage second-life batteries, a gas-fired campus power plant, and a wind turbine while considering the potential loads of a prosumer microgrid. A linear optimization problem is derived from the system by scheduling energy exchanges with the Ontario grid through net metering and solved by using Python 3.11. The aim of this work is to support Sustainable Development Goals, namely 7 (Affordable and Clean Energy), 11 (Sustainable Cities and Communities), 12 (Responsible Consumption and Production), and 13 (Climate Action). A comparison between a base case scenario and the results achieved with the proposed scenarios shows a significant reduction in electricity cost and greenhouse gas emissions and an increase in self-consumption rate and renewable fraction. This research work provides valuable insights and guidelines to policymakers. Full article
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23 pages, 8106 KiB  
Article
Study on the Flexible Scheduling Strategy of Water–Electricity–Hydrogen Systems in Oceanic Island Groups Enabled by Hydrogen-Powered Ships
by Qiang Wang, Binbin Long and An Zhang
Energies 2025, 18(14), 3627; https://doi.org/10.3390/en18143627 - 9 Jul 2025
Viewed by 328
Abstract
In order to improve energy utilization efficiency and the flexibility of resource transfer in oceanic-island-group microgrids, a water–electricity–hydrogen flexible scheduling strategy based on a multi-rate hydrogen-powered ship is proposed. First, the characteristics of the seawater desalination unit (SDU), proton exchange membrane electrolyzer (PEMEL), [...] Read more.
In order to improve energy utilization efficiency and the flexibility of resource transfer in oceanic-island-group microgrids, a water–electricity–hydrogen flexible scheduling strategy based on a multi-rate hydrogen-powered ship is proposed. First, the characteristics of the seawater desalination unit (SDU), proton exchange membrane electrolyzer (PEMEL), and battery system (BS) in consuming surplus renewable energy on resource islands are analyzed. The variable-efficiency operation characteristics of the SDU and PEMEL are established, and the effect of battery life loss is also taken into account. Second, a spatio-temporal model for the multi-rate hydrogen-powered ship is proposed to incorporate speed adjustment into the system optimization framework for flexible resource transfer among islands. Finally, with the goal of minimizing the total cost of the system, a flexible water–electricity–hydrogen hybrid resource transfer model is constructed, and a certain island group in the South China Sea is used as an example for simulation and analysis. The results show that the proposed scheduling strategy can effectively reduce energy loss, promote renewable energy absorption, and improve the flexibility of resource transfer. Full article
(This article belongs to the Special Issue Hybrid-Renewable Energy Systems in Microgrids)
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18 pages, 1972 KiB  
Article
Learning from Arctic Microgrids: Cost and Resiliency Projections for Renewable Energy Expansion with Hydrogen and Battery Storage
by Paul Cheng McKinley, Michelle Wilber and Erin Whitney
Sustainability 2025, 17(13), 5996; https://doi.org/10.3390/su17135996 - 30 Jun 2025
Viewed by 438
Abstract
Electricity in rural Alaska is provided by more than 200 standalone microgrid systems powered predominantly by diesel generators. Incorporating renewable energy generation and storage to these systems can reduce their reliance on costly imported fuel and improve sustainability; however, uncertainty remains about optimal [...] Read more.
Electricity in rural Alaska is provided by more than 200 standalone microgrid systems powered predominantly by diesel generators. Incorporating renewable energy generation and storage to these systems can reduce their reliance on costly imported fuel and improve sustainability; however, uncertainty remains about optimal grid architectures to minimize cost, including how and when to incorporate long-duration energy storage. This study implements a novel, multi-pronged approach to assess the techno-economic feasibility of future energy pathways in the community of Kotzebue, which has already successfully deployed solar photovoltaics, wind turbines, and battery storage systems. Using real community load, resource, and generation data, we develop a series of comparison models using the HOMER Pro software tool to evaluate microgrid architectures to meet over 90% of the annual community electricity demand with renewable generation, considering both battery and hydrogen energy storage. We find that near-term planned capacity expansions in the community could enable over 50% renewable generation and reduce the total cost of energy. Additional build-outs to reach 75% renewable generation are shown to be competitive with current costs, but further capacity expansion is not currently economical. We additionally include a cost sensitivity analysis and a storage capacity sizing assessment that suggest hydrogen storage may be economically viable if battery costs increase, but large-scale seasonal storage via hydrogen is currently unlikely to be cost-effective nor practical for the region considered. While these findings are based on data and community priorities in Kotzebue, we expect this approach to be relevant to many communities in the Arctic and Sub-Arctic regions working to improve energy reliability, sustainability, and security. Full article
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27 pages, 14158 KiB  
Article
Application of Repetitive Control to Grid-Forming Converters in Centralized AC Microgrids
by Hélio Marcos André Antunes, Ramon Ravani Del Piero and Sidelmo Magalhães Silva
Energies 2025, 18(13), 3427; https://doi.org/10.3390/en18133427 - 30 Jun 2025
Viewed by 238
Abstract
The electrical grid is undergoing increasing integration of decentralized power sources connected to the low-voltage network. In this context, the concept of a microgrid has emerged as a system comprising small-scale energy sources, loads, and storage devices, coordinated to operate as a single [...] Read more.
The electrical grid is undergoing increasing integration of decentralized power sources connected to the low-voltage network. In this context, the concept of a microgrid has emerged as a system comprising small-scale energy sources, loads, and storage devices, coordinated to operate as a single controllable entity capable of functioning in either grid-connected or islanded mode. The microgrid may be organized in a centralized configuration, such as a master-slave scheme, wherein the centralized converter, i.e., the grid-forming converter (GFC), plays a pivotal role in ensuring system stability and control. This paper introduces a plug-in repetitive controller (RC) strategy tuned to even harmonic orders for application in a three-phase GFC, diverging from the conventional approach that focuses on odd harmonics. The proposed control is designed within a synchronous reference frame and is targeted at centralized AC microgrids, particularly during islanded operation. Simulation results are presented to assess the microgrid’s power flow and power quality, thereby evaluating the performance of the GFC. Additionally, the proposed control was implemented on a Texas Instruments TMS320F28335 digital signal processor and validated through hardware-in-the-loop (HIL) simulation using the Typhoon HIL 600 platform, considering multiple scenarios with both linear and nonlinear loads. The main results highlight that the RC improves voltage regulation, mitigates harmonic distortion, and increases power delivery capability, thus validating its effectiveness for GFC operation. Full article
(This article belongs to the Special Issue Energy, Electrical and Power Engineering: 4th Edition)
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24 pages, 2477 KiB  
Article
Techno-Economic Optimization of an Isolated Solar Microgrid: A Case Study in a Brazilian Amazon Community
by Nikole Teran Uruchi, Valentin Silvera Diaz, Norah Nadia Sánchez Torres, Joylan Nunes Maciel, Jorge Javier Gimenez Ledesma, Marco Roberto Cavallari, Mario Gazziro, Taynara Geysa Silva do Lago and Oswaldo Hideo Ando Junior
Eng 2025, 6(7), 133; https://doi.org/10.3390/eng6070133 - 21 Jun 2025
Viewed by 484
Abstract
Many communities in the Brazilian Amazon region remain without reliable access to electricity due to geographical barriers and the high cost of connecting to the national grid. This study aims to evaluate the techno-economic feasibility of implementing battery storage systems in an existing [...] Read more.
Many communities in the Brazilian Amazon region remain without reliable access to electricity due to geographical barriers and the high cost of connecting to the national grid. This study aims to evaluate the techno-economic feasibility of implementing battery storage systems in an existing isolated solar–diesel microgrid located in Tunui-Cachoeira, in the district of São Gabriel da Cachoeira (AM). The analysis uses an energy balance methodology, implemented through the HOMER Pro simulation platform, to assess three scenarios: (i) without batteries, (ii) with lithium-ion batteries, and (iii) with lead–acid batteries. Technical and economic indicators such as net present cost (NPC), levelized cost of energy (LCOE), diesel consumption, and renewable fraction were compared. The results indicate that incorporating lead–acid batteries yields the lowest LCOE (1.99 R$/kWh) and the highest renewable fraction (96.8%). This demonstrates that adding energy storage systems significantly enhances the performance and cost-effectiveness of microgrids, offering a viable path to electrify remote and hard-to-reach communities in the Amazon. Full article
(This article belongs to the Section Electrical and Electronic Engineering)
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36 pages, 6279 KiB  
Article
Eel and Grouper Optimization-Based Fuzzy FOPI-TIDμ-PIDA Controller for Frequency Management of Smart Microgrids Under the Impact of Communication Delays and Cyberattacks
by Kareem M. AboRas, Mohammed Hamdan Alshehri and Ashraf Ibrahim Megahed
Mathematics 2025, 13(13), 2040; https://doi.org/10.3390/math13132040 - 20 Jun 2025
Cited by 1 | Viewed by 474
Abstract
In a smart microgrid (SMG) system that deals with unpredictable loads and incorporates fluctuating solar and wind energy, it is crucial to have an efficient method for controlling frequency in order to balance the power between generation and load. In the last decade, [...] Read more.
In a smart microgrid (SMG) system that deals with unpredictable loads and incorporates fluctuating solar and wind energy, it is crucial to have an efficient method for controlling frequency in order to balance the power between generation and load. In the last decade, cyberattacks have become a growing menace, and SMG systems are commonly targeted by such attacks. This study proposes a framework for the frequency management of an SMG system using an innovative combination of a smart controller (i.e., the Fuzzy Logic Controller (FLC)) with three conventional cascaded controllers, including Fractional-Order PI (FOPI), Tilt Integral Fractional Derivative (TIDμ), and Proportional Integral Derivative Acceleration (PIDA). The recently released Eel and Grouper Optimization (EGO) algorithm is used to fine-tune the parameters of the proposed controller. This algorithm was inspired by how eels and groupers work together and find food in marine ecosystems. The Integral Time Squared Error (ITSE) of the frequency fluctuation (ΔF) around the nominal value is used as an objective function for the optimization process. A diesel engine generator (DEG), renewable sources such as wind turbine generators (WTGs), solar photovoltaics (PVs), and storage components such as flywheel energy storage systems (FESSs) and battery energy storage systems (BESSs) are all included in the SMG system. Additionally, electric vehicles (EVs) are also installed. In the beginning, the supremacy of the adopted EGO over the Gradient-Based Optimizer (GBO) and the Smell Agent Optimizer (SAO) can be witnessed by taking into consideration the optimization process of the recommended regulator’s parameters, in addition to the optimum design of the membership functions of the fuzzy logic controller by each of these distinct algorithms. The subsequent phase showcases the superiority of the proposed EGO-based FFOPI-TIDμ-PIDA structure compared to EGO-based conventional structures like PID and EGO-based intelligent structures such as Fuzzy PID (FPID) and Fuzzy PD-(1 + PI) (FPD-(1 + PI)); this is across diverse symmetry operating conditions and in the presence of various cyberattacks that result in a denial of service (DoS) and signal transmission delays. Based on the simulation results from the MATLAB/Simulink R2024b environment, the presented control methodology improves the dynamics of the SMG system by about 99.6% when compared to the other three control methodologies. The fitness function dropped to 0.00069 for the FFOPI-TIDμ-PIDA controller, which is about 200 times lower than the other controllers that were compared. Full article
(This article belongs to the Special Issue Mathematical Methods Applied in Power Systems, 2nd Edition)
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23 pages, 6078 KiB  
Article
Multi-Energy Optimal Dispatching of Port Microgrids Taking into Account the Uncertainty of Photovoltaic Power
by Xiaoyong Wang, Xing Wei, Hanqing Zhang, Bailiang Liu and Yanmin Wang
Energies 2025, 18(12), 3216; https://doi.org/10.3390/en18123216 - 19 Jun 2025
Viewed by 349
Abstract
To tackle the problems of high scheduling costs and low photovoltaic (PV) accommodation rates in port microgrids, which are caused by the coupling of uncertainties in new energy output and load randomness, this paper proposes an optimized scheduling method that integrates scenario analysis [...] Read more.
To tackle the problems of high scheduling costs and low photovoltaic (PV) accommodation rates in port microgrids, which are caused by the coupling of uncertainties in new energy output and load randomness, this paper proposes an optimized scheduling method that integrates scenario analysis with multi-energy complementarity. Firstly, based on the improved Iterative Self-organizing Data Analysis Techniques Algorithm (ISODATA) clustering algorithm and backward reduction method, a set of typical scenarios that represent the uncertainties of PV and load is generated. Secondly, a multi-energy complementary system model is constructed, which includes thermal power, PV, energy storage, electric vehicle (EV) clusters, and demand response. Then, a planning model centered on economy is established. Through multi-energy coordinated optimization, supply–demand balance and cost control are achieved. The simulation results based on the port microgrid of the LEKKI Port in Nigeria show that the proposed method can significantly reduce system operating costs by 18% and improve the PV accommodation rate through energy storage time-shifting, flexible EV scheduling, and demand response incentives. The research findings provide theoretical and technical support for the low-carbon transformation of energy systems in high-volatility load scenarios, such as ports. Full article
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29 pages, 12629 KiB  
Article
Forecast-Aided Converter-Based Control for Optimal Microgrid Operation in Industrial Energy Management System (EMS): A Case Study in Vietnam
by Yeong-Nam Jeon and Jae-ha Ko
Energies 2025, 18(12), 3202; https://doi.org/10.3390/en18123202 - 18 Jun 2025
Viewed by 378
Abstract
This study proposes a forecast-aided energy management strategy tailored for industrial microgrids operating in Vietnam’s tropical climate. The core novelty lies in the implementation of a converter-based EMS that enables bidirectional DC power exchange between multiple subsystems. To improve forecast accuracy, an artificial [...] Read more.
This study proposes a forecast-aided energy management strategy tailored for industrial microgrids operating in Vietnam’s tropical climate. The core novelty lies in the implementation of a converter-based EMS that enables bidirectional DC power exchange between multiple subsystems. To improve forecast accuracy, an artificial neural network (ANN) is used to model the relationship between electric load and localized meteorological features, including temperature, dew point, humidity, and wind speed. The forecasted load data is then used to optimize charge/discharge schedules for energy storage systems (ESS) using a Particle Swarm Optimization (PSO) algorithm. The strategy is validated using real-site data from a Vietnamese industrial complex, where the proposed method demonstrates enhanced load prediction accuracy, cost-effective ESS operation, and multi-microgrid flexibility under weather variability. This integrated forecasting and control approach offers a scalable and climate-adaptive solution for EMS in emerging industrial regions. Full article
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28 pages, 6345 KiB  
Article
Multimodal Switching Control Strategy for Wide Voltage Range Operation of Three-Phase Dual Active Bridge Converters
by Chenhao Zhao, Chuang Huang, Shaoxu Jiang and Rui Wang
Processes 2025, 13(6), 1921; https://doi.org/10.3390/pr13061921 - 17 Jun 2025
Viewed by 303
Abstract
In recent years, to achieve “dual carbon” goals, increasing the penetration of renewable energy has become a critical approach in China’s power sector. Power electronic converters play a key role in integrating renewable energy into the power system. Among them, the Dual Active [...] Read more.
In recent years, to achieve “dual carbon” goals, increasing the penetration of renewable energy has become a critical approach in China’s power sector. Power electronic converters play a key role in integrating renewable energy into the power system. Among them, the Dual Active Bridge (DAB) DC-DC converter has gained widespread attention due to its merits, such as galvanic isolation, bidirectional power transfer, and soft switching. It has been extensively applied in microgrids, distributed generation, and electric vehicles. However, with the large-scale integration of stochastic renewable sources and uncertain loads into the grid, DAB converters are required to operate over a wider voltage regulation range and under more complex operating conditions. Conventional control strategies often fail to meet these demands due to their limited soft-switching range, restricted optimization capability, and slow dynamic response. To address these issues, this paper proposes a multi-mode switching optimized control strategy for the three-port DAB (3p-DAB) converter. The proposed method aims to broaden the soft-switching range and optimize the operation space, enabling high-power transfer capability while reducing switching and conduction losses. First, to address the issue of the narrow soft-switching range at medium and low power levels, a single-cycle interleaved phase-shift control mode is proposed. Under this control, the three-phase Dual Active Bridge can achieve zero-voltage switching and optimize the minimum current stress, thereby improving the operating efficiency of the converter. Then, in the face of the actual demand for wide voltage regulation of the converter, a standardized global unified minimum current stress optimization scheme based on the virtual phase-shift ratio is proposed. This scheme establishes a unified control structure and a standardized control table, reducing the complexity of the control structure design and the gain expression. Finally, both simulation and experimental results validate the effectiveness and superiority of the proposed multi-mode optimized control strategy. Full article
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