Search Results (1,337)

This paper investigates frequency regulation of an airport microgrid (AIM) through the application of an integral absolute error (IAE)-assisted control approach. The islanded AIM is initially captured using a linearized transfer function model to accurately reflect its dynamic characteristics. This model is then simplified using a first-order plus dead time (FOPDT) approximation derived via a reaction-curve-based method, which balances between model simplicity and accuracy. Two different proportional–integral–derivative (PID) controllers are designed to meet distinct objectives: one focuses on set-point tracking (SPT) to maintain the target frequency levels, while the other addresses load disturbance rejection (LDR) to reduce the effects of load fluctuations. A thorough comparison of these controllers demonstrates that the SPT-mode PID controller outperforms the LDR-mode controller by providing an improved transient response and notably lower error measures. The results underscore the effectiveness of combining IAE-based control with reaction curve modeling to tune PID controllers for islanded AIM systems, contributing to enhanced and reliable frequency regulation for microgrid operations. Full article

This study models different hybrid systems based on renewable energies that can be supported by diesel generators to meet the energy needs of isolated homes in the Canary Islands. The research will cover the energy requirements of a residential house, including the production of fresh water using a reverse osmosis desalination plant. The system is designed to operate independently of the electrical grid. The HOMER software package was used to model and optimize the hybrid systems. The model was fed with data on the electrical demands of residential homes (including the consumption by the small reverse osmosis desalination plant) as well as the technical specifications of the various devices and renewable energy sources, such as solar radiation and wind speed potentials. The software considers various configurations to optimize hybrid systems, selecting the most suitable one based on the available renewable energy sources at the selected location. The data used in the research were collected on the eastern islands of the Canary Islands (Gran Canaria, Lanzarote and Fuerteventura). Based on the system input parameters, the simulation and optimization performed in HOMER, taking into account the lowest “Levelized Cost of Energy”, it can be concluded that the preferred hybrid renewable energy system for this region is a small wind turbine with a nominal power of 1.9 kW, eight batteries, and a small diesel generator with a nominal power of 1.0 kW. The knowledge from this research could be applied to other geographical areas of the world that have similar conditions, namely a shortage of water and plentiful renewable energy sources. Full article

Agriculture is Ireland’s largest sector with agri-food exports amounting to EUR 15.2B in 2021. However, agriculture is also Ireland’s largest contributor to GHGs, accounting for 37.4% of emissions in 2020. Developing indigenous renewable energy sources is a national objective towards reducing GHG emissions. The National Policy Statement on the Bioeconomy of Ireland advises a cascading principle of biomass use, where higher-value applications are derived from biomass before energy generation. This research quantifies and characterises biomass wastes at farms, food production, and forestry settings in counties Monaghan and Tipperary, Ireland. Value chains, along with Sankey diagrams, are presented, which identify biomass that can be exploited for valorisation and show their fates in industry/environment. The quantity of biomass wastes available for valorisation under Business as Usual (BAU) vs. Best-Case Scenario (BCS) models is presented. BCS assumes a co-operative system to increase the feedstock available for valorisation. In Monaghan, 73 t of biomass waste vs. 240 t are available for valorisation under Scenario A vs. Scenario B, respectively. In contrast, in Tipperary, a 7-fold increase in biomass waste is achieved, comparing Scenario A (126 t) against Scenario B (905 t). This highlights the importance of engaging local stakeholders to build co-operative models for biomass valorisation. Not only is this environmentally beneficial, but also socially and economically advantageous. Creating indigenous fertiliser and energy sources is important for the island of Ireland, not only in meeting market demand, but also in reducing greenhouse gas (GHG) emissions and achieving emission reduction targets. Full article

As crucial transportation hubs and economic nodes, the underwater security and infrastructure maintenance of harbors are of paramount importance. Harbors are characterized by high vessel traffic and complex underwater environments, where traditional underwater inspection methods, such as diver operations, face challenges of low efficiency, high risk, and limited operational range. This paper introduces a collaborative survey and disposal system that integrates a deformable unmanned surface vehicle (USV) with a lightweight remotely operated vehicle (ROV). The USV is equipped with a side-scan sonar (SSS) and a multibeam echo sounder (MBES), enabling rapid, large-area searches and seabed topographic mapping. The ROV, equipped with an optical camera system, forward-looking sonar (FLS), and a manipulator, is tasked with conducting close-range, detailed observations to confirm and dispose of abnormal objects identified by the USV. Field trials were conducted at an island harbor in the South China Sea, where simulated underwater objects, including an iron drum, a plastic drum, and a rubber tire, were deployed. The results demonstrate that the USV-ROV collaborative system effectively meets the demands for underwater environmental measurement, object localization, identification, and disposal in complex harbor environments. The USV acquired high-resolution (0.5 m × 0.5 m) three-dimensional topographic data of the harbor, effectively revealing its topographical features. The SSS accurately localized and preliminarily identified all deployed simulated objects, revealing their acoustic characteristics. Repeated surveys revealed a maximum positioning deviation of 2.2 m. The lightweight ROV confirmed the status and location of the simulated objects using an optical camera and an underwater positioning system, with a maximum deviation of 3.2 m when compared to the SSS locations. The study highlights the limitations of using either vehicle alone. The USV survey could not precisely confirm the attributes of the objects, whereas a full-area search of 0.36 km² by the ROV alone would take approximately 20 h. In contrast, the USV-ROV collaborative model reduced the total time to detect all objects to 9 h, improving efficiency by 55%. This research offers an efficient, reliable, and economical practical solution for applications such as underwater security, topographic mapping, infrastructure inspection, and channel dredging in harbor environments. Full article

Antarctic research stations require reliable low-carbon power under extreme conditions. This study compiles a synchronized PV-meteorological time-series data set on Horseshoe Island (Antarctica) at 30 s, 1 min, and 5 min resolutions and compares four PV module types (monocrystalline, polycrystalline, flexible mono, and semitransparent) under controlled field operation. Model development adopts an interpretable, multi-objective framework: a modified SPEA-2 searches rule sets on the Pareto front that jointly optimize precision and recall, yielding transparent, physically plausible decision rules for operational use. For context, benchmark machine-learning models (e.g., kNN, SVM) are evaluated on the same splits. Performance is reported with precision, recall, and complementary metrics (F1, balanced accuracy, and MCC), emphasizing class-wise behavior and robustness. Results show that the proposed rule-based approach attains competitive predictive performance while retaining interpretability and stability across panel types and sampling intervals. Contributions are threefold: (i) a high-resolution field data set coupling PV output with solar radiation, temperature, wind, and humidity in polar conditions; (ii) a Pareto-front, explainable rule-extraction methodology tailored to small-power PV; and (iii) a comparative assessment against standard ML baselines using multiple, class-aware metrics. The resulting XAI models achieved 92.3% precision and 89.7% recall. The findings inform the design and operation of PV systems for harsh, high-latitude environments. Full article

Microgrid systems play a vital role in managing distributed energy resources like solar, wind, batteries, and supercapacitors. However, maintaining stable AC/DC bus voltages and minimizing grid reliance under dynamic conditions is challenging. Traditional control methods such as Sliding Mode Controllers (SMCs) suffer from issues like chattering and slow convergence, reducing practical effectiveness. This paper proposes a hybrid AC/DC microgrid that operates in both grid-connected and islanded modes while ensuring voltage stability and efficient energy use. A Conditional-Based Super-Twisting Sliding Mode Controller (CBSTSMC) is employed to address the limitations of conventional SMCs. The CBSTSMC enhances system performance by reducing chattering, improving convergence speed, and offering better tracking and disturbance rejection. To further refine controller performance, an Improved Grey Wolf Optimization (IGWO) algorithm is used for gain tuning, resulting in enhanced system robustness and precision. An Energy Management System (EMS) is integrated to intelligently regulate power flow based on renewable generation and storage availability. The proposed system is tested in real time using a Texas Instruments Delfino C2000 microcontroller through a Controller-in-the-Loop (CIL) setup. The simulation and hardware results confirm the system’s ability to maintain stability and reliability under diverse operating scenarios, proving its suitability for future smart grid applications. Full article

Hybrid water supply systems (WSSs) integrating centralized and decentralized water systems have gained increasing interest in recent years to enhance water service sustainability and system resilience. An example of implementing hybrid WSSs is water microgrids, inspired by energy microgrids. Water microgrids can be depicted as a network (grid) of localized networks (sub-grids) comprising local water sources and their storage and distribution systems that operate in conjunction with a central WSS. They can operate in both ‘grid-connected or ‘islanded’ mode and support interaction and demand trade-offs with centralized WSSs at varying degrees of decentralization, providing flexibility and increased control over water resources. However, the concept of water microgrids is still in its infancy, and their application is limited due to a lack of design guidance and frameworks. This paper provides a comprehensive review of water microgrids, discussing the concept, design, benefits, and potential challenges by drawing insights from energy microgrids, and also discusses the standpoint in comparison with centralized, decentralized, and hybrid WSSs. It also explores integration of decentralized and hybrid infrastructure within existing WSSs, highlighting the balance between localized optimization and systemwide sustainability. The findings aim to broaden understanding of water microgrids, assessing their applicability and operational strategies in urban settings. Full article

The Gadouras Reservoir, Rhodes Island’s primary water source, experiences recurrent whiting events—milky turbidity from calcium carbonate precipitation—that challenge treatment operations, with impacts compounded by a major 2023 wildfire in this fire-prone Mediterranean setting. To elucidate these dynamics, a pragmatic, multi-source monitoring framework integrates archived Sentinel-2 and Landsat imagery with treatment-plant records (2017–mid-2025). Unitless spectral indices (e.g., AreaBGR) for whiting detection and chlorophyll-a proxies are combined with laboratory measurements of turbidity, pH, total organic carbon, manganese, and hydrological metrics, analyzed via spatiotemporal Hovmöller diagrams, Pearson correlations, and interrupted time-series models. Two seasonal whiting regimes are identified: a biogenic summer mode (southern origin; elevated chlorophyll-a; water temperature > 15 °C; pH > 8.5) and a non-biogenic winter mode (northern inflows). Following the wildfire, the system exhibits characteristics that could be related to possible hypolimnetic anoxia, prolonged whiting, a ~50% rise in organic carbon, and a manganese excursion to ~0.4 mg L⁻¹ at the deeper intake. Crucially, the post-fire period shows a decoupling of AreaBGR from turbidity (r ≈ 0.233 versus ≈ 0.859 pre-fire)—a key diagnostic finding that confirms a fundamental shift in the composition and optical properties of suspended particulates. The manganese spike is best explained by the confluence of a wildfire-induced biogeochemical predisposition (anoxia and Mn mobilization) and a consequential operational decision (relocation to a deeper, Mn-rich intake). This framework establishes diagnostic baselines and thresholds for managing fire-impacted reservoirs, supports the use of remote sensing in data-scarce systems, and informs adaptive operations under increasing climate pressures. Full article

Pressure on fresh water resources has been aggravated in recent decades, basically due to population growth, rapid urbanization, and global warming. Integrated engineering solutions and the circular economy, considering the urban water cycle as a whole, are becoming fundamental, particularly in arid and semi-arid regions under permanent or recurrent hydric deficit. This study aims to develop and present an integrated engineering solution for water supply, wastewater collection, and treated wastewater reuse for landscape irrigation in a large, topographically complex, and arid to semi-arid coastal urban region at the south of Santiago Island, Cape Verde. The region is one of the driest and most arid of the Island, with a current average annual precipitation between about 100 and 200 mm, and has very limited underground water resources. The main study area, with about 600 ha, has altitudes ranging from values close to sea level up to about 115 m and has several topographic difficulties, including several relatively rugged zones. The devised water supply system considers four altimetric distribution levels, three main reservoirs connected to each other by a serial system of pipelines with successive pumping, a fourth downstream reservoir for pressure balance in one of the levels, and desalinated water as the source. The sanitary sewer pipes of the urbanizations drain to an interceptor system that operates predominantly in open channel flow in a closed pipe. The long interceptor crosses laterally along the coast several very dug valleys in the path to the Praia Wastewater Treatment Plant in the east, and requires several conduits working under pressure for the crossings, either lifting or governed by gravity. The under-pressure pipeline system of recycled water is partially forced and partially ruled by gravity and transports the treated wastewater from the plant in the opposite direction of the interceptor to a natural reservoir or lake located in the region of urbanizations and the main green spaces to be irrigated. The conceived design of the interceptor and recycled water pipeline minimizes the construction and operation costs, maximizing their hydraulic performance. Full article

Background/Objectives: The deep circumflex iliac artery (DCIA) free flap with internal abdominal oblique muscle (IAOM) is a well-known method of reconstruction used in cases of oral cavity neoplasms. Because the IAOM can be insufficient for extensive defects after removal of advanced carcinomas of the tongue, floor of the mouth, or gingiva, the additional preparation of a perforator-supported external abdominal oblique (EAOM) muscle flap can be useful. The aim of this study was to introduce the use of a DCIA flap with an IAOM and EAOM island in the reconstruction of oral cavity compound defects. Methods: A retrospective analysis was performed involving eight patients who underwent reconstruction using a DCIA free flap with IAOM and perforator-supported EAOM island. Patients underwent the operation between June 2021 and February 2025 in the Department of Maxillofacial Surgery of the Rydygier Hospital in Kraków, Poland. Results: A group of eight patients underwent an operation due to squamous cell carcinoma of the oral cavity. The most common primary subsite of disease was the floor of the mouth (n = 4, 50%), followed by the lower gingiva (n = 2, 25%) and retromolar area (n = 2, 25%). All patients required resection involving part of the mandible, the floor of the mouth, and part of the tongue simultaneously with reconstruction using a DCIA free flap with IAOM and perforator-supported EAOM island. Osteotomies were performed in two flaps (one single osteotomy, one double osteotomy). Reconstruction was successfully performed in seven out of eight patients (overall success rate 88%). Conclusions: The DCIA free flap with IAOM and perforator-supported EAOM flap is a reliable method for compound soft tissue and bone defects in maxillofacial reconstruction. The use of IAOM and EAOM can be helpful in cases of three-dimensional soft tissue defects of the lower gingiva, the floor of the mouth, and the tongue. The lower gingiva and floor of the mouth can be reconstructed with IAOM, while the more mobile part of the tongue can be reconstructed with a perforator-supported EAOM island. Full article

The increasing frequency of climate- and cyber-induced blackouts in modern distribution networks calls for restoration strategies that are both resilient and control-aware. Traditional black-start schemes, based on predefined energization sequences from synchronous machines, are inadequate for inverter-dominated grids characterized by high penetration of distributed energy resources and limited system inertia. This paper proposes a novel multi-layered black-start planning framework that explicitly incorporates the dynamic capabilities and operational constraints of grid-forming energy storage systems (GFESs). The approach formulates a multi-objective optimization problem solved via the Non-Dominated Sorting Genetic Algorithm III (NSGA-III), jointly minimizing total restoration time, voltage–frequency deviations, and maximizing early-stage load recovery. A graph-theoretic partitioning module identifies restoration subgrids based on topological cohesion, critical load density, and GFES proximity, enabling localized energization and autonomous island formation. Restoration path planning is embedded as a mixed-integer constraint layer, enforcing synchronization stability, surge current thresholds, voltage drop limits, and dispatch-dependent GFES constraints such as SoC evolution and droop-based frequency support. The model is evaluated on a modified IEEE 123-bus system with five distributed GFES units under multiple blackout scenarios. Simulation results show that the proposed method achieves up to 31% faster restoration and 46% higher voltage compliance compared to MILP and heuristic baselines, while maintaining strict adherence to dynamic safety constraints. The framework yields a diverse Pareto frontier of feasible restoration strategies and provides actionable insights into the coordination of distributed grid-forming resources for decentralized black-start planning. These results demonstrate that control-aware, partition-driven optimization is essential for scalable, safe, and fast restoration in the next generation of resilient power systems. Full article

Electric power systems are increasingly becoming more decentralized. Many communities depend on isolated power systems that operate independently of the main grid. Remote, islanded, and isolated systems face challenges due to the intermittency and unpredictability of renewable energy sources. This paper reviews the current status of renewable integration and control in stand-alone power systems. It examines techniques to enhance system reliability through energy storage, hybrid systems, and advanced predictive models. Additionally, the issues related to connecting stand-alone systems, focusing on reliability and renewable penetration, are discussed. The scalability of stand-alone power systems is analyzed based on classifications of small-, medium-, and large-scale systems, highlighting their differences and specific challenges. The South West Interconnected System of Western Australia is used as a case study at a large scale to illustrate the complexities of operating a power system with high levels of rooftop solar and wind units. This paper also reviews various methodologies for modeling the uncertainty associated with these systems, which are categorized into stochastic, fuzzy, hybrid, Information Gap Decision Theory, robust, interval, and data-driven approaches. The advantages and limitations of each method in uncertainty modeling are discussed. Full article

The islanded line-commutated-converter-based high-voltage direct-current (LCC-HVDC) transmission system is becoming a key solution for delivering multiple types of clean energy from large-scale renewable energy bases, including wind power, photovoltaic power, hydropower, and energy storage. However, the high penetration of renewable sources significantly increases the risks of frequency fluctuations and voltage violations due to their inherent volatility and uncertainty, posing serious challenges to system stability. To enhance the integration capacity of clean energy and ensure the stable operation of islanded systems, this paper proposes a maximum capacity optimization method tailored for islanded DC transmission involving multiple energy types. A K-medoids clustering algorithm is applied to historical data to extract typical wind and photovoltaic output scenarios, and a virtual balancing node is introduced. Subsequently, an active power droop control strategy and reactive power regulation are applied to enhance system frequency and voltage stability. Finally, the capacities of wind, photovoltaic, and energy storage systems are jointly optimized using particle swarm optimization. Simulation results demonstrate that the proposed approach can accurately determine the maximum allowable integration of wind and photovoltaic power while satisfying system operational constraints, and effectively reduce the required energy storage capacity. Full article

Thursday Island, a remote administrative hub in Australia’s Torres Strait, exemplifies the socio-technical challenges of transitioning to sustainable energy amid diesel dependence and the intermittency of renewables. As Australia pursues Net Zero by 2050, innovative storage solutions are pivotal for enabling green innovation in isolated microgrids. This study evaluates Vanadium Redox Flow Batteries (VRFBs) and Lithium-Ion batteries as key enabling technologies, using a stochastic Monte Carlo simulation to assess their economic viability through Levelized Cost of Storage (LCOS), incorporating uncertainties in capital costs, operations, and performance over 20 years. Employing a stochastic Monte Carlo simulation with 10,000 iterations, this study provides a probabilistic assessment of LCOS, incorporating uncertainties in key parameters such as CAPEX, OPEX, efficiency, and discount rates, offering a novel, data-driven framework for evaluating storage viability in remote microgrids. Results indicate VRFBs’ superiority with a mean LCOS of 168.30 AUD/MWh versus 173.50 AUD/MWh for Lithium-Ion, driven by scalability, durability, and safety—attributes that address socio-economic barriers like high operational costs and environmental risks in tropical, off-grid settings. By framing VRFBs as an innovative green solution, this analysis highlights opportunities for new business models in remote energy sectors, such as reduced fossil fuel reliance (3.6 million litres diesel annually) and enhanced community resilience against energy poverty. It also underscores challenges, including capital uncertainties and policy needs for innovation uptake. This empirical case study contributes to the sustainable energy transition discourse, offering insights for policymakers on overcoming resistance to decarbonization in geographically constrained contexts, aligning with green innovation goals for systemic sustainability. Full article

Power system models of electric systems are crucial in system planning for operations, economics, and expansion analyses. However, as these models contain critical infrastructure data, they are not publicly available. This poses challenges in future expansion scenarios and evaluating technological advancements in an electric grid. Synthetic models are realistic power system models, both topologically and operationally. However, since the electrical network is typically produced using statistical data and often uses machine learning, it does not contain propriety information. This allows researchers to evaluate system behavior under various operating conditions and as test cases for emerging technologies. These test cases are particularly important in highly evolving electric grids and areas of high renewable energy integration such as Alaska. Currently, no publicly available benchmark power system models of rural Alaskan island microgrids exist. This paper presents a rural Alaskan microgrid synthetic power system model and the methodology adopted to develop the model. The performance of the developed synthetic grid was assessed through steady state and positive-sequence dynamic simulations under various operating conditions. Full article