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17 pages, 9179 KiB

Open AccessArticle

Effect of Guide Vane Opening on Flow Distortion and Impeller Stress in a Pump-Turbine Under Extremely Low-Head Conditions

by Xiangyu Chen, Qifei Li, Lu Xin, Shiang Zhang, Mingjie Cheng and Tianding Han

Energies 2025, 18(10), 2576; https://doi.org/10.3390/en18102576 - 16 May 2025

Viewed by 20

Abstract

Under extremely low-head conditions, the performance and stability of pump-turbine units are strongly influenced by the flow distortion caused by variations in guide vane opening. In this study, a pump-turbine model—representative of a domestic pumped storage power station—was investigated through a combination of [...] Read more.

Under extremely low-head conditions, the performance and stability of pump-turbine units are strongly influenced by the flow distortion caused by variations in guide vane opening. In this study, a pump-turbine model—representative of a domestic pumped storage power station—was investigated through a combination of experimental observations and three-dimensional unsteady numerical simulations employing the SST k-ω turbulence model. The analysis focused on characterizing the variations in turbulence kinetic energy, pressure pulsations, and impeller force fluctuations as the guide vane opening was altered. The results reveal that, with increasing guide vane opening, the turbulence kinetic energy within the impeller region is notably reduced. This reduction is primarily attributed to a decrease in energy losses along the suction surfaces of the blades and within the straight pipe section of the tailwater tunnel. Simultaneously, pressure pulsations were detected at multiple locations including the volute inlet, the blade-free zone, downstream of the conical pipe, and along the inner surface of the shaft tube. While most regions experienced a decline in pressure pulsation intensity with larger openings, the bladeless zone exhibited a significant increase. Moreover, force analysis at four distinct guide vane settings indicated that an opening of 41 mm resulted in relatively uniform fluctuations in the impeller forces. This uniformity suggests that an optimal guide vane configuration exists, which minimizes uneven stress distributions and enhances the operational stability of the pump-turbine under extremely low-head conditions. These findings offer valuable insights for the design and operational optimization of pump-turbine systems in pumped storage power stations. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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31 pages, 2108 KiB

Open AccessArticle

Evaluating the Impact of Frequency Decomposition Techniques on LSTM-Based Household Energy Consumption Forecasting

by Maissa Taktak and Faouzi Derbel

Energies 2025, 18(10), 2507; https://doi.org/10.3390/en18102507 - 13 May 2025

Viewed by 146

Abstract

Accurate energy consumption forecasting is essential for efficient power grid management, yet existing deep learning models struggle with the multi-scale nature of energy consumption patterns. Contemporary approaches like LSTM and GRU networks process raw time series directly, failing to distinguish between distinct frequency [...] Read more.

Accurate energy consumption forecasting is essential for efficient power grid management, yet existing deep learning models struggle with the multi-scale nature of energy consumption patterns. Contemporary approaches like LSTM and GRU networks process raw time series directly, failing to distinguish between distinct frequency components that represent different physical phenomena in household energy usage. This study presents a novel methodological method that systematically decomposes energy consumption signals into low-frequency components representing gradual trends and daily routines and high-frequency components capturing transient events, such as appliance switching, before applying predictive modeling. Our approach employs computationally efficient convolution-based filters—uniform and binomial—with varying window sizes to separate these components for specialized processing. Experiments on two real-world datasets at different temporal resolutions (1 min and 15 min) demonstrate significant improvements over state-of-the-art methods. For the Smart House dataset, our optimal configuration achieved an R² of 0.997 and RMSE of 0.034, substantially outperforming previous models with R² values of 0.863. Similarly, for the Mexican Household dataset, our approach yielded an R² of 0.994 and RMSE of 13.278, compared to previous RMSE values exceeding 82.488. These findings establish frequency decomposition as a crucial preprocessing step for energy forecasting as it significantly improve the prediction in smart grid applications. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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25 pages, 1561 KiB

Open AccessArticle

A Forward-Looking Assessment of Robotized Operation and Maintenance Practices for Offshore Wind Farms

by Henrique Vieira and Rui Castro

Energies 2025, 18(6), 1508; https://doi.org/10.3390/en18061508 - 18 Mar 2025

Viewed by 236

Abstract

Operation and maintenance (O&M) activities represent a significant share of the levelized cost of energy (LCOE) for offshore wind farms (OWFs), making cost reduction a key priority. Robotic-based solutions, leveraging aerial and underwater vehicles in a cooperative framework, offer the potential to optimize [...] Read more.

Operation and maintenance (O&M) activities represent a significant share of the levelized cost of energy (LCOE) for offshore wind farms (OWFs), making cost reduction a key priority. Robotic-based solutions, leveraging aerial and underwater vehicles in a cooperative framework, offer the potential to optimize O&M logistics and reduce costs. Additionally, the deployment of persistent autonomous robotic systems can minimize the need for human intervention, enhancing efficiency. This study presents the development of an O&M cost calculator that integrates multiple modules: a weather forecast module to account for meteorological uncertainties, a failure module to model OWF failures, a maintenance module to estimate costs for both planned and unplanned activities, and a power module to quantify downtime-related losses. A forward-looking comparative economic analysis is conducted, assessing the cost-effectiveness of human-based versus robot-based inspection, maintenance, and repair (IMR) activities. The findings highlight the economic viability of robotic solutions in offshore wind O&M, supporting their potential role in reducing operational expenditures and improving energy production efficiency. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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25 pages, 2723 KiB

Open AccessArticle

A Cost-Optimizing Analysis of Energy Storage Technologies and Transmission Lines for Decarbonizing the UK Power System by 2035

by Liliana E. Calderon Jerez and Mutasim Nour

Energies 2025, 18(6), 1489; https://doi.org/10.3390/en18061489 - 18 Mar 2025

Cited by 1 | Viewed by 394

Abstract

The UK net zero strategy aims to fully decarbonize the power system by 2035, anticipating a 40–60% increase in demand due to the growing electrification of the transport and heating sectors over the next thirteen years. This paper provides a detailed technical and [...] Read more.

The UK net zero strategy aims to fully decarbonize the power system by 2035, anticipating a 40–60% increase in demand due to the growing electrification of the transport and heating sectors over the next thirteen years. This paper provides a detailed technical and economic analysis of the role of energy storage technologies and transmission lines in balancing the power system amidst large shares of intermittent renewable energy generation. The analysis is conducted using the cost-optimizing energy system modelling framework REMix, developed by the German Aerospace Center (DLR). The obtained results of multiple optimization scenarios indicate that achieving the lowest system cost, with a 73% share of electricity generated by renewable energy sources, is feasible only if planning rules in England and Wales are flexible enough to allow the construction of 53 GW of onshore wind capacity. This flexibility would enable the UK to become a net electricity exporter, assuming an electricity trading market with neighbouring countries. Depending on the scenario, 2.4–11.8 TWh of energy storage supplies an average of 11% of the electricity feed-in, with underground hydrogen storage representing more than 80% of that total capacity. In terms of storage converter capacity, the optimal mix ranges from 32 to 34 GW of lithium-ion batteries, 13 to 22 GW of adiabatic compressed air energy storage, 4 to 24 GW of underground hydrogen storage, and 6 GW of pumped hydro. Decarbonizing the UK power system by 2035 is estimated to cost $37–56 billion USD, with energy storage accounting for 38% of the total system cost. Transmission lines supply 10–17% of the total electricity feed-in, demonstrating that, when coupled with energy storage, it is possible to reduce the installed capacity of conventional power plants by increasing the utilization of remote renewable generation assets and avoiding curtailment during peak generation times. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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19 pages, 8944 KiB

Open AccessArticle

Fault Detection and Protection Strategy for Multi-Terminal HVDC Grids Using Wavelet Analysis

by Jashandeep Kaur, Manilka Jayasooriya, Muhammad Naveed Iqbal, Kamran Daniel, Noman Shabbir and Kristjan Peterson

Energies 2025, 18(5), 1147; https://doi.org/10.3390/en18051147 - 26 Feb 2025

Viewed by 795

Abstract

The growing demand for electricity, integration of renewable energy sources, and recent advances in power electronics have driven the development of HVDC systems. Multi-terminal HVDC (MTDC) grids, enabled by Voltage Source Converters (VSCs), provide increased operational flexibility, including the ability to reverse power [...] Read more.

The growing demand for electricity, integration of renewable energy sources, and recent advances in power electronics have driven the development of HVDC systems. Multi-terminal HVDC (MTDC) grids, enabled by Voltage Source Converters (VSCs), provide increased operational flexibility, including the ability to reverse power flow and independently control both active and reactive power. However, fault propagation in DC grids occurs more rapidly, potentially leading to significant damage within milliseconds. Unlike AC systems, HVDC systems lack natural zero-crossing points, making fault isolation more complex. This paper presents the implementation of a wavelet-based protection algorithm to detect faults in a four-terminal VSC-HVDC grid, modelled in MATLAB and SIMULINK. The study considers several fault scenarios, including two internal DC pole-to-ground faults, an external DC fault in the load branch, and an external AC fault outside the protected area. The discrete wavelet transform, using Symlet decomposition, is applied to classify faults based on the wavelet entropy and sharp voltage and current signal variations. The algorithm processes the decomposition coefficients to differentiate between internal and external faults, triggering appropriate relay actions. Key factors influencing the algorithm’s performance include system complexity, fault location, and threshold settings. The suggested algorithm’s reliability and suitability are demonstrated by the real-time implementation. The results confirmed the precise fault detection, with fault currents aligning with the values in offline models. The internal faults exhibit more entropy than external faults. Results demonstrate the algorithm’s effectiveness in detecting faults rapidly and accurately. These outcomes confirm the algorithm’s suitability for a real-time environment. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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18 pages, 1262 KiB

Open AccessArticle

Evaluation of Technical Aspects of Solar Photovoltaic (PV) Power Installations on Farmland

by Lorenzo Sabino, Rafiq Asghar, Fabio Crescimbini and Francesco Riganti Fulginei

Energies 2025, 18(2), 317; https://doi.org/10.3390/en18020317 - 13 Jan 2025

Viewed by 609

Abstract

This research evaluates the technical and economic aspects of solar photovoltaic (PV) power installations on farmland, utilizing a simulation model in MATLAB to forecast annual system output based on nominal power and meteorological data. This study compares various configurations, including single-sided versus double-sided [...] Read more.

This research evaluates the technical and economic aspects of solar photovoltaic (PV) power installations on farmland, utilizing a simulation model in MATLAB to forecast annual system output based on nominal power and meteorological data. This study compares various configurations, including single-sided versus double-sided modules and fixed versus tracker structures, to determine their efficiency, losses, and economic viability. The findings indicate that, while theoretically superior technologies may offer better production rates, their economic feasibility varies significantly depending on specific project conditions. The main conclusions drawn from this research emphasize that land-based PV systems present a promising solution for sustainable energy generation. By addressing challenges such as solar energy intermittency and the need for supportive infrastructure, this study highlights the potential for these systems to significantly contribute to reducing greenhouse gas emissions and enhancing energy resilience. This analysis underscores the importance of optimizing configurations to maximize both technical performance and economic returns, ultimately supporting a transition towards a more sustainable energy future. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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40 pages, 7137 KiB

Open AccessEditor’s ChoiceArticle

Heterojunction Technology vs. Passivated Emitter and Rear Contact Photovoltaic Panels: Evaluating Efficiency and Profitability Under Challenging Summer Conditions in Lisbon Using Extensive Field Data

by André Sapina and Paulo Branco

Energies 2025, 18(1), 114; https://doi.org/10.3390/en18010114 - 30 Dec 2024

Viewed by 1250

Abstract

Renewable energy is essential for reducing fossil fuel dependence and achieving carbon neutrality by 2050. This study compares the widely used passivated emitter and rear contact (PERC) cells with advanced heterojunction technology (HJT) cells. Conducted in Lisbon during August 2022, this research evaluates [...] Read more.

Renewable energy is essential for reducing fossil fuel dependence and achieving carbon neutrality by 2050. This study compares the widely used passivated emitter and rear contact (PERC) cells with advanced heterojunction technology (HJT) cells. Conducted in Lisbon during August 2022, this research evaluates the energy yield of PV installations over 400 W under challenging summer conditions. HJT cells, which combine monocrystalline silicon and amorphous layers, showed a 1.88% higher efficiency and a 3% to 6% increase in energy yield compared to PERC cells. This study also examines the effects of irradiance and temperature on performance using experiment field data. HJT modules are ideal for limited space or power constraints, offering long-term profitability, while PERC modules are more cost-effective for budget-limited projects. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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20 pages, 4395 KiB

Open AccessEditor’s ChoiceArticle

Effect of Solar Irradiation Inter-Annual Variability on PV and CSP Power Plants Production Capacity: Portugal Case-Study

by Ailton M. Tavares, Ricardo Conceição, Francisco M. Lopes and Hugo G. Silva

Energies 2024, 17(21), 5490; https://doi.org/10.3390/en17215490 - 2 Nov 2024

Viewed by 1140

Abstract

The sizing of solar energy power plants is usually made using typical meteorological years, which disregards the inter-annual variability of the solar resource. Nevertheless, such variability is crucial for the bankability of these projects because it impacts on the production goals set at [...] Read more.

The sizing of solar energy power plants is usually made using typical meteorological years, which disregards the inter-annual variability of the solar resource. Nevertheless, such variability is crucial for the bankability of these projects because it impacts on the production goals set at the time of the supply agreement. For that reason, this study aims to fill the gap in the existing literature and analyse the impact that solar resource variability has on solar power plant production as applied to the case of Portugal (southern Europe). To that end, 17 years (2003–2019) of meteorological data from a network of 90 ground stations hosted by the Portuguese Meteorological Service is examined. Annual capacity factor regarding photovoltaic (PV) and concentrating solar power (CSP) plants is computed using the System Advisor Model, used here for solar power performance simulations. In terms of results, while a long-term trend for increase in annual irradiation is found for Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI), 0.4148 and 3.2711 kWh/m²/year, respectively, consistent with a solar brightening period, no corresponding trend is found for PV or CSP production. The latter is attributed to the long-term upward trend of 0.0231 °C/year in annual average ambient temperature, which contributes to PV and CSP efficiency reduction. Spatial analysis of inter-annual relative variability for GHI and DNI shows a reduction in variability from the north to the south of the country, as well as for the respective power plant productions. Particularly, for PV, inter-annual variability ranges between 2.45% and 12.07% in Faro and Santarém, respectively, while higher values are generally found for CSP, 3.71% in Faro and 16.04% in São Pedro de Moel. These results are a contribution to future instalments of PV and CSP systems in southern Portugal, a region with very favourable conditions for solar energy harvesting, due to the combination of high production capacity and low inter-annual variability. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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35 pages, 2143 KiB

Open AccessArticle

A Holistic Multi-Criteria Assessment of Solar Energy Utilization on Urban Surfaces

by Hassan Gholami

Energies 2024, 17(21), 5328; https://doi.org/10.3390/en17215328 - 26 Oct 2024

Cited by 2 | Viewed by 1718

Abstract

Urban surfaces such as rooftops, facades, and infrastructure offer significant potential for solar energy integration, contributing to energy efficiency and sustainability in cities. This article introduces an advanced multi-criteria assessment (MCA) framework designed to evaluate the suitability of various urban surfaces for solar [...] Read more.

Urban surfaces such as rooftops, facades, and infrastructure offer significant potential for solar energy integration, contributing to energy efficiency and sustainability in cities. This article introduces an advanced multi-criteria assessment (MCA) framework designed to evaluate the suitability of various urban surfaces for solar energy deployment. The framework extends beyond traditional economic, environmental, and technological factors to include social, political, legal, health and safety, cultural, and psychological dimensions, providing a comprehensive evaluation of photovoltaic (PV) applications in urban contexts. By synthesizing existing literature and applying this holistic MCA framework, this research offers valuable insights for urban planners, architects, and policymakers, enabling strategic optimization of solar energy integration in urban environments. The findings underscore the importance of sustainable urban development and climate resilience, highlighting key factors influencing solar technology deployment and proposing actionable recommendations to address existing challenges. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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15 pages, 3250 KiB

Open AccessArticle

Design of Solar-Powered Cooling Systems Using Concentrating Photovoltaic/Thermal Systems for Residential Applications

by Fadi Ghaith, Taabish Siddiqui and Mutasim Nour

Energies 2024, 17(18), 4558; https://doi.org/10.3390/en17184558 - 11 Sep 2024

Viewed by 1593

Abstract

This paper addresses the potential of integrating a concentrating photovoltaic thermal (CPV/T) system with an absorption chiller for the purpose of space cooling in residential buildings in the United Arab Emirates (UAE). The proposed system consists of a low concentrating photovoltaic thermal (CPV/T) [...] Read more.

This paper addresses the potential of integrating a concentrating photovoltaic thermal (CPV/T) system with an absorption chiller for the purpose of space cooling in residential buildings in the United Arab Emirates (UAE). The proposed system consists of a low concentrating photovoltaic thermal (CPV/T) collector that utilizes mono-crystalline silicon photovoltaic (PV) cells integrated with a single-effect absorption chiller. The integrated system was modeled using the Transient System Simulation (TRNSYS v17) software. The obtained model was implemented in a case study represented by a villa situated in Abu Dhabi having a peak cooling load of 366 kW. The hybrid system was proposed to have a contribution of 60% renewable energy and 40% conventional nonrenewable energy. A feasibility study was carried out that demonstrated that the system could save approximately 670,700 kWh annually and reduce carbon dioxide emissions by 461 tons per year. The reduction in carbon dioxide emissions is equivalent of removing approximately 98 cars off the road. The payback period for the system was estimated to be 3.12 years. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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20 pages, 2989 KiB

Open AccessEditor’s ChoiceArticle

Enhanced Microgrid Control through Genetic Predictive Control: Integrating Genetic Algorithms with Model Predictive Control for Improved Non-Linearity and Non-Convexity Handling

by Muhammed Cavus and Adib Allahham

Energies 2024, 17(17), 4458; https://doi.org/10.3390/en17174458 - 5 Sep 2024

Cited by 17 | Viewed by 1428

Abstract

Microgrid (MG) control is crucial for efficient, reliable, and sustainable energy management in distributed energy systems. Genetic Algorithm-based energy management systems (GA-EMS) can optimally control MGs by solving complex, non-linear, and non-convex problems but may struggle with real-time application due to their computational [...] Read more.

Microgrid (MG) control is crucial for efficient, reliable, and sustainable energy management in distributed energy systems. Genetic Algorithm-based energy management systems (GA-EMS) can optimally control MGs by solving complex, non-linear, and non-convex problems but may struggle with real-time application due to their computational demands. Model Predictive Control (MPC)-based EMS, which predicts future behaviour to ensure optimal performance, usually depends on linear models. This paper introduces a novel Genetic Predictive Control (GPC) method that combines a GA and MPC to enhance resource allocation, balance multiple objectives, and adapt dynamically to changing conditions. Integrating GAs with MPC improves the handling of non-linearities and non-convexity, resulting in more accurate and effective control. Comparative analysis reveals that GPC significantly reduces excess power production, improves resource allocation, and balances cost, emissions, and power efficiency. For example, in the Mutation–Random Selection scenario, GPC reduced excess power to 76.0 W compared to 87.0 W with GA; in the Crossover-Elitism scenario, GPC achieved a lower daily cost of USD 113.94 versus the GA’s USD 127.80 and reduced carbon emissions to 52.83 kg CO2e compared to the GA’s 69.71 kg CO2e. While MPC optimises a weighted sum of objectives, setting appropriate weights can be difficult and may lead to non-convex problems. GAs offer multi-objective optimisation, providing Pareto-optimal solutions. GPC maintains optimal performance by forecasting future load demands and adjusting control actions dynamically. Although GPC can sometimes result in higher costs, such as USD 113.94 compared to USD 131.90 in the Crossover–Random Selection scenario, it achieves a better balance among various metrics, proving cost-effective in the long term. By reducing excess power and emissions, GPC promotes economic savings and sustainability. These findings highlight GPC’s potential as a versatile, efficient, and environmentally beneficial tool for power generation systems. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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Review

Jump to: Research

20 pages, 958 KiB

Open AccessReview

Assessment of Transmission Reliability Margin: Existing Methods and Challenges and Future Prospects

by Uchenna Emmanuel Edeh, Tek Tjing Lie and Md Apel Mahmud

Energies 2025, 18(9), 2267; https://doi.org/10.3390/en18092267 - 29 Apr 2025

Viewed by 950

Abstract

The integration of renewable energy sources (RESs), such as wind and solar, introduces significant uncertainties into power system operations, complicating Available Transfer Capability (ATC) assessment. A key factor in ATC determination, the Transmission Reliability Margin (TRM), accounts for uncertainties like load variations, generation [...] Read more.

The integration of renewable energy sources (RESs), such as wind and solar, introduces significant uncertainties into power system operations, complicating Available Transfer Capability (ATC) assessment. A key factor in ATC determination, the Transmission Reliability Margin (TRM), accounts for uncertainties like load variations, generation fluctuations, and network dynamics. The traditional deterministic TRM methods often fail to capture the stochastic nature of modern grids, leading to inaccurate estimations. This paper reviews the TRM assessment methodologies, emphasizing probabilistic approaches that enhance accuracy in high-RES environments. It explores adaptive statistical techniques, such as rolling window analysis, for dynamic TRM computation. Key challenges, emerging trends, and potential solutions are discussed to support the development of robust ATC modeling frameworks for secure and efficient renewable energy integration. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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20 pages, 2562 KiB

Open AccessReview

A Comprehensive Review of Hybrid State Estimation in Power Systems: Challenges, Opportunities and Prospects

by Leila Kamyabi, Tek Tjing Lie, Samaneh Madanian and Sarah Marshall

Energies 2024, 17(19), 4806; https://doi.org/10.3390/en17194806 - 25 Sep 2024

Cited by 3 | Viewed by 1658

Abstract

Due to the increasing demand for electricity, competitive electricity markets, and economic concerns, power systems are operating near their stability margins. As a result, power systems become more vulnerable following disturbances, particularly from a dynamic point of view. To maintain the stability of [...] Read more.

Due to the increasing demand for electricity, competitive electricity markets, and economic concerns, power systems are operating near their stability margins. As a result, power systems become more vulnerable following disturbances, particularly from a dynamic point of view. To maintain the stability of power systems, operators need to continuously monitor and analyze the grid’s state. Since modern power systems are large-scale, non-linear, complex, and interconnected, it is quite challenging and computationally demanding to monitor, control, and analyze them in real time. State Estimation (SE) is one of the most effective tools available to assist operators in monitoring power systems. To enhance measurement redundancy in power systems, employing multiple measurement sources is essential for optimal monitoring. In this regard, this paper, following a brief explanation of the SE concept and its different categories, highlights the significance of Hybrid State Estimation (HSE) techniques, which combine the most used data resources in power systems, traditional Supervisory Control and Data Acquisition (SCADA) system measurements and Phasor Measurement Units (PMUs) measurements. Additionally, recommendations for future research are provided. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)

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