Search Results (502)

The Union of the Comoros, located in the Indian Ocean, faces persistent energy challenges due to its geographic isolation, heavy dependence on imported fossil fuels, and underdeveloped electricity infrastructure. This study investigates the techno-economic optimization of a hybrid microgrid designed to supply electricity to a rural village in Grande Comore. The proposed system integrates photovoltaic (PV) panels, wind turbines, a diesel generator, and battery storage. Detailed modeling and simulation were conducted using HOMER Energy, accompanied by a sensitivity analysis on solar irradiance, wind speed, and diesel price. The results indicate that the optimal configuration consists solely of PV and battery storage, meeting 100% of the annual electricity demand with a competitive levelized cost of energy (LCOE) of 0.563 USD/kWh and zero greenhouse gas emissions. Solar PV contributes over 99% of the total energy production, while wind and diesel components remain unused under optimal conditions. Furthermore, the system generates a substantial energy surplus of 63.7%, which could be leveraged for community applications such as water pumping, public lighting, or future system expansion. This study highlights the technical viability, economic competitiveness, and environmental sustainability of 100% solar microgrids for non-interconnected island territories. The approach provides a practical and replicable decision-support framework for decentralized energy planning in remote and vulnerable regions. Full article

The large-scale integration of new energy is an inevitable trend to achieve the low-carbon transformation of power systems. However, the strong randomness of wind power, photovoltaic power, and loads poses severe challenges to the safe and stable operation of systems. Existing studies demonstrate insufficient integration and handling of source-load bilateral uncertainties in wind–solar–fossil fuel storage complementary systems, resulting in difficulties in balancing economy and low-carbon performance in their energy storage configuration. To address this insufficiency, this study proposes an optimal energy storage configuration method considering source-load uncertainties. Firstly, a deterministic bi-level model is constructed: the upper level aims to minimize the comprehensive cost of the system to determine the energy storage capacity and power, and the lower level aims to minimize the system operation cost to solve the optimal scheduling scheme. Then, wind and solar output, as well as loads, are treated as fuzzy variables based on fuzzy chance constraints, and uncertainty constraints are transformed using clear equivalence class processing to establish a bi-level optimization model that considers uncertainties. A differential evolution algorithm and CPLEX are used for solving the upper and lower levels, respectively. Simulation verification in a certain region shows that the proposed method reduces comprehensive cost by 8.9%, operation cost by 10.3%, the curtailment rate of wind and solar energy by 8.92%, and carbon emissions by 3.51%, which significantly improves the economy and low-carbon performance of the system and provides a reference for the future planning and operation of energy systems. Full article

Photovoltaic panels have become a promising solution for generating renewable energy and reducing our reliance on fossil fuels by capturing solar energy and converting it into electricity. The effectiveness of this conversion depends on several factors, such as the quality of the solar panels and the amount of solar radiation received in a specific region. This makes accurate solar irradiance forecasting essential for planning and managing efficient solar power systems. This study examines the application of machine learning (ML) models for accurately predicting global horizontal irradiance (GHI) using a three-year dataset from six distinct photovoltaic stations: NELHA, ULL, HSU, RaZON+, UNLV, and NWTC. The primary aim is to identify optimal shared features for GHI prediction across multiple sites using a 30 min time shift based on autocorrelation analysis. Key features identified for accurate GHI prediction include direct normal irradiance (DNI), diffuse horizontal irradiance (DHI), and solar panel temperatures. The predictions were performed using tree-based algorithms and ensemble learners, achieving $R^2$ values exceeding 95% at most stations, with NWTC reaching 99%. Gradient Boosting Regression (GBR) performed best at NELHA, NWTC, and RaZON, while Multi-Layer Perceptron (MLP) excelled at ULL and UNLV. CatBoost was optimal for HSU. The impact of time-shifting values on performance was also examined, revealing that larger shifts led to performance deterioration, though MLP performed well under these conditions. The study further proposes a stacking ensemble approach to enhance model generalizability, integrating the strengths of various models for more robust GHI prediction. Full article

As the global energy system accelerates its transition toward a low-carbon economy, renewable energy sources (RESs), such as wind and photovoltaic power, are rapidly replacing traditional fossil fuels. These RESs are becoming a critical element of deeply decarbonized power systems (DDPSs). However, the inherent non-stationarity, multi-scale volatility, and uncontrollability of RES output significantly increase the risk of source–load imbalance, posing serious challenges to the reliability and economic efficiency of power systems. Scenario generation technology has emerged as a critical tool to quantify uncertainty and support dispatch optimization. Nevertheless, conventional scenario generation methods often fail to produce highly credible wind and solar output scenarios. To address this gap, this paper proposes a novel renewable energy scenario generation method based on a multi-resolution diffusion model. To accurately capture fluctuation characteristics across multiple time scales, we introduce a diffusion model in conjunction with a multi-scale time series decomposition approach, forming a multi-stage diffusion modeling framework capable of representing both long-term trends and short-term fluctuations in RES output. A cascaded conditional diffusion modeling framework is designed, leveraging historical trend information as a conditioning input to enhance the physical consistency of generated scenarios. Furthermore, a forecast-guided fusion strategy is proposed to jointly model long-term and short-term dynamics, thereby improving the generalization capability of long-term scenario generation. Simulation results demonstrate that MDDPM achieves a Wasserstein Distance (WD) of 0.0156 in the wind power scenario, outperforming DDPM (WD = 0.0185) and MC (WD = 0.0305). Additionally, MDDPM improves the Global Coverage Rate (GCR) by 15% compared to MC and other baselines. Full article

This study analyzes the feasibility of energy mixes composed of different shares of various types of power generation units, including photovoltaic (PV) and wind farms, hydropower, fossil fuel-based plants, and nuclear power. The analysis uses the concept of Energy Return on Investment (EROI), which is considered the most reliable indicator for comparing different technologies as it measures the energy required rather than monetary costs needed to build and operate each technology. Literature-based EROI values for individual generation technologies were used, along with the minimum EROI thresholds for the entire energy mix that are necessary to sustain developed societies and a high quality of life. The results show that, depending on the assumed minimum EROI value, which ranges from 10 to 30, the maximum share of intermittent renewable energy sources (IRESs), such as PV and wind farms, in the system cannot exceed 90% or 60%, respectively. It is important to emphasize that this EROI-based analysis does not account for power grid stability, which currently can only be maintained by the inertia of large synchronous generators. Therefore, the scenario with a 90% IRES share should be regarded as purely theoretical. Full article

Environmental problems, along with the increasing energy demand and high electricity costs in the agricultural sector, justify the need to explore renewable energy sources in order to improve irrigation efficiency and sustainability. Therefore, the objective of this study is to analyse the feasibility of installing floating photovoltaic panels in the irrigation ponds of irrigation communities (ICs) in the province of Alicante. To this end, a practical case study based on the operating data of a photovoltaic installation on an irrigation pond, which shows 31% self-consumption and a 27% reduction in energy costs, is presented. Based on these results, this type of installation has been considered for the rest of the ponds in the province of Alicante, with an estimated total investment of EUR 130 million and annual savings of EUR 23 million in energy costs. Additionally, barriers such as the initial investment and the need for public financing for large-scale implementation are identified. Finally, it is concluded that the adoption of floating photovoltaic energy represents a key opportunity to reduce dependence on fossil fuels, mitigate environmental impact, and promote the circular economy in the agricultural sector. Full article

At present, transportation energy comes primarily from fossil fuels. In order to mitigate the effects of greenhouse gas emissions, it is necessary to transition to low-carbon transportation technologies. These technologies can include battery electric vehicles, fuel cell vehicles and biofuel vehicles. This transition includes not only the development and production of suitable vehicles, but also the development of appropriate infrastructure. For example, in the case of battery electric vehicles, this infrastructure would include additional grid capacity for battery charging. For fuel cell vehicles, infrastructure could include facilities for the production of suitable electrofuels, which, again, would require additional grid capacity. In the present paper, we look at some specific examples of infrastructure requirements for battery electric vehicles and vehicles using hydrogen and other electrofuels in either internal combustion engines or fuel cells. Analysis includes the necessary additional grid capacity, energy storage requirements and land area associated with renewable energy generation by solar photovoltaics and wind. The present analysis shows that the best-case scenario corresponds to the use of battery electric vehicles powered by electricity from solar photovoltaics. This situation corresponds to a 47% increase in grid electricity generation and the utilization of 1.7% of current crop land. Full article

Continuous growth in energy demand is observed throughout the world, with simultaneous rapid consumption of fossil fuels. New effective technologies and systems are needed that allow for a significant increase in the use of renewable energy sources, such as the sun, wind, biomass, and sea tides. Currently, one of the main research challenges refers to thermal energy management, taking into account the discontinuity and intermittency of both energy supply and demand. Phase change materials (PCMs) are a useful solution in the design and manufacturing of multifunctional materials for energy storage technologies such as solar cells and photovoltaic systems. In order to design efficient PCM-based systems for energy applications, ideas and behaviors from nature should be taken account as it has created over millions of years a plethora of unique structures and morphologies in complex hierarchical materials. Inspirations for nature have been applied to improve and adjust the properties of materials for energy conversion and storage as well as in the design of advanced energy systems. Therefore, this review presents recent developments in biomimetic and bio-inspired multifunctional phase change materials for the energy storage and conversion of different types of renewable energy to thermal or electrical energy. Future outlooks are also provided to initiate integrated interdisciplinary bio-inspired efforts in the field of modern sustainable PCM technologies. Full article

The use of a rock-bed accumulator for a short-term heat storage and air exchange in a building facility is an economical and energy-efficient technological solution to balance and optimize the energy supplied to the facility. Existing scientific studies have not addressed, as yet, the environmental impacts of using a rock bed for heat storage. The purpose of the research is the environmental life cycle assessment (LCA) of a heat storage system in a rock-bed accumulator supported by a photovoltaic installation. The boundaries of the analyzed system include manufacturing the components of the storage device, land preparation for the construction of the accumulator, the entire construction process, including transportation of materials, and its operation in cooperation with a horticultural facility (foil tunnel) during one growing season, as well as the photovoltaic installation. The functional unit in the analysis is 1 square meter of rock-bed accumulator surface area. SimaPro 8.1 software and Ecoinvent database were used to perform the LCA, applying the ReCiPe model to analyze environmental impact. The analysis showed the largest negative environmental impact occurs during raw materials extraction and component manufacturing (32.38 Pt). The heat stored during one season (April to October) at a greenhouse facility reduces this negative impact by approx. 7%, mainly due to the reduction in the use of fossil fuels to heat the facility. A 3 °C increase in average air temperature results in an average reduction of 0.7% per year in the negative environmental impact of the rock-bed thermal energy storage system. Full article

This study provides a comprehensive life-cycle assessment (LCA) of renewable energy sources, focusing on the ${\mathrm{CO}}_2$ emissions and ecological impacts associated with photovoltaic (PV) systems and wind energy technologies. The research evaluates emissions from raw material extraction, production, operation, and disposal, as well as the role of energy-storage systems. Photovoltaic systems exhibit life-cycle ${\mathrm{CO}}_2$ emissions ranging between 28–100 [g ${\mathrm{CO}}_2$eq/kWh], influenced by factors like production energy mix and panel efficiency. Wind turbines demonstrate lower emissions, approximately 7–38 [g ${\mathrm{CO}}_2$eq/kWh], with variations based on turbine type and operational conditions. Despite low operational emissions, the full environmental impact of renewables includes biodiversity disruptions, land use changes, and material recycling challenges. The findings highlight that while renewable technologies significantly reduce ${\mathrm{CO}}_2$ emissions compared to fossil fuels, their ecological footprint necessitates integrated sustainability strategies. The analysis supports policymakers and stakeholders in making informed decisions for a balanced energy transition, emphasizing the need for continued innovation in renewable technology life-cycle management. Full article

The challenges of global warming and other environmental concerns have prompted governments worldwide to transition from fossil-fuel vehicles to low-emission electric vehicles (EVs). The energy crisis, coupled with environmental issues like air pollution and climate change, has been a driving force behind the development of EVs. In recent years, EVs have emerged as one of the most innovative and vital advancements in clean transportation. According to recent reports, EVs are gradually replacing traditional automobiles, offering benefits such as pollution reduction and the conservation of natural resources. This research focuses on analyzing and reviewing the impact of EV integration on electrical networks, with particular attention to photovoltaic (PV) energy as a sustainable charging solution. It examines both current and anticipated challenges, especially those related to power quality, harmonics, and voltage imbalance. A special emphasis is placed on Tunisia, a country with high solar energy potential and increasing interest in EV deployment. By exploring the technical and infrastructural readiness of Tunisia for PV-based EV charging systems, this paper aims to inform regional strategies and contribute to the broader goal of sustainable energy integration in developing countries as part of future work. Full article

Buildings account for about a third of global energy and it is thus imperative to eliminate the use of fossil fuels to power and provide for their thermal needs. Solar photovoltaic (PV) technology can provide power and with electrification, heating/cooling, but there is often a load mismatch with the intermittent solar supply. Electric batteries can overcome this challenge at high solar penetration rates but are still capital-intensive. A promising solution is thermal energy storage (TES), which has a low cost per unit of energy. This review provides an in-depth analysis of TES but specifically focuses on phase change material (PCM)-based TES, and its significance in the building sector. The classification, characterization, properties, applications, challenges, and modeling of PCM-TES are detailed. Finally, the potential for integrating TES with PV and heat pump (HP) technologies to decarbonize the residential sector is detailed. Although many studies show proof of carbon reduction for the individual and coupled systems, the integration of PV+HP+PCM-TES systems as a whole unit has not been developed to achieve carbon neutrality and facilitate net zero emission goals. Overall, there is still a lack of available literature and experimental datasets for these complex systems which are needed to develop models for global implementation as well as studies to quantify their economic and environmental performance. Full article

The industrial sector dominates global energy usage, accounting for approximately 50% of total energy demand, with process heat representing two-thirds of this consumption. Although renewable energy technologies have become increasingly cost-competitive, industrial users have been hesitant to replace fossil fuels to meet heat generation requirements. This study presents a practical framework for industrial energy transition, proposing a phased approach toward sustainable manufacturing practices, processes, and energy technologies. The framework emphasises that while energy efficiency measures form the foundation, strategic technological investment priorities should target the replacement of fossil fuels with sustainable and renewable energy technologies. The formulation of the three-phased energy technology advancement framework is informed by techno-economic analyses across a range of technical interventions available to plant operators, namely beverage manufacturers. For South African conditions, cost–benefit analyses suggest that the industry will prioritise investments in photovoltaic and battery energy storage systems, driven by attractive returns on investment, which are expected to improve. However, sustainability plans and efforts must extend beyond immediate financial returns, particularly in terms of future space requirements and capital allocation. This more holistic approach will ensure long-term sustainability while meeting increasingly stringent environmental commitments. Full article

The transition to renewable energy is critical to enhance Puerto Rico’s energy resilience and reduce dependence on imported fossil fuels. Rooftop photovoltaic (PV) systems provide a scalable opportunity to meet these objectives. This study evaluates the potential of rooftop PV systems across Puerto Rico using the National Renewable Energy Laboratory’s (NREL) PV Rooftop Database, processing detailed roof surface data to estimate installed capacity, energy generation, Levelized Cost of Electricity (LCOE), and solar resource potential at municipal and barrio levels. Findings reveal high solar rooftop capacity in urban neighborhoods, with areas like Sabana Abajo and Hato Tejas each exceeding 450 GWh/year in potential generation. Solar rooftop resource values peak at 3.67 kWh/kW in coastal areas, with LCOE values (0.071–0.215 USD/kWh) below current electricity rates. All municipalities demonstrate technical potential to meet their electricity demand with rooftop PV system alone. This research contributes through (1) developing Puerto Rico’s first comprehensive solar rooftop potential map; (2) providing unprecedented barrio-level analysis; (3) introducing a methodology for estimating missing post-disaster consumption data; and (4) integrating technical, economic, and equity indicators to inform energy policy. These findings demonstrate the importance of rooftop solar in achieving renewable energy goals and provide an understanding of spatial energy inequalities. Full article

Overdependence on fossil fuels contributes to global warming and environmental degradation. Solar energy, particularly photovoltaic (PV) power generation, has emerged as a widely adopted clean and renewable alternative. To increase and enhance the efficiency of PV systems, maximum power point tracking (MPPT) technology is essential. However, achieving accurate tracking control while balancing overall performance in terms of stability, dynamic response, and robustness remains a challenge. In this study, an improved MPPT control scheme based on the technique of predicting the reference current at the MPP and regulating the optimal current is proposed. Support vector regression (SVR) endowed with a strong generalization stability was adopted to model the nonlinear relationship between the PV output current and the environmental factors of irradiance and temperature. The sparrow search algorithm (SSA), recognized for its excellent global search capability, was employed to optimize the hyperparameters of SVR to further increase the prediction accuracy. To satisfy the performance requirements for the current-tracking process, a linear quadratic (LQ) optimal control strategy was applied to design the current regulator based on the PV system’s state-space model. The effectiveness and superior performance of the suggested SSA-SVR-LQ control scheme were validated using measured data under real operating conditions. Full article