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Distributed photovoltaic generation has been raised as a dependable electricity substitute for implementing a decarbonised energy transition. The dynamics of PV systems with battery storage have led to new electricity end-user classifications that select their electricity systems and resources wisely, i.e. Prosumers and Prosumagers. This work presents a technical and economic assessment to analyse the effect of decision-making independent end-users and electricity management strategies through a novel time-discrete deterministic simulation model. The end-user's choice of battery storage technology and their approach to electricity management emerge as pivotal factors influencing their strategic decisions. Adopting a prosumer strategy, such as storing and selling surplus self-production, reduces the Levelized Cost of Energy (LCOE), benefiting the end-user economically. Notably, the most effective battery storage technology may only sometimes be the one that is most readily available in the market. These findings enhance our understanding of novel end-user types and underscore the practical implications of their evolutionary shift towards independence. [ABSTRACT FROM AUTHOR]

The gradient concentration in nature has garnered significant attention as a promising source for energy harvesting. Researchers have explored various methods to harness electricity from gradient‐concentration‐induced flows, including evaporation‐driven nanogenerators and humidity‐gradient‐based power generators. However, their low current and power density are the main obstacles toward practical applications. Herein, a Bilayer Hydrogel Electricity Generator (BHEG) is presented to enable efficient energy harvesting through the synergy between ion gradient concentration and galvanic effects. A BHEG unit employing identical materials for both electrodes demonstrates an open‐circuit voltage of 0.7 V and a short‐circuit current of 4.34 mA—surpassing the currently reported average by over 73 times—and achieves a maximum power density of 72.2 mW m−2. Moreover, another BHEG unit using Zn─C electrode materials exhibit an open‐circuit voltage of 1.86 V and a short‐circuit current of 92 mA. Furthermore, the versatility of the BHEG extends beyond power generation, effectively providing passive thermal management for electronics, resulting in a maximum temperature reduction of ≈20 °C. Consequently, the study contributes insights into the design and fabrication of efficient hydrogel‐based power generators, providing a promising avenue for leveraging natural‐flow‐induced energy for various applications. [ABSTRACT FROM AUTHOR]

Distributed generation can actively participate in the day-ahead markets, real-time power balance, and wholesale gas markets to achieve various goals, such as supplying gas to various electric power generation plants. A multi-objective network with two types of loads is considered in this paper. The reason for the simultaneous optimization of these two networks is that these two energy carriers are dependent on each other and gas is needed to produce electricity, so this issue can be addressed with a multi-objective function. The simulation carried out in this article is coded in GAMS software as a mixed integer linear programming (MILP). The efficiency of gas turbines and fuel cells in this article is dependent on their working point, and considering the exact model of these resources and the relationships related to the calculation of their fuel consumption is non-linear. On the other hand, a binary variable has been used to show the charging and discharging state of the storage and the on-and-off state of the gas turbines. Therefore, the problem considered in this article is a MILP problem. The results of this article are the proper planning of charging and discharging of the energy storage system with the proper planning of the power generation of different energy sources considering the network loads in two optimized and non-optimized scenarios. [ABSTRACT FROM AUTHOR]

This research explores the dynamics of total electricity generation (TEG) in South Africa through an analysis of data from the International Energy Agency database from 1990 to 2020. A comprehensive examination of various energy sources, including coal, oil, biofuels, nuclear, hydro, solar photovoltaic (PV), solar thermal, and wind, is conducted to ascertain their respective contributions to TEG. Employing the R software environment, the study employs a methodical analytical framework encompassing meticulous data preparation, statistical analysis, and model formulation. The data preparation phase involves intricate processes such as structuring, cleansing, and visualization aimed at eliminating stochastic variables and outliers. Missing data are addressed through the application of the Piecewise Cubic Hermite Interpolating Polynomial method. Subsequent statistical analyses are informed by tests for normality and homogeneity of variance, revealing deviations from normality and disparate variances across energy source groups. Consequently, non‐parametric methodologies such as the Kruskal–Wallis test are adopted. Findings underscore the significant role of nuclear energy in TEG despite facing challenges. Model development entails the construction of multiple linear regression models with varying predictor sizes, with Model m06 emerging as the optimal choice, incorporating key predictors such as coal, nuclear, and solar PV. Rigorous diagnostic assessments confirm the robustness of Model m06 and its suitability for TEG prediction. Comparative analysis against actual data validates its superior performance, characterized by minimal errors and high predictive accuracy. The efficacy of Model m06 in capturing TEG dynamics underscores its utility for informing energy planning initiatives. Recommendations derived from the study advocate for prioritizing renewable energy integration, infrastructure investment, research endeavors, monitoring mechanisms, and public awareness campaigns to advance sustainable energy development goals in South Africa. [ABSTRACT FROM AUTHOR]

Hydrogen hubs are emerging as strategic solutions to meet governmental emission reduction targets. A critical aspect of hydrogen hub design involves diversifying end uses, encompassing mobility, backup/storage, heating and cooling provision, onsite electricity generation, and grid energy supply. This paper introduces a comprehensive hydrogen hub model catering to these varied applications. Additionally, a novel multi-stage planning framework is proposed to assist hub operators in making informed decisions regarding the integration of diverse renewable energy sources and infrastructure. This framework addresses varying demands efficiently and economically. Moreover, to align with governmental emission reduction policies leading to net-zero targets, a proactive strategy is suggested. Through zoning for commercial, residential, educational, and healthcare sectors, the Sydney hydrogen hub is envisioned under two scenarios: business-as-usual and towards-net-zero design. Notably, CO 2 emissions are projected to decrease from 18.3 ktonnes in the former to 4.7 ktonnes in the latter scenario. [Display omitted] • Introduces a comprehensive hydrogen hub model catering to varied applications. • Multi-stage planning framework to assist hub operators in making informed decisions. • A proactive strategy aligning with governmental emission reduction/net-zero policy. • Determines optimal sizing, scheduling, and timing for a mix of technologies. • Designing Sydney H 2 hub zoned for commercial, residential, and educational tenants. [ABSTRACT FROM AUTHOR]

This paper presents a novel and effective approach for calculating Levelized Cost of Hydrogen production across the globe, without requiring timely resolved modelling or data. We select characteristic production patterns of photovoltaic and wind turbine power generation based on location qualities indicated by full load hours. These representative patterns are applied worldwide on similar locations to evaluate the proportion of electricity that electrolyzers can use if they have a smaller capacity than the renewable electricity source. Hence, the ratio of capacities is optimized to minimize hydrogen cost. The findings from various worldwide locations reveal that decreasing electrolyzer capacity is economically beneficial across all locations for boosting full load hours and curbing investments, particularly in locations with lower electricity generation. Validation using precise electricity production timeseries in specific locations revealed minimal errors in the methodology, though the quality of the results is impacted by the seasonality index differences between representative and exact location. Levelized cost of hydrogen from wind electricity for different countries depending on the ratio between wind turbine capacity and electrolysis capacity. [Display omitted] [ABSTRACT FROM AUTHOR]

Electrical vehicles are finding wide acceptance in the Jordanian transportation market; this has caused an accelerating shift in the emissions of greenhouse gases from the direct burning of fossil fuels consumed by the transportation sector towards the power generation sector. On the other hand, as electric vehicles gain more popularity, an extra load is added to the electrical power generation systems, raising essential concerns such as the capability of the power network to support this massive extra load and the increased emission of greenhouse gases caused by power plants. Studies show that Jordan's weather is known for being bright, sunny, and very suitable for the generation of electric power from solar energy sources. Therefore, with an infrastructure that can support convenient off-grid charging, a huge burden will be taken off the national grid and the environment. Therefore, this work proposes a basic design for an off-grid PV-covered carport and presents a study of the economics and effectiveness of using such a system to charge electric vehicles owned by the students and employees of the Applied Science Private University. The study is based on actual solar irradiance data collected on-site during university working hours (8 a.m.–5 p.m.) to allow students and employees to charge their electric vehicles from an off-grid carport system while on campus. Space limitations for carport design, initial design cost, return on investment, and annual electricity consumption are discussed to demonstrate the benefits of such a system for both the consumer (convenience and low charging cost) and the power company provider (less load to maintain). [ABSTRACT FROM AUTHOR]

This paper presents reduced-order modeling of thermal power dispatch (TPD) from a pressurized water reactor (PWR) for providing heat to nearby heat consuming industrial processes that seek to take advantage of nuclear heat to reduce carbon emissions. The reactor model includes the neutronics of the reactor core, thermal–hydraulics of the primary coolant cycle, and a three-lump model of the steam generator (SG). The secondary coolant cycle is represented with quasi-steady state mass and energy balance equations. The secondary cycle consists of a steam extraction system, high-pressure and low-pressure turbines, moisture separator and reheater, high-pressure and low-pressure feedwater heaters, deaerator, feedwater and condensate pumps, and a condenser. The steam produced by the SG is distributed between the turbines and the extraction steam line (XSL) that delivers steam to nearby industrial processes, such as production of clean hydrogen. The reduced-order simulator is verified by comparing predictions with results from separate validated steady-state and transient full-scope PWR simulators for TPD levels between 0% and 70% of the rated reactor power. All simulators indicate that the flow rate of steam in the main steam line and turbine systems decrease with increasing TPD, which causes a reduction in PWR electric power generation. The results are analyzed to assess the impact of TPD on system efficiency and feedwater flow control. Due to the simplicity of the proposed reduced-order model, it can be scaled to represent a PWR of any size with a few parametric changes. In the future, the proposed reduced-order model will be integrated into a power system model in a digital real-time simulator (DRTS) and physical hardware-in-the-loop simulations. [ABSTRACT FROM AUTHOR]

The instability of the increasingly important photovoltaic (PV) electricity generation in Korea due to a dependence on meteorological conditions is an emerging problem. In this study, we examined the influence of various meteorological conditions on the prediction accuracy of PV generation and module temperature. The predictions were based on weather data acquired from the Korea Meteorological Administration and compared with actual PV generation data from the Dangjin coal yard PV power facility. The results were analyzed on the basis of meteorological conditions, insolation, ambient temperature, and wind velocity. [ABSTRACT FROM AUTHOR]

Solar photovoltaics have emerged as an economic source of renewable electricity generation for regions with high solar irradiation. Still, the installation of utility-scale PV systems is often disrupted due to the unavailability of land. Sparsely populated areas with a hot, dry climate can mitigate the land-energy conflict as they experience higher solar irradiation. In arid areas, the PV systems incur more losses due to dust deposition on PV modules and reduced energy conversion efficiency at higher temperatures. The shortage of water makes the module cleaning procedures cost-prohibitive. Floating Solar photovoltaic (FSPV) systems resolve these problems due to their reduced land footprint, higher efficiency, and reduce evaporative water loss. This study estimates the energy generation of a 4.8 MW FSPV-based microgrid in a hot, semi-arid urban area. By utilizing 5% area of the waterbody, the FSPV system yields 8.876 GWh of electricity annually, to meet 41.7% electricity demand of the study area. The system generates 16.7% more power compared to the land-based PV system. The performance ratio of 82%, and a DC capacity utilization factor of 20.3% is achieved. The system saves 52,810.32 m3 of water per year, compensating for the water requirement of 786.99 m3. for cleaning and dust removal of PV modules. The weekly cleaning procedure limits the soiling loss to 2.79%, compared to 8.47% after a month without cleaning. The FSPV-based microgrid reduces annual CO2 emissions by 2.93 tonnes. This study shall enable engineers, urban planners, and policymakers to develop clean energy-based, sustainable microgrid solutions for urban areas. [ABSTRACT FROM AUTHOR]

A study was carried out to evaluate phytodiversity along with the metal accumulation potential of native plants growing in the vicinity of a thermal power plant (TPP). We documented 26 tree species, six shrubs, and 35 herbs. Importance value index (IVI), which measures the extent to which a species dominates in an area, was found highest for Senna siamea (95.7) followed by Tectona grandis (56.5), and Pithecellobium dulce (19.6). Soil was acidic (pH 5.4) in nature with higher concentrations of Al and Fe. The pH of ground water was found acidic while pH of nearby river was found slightly alkaline. Values of PM2.5 and PM10 were slightly higher than NAAQS standards for industrial areas. The concentration of metals was found higher in aquatic plants than in terrestrial plants. In general, herbs and shrubs showed more metal accumulation potential than trees. Our results suggest that Senna siamea could be used for revegetation purposes in FA landfills. Further, terrestrial and aquatic plants such as Ageratina adenophora and Stuckenia pectinata could be used for reclamation of Mn, Zn, Al, and Fe from contaminated soils. Hydrilla verticillata (Ni and Mn), Nelumbo nucifera, and Ipomoea aquatica (Cr) can be used for metal removal from contaminated water. Novelty statement: The study focuses on the assessment of phytodiversity, soil and water analysis, ambient air quality, and bioaccumulation of heavy metals in plants growing in and around a thermal power plant. The study assumes significance as more than 65% of India's electricity generation is still by coal-fired power plants, having major implications for air, soil, and water pollution. By selecting native plant species adapted to the region, we can enhance biodiversity, restore habitats, and contribute to the overall ecological health of the area surrounding the power plant. [ABSTRACT FROM AUTHOR]

Summary: According to recent research work, increasing electric power generation is one of the significant advantages of the dual‐rotor wind turbine (DRWT) compared to the other types for the same wind speed. In this research work, a modified super‐twisting sliding mode control (STSMC) based on the neural network (NN) is suggested to regulate the stator powers of a DRWT‐based doubly‐fed induction generator (DFIG) in normal and unbalanced grid fault modes. The design of this strategy involves replacing the gains of conventional STSMC with the NN algorithm to enhance robustness, mitigate the impact of unbalanced grid voltage, and consequently improve the quality of the generated power of DRWT‐based DFIG. This forms the primary contribution of this work. The suggested strategy is compared with vector control (VC) and conventional STSMC in terms of reference tracking, power ripples, response dynamics, harmonic distortion of stator current, and the effect of an unbalanced grid fault. Finally, the utility and effectiveness of the designed controller are confirmed through computer simulations. Furthermore, when the grid is subjected to a 20% voltage drop, the results demonstrate that the suggested strategy reduced the total harmonic distortion (THD) value of the stator current by 12.92% compared to VC and by 9.29% compared to conventional STSMC. [ABSTRACT FROM AUTHOR]

Summary: LLC resonant converters have attracted much attention for its characteristics of high efficiency and high‐power density in recent years. Yet, with the diversity of application needs such as photovoltaic power generation and electric vehicles, traditional control solutions have gradually been unable to meet the increasing requirements, such as fast response to parameters perturbations. Besides, LLC converter is a high‐order nonlinear system, and it adds complexity to controller design. In order to solve these issues, taking the HB‐LLC converter as an example, this paper presents a simplified model‐based nonlinear control with fast response and simple design. The proposed controller is based on a second‐order model of LLC circuit, and the reverse design idea of the backstepping method is used to simplify the controller design. An experimental platform is built, and the results show that compared with PID control and linear active disturbance rejection control (LADRC), the proposed method has much smaller voltage undershoot (approximately 53.1% of PID and 68.4% of LADRC) and shorter settling time (approximately 27.8% of PID and 39.3% of LADRC) under input voltage change. [ABSTRACT FROM AUTHOR]

Load shifting for existing electric resistance water heaters (EWHs) presents a potential solution to utility challenges caused by the temporal mismatch between solar generation and electricity consumption. A case study in the Florida Power & Light (FPL) territory for both an individual and a fleet of EWHs evaluates this potential. Two optimization problems are solved using mixed-integer linear programming to maximize solar self-consumption and minimize electricity cost for an individual EWH. Compared to default operation, the solar maximization strategy results in nearly twice as much heating electricity from solar (80% vs. 42%) and 14% increased electricity cost based on FPL rates. An energy balance approach shows the aggregate impact of all FPL EWHs on days of peak and minimal load, June 25th and December 3rd. Publicized goals of increased solar capacity by 2030 will cause changes to the FPL net load, total load minus solar generation. The four million EWHs in the territory can stabilize the net load in 2030 as shifting their load causes a 24% decrease in the standard deviation of the predicted load on both dates. These results encourage widespread adoption of retrofit devices that control EWHs based on solar generation profiles and water consumption schedules. [ABSTRACT FROM AUTHOR]

This work reports a novel TiO2/g-C3N4 photoanode-based photocatalytic fuel cell (PFC) designed to convert chemical energy from simulated wastewater. The g-C3N4 modified TiO2 nanorod was successfully synthesized by a facile hydrothermal method. The results indicated that the maximum photocurrent density reached 2.44 mA cm-2 at 1.23 V vs. RHE by 1.167 g L-1 g-C3N4 loaded TiO2 composite. On the basis of analysis, the photoelectrochemical mechanism of the composite photoanode was proposed. This mainly demonstrated that the composite photoanode increases the electron donor density and boosts charge separation efficiency. In addition, the power density and hydrogen production of the proposed PFC were enhanced by 5.37 and 1.49 times compared to TiO2 photoanode-based PFC. To find the origins of the excellent performance of PFC, the influence of the organic compounds were investigated. The ESR measurement results indicated that the organic matter was captured by the photoexcited holes directly to facilitate the charge separation. The achieved power density and hydrogen production of 0.14 mW cm-2 and 21.60 μmol h-1 cm-2 were measured using RhB as the model pollutant, which was 2.42 and 1.23 times higher than the experiments with PBS electrolyte. This study proposed a novel PFC system converts the organic pollutant to the hydrogen and the electricity. [ABSTRACT FROM AUTHOR]

Small biomass piece, huge power—a fulcrum to lift two global lifelines, where water and energy meet. Initiative of new-to-nature electron–ion nexus and inter-functional synergy showcased sustainable integration between over-limit solar-evaporative desalination, even in backlit environments, and robust long-term all-day clean electricity co-generation. Sparks were created when intersecting with engineering. [Display omitted] The water–energy nexus has garnered worldwide interest. Current dual-functional research aimed at co-producing freshwater and electricity faces significant challenges, including sub-optimal capacities ("1 + 1 < 2"), poor inter-functional coordination, high carbon footprints, and large costs. Mainstream water-to-electricity conversions are often compromised owing to functionality separation and erratic gradients. Herein, we present a sustainable strategy based on renewable biomass that addresses these issues by jointly achieving competitive solar-evaporative desalination and robust clean electricity generation. Using hydrothermally activated basswood, our solar desalination exceeded the 100% efficiency bottleneck even under reduced solar illumination. Through simple size-tuning, we achieved a high evaporation rate of 3.56 kg h−1 m−2 and an efficiency of 149.1%, representing 128%–251% of recent values without sophisticated surface engineering. By incorporating an electron–ion nexus with interfacial Faradaic electron circulation and co-ion-predominated micro-tunnel hydrodynamic flow, we leveraged free energy from evaporation to generate long-term electricity (0.38 W m−3 for over 14 d), approximately 322% of peer performance levels. This inter-functional nexus strengthened dual functionalities and validated general engineering practices. Our presented strategy holds significant promise for global human–society–environment sustainability. [ABSTRACT FROM AUTHOR]

Wearable technology is experiencing remarkable progress, prompting the need for sustainable power sources like triboelectric nanogenerators (TENGs). However, integrating TENGs into fabrics and insufficient power outputs that allows for comfortable wear without obstructing user's movements presents a significant challenge. In this study, a novel kind of diamond‐structured fabric‐based triboelectric nanogenerators (DSF‐TENGs) is introduced utilizing an easy, economical, and scalable weaving method without any chemical modification. Owing to its 3D diamond pattern, surface interactions are enhanced for greater charge generation together with strengthened mechanical engagement for more effective charge transfer. The DSF‐TENG, with its unique self‐resilient structure, achieves impressive electric performance, including output voltage of ≈763 V, short‐circuit current of ≈20.4 µA, and power density of 2862.78 mW m−2, which is multiple times higher than most existing fabric‐based TENGs. It also offers excellent air permeability of 560 mm s−1, consistent electricity generation and sensing even after ten washing cycles, and incredible durability, withstanding over 30 000 cycles. Furthermore, DSF‐TENG is included in an insole that is capable of sensing gait patterns, walking speed, and fall detections of patients with Parkinson's disease. The remarkable power generation capabilities of DSF‐TENG indicate a strong potential for future developments in wearable electronics and healthcare applications. [ABSTRACT FROM AUTHOR]

Using renewable energies is one of the alternatives to mitigate climate change. Among them, photovoltaic energy has shown a relevant growth of participation in the electric sector. In the backdrop of such growth, in countries such as Brazil, photovoltaic energy has surpassed the generation of electricity by petroleum derivatives since 2019. The significant growth in photovoltaic generation around the world can be attributed to several key factors, including abundant sunlight, supportive government policies, falling solar panel costs, environmental concerns, energy diversification goals, investor interest, job creation, and local manufacturing. However, photovoltaic system performance is heavily tied to weather variability. Different models are used to account for this meteorological dependence; however, there is a gap regarding the differences in the outputs of these models. The study presented here investigates the variability and sensitivity of the models used to estimate photovoltaic production ( P p v ). Six models were compared by percentage difference analysis. Statistical analyses from the perspective of variability revealed that the difference between the P p v estimated by these models reaches a 12.89% absolute power difference. Considering that temperature and solar irradiance are the meteorological variables that most influence P p v , the sensitivity analysis focused on these. Regarding sensitivity, in the context of temperature changes, the average relative difference in P p v between models can reach up to 5.32% for a 10 °C change, while in the context of changes in solar irradiance, the average relative difference can reach up to 19.05% for a change of 41.67 W/m2. The consideration of the variability and sensitivity of the main sets of equations used to estimate the potential of photovoltaic energy production can help refine methodologies and assumptions in future research in this area. There are variations and sensitivities, as observed, of such magnitude that, depending on the set of equations adopted in the study, they can alter the conclusion about photovoltaic energy production in a given region. Accurate estimations are pivotal not only for feasibility analyses but also for gauging economic and socio-environmental impacts. These divergences can, in turn, reformulate feasibility analyses and compromise the reliability of photovoltaic energy systems, thus leading to different economic and socio-environmental consequences. [ABSTRACT FROM AUTHOR]

This document explores the challenges and solutions related to the sustainable development of new power systems under dual carbon goals. The integration of renewable energy sources has impacted the stability of power systems, requiring measures such as grid control, optimization, and accurate forecasting of renewable energy generation. The accurate prediction of photovoltaic and wind power is crucial, and deep learning-based models have shown superior forecasting accuracy. Control and optimization strategies, such as voltage feedforward control and adaptive controllers, enhance system stability. Effective control of the power grid also has economic benefits, and planning and scheduling play a significant role in power system reliability and stability. System state management and intelligent question-answering systems contribute to efficient system operation. The advancement of artificial intelligence technology and big data analytics is crucial for enhancing power system stability and efficiency. Overall, these measures are essential for the sustainable development of power systems. [Extracted from the article]

The MGM (1, n) model has the characteristics of less data required, simple modeling, and high prediction accuracy. It has been successfully applied to short-term forecasting across various economic, social, and technological domains, yielding promising outcomes. There is insufficient attention paid to the interpolation coefficient of the model. The interpolation coefficients determine the extent of model fitting, which, in turn, impacts its prediction accuracy. This study made some improvements to the interpolation coefficients and proposed an improved MGM (1, n) model. IMGM (1, n) model and MGM (1, n) model were employed to compare the performance of the improved MGM (1, n) model. Upon a series of comparisons and analyses, it was concluded that the improved MGM (1, n) model has higher fitting and prediction accuracy than the other two forecasting methods. The method was used to forecast the short-term electricity consumption of Linfen City. The findings revealed that by 2030, the electricity demand in Linfen City is projected to be 563.7 billion kWh. [ABSTRACT FROM AUTHOR]

Urban expansion and fossil fuel dependence have led to energy and environmental concerns, highlighting the need for sustainable solutions. Rooftop photovoltaic (RPV) systems offer a viable solution for urban energy transition by utilizing idle rooftop space and meeting decentralized energy needs. However, due to limited information on building function attributes, detailed assessments of RPV potential at the city scale are still complicated. This study introduces a cost-effective framework that combines big Earth data and deep learning to evaluate RPV potential for various investment entities. We introduced a sample construction strategy that considers built environment and location awareness to improve the effectiveness and generalizability of the framework. Applied to Shanghai, our building function recognition model achieved 88.67%, 88.51%, and 67.18% for accuracy, weighted-F1, and kappa, respectively. We identified a potential installed capacity of 42 GW with annual electricity generation of 17 TWh for industrial and commercial, 16 TWh for residential, and 10 TWh for public RPVs. The levelized cost of electricity ranges from 0.32 to 0.41 CNY/kWh, demonstrating that both user-side and plant-side grid parity was achieved. This study supports sustainable development by providing detailed urban energy assessments and guiding local energy planning. The methods and findings may offer insights for similar studies globally. [ABSTRACT FROM AUTHOR]

Energy waste from power plants, typically emitted into the atmosphere, contributes to climate change and resource depletion. Integrating heat recovery systems into power plants can improve overall efficiency. This study focused on utilizing waste heat from a 500-MWe coal-based supercritical standalone plant through the organic Rankine cycle. The power plant uses Indian coal as a fuel input, and five distinct working fluids, R245fa, methanol, acetone, ethanol, and benzene, are considered working fluids for the ORC system. Thermodynamic analysis indicates that the standalone plant exhibits energy and exergy efficiencies of 27.33% and 25.01%, respectively. Following the integration of ORC, an overall efficiency improvement is observed. The increment in efficiency is because of the waste heat utilization, where the ORC generates additional electricity generation with outputs of 9.91 MWe for R245fa, 13.71 MWe for methanol, 13.97 MWe for acetone, 14.04 MWe for ethanol, and 14.11 MWe for benzene. Additionally, the study reveals a substantial reduction in CO2 emissions compared to the coal-based power plant with the same production of power, amounting to approximately 216.43 tons for R245fa, 299.43 tons for methanol, 305.10 tons for acetone, 306.63 tons for ethanol, and 308.16 tons for benzene. The thermodynamic investigation identifies the superior performance of the benzene-based ORC among the chosen fluids, and the economic study concludes that the ethanol-based ORC stands out as the most favorable option among the considered alternatives. [ABSTRACT FROM AUTHOR]

Solar thermal energy-based electricity is capital-intensive, and complex while technically evolving to achieve an optimal design. Global commitments and timelines to increase renewable energy share in the grid have promoted technically mature solar photovoltaics and wind. However, the potential of solar thermal energy for industrial applications, cogeneration and polygeneration is on the back foot for lack of policy, complexity, technical readiness level, cost of components and workable business models. Solar collectors that can generate high-quality steam for power generation is complex and costly; while, modified version of linear Fresnel reflector's (LFR) are prospective for various requirements. The current work looks into the possibility of an LFR and heliostat combination to generate steam at 45 bar, 400C temperature to produce electricity. The levelized cost of electricity (LCOE) and levelized cost of water (LCOW) is found to be INR 5.11 kWh−1 and INR 43.03 m−3, in a 70:30 debt–equity scenario. An IRR of 8.55% is achieved with a payback of 12.5 years, with the sale of electricity at INR 10.11 kWh−1 and water at INR 45 m−3. To reduce the LCOE, LCOW and have an attractive IRR, the viability gap funding (VGF) as an option is tried out. The impact of VGF at, 0%, 10%, 20% and 30% on water generation, electricity generation, IRR, NPV and payback are found. It is found that as the VGF increase, there is a better generation cost for electricity and water, with an improved IRR. However, with the VGF trend and corresponding reduction in electricity and water production cost, it will be ideal to have the VGF close to 15% to keep the electricity sale price at approximately INR 8.5 kWh−1 and water pricing at INR 46 m−3. [ABSTRACT FROM AUTHOR]

Power to Methane (PtM) systems are considered an attractive alternative for power generation, renewable sources' potential harnessing, and atmospheric carbon dioxide (CO 2) utilization. This study analyzes the potential use of Synthetic Natural Gas (SNG) for electrical power generation or its direct injection into the currently available Natural Gas Transportation infrastructure. A simulation approach using Aspen Plus v14 software was employed to assess various PtM configurations. Six different systems were analyzed for methanation processes, utilizing three types of electrolysis systems: Alkaline (AE), Proton Exchange Membrane (PEME), and Solid Oxide (SOE). Two primary methane applications were considered: integrated into a combined cycle for power generation and a standalone gas treatment stage for grid injection. As a result, the PEME-based system showed the highest generated-to-fed power ratio, larger than SOE (1.45% higher) and AE (20.66% higher). In addition, PEME technology reports the largest generation of SNG per power supply, exceeding 3.4% and 16.4% of those of SOE and AE, respectively. However, the SOE technology showed a larger efficiency than PEME technology by 8.2% and a PtM efficiency larger than PEME by 12.4%. Fixed capital investment for the PtM systems is around 8.6 and 13.9 million USD$, and their total earnings are between −8.2 and 20.9 thousand USD$ a year, depending on the electrolysis technology, methane application, and carbon credits scenario. According to these results, the PEME-based system is the most suitable option regarding technical and economic criteria. • PEME demonstrates superior efficiency and cost-effectiveness for producing Synthetic Natural Gas (SNG). • The primary application for this SNG is in electric power generation because its simplicity and potential to storage energy. • Integrating SNG into the national grid presents an important opportunity in energy transition, but its challenges are related to the high costs to meet regulatory standards. • Hydrogen-SNG blends can be interesting to be evaluated to meet regulatory standards. • SNG is an interesting route for contributing to a more sustainable and efficient energy landscape. [ABSTRACT FROM AUTHOR]

The Aotearoa New Zealand electricity sector is undergoing a transition to more distributed electricity generation, largely driven by the private sector. Local actors, however, are increasingly interested in playing a role in the energy transition, and addressing their resilience, with community renewable energy (CRE). These projects often have a wide range of impacts, dependent on the community’s motivations, as well as the design and operation of the project. However, there is a lack of tools that can accurately quantify the impacts derived from CRE projects, and guide communities to build a portfolio of projects. This study used system dynamics modelling to analyse the impacts of CRE projects over a 40-year time span. The Energise Ōtaki community group in Aotearoa New Zealand was used as a case study given their already established CRE project and goals to expand their project portfolio. The system dynamics model showed if the community reinvested 80% of the profits from the first project into a second project would provide the greatest long-term benefit for the community in terms of the impact areas important to them. System dynamics modelling proved a useful tool in evaluating the wide range of impacts, and how they interact. [ABSTRACT FROM AUTHOR]

This study develops a an optimization model focused on the layout and dispatch of a low-carbon hydrogen supply chain. The objective is to identify the lowest Levelized Cost of Hydrogen for a given demand. The model considers various elements, including electricity supply from the local grid and renewable sources (photovoltaic and wind), alongside hydrogen production, compression, storage, and transportation to end users. Applied to an industrial case study in Sweden, the findings indicate that the major cost components are linked to electricity generation and investment in electrolyzers, with the LCOH reaching 5.2 EUR/kgH2 under typical demand conditions. Under scenarios with higher peak demands and greater demand volatility, the LCOH increases to 6.8 EUR/kgH2 due to the need for additional renewable energy capacity. These results highlight the critical impact of electricity availability and demand fluctuations on the LCOH, emphasizing the complex interdependencies within the hydrogen supply chain. This study provides valuable insights into the feasibility and cost-effectiveness of adopting hydrogen as an energy carrier for renewable electricity in the context of decarbonizing industrial processes in the energy system. • MILP for optimizing the LCOH. • Identifying the optimum layout and dispatch for a hydrogen supply chain. • Hydrogen for decarbonizing industrial sector. • Identifying the primary cost drivers of LCOH. [ABSTRACT FROM AUTHOR]

Wave energy conversion holds promise for renewable energy, but challenges like high initial costs hinder commercialization. Integrating wave-energy converters (WECs) into shore-protection structures creates dual-function structures for both electricity generation and coastal protection. Oscillating water columns (OWCs) have been well studied in the past with their simple generation mechanism and their out-of-water power take-off (PTO) system, which can minimize bio-fouling effects and maintenance costs compared to other submerged WECs. In addition, a slotted barrier allows for better circulation behind the breakwater while dissipating incoming wave energy through viscous damping. This study examines the performance of a new design which combines an OWC with a slotted breakwater. Small-scale (1:49) laboratory tests were performed with a piston-type wave generator. The performance is evaluated in terms of wave transmission, wave energy extraction, and wave loading under various wave conditions while focusing on the effects of the porosity of the slotted barrier and tide level changes. Results show that under larger waves, a decreasing wave transmission, increasing power extraction from the OWC, and energy dissipation from the slotted barrier are observed. On the other hand, under increasing wavelengths, wave transmission is observed to be constant; this is important for harbor design, which means that the breakwater is effective under a wider range of wavelengths. Porosity allows for more transmission while inducing less horizontal force on the structure. [ABSTRACT FROM AUTHOR]

This study investigates how differences in energy-related properties of cities influence the composition of a cost-efficient urban energy system, assuming electrification of the transport and industry sectors and zero-emission of CO2. These differences are evaluated for two scenarios regarding the capacities of the modeled cities to import electricity. A linear optimization model that encompasses the electricity, heating, industry, and transport sectors, using measured data from six cities in Sweden, is applied. Results show that when strict constraints on electricity imports are enforced, cities with a lower ratio of annual electricity demand for heat encourage the implementation of power-to-heat solutions in the heating sector. This study also reveals that under such stringent electricity import conditions, cities with a high level of flexibility in electricity demand favor a combination of batteries and solar photovoltaics as opposed to biomass-based electricity production. Conversely, when electricity importation is less restricted and biomass prices surpass 20 EUR/MWh, local electricity generation is outcompeted by imports, and large-scale heat pumps working in tandem with thermal energy storage dominate the heating sector in all modeled cities. This assertion holds true when the maximum electricity import capacity is utilized up to 5000 h annually. [ABSTRACT FROM AUTHOR]

This publication explores current and prospective methods for hydrogen production and purification, with a strong emphasis on membrane-based technologies for purification and separation. This focus is justified by the ongoing shift towards renewable energy sources (RESs) in electricity generation, necessitating strategic changes to increase hydrogen utilization, particularly in the automotive, heavy road, and rail sectors, by 2025–2030. The adoption of hydrogen from RESs in the construction, energy, and industrial sectors (e.g., for process heat or fertilizer production) is also under consideration, driving the need for innovative production, separation, and purification methods. Historically, industrial-scale hydrogen has been predominantly derived from fossil fuels, but renewable sources such as electrolysis, biological, and thermal processes now offer alternatives with varying production efficiencies (0.06–80%) and gas compositions. Therefore, selecting appropriate separation and purification methods is critical based on specific usage requirements and the gas composition. Industrial-scale hydrogen purification commonly employs pressure swing adsorption (PSA) technologies, capable of achieving up to 99.99% purity. Cryogenic distillation is suitable for applications needing up to 95% purity. Membrane technologies, including polymer, metallic, and electrolytic membranes, have traditionally been limited to moderate volumes of pure gas production but are crucial for hydrogen purification and separation. This publication critically evaluates the potential of membrane technology for hydrogen separation, particularly in response to the anticipated rise in demand for RES-derived hydrogen, including from renewable feedstocks. [ABSTRACT FROM AUTHOR]

The relationship between a region's dependency on variable renewable energy (VRE) and the viability of long-duration energy storage (LDES) technologies is recognised through various electricity grid modelling efforts in the contemporary literature. Numerous studies state a specific VRE penetration level in total electricity generation as an indicator of the emergence of an LDES market. However, there is considerable variability across studies when comparing VRE penetration levels in conjunction with LDES technology utilisation, and significant diversity exists in electricity grid modelling approaches. This review aims to highlight these inconsistencies by offering an overview of disparate findings and dissecting the influencing variables. Sixteen parameters are identified from reviewed studies, complemented by an additional five recognised through in-depth analysis. This comprehensive examination not only sheds light on critical aspects overlooked in previous reviews, requiring further investigation, but also provides novel insights into the complexity of this correlation, elevating the understanding of LDES market creation by unravelling the factors that influence the technology adoption across various contexts. Furthermore, it provides clarity in LDES research terminology by rectifying ambiguous language in the existing literature. Altogether, seven databases were explored to produce a trustworthy foundation for the study. [ABSTRACT FROM AUTHOR]

This simulation study explores the potential of a novel façade design with integrated control system comprising a dynamic photovoltaic (PV) facade integrated with dimming lighting control to enhance the work environment in office buildings and achieve energy-efficient solutions. Parametric modeling using the Grasshopper plug-in for Rhino software 7, coupled with energy simulation through the Honeybee environmental plug-in for the EnergyPlus program, are used in the methodology. The integrated control strategy was simulated to study in a single office space, utilizing the Daysim engine to assess indoor daylight quality and focusing on Daylight Factor (DF) and Daylight Glare Probability (DGP). Additionally, two artificial lighting control systems were examined for potential integration with the dynamic PV facade to minimize lighting load. The study employs the Galapagos evolutionary solver function embedded within Grasshopper to identify optimum solutions. The dynamic PV façade achieves substantial reductions in overall energy consumption, cutting it by 73% in June, 54% in July, 54.5% in August, and 52.55% in September. The results demonstrate substantial reductions in total energy consumption, with notable savings in heating and cooling due to the dynamic facade's ability to balance and control solar radiation during working hours. Moreover, the dynamic PV facade contributes to electricity generation, demonstrating its potential to improve visual comfort, decrease energy consumption, and generate electric energy through rotational adjustments and varying transparency levels. [ABSTRACT FROM AUTHOR]

Solar tower with thermal energy storage (ST-TES) represents a promising technology for large-scale exploitation of solar irradiation for electricity generation. A ST-TES has the potential to extend electricity generation to more favorable conditions, such as high electricity prices. The size of TES, however, constrains the flexibility of dispatching, especially when there is significant uncertainty in forecasts of solar irradiation and electricity prices. This study explores the impact of TES size when the plant uses model-predictive control (MPC) for dispatch planning. The performance of MPC is benchmarked against one perfect knowledge (PK) and two day-ahead strategies. The optimal achievable profit for each TES size is determined using the PK strategy. An analysis is conducted to evaluate the relative profit losses for all the other simulated strategies compared to the PK strategy. A case study is conducted for a hypothetical 115 MWe ST-TES in South Australia. For January and August, 100 tests are performed for each dispatch policy, with the TES size varying from 6 to 14 h. The revenue evaluation is conducted with both fixed and wholesale spot prices. The analysis shows that MPC-aided dispatching enables the adoption of a smaller TES compared to day-ahead policies while maintaining the same expected profit. The resulting TES size reduction from 14 to 10 h translates into approximately up to $45.4 million in capital cost savings. The findings of this study can inform the ST-TES plant's design procedures and facilitate negotiations for electricity sales contracts. [ABSTRACT FROM AUTHOR]

The escalating concern over global warming has garnered significant international attention, with carbon emission intensity emerging as a crucial barrier to sustainable economic development across various regions. While previous studies have largely focused on annual scales, this study introduces a novel examination of Tianjin's quarterly carbon emission intensity and its influencing factors from 2012 to 2022 using quarterly data and the Logarithmic Mean Divisia Index (LMDI) model. The analysis considers the carbon emission effects of thermal power generation, the power supply structure, power intensity effects, and economic activity intensity. The results indicate a general decline in Tianjin's carbon emission intensity from 2012 to 2020, followed by an increase in 2021 and 2022. This trend, exhibiting significant seasonal fluctuations, revealed the highest carbon emission intensity in the first quarter (an average of 1.4093) and the lowest in the second quarter (an average of 1.0019). Economic activity intensity emerged as the predominant factor influencing carbon emission intensity changes, particularly notable in the second quarter (an average of −0.0374). Thermal power generation and electricity intensity effects were significant in specific seasons, while the power supply structure's impact remained relatively minor yet stable. These findings provide essential insights for formulating targeted carbon reduction strategies, underscoring the need to optimize energy structures, enhance energy efficiency, and account for the seasonal impacts of economic activity patterns on carbon emissions. [ABSTRACT FROM AUTHOR]

The goal of securing almost 100 % of electricity generation in Germany with renewable energies (RE) and green energy imports is analyzed. The annual continuous load lines of the ways of generating electricity with RE demonstrate the actual supply capacity of RE as a function of the installed capacity. The increasing volatility resulting from the expansion of RE has a negative impact on the effectiveness of electricity generation and leads to high residual loads. It is not possible to compensate for this by storing the surplus electricity with hydrogen and regenerating electricity and importing green energy sources. A globally feasible concept of the complementary decarbonization of electricity generation from RE and fossil fuels via natural gas pyrolysis and the material‐energetic use of lignite is proposed. [ABSTRACT FROM AUTHOR]

Emergy analysis (EmA) is the quantitative sustainability method that analyses materials, energy resources, goods, or services under a common unit of solar emergy (seJ). Meanwhile, life cycle assessment (LCA) is one of the popular tools to evaluate environmental impacts. Both methods have been widely used in various applications, hence, the idea of co‐jointing these two methods has been increasing to optimize the assessment's inclusivity. However, the existing integrated LCA–EmA methods are applied segmentally with minimal data integration, which has limited the potential of co‐benefits in sustainability accounting. This research proposes a more comprehensive integration between LCA and EmA, known as life cycle emergy analysis (LCEmA). The process data is fully integrated, and the detailed methodological approach is presented to demonstrate the assessment process. Diaper manufacturing is selected as a case study to validate the functionality of the proposed LCEmA approach. The inclusion of foreground and background data offered in LCEmA approach considers backend processes such as electricity generation for manufacturing activities. This has shifted the sustainability hotspot from raw material extraction to the manufacturing process. This research demonstrates that the LCEmA approach can perform comprehensive analysis as a promising alternative to the existing integrated LCA–EmA methods. [ABSTRACT FROM AUTHOR]

Deployment of wind and solar electricity technologies is crucial for the energy transition, yet anticipated deployment rates differ widely often underestimating actual deployments. This issue is significant for countries like Aotearoa New Zealand, leading the way in major energy transitions. This study addresses two main issues: the historical underestimation of deployment rates and the need to synthesise various future scenarios to assess their potential impacts on the energy system. To address these problems, an empirical modelling approach based on logistic growth is adopted to create and analyse scenarios for the deployment of solar and wind technologies in New Zealand. We propose two scenarios: a reference growth scenario, which represents prevailing estimations for the deployment of solar and wind from previous forecasts; and a disruptive scenario, which anticipates a more rapid deployment pace. Both scenarios envision phasing out fossil fuels by 2030 but differ in the remaining electricity supply. In the disruptive scenario, the installed electricity generation broadens, in which solar and wind generation could represent 72% of the electricity generation capacity by 2050. Our findings emphasise the transformative potential of rapid wind and solar technologies deployment and highlight the importance of preparing for a disruptive future that challenges conventional expectations. [ABSTRACT FROM AUTHOR]

Multi‐purpose land use is of great importance for sustainable development, particularly in the context of increasing pressures on land to provide ecosystem services (e.g. food, energy) and support biodiversity. The recent global increase in land‐take for utility‐scale ground‐mounted solar farms (hereafter referred to as solar farms) to meet Net Zero targets presents an opportunity for enhanced delivery of ecosystem services, especially in temperate ecosystems where solar farm development often results in land use change away from comparatively intensive agricultural land management. Solar farms have long operational lifespans, experience low levels of disturbance during operation and can be managed for ecosystem services beyond low‐carbon electricity generation, including food production and biodiversity conservation. Here, we briefly synthesise the mechanisms by which solar farm development and operation may impact natural capital and ecosystem services, and provide policy recommendations for policymakers and the solar farm sector. Solar farms can deliver environmental benefits for hosting ecosystems while minimising negative impacts, with outcomes depending on location, construction techniques, and land management practices. However, the historical misalignment between climate, nature, and land use policies has hindered efforts to simultaneously address the climate and biodiversity crises through land use change for solar farms. For instance, existing public financial incentives in the UK that encourage landowners and developers to manage land for biodiversity largely exclude land with solar farms. Policy implications: We call for public policymakers to identify appropriate opportunities to amend existing national laws that address climate and biodiversity separately to improve integration of multiple aspects of the climate‐nature‐land use nexus into policymaking by: (1) formulating ecological and socio‐economic indicators and metrics that are appropriate to underpin the development, implementation, and assessment of public policies; (2) adopting a cross‐sectoral and cross‐government approach to form public policies; (3) ensuring solar farms can access public financial incentives that encourage sustainable land use; (4) implementing land use policies that incentivise funding from non‐government sources (e.g. private sector) into nascent nature markets; (5) embedding solar farms in biodiversity‐inclusive spatial planning policies and decision‐making; and (6) building equity and clarity into responsibilities and benefits for all actors involved. [ABSTRACT FROM AUTHOR]

The quest for sustainable energy solutions has intensified interest in marine renewables, particularly wave energy. This study addresses the crucial need for an objective assessment of Wave Energy Converter (WEC) technologies, which are instrumental in harnessing ocean waves for electricity generation. To benchmark WEC technologies, we employed an integrated approach combining the MEthod based on the Removal Effects of Criteria (MEREC) and the Spherical Fuzzy Combine Compromise Solution (SF-CoCoSo). MEREC provided a systematic way to determine the importance of various benchmarking criteria, while SF-CoCoSo facilitated the synthesis of complex decision-making data into a coherent evaluation score for each technology. The results of the study offer a definitive ranking of WEC technologies, with findings emphasizing the importance of grid connectivity and adaptability to various wave conditions as pivotal to the technologies' success. While the study makes significant strides in the evaluation of WECs, it also recognizes limitations, including the potential for evolving market dynamics to influence criteria weightings and the assumption that the MCDM methods capture all decision-making complexities. Future work should expand the evaluative criteria and explore additional MCDM methods to validate and refine the benchmarking process further. [ABSTRACT FROM AUTHOR]

We address the shortcomings associated with modelling national aggregate electricity consumption in a large and diverse country with unique regional characteristics. Focusing on Saudi Arabia, we employ an econometric approach to analyse the distinct responses of its regions to electricity prices and income levels. The study employs a general to specific modelling approach, utilizing data from 1990 to 2019 within the conventional energy demand theoretical framework. Our region‐specific estimations reveal income and price as the primary drivers, with the southern region exhibiting a higher sensitivity to income, while the eastern region shows a comparatively smaller response to prices attributed to its significant industrial presence. Elasticities for the central and western regions align with previous research, while eastern and southern regions exhibit larger elasticities. Weather impacts are observed only in the warmest western region, characterised by a substantial share of residential electricity consumption. Furthermore, we utilise our estimated model to project a regional baseline demand for electricity in Saudi Arabia and demonstrate how prices affect regions differently. This information is important for an oil‐exporting country like Saudi Arabia, considering the diverse fuel mix used for electricity generation across regions. Assuming moderate economic growth and no price change, our baseline projections indicate a total electricity demand of 366 terawatt hours (TWh) by 2030. [ABSTRACT FROM AUTHOR]

Hydrogen is increasingly recognized as a pivotal fuel source globally, and the generation of hydrogen from solar energy is playing a crucial role in this trend. Solar energy is highly valued for its renewability, eco-friendliness, cost-effectiveness, and ease of installation. In this present work, we assessed the electricity generation of photovoltaic-thermal and photovoltaic systems which are using solar energy. The water-cooled PV-T system was cooled at three different flow rates (0.3 kg/s, 0.39 kg/s, and 0.48 kg/s) for a total panel area of 108 m2. Electricity generated within both systems was actively utilized for hydrogen production. This electricity was employed in a Proton Exchange Membrane electrolyzer to generate hydrogen. The simulations were carried out utilizing the Engineering Equation Solver for a specific day in July, encompassing the hours from 8 a.m. to 5 p.m., with each hour being considered. Daily electrolyzer performance was affected by the voltage and current density effects of four different electricity generation configurations, as well as the change in ambient temperature. The daily electricity production for PVs and PV-Ts, with cooling flow ratios of 0.3 kg/s, 0.39 kg/s, and 0.48 kg/s, was 338.2 MJ, 344.89 MJ, 351.42 MJ, and 356.08 MJ, respectively. Additionally, the daily hydrogen production with PEM in combination with PVs and PV-Ts, both without cooling and with the same flow rates, was 1617.2 g, 1646.5 g, 1675.3 g, and 1696 g, respectively. The maximum energy efficiency for PEM was 70.01 %, 69.98 %, 69.95 %, and 69.92 %, while the highest exergy efficiency for the same configuration was 59.75 %, 59.72 %, 59.69 %, and 59.67 %, respectively. In summary, the application of cooling to solar panels leads to increased electricity generation, resulting in higher current and voltage for the PEM. This has minimal adverse effects on the energy and exergy efficiencies of the PEM. Despite a slight negative impact, the cooled system outperforms the non-cooled one in hydrogen production. Furthermore, the system achieved its maximum energy and exergy efficiencies, reaching 50.24 % and 9.772 % when using mass flow ratios of 0.48 kg/s and 0.30 kg/s in PV-T on the selected day. • Hydrogen production of the PEM with PVs and PV-Ts. • Thermodynamic performances of PV, PV-T, PEM and overall the systems. • The comparison of the electrical energy production PVs and PV-Ts. • The impact daily ambient temperature and solar radiation on the systems. [ABSTRACT FROM AUTHOR]

Ensuring a balance between supply and demand is critical within electricity grids, requiring a supply composition that guarantees consistent service provision in the short and medium term. Between 2008 and 2017, Ecuador's electricity generation capacity expanded significantly, with an investment of approximately USD 8150 million into harnessing the potential energy of water. This led to the construction of five high-capacity hydroelectric projects by 2017, contributing 33.4% of the sector's energy output by 2023. However, it is important to note that if installed hydroelectric projects operate as run-of-river plants, with limited reservoir capacity, they can only regulate water use for electricity generation on an hourly basis. As of 2023, these run-of-river plants represent 68.8% of Ecuador's total hydroelectric capacity within the National Interconnected System (SNI). Consequently, during periods of low inflows, supplementary energy from other power generation plants is necessary to prevent energy crises. This paper addresses the impact on energy storing for electricity generation resulting from the evolution of hydroelectric power plant entry from 2006 to 2023. This aspect has not been thoroughly examined in hydrothermal systems, which primarily focus on potential energy obtained from dams. Our approach involves a statistical analysis of hydroelectric dam reservoir operational levels. We further explore the influence on demand service within Ecuador's electricity system, particularly during observed energy crises towards the end of 2023. [ABSTRACT FROM AUTHOR]

This article presents a comprehensive review of the current landscape and prospects of large-scale hydrogen storage technologies, with a focus on both onshore and offshore applications, and flexibility. Highlighting the evolving technological advancements, it explores storage and compression techniques, identifying potential research directions and avenues for innovation. Underwater hydrogen storage and hybrid metal hydride compressed gas tanks have been identified for offshore buffer storage, as well as exploration of using metal hydride slurries to transport hydrogen to/from offshore wind farms, coupled with low pressure, high flexibility electrolyser banks. Additionally, it explores the role of metal hydride hydrogen compressors and the integration of oxyfuel processes to enhance roundtrip efficiency. With insights into cost-effectiveness, environmental and technology considerations, and geographical factors, this review offers insights for policymakers, researchers, and industry stakeholders aiming to advance the deployment of large-scale hydrogen storage systems in the transition towards sustainable energy. [Display omitted] • Underwater H 2 buffer storage is proposed for deepwater floating wind installations. • Hybrid metal hydride – H 2 gas buffer stores are attractive for offshore locations. • Potential of thermal compression recognised for large-scale H 2 storage (LSHS). • Explore use of oxyfuel processes to improve roundtrip efficiency of LSHS. [ABSTRACT FROM AUTHOR]

Graphene oxide has attracted many interests in the recent decade due to its unique mechanical and chemical properties. This study focuses on the modification of graphene oxide and preparation proton exchange membrane (PEM) by sulfonated poly ether ether ketone (SPEEK) as base polymer for using in MFC as a modified membrane to remove COD and electricity generation. The scanning electron microscope (SEM) images, Fourier transform infrared (FTIR) and contact angle measurements were used to verify hydrophilic properties of the synthesized membranes. First, preparation procedures and properties of sulfonated reduced graphene oxide are briefly described. Subsequently, modification of proton exchange membrane from SPEEK polymer with prepared nano particle of sulfonated reduced graphene oxide 0.5 wt. % and its operation in MFC was considered. COD removal, power density, current density and coulombic efficiency were monitored during the process operation to evaluate the MFC performance. During the process operation, COD removal, power density, current density, and coulombic efficiency were tracked to assess the MFC performance. The power density and current density, 39.43 mW/m² and 161 mA/m² and the columbic efficiency 48.9 % was obtained, respectively. The COD removal of 89.5 % was obtained. [ABSTRACT FROM AUTHOR]

Smart grids are conceived as a system to optimally manage the set of means that are part of the electricity grid to achieve adequate performance in the distributed generation system in the supply of quality electricity. The objective of this study was to analyze the importance of smart grids in distributed generation and how the elements that make it up allow the implementation of this technological innovation. The methodology was based on the mixed approach, of experimental design with descriptive scope and documentary support, the experimental method was applied for programming with the use of Homer Pro software. The results were obtained by simulation, carried out for a distributed generation system with a consumption of 197.78 kWh/day, obtaining important data such as the amount of kW of electricity generation supplied in a year, with a value of 98,114 kWh/year. [ABSTRACT FROM AUTHOR]

Hybrid power plants have recently emerged as reliable and flexible electricity generation stations by combining multiple renewable energy sources, energy storage systems (ESS), and fossil-based output. However, the effective operation of the hybrid power plants to ensure continuous energy dispatch under challenging conditions is a complex task. This paper proposes a dispatch engine (DE) based on mixed-integer linear programming (MILP) for the planning and management of hybrid power plants. To maintain the committed electricity output, the dispatch engine will provide schedules for operation over extended time periods as well as monitor and reschedule the operation in real time. Through precise prediction of the load and the photovoltaic (PV) and wind power outputs, the proposed approach guarantees optimum scheduling. The precise predictions of the load, PV, and wind power levels are achieved by employing a predictor of the Feed-Forward Neural Network (FFNN) type. With such a dispatch engine, the operational costs of the hybrid power plants and the use of diesel generators (DGs) are both minimized. A case study is carried out to assess the feasibility of the proposed dispatch engine. Real-time measurement data pertaining to load and the wind and PV power outputs are obtained from different locations in the Sultanate of Oman. The real-time data are utilized to predict the future levels of power output from PV and from the wind farm over the course of 24 h. The predicted power levels are then used in combination with a PV–Wind–DG–ESS–Grid hybrid plant to evaluate the performance of the proposed dispatch engine. The proposed approach is implemented and simulated using MATLAB. The results of the simulation reveal the proposed FFNN's powerful forecasting abilities. In addition, the results demonstrate that adopting the proposed DE can minimize the use of DG units and reduce a plant's running expenses. [ABSTRACT FROM AUTHOR]

Currently, most studies on the optimization of wind farm layouts on flat terrain employ a discrete grid-based arrangement method and result in irregular layouts that may damage the visual appeal of wind farms. To meet the practical requirements of wind farms, a two-step optimization method called "grid–coordinate" based on a genetic algorithm is proposed in this paper. The core idea is to initially determine the number of wind turbines and their initial positions using a grid-based approach, followed by a fine-tuning of the wind farm layout by moving the turbines in a row/column manner. This two-step process not only achieves an aesthetically pleasing arrangement but also maximizes power generation. This algorithm is conducted to optimize a 2 km × 2 km wind farm under three classic wind conditions, one improved wind condition, and a real wind condition employing both the Jensen and Gaussian wake models. To validate the effectiveness of the proposed method, the optimization of configurations based on different wake models was conducted, yielding results including the efficiency, total power output, number of wind turbines, and unit cost of electricity generation. These results were compared and analyzed against the classical literature. The findings indicate that the unit cost of electricity generation using the two-step optimization approach with the Gaussian wake model is higher than that of the initial grid optimization method. Additionally, varying the number of wind turbines can lead to instances of high power generation coupled with low efficiency. This phenomenon should be carefully considered in the wind farm layout optimization process. [ABSTRACT FROM AUTHOR]

Recently, there has been a push by countries to diversify their energy mix considering various factors. In this regard, there have been several studies conducted to assess the potential for using sources such as wind and solar to generate supplemental energy to the already present energy generation setup. In this regard, this study explores the potential of wind for the Commonwealth of Kentucky. To perform this study, wind data were sourced for eight locations across Kentucky from the publicly accessible wind speed information present at Weather Underground for the years 2020–2021 (two years). An analysis was performed concerning the seasonal, monthly, and hourly variation in the wind speed so as to identify the expected times of sufficient wind energy generation. Moreover, a comparison of the collected data was performed with data from a home-based weather station as well as a deployed wind turbine to validate the variation pattern of the publicly sourced data. Finally, in order to investigate the variation patterns of wind and solar energy sources, a comparative analysis was also performed using data from a solar power generation plant in Kentucky. A seasonal and monthly complementarity was observed between the wind and solar energy. However, when considering daily patterns, the wind was found to follow solar generation with an offset. While further research is required, this analysis indicates that it is possible to deploy wind energy power generation projects in the Commonwealth of Kentucky. The seasonal complementary behavior of wind and solar energy can be used along with battery storage in conjunction with natural gas to provide a diversified electricity generation portfolio. [ABSTRACT FROM AUTHOR]