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Concentrated solar power (CSP) is one of the few sustainable energy technologies that offers day-to-night energy storage. Recent development of the supercritical carbon dioxide (sCO2) Brayton cycle has made CSP a potentially cost-competitive energy source. However, as CSP plants are most efficient in desert regions, where there is high solar irradiance and low land cost, careful design of a dry cooling system is crucial to make CSP practical. In this work, we present a machine learning system to optimize the factory design and configuration of a dry cooling system for an sCO2 Brayton cycle CSP plant. For this, we develop a physics-based simulation of the cooling properties of an air-cooled heat exchanger. The simulator is able to construct a dry cooling system satisfying a wide variety of power cycle requirements (e.g., 10–100 MW) for any surface air temperature. Using this simulator, we leverage recent results in high-dimensional Bayesian optimization to optimize dry cooler designs that minimize lifetime cost for a given location, reducing this cost by 67% compared to recently proposed designs. Our simulation and optimization framework can increase the development pace of economically-viable sustainable energy generation systems. [ABSTRACT FROM AUTHOR]

Translation abstract Innovative foundation for noise barriers – a Deutsche Bahn pilot project with ground screwsIn geotechnical engineering, ground screws are often associated with lightweight constructions and are established worldwide as a foundation for solar power plants. Larger ground screw designs are currently being developed and tested as part of pilot projects. At approx. 406 mm, these ground screws have around four times the tube diameter of the above mentioned and are therefore to be classified and dimensioned as pile foundations. In contrast to conventional driven steel piles, the ground screws are driven into the ground without vibration. It is obvious that the foundation elements should be used where particular attention must be paid to noise and vibration emissions. For example, as a foundation element for noise barriers as part of the special noise remediation program for the Middle Rhine Valley. This article presents the Deutsche Bahn pilot project, provides information on the design of the large ground screws and highlights the advantages of the innovative foundation system. [ABSTRACT FROM AUTHOR]

Solar energy holds promise as a sustainable and environmentally friendly source of power. In this study, we focus on improving the thermal efficiency of parabolic trough solar collectors (PTSCs) by investigating the performance of three different binary micropolar nanofluids – micropolar‐Casson, micropolar‐Maxwell, and micropolar‐Williamson – when used as heat transfer fluids within these collectors, with engine oil as the base fluid. The problem studied revolves around enhancing the heat transfer characteristics within PTSCs, crucial for maximizing energy conversion efficiency in solar power generation. By exploring the behavior of these nanofluids under various flow conditions, we aim to optimize the design and operation of PTSC systems for improved performance and sustainability. The importance of this research lies in its potential to significantly enhance the efficiency of solar energy harvesting, thereby contributing to the transition toward cleaner energy sources and reducing dependence on fossil fuels. Additionally, the findings have implications for diverse applications, including solar aviation, solar‐powered maritime vessels, solar thermal power plants, industrial process heating, and solar‐driven water pumping mechanisms, where improved heat transfer efficiency is paramount for enhancing overall system performance and reducing operational costs. Furthermore, the investigation delves into the influence of various factors governing the flow of these binary micropolar nanofluids within PTSC setups, including aspects such as velocity, thermal characteristics, entropy generation, skin friction, drag force, and local Nusselt number. The results notably reveal substantial enhancements in thermal efficiency, with maximal relative enhancements quantified as 22.1768%, 19.3662%, and 17.7349% for micropolar‐Casson, micropolar‐Maxwell, and micropolar‐Williamson nanofluids, respectively. [ABSTRACT FROM AUTHOR]

This work concentrates on the design parameters of a turbine blade for a small-scale solar chimney plant. The pitch angle (θ), relative wind angles (ϕ and ψ), lift force (FL) and relative chord length (lcr) of the turbine blade are determined. Betz and Bernoulli's theories were used for estimating and optimizing the above blade parameters. The coefficients of power, drag, lift and thrust forces are estimated and analyzed. Two wind speeds were considered. One represented higher speed (10 m/s) and the other for lower speed (2 m/s). At 10 m/s, the required rotor diameter is drastically reduced for producing the same power output. At 2 m/s, θ, ϕ, ψ and FL were optimized and they are; θ = 18.4°, ϕ = 26.4°, ψ = 75.6° and FL = 0.0073 N for maintaining the maximum power (P) of 0.026 W. The required diameter for the rotor blade is estimated and is varied from 0.66 to 6.56 m for producing a power range of 1–100 W. At 10 m/s, the optimized parameters are; θ = 42.9°, ϕ = 50.94° and ψ = 20.39° and FL = 0.4082 N for reaching the maximum P of 2.538 W. The estimated results were validated with existing studies and observed a good match. [ABSTRACT FROM AUTHOR]

This paper presents an extensive analysis of the UK's largest bifacial photovoltaic (PV) power plant, located in North Yorkshire. Commissioned in January 2020, this trailblazing facility, with a total installed capacity of 34.7 MW, is a benchmark for the evaluation of bifacial solar technology within the region. This pioneering study provides a thorough comparative assessment of bifacial and monofacial PV systems through a methodical investigation of their energy production, degradation rates, and spectral responses over a 4-year operational period. Our findings reveal that bifacial PV modules, distributed across four segments of the power plant, demonstrate a remarkable average power gain ranging between 15.12% and 17.31% compared with monofacial modules. Despite experiencing marginally higher annual degradation rates—1.17% for bifacial compared with 0.91% for monofacial systems—bifacial modules show superior resilience and energy yield, particularly during winter months when albedo effects are pronounced due to snow coverage. The study also highlights the strategic importance of spectral response analysis in optimizing PV performance. Bifacial modules have shown greater efficiency in capturing infrared radiation—a property that could be exploited to enhance overall energy yield under specific environmental conditions. The empirical data indicate a consistent performance of bifacial modules with an average normalized energy output clustering around the expected efficiency level. Therefore, the results of this study are pivotal for understanding the practical implications of deploying bifacial PV technology on a large scale. They provide valuable data for stakeholders in the solar energy sector, guiding future installations and innovations in solar panel technology. [ABSTRACT FROM AUTHOR]

An axial flow fan is designed for dry cooling of a sCO2 Brayton cycle for a CSP plant, and a scaled model of the fan is manufactured and tested experimentally in an ISO 5801:2017 Type A fan test facility. While the design procedure's estimate of the total-to-static efficiency at the design flow rate is relatively high, at 74.4%, the experimental fan efficiency was found to be only 50.6%. This paper details an investigation into the causes of fan performance degradation, using both experimental and numerical methods. The investigation finds that the hub configuration, tip clearance size, and scale of the test fan is responsible for the reduced performance. Two alternative hub and casing configurations are identified which improve the fan's performance significantly. [ABSTRACT FROM AUTHOR]

Renewable energies are a major tool to reduce greenhouse gas emissions and combat climate change. Among renewables, solar parks are a key technology and their expansion will strongly increase in the future. Hence, there is a great need for research regarding their impact on biodiversity. In this study, we investigated the importance of three solar parks in northern Germany as habitat for carabid beetles. More specifically, we determined how habitat characteristics (temperature, vegetation structure), species richness, activity densities and carabid beetle assemblages vary between different locations within solar parks: areas under solar panels "UNDR", gaps between panel rows "BTW" and areas at the edge of solar parks "EDGE". We found that UNDR strongly differed from BTW/EDGE in terms of habitat conditions, species richness and activity densities of carabid beetles. UNDR mainly provided habitat for a species- and individual-poor subset of species already present in BTW/EDGE and made only a small contribution to the total species richness of the investigated solar parks. BTW and EDGE, on the other hand, differed only slightly. Thus, the narrow gaps between the panel rows were of similar importance as a habitat for carabid beetles as the edge areas. Overall, the investigated solar parks—and thus also the more species-rich areas EDGE and BTW—almost exclusively provided habitat for widespread and common non-threatened generalists, while species of conservation concern were extremely rare. Implications for insect conservation: The low importance of UNDR for carabid beetles should be considered when assessing the biodiversity value of solar parks, since a large proportion of these facilities is covered with solar panels. Between panel rows and at the edge of solar parks, larger areas should be kept free from construction with solar panels in order to provide habitats for carabid beetles and other species groups. More research should be conducted on how to further improve solar parks for carabid beetles and overall biodiversity. [ABSTRACT FROM AUTHOR]

The objective of this study is to assess the economic feasibility of installing high-efficiency solar panels in a yacht marina in the Çeşme district of Izmir, Türkiye. In this aim, the facility's energy demand from the grid is reduced. The study compares ten different PV panel modules with various installation configurations, including fixed, horizontal, vertical, and two-axis. The most cost-effective option is determined with novel comparative economic indicators involving the costs associated with purchasing electricity from the grid. The PVGIS online tool is used to simulate energy production from solar panel systems and determine the ideal quantity of solar panels that can be deployed within the designated regions. New economic indicators, Relative Levelized Energy Cost (RLEC), and Relative Payback Period (RPBP) are proposed in the study to compare the economic performance of the different solar panel sets. The results indicate that the facility can compensate for 14.44% of its energy demand with the two-axis configuration. Module 5 yielded the best relative economic performance with an RLEC of 0.090 $/kWh. The best Payback Period (PBP) is obtained from fixed module 7, while the best RPBP is achieved with fixed module 5 at 7.113 years, which shows the importance of using comparative economic indicators for suitable energy systems. [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]

Quadrotor technology has become increasingly important in the field of photovoltaic (PV) solar farm monitoring, but short battery life is one of the primary factors limiting its further application. To address above issue, this study proposes a linear temporal logic (LTL)-based path planning algorithm that considers the need for charging together with multiple visits to PV equipments, a single visit to communication equipment, and the avoidance of restricted regions, which enables the long-term monitoring of PV solar farms. Particularly, the location of a charging station can be determined optimally and efficiently by a heuristic algorithm based on the nonlinear programming and branch and bound (NLP-BB) algorithm. The simulation results indicate that the proposed method effectively solves the long-term monitoring path planning problem that is coupled with the optimal deployment of the charging station. [ABSTRACT FROM AUTHOR]

Distributed photovoltaic (PV) power stations generally lack historical meteorological data, which is one of the main reasons for their insufficient power prediction accuracy. To address this issue, this paper proposes a power prediction method for regional distributed PV power stations based on meteorological encryption and spatio-temporal graph networks. First, inverse distance weighted meteorological encryption technology is used to achieve the comprehensive coverage of key meteorological resources based on the geographical locations of PV power stations and the meteorological resources of weather stations. Next, the historical power correlations between PV power stations are analyzed, and highly correlated stations are connected to construct a topological graph structure. Then, an improved spatio-temporal graph network model is established based on this graph to deeply mine the spatio-temporal characteristics of regional PV power stations. Furthermore, a dual-layer attention mechanism is added to further learn the feature attributes of nodes and enhance the spatio-temporal features extracted by the spatio-temporal graph network, ultimately achieving power prediction for regional PV power stations. The simulation results indicate that the proposed model demonstrates excellent prediction accuracy, robustness, extensive generalization capability, and broad applicability. [ABSTRACT FROM AUTHOR]

To address the carbon emission issue of combined heat and power (CHP) units in park-level integrated energy system (IES), this paper proposes an optimization scheduling model of park-level IES by considering combined weights. Firstly, a park-level IES is established within a designated park area, incorporating gas storage (GS), power to gas (P2G), carbon capture and storage (CCS), CHP units, wind power and photovoltaic power stations. Based on the analysis of the operational characteristics of GS, P2G, CCS, and CHP, an optimal scheduling model of the GS–P2G–CCS–CHP integrated system is proposed to optimize CHP with low carbon. Secondly, to achieve economic viability and the accommodation of renewable energy, a combined weights approach is proposed for the objective function, considering subjective and objective weights. Finally, to verify the feasibility of the proposed method, four operational strategies are compared, and based on the operational characteristics of GS, P2G, CCS, and CHP, the optimal capacities of P2G and GS are determined. [ABSTRACT FROM AUTHOR]

The global trend of reducing the "carbon footprint" has influenced the dynamic development of projects that use renewable energy sources, including the development of solar energy in large solar power plants. Consequently, there is an increasingly pronounced need in scientific circles to consider the impact these projects have on space and the environment. The fact that international financial institutions consider environmental effect to be a significant factor when funding solar energy projects is one of the main reasons this topic is so important in professional circles, particularly among solar energy investors. This paper highlights the fact that solar power plants can have both positive and negative impacts on space and the environment. Those impacts need to be defined in order to choose optimal spatial and territorial solutions that ensure preventive planning and active environmental protection. In the process, the application of strategic environmental assessment (SEA) in the planning and spatial organization of solar power plants becomes important. SEA is characterized by a holistic approach where complex interactions and correlations in the location of planned implementation of the solar power plant can be understood at the earliest stage of project development. By doing this, it is possible to prevent all potential risks that may emerge in the project's later stages of implementation, which is favorable both from the aspect of effective environmental protection and from the point of view of investors investing in solar power plant projects. Optimal solutions that bring about the basic role of SEA are sought primarily in the analysis of the spatial relations of the solar power plant with regard to land, biodiversity, landscape, and basic environmental factors, which is particularly highlighted in the paper. Also, the basic methodological concept applied in SEA is demonstrated, combining different methodological approaches and methods for impact assessment, as part of a unique semi-quantitative method of multi-criteria evaluation of planning solutions. [ABSTRACT FROM AUTHOR]

A hydro–solar hybrid system is an important solution for expanding renewable generation capacity under the percepts of the energy transition. This type of association allows for the coordinated dispatch of solar and hydropower plants, resulting in operational benefits in terms of energy generation and reservoir management, that is, the better use of available water and energy resources. As in this case, the operation of the hydropower plant is associated with the cascade in which it operates, when it is hybridized (for example, by associating with a solar power plant), in addition to local changes, there are impacts on the operating conditions of the other hydropower plants in the same cascade. From such a perspective, this study presents an energy system management model for hybrid power plants composed of hydro and solar sources, aiming to optimize the joint operation and measure the operational consequences at the local level and in the cascade. The results from a case study of a hydro–solar power plant hybridization in the Tietê River (Brazil) revealed increased energy production and improvement in the operating conditions of the cascade's reservoirs, while the grid capacity was found to be an important constraint that limits the capture of synergies resulting from the generation sources complementarity and thus on the benefits to the cascade. [ABSTRACT FROM AUTHOR]

We compare the performance of photovoltaic (PV), flat-plate and evacuated-tube solar-thermal (ST), and hybrid photovoltaic-thermal (PV-T) collectors to meet the energy demands of multi-effect distillation (MED) desalination plants across four locations. We consider three scales: 1700 m3day−1, 120 m3day−1 and 3 m3day−1. We find a strong dependence of the capacity and configuration of the solar collectors on both the cost of sourcing electricity from the grid and the specific collector employed. We find specific costs as low as 7.8, 3.4 and 3.7 USDm−3 for the three plant capacities. We find that solar-driven systems optimised for the lowest specific cost result in CO2eq emissions equal to, or higher than, those from grid-driven reverse osmosis (RO) and in line with PV-RO. This highlights the need to consider the environmental footprint of these systems to ensure that desalination is in line with the United Nations' Sustainable Development Goal 6. [ABSTRACT FROM AUTHOR]

Renewable energy, particularly solar power, is clean, cost-effective, and virtually limitless, making it an essential source of energy for developing countries. In the Kurdistan region, however, dependence on fossil fuels remains high, with 85 percent of electricity generated from these sources, whereas solar power contributes less than 1 percent. This study addresses this disparity by employing Boolean logical analytical hierarchy process techniques and a comprehensive set of criteria encompassing technical, ecological, and economic factors to identify suitable sites for solar power plants in Duhok Governorate. The results indicate that 68.5 percent of the governorate’s area is deemed suitable for solar power station construction, with the most promising zone comprising 132.2 km2 and capable of generating more than 8,000 megawatts of solar energy. Notably, most suitable areas are concentrated in the south and southwest, particularly in the districts of Bardarash, Shekhan, and Semel. This study paves the way for a significant shift toward renewable energy in northern Iraq. Identifying vast suitable areas for solar power plants offers a practical roadmap to reduce dependence on fossil fuels, provide a clean energy source, and enable a large-scale solar power project. This study empowers policymakers, energy companies, and investors to make informed decisions toward realizing this renewable energy potential, ultimately transforming the energy landscape in northern Iraq. [ABSTRACT FROM AUTHOR]

Solar panels often suffer from dust accumulation, significantly reducing their output, especially in desert regions where many of the world's largest solar plants are located. Here, an autonomous dust removal system for solar panels, powered by a wind‐driven rotary electret generator is proposed. The generator applies a high voltage between one solar panel's output electrode and an upper mesh electrode to generate a strong electrostatic field. It is discovered that dust particles on the insulative glass cover of the panel can be charged under the high electrical field, assisted by adsorbed water, even in low‐humidity environments. The charged particles are subsequently repelled from the solar panel with the significant Coulomb force. Two panels covered with sand dust are cleaned in only 6.6 min by a 15 cm diameter rotary electret generator at 1.6 m s−1 wind speed. Experimental results manifest that the system can work effectively in a wide range of environmental conditions, and doesn't impact the panel performance for long‐term operation. This autonomous system, with its high dust removal efficiency, simplicity, and low cost, holds great potential in practical applications. [ABSTRACT FROM AUTHOR]

This paper applies jellyfish search optimization algorithm (JSOA) to maximize electric sale revenue for renewable power plants (RNPPs) with the installation of battery energy storage systems (BESS). Wind turbines (WTs) and solar photovoltaic arrays (SPVAs) are major power sources; meanwhile, the BESS can store energy generated at low-electricity price hours and supply the electricity to loads at other high-electricity price hours. In the first four cases with one operating day, JSOA and three other algorithms are implemented. JSOA reaches greater total revenue than the three other ones. BESS can support a renewable power plant (RNPP) to get more revenue by $495.2. Applying JSOA for two other cases with the change of requested saving energy levels and capacity of BESS, the results indicate that for increasing 10% saving energy or the reduction of 10% BESS capacity, the profit can be reduced by 10% of the maximum profit. In the last study case, BESS is connected between two plants in Vietnam, the Adani Phuoc Minh wind power plant and the Adani Phuoc Minh solar power plant, over one operating year. BESS supports the two power plants, reaching a profit of $733,322.5, about 4.15% of total revenue from the system without BESS. Considering BESS's investment costs, the profit of BESS over ten operating years is greater than the costs of the cheapest BESS technology by $3,703,225. However, the profit is smaller than other more modern BESS technologies. So, using BESS can bring a high profit to RNPPs, and the selection of BESS technologies impacts the economic issue of the RNPPs. [ABSTRACT FROM AUTHOR]

To reduce greenhouse gas emissions and the environmental impact of fossil fuels, Morocco has decided to increase the use of renewable energy resources. The intermittent nature of renewable energy resources causes instability in the power grid. Energy storage is the appropriate solution to this problem. Compressed air energy storage is a technology that stores energy in the form of high-pressure compressed air in above ground tanks or underground caverns. Large-scale storage of compressed air energy requires the storage of large volumes in salt caverns or aquifers. The aim of this paper is to find out the benefits of integrating underground compressed air energy storage technology. A case study in Morocco is used to estimate the levelized cost of energy plus storage (LCOES). The annual capacity factor for solar and wind power plants and the potential of underground caverns in Morocco were analyzed. The results illustrate that for a system with 100 MW capacity installed in the Casablanca region, the combination of an adiabatic compressed air energy storage system (ACAES) with a wind turbine installation offers the lowest electricity price per kWh, with average LCOES of 0.04 $/kWh. [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]

Solar-boosted photo-technology stands out as a powerful strategy for photosynthesis and photocatalytic processes due to its minimal energy requirements, cost-effectiveness and operation under milder, environmentally friendly conditions compared to conventional thermocatalytic options. The design and development of photocatalysts have received a great deal of attention, whereas photoreactor development must be studied deeper to enable the design of efficient devices for practical exploitation. Furthermore, scale-up issues are important for this application, since light distribution through the photoreactor is a concurrent factor. This review represents a comprehensive study on the development of photoreactors to be used mainly for the photoreduction of CO2 to fuels, but with concepts easily transferable to other photosynthetic applications such as ammonia synthesis and water splitting, or wastewater treatment, photovoltaics combined to photoreactors, etc. The primary categories of photoreactors are thoroughly examined. It is also explained which parameters influence the design of a photoreactor and next-generation high-pressure photoreactors are also discussed. Last but not least, current technologies for solar concentrators are recalled, considering their possible integration within the photoreactor. While many reviews deal with photocatalytic materials, in the authors' view, photoreactors with significant scale and their merged devices with solar concentrators are still unexploited solutions. These are the key to boost the efficiency of these processes towards commercial viability; thus, the aim of this review is to summarise the main findings on solar photoreactors for the photoreduction of CO2 and for related applications. [ABSTRACT FROM AUTHOR]

Molten salts have been used as heat transfer fluids since the middle of the 20th century. More recently, molten chloride salts have been studied for use in concentrated solar power plants or molten salt reactors. However, none of the materials studied to date has been able to withstand this highly corrosive environment without controlling the salt's redox potential. The alumina-forming alloy was a promising option, as it has not yet been widely studied. To investigate this possibility, two iron-based alumina-forming alloys were corroded in NaCl-MgCl2 eutectic at 600 °C for 500 h after being pre-oxidised to grow a protective layer of α-alumina on each alloy. A salt purification protocol based on salt electrolysis was implemented to ensure comparable and reproducible results. During immersion, alumina was transformed into MgAl2O4, as shown by FIB-SEM observation. Inter and intragranular corrosion were observed, with the formation of MgAl2O4 in the corroded zones. The nature of the oxides was explained by the predominance diagram. Intragranular corrosion was 2 µm deep, and intergranular corrosion 10 µm deep. Alumina formed at the bottom of the intergranular corrosion zones. The depth of intergranular corrosion is consistent with O diffusion control at the grain boundary. [ABSTRACT FROM AUTHOR]

Summary: With the rapid development of the global renewable energy source field, the importance of dynamic index processing technology in distributed energy systems has become more and more obvious. To better improve the real‐time dynamic interaction means of microgrids in the energy Internet and optimize the relevant methods for microgrid energy consumption detection, this article proposes to introduce the distributed Hadoop platform into the electrical thermal coupling multivariate data in the form of cluster configuration, and then use the Spark framework to detect and capture real‐time data, to complete the tracking and analysis of energy consumption data. At the same time, the Internet of Things and the cloud intelligent monitoring system are combined to further clean and explore the data, to achieve the in‐depth detection of the energy consumption problem of the microgrid under the premise of reducing the initial investment, and achieve the purpose of reducing the operating cost. In this case, the outliers are detected according to the photovoltaic indicators of photovoltaic power stations, the filtration and purification functions of photovoltaic indicators are used by the nuclear density curve, and the sustainable solar energy is optimized by combining multiple indicators such as wind direction and temperature. Based on reducing energy consumption, the overfitting phenomenon of the controller is controlled, and an optimized controller‐led cloud platform is established. By establishing the objective function model, the robustness of the controller is guaranteed and the detection expectation is satisfied by the experiment of energy consumption data. In addition, when the cloud platform is created, this study uses a genetic algorithm to optimize the controller index and then builds a cloud console detection mechanism that collaborates with the Internet. Through the research, it is found that outliers may lead to the redundancy of energy consumption indicators in the non‐processing state. This study adopts the optimization of energy consumption parameters and the help of a distributed data framework to deal with and effectively solve this problem. In terms of interpolation simulation verification combined with experimental data, this paper proposes to use the Internet of Things, wearable devices, sensors, and other means to monitor the cost of energy consumption, to realize the distributed dynamic storage of massive real‐time data in the process of parallel processing, as well as the evaluation and detection of real‐time data replacement. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to shed light on the experience of the United Arab Emirates (UAE) in balancing three main pillars: the environmental criteria, the reduction of CO2 emissions and the economic growth. Based on the environmental Kuznets curve (EKC) framework, it will assess the causal relationship between economic indicators such as gross domestic product (GDP) per capita, trade openness and energy use and environmental indicators such as CO2 emissions. Design/methodology/approach: The analysis relies on a period of 40 years (1981–2020) where data is extracted from the World Bank database. This study uses the unit root test for time series stationarity, the optimal lag length test, the "Johansen" test for co-integration and the vector error correction model. Findings: The paper concludes to two major findings. On a short-term basis, CO2 emissions and economic indicators are negatively correlated, whereas on a long-term basis, there is no association between CO2 emissions and economic indicators in the UAE. Research limitations/implications: The research ends with important recommendations. It illustrates the importance of rationalizing the use of primary resources and the necessity to embrace successful and efficient policies in the energy production. Practical implications: More specifically, UAE is urged to address the problem of CO2 emissions in the electricity sector and increase awareness of the use of environmentally friendly processes in the transport and industrial sectors. While setting their economic agendas, UAE are encouraged to meet environmental criteria and invest in renewable energy projects such as "Shams 1", the largest solar power plant outside of Spain and the USA. Originality/value: The current study is significant in its research on the environmental impact of economic development, trade openness and energy use policies in the UAE. It uses CO2 emissions as an environmental proxy and evaluates the environmental policies adopted in the UAE to reduce its impact. [ABSTRACT FROM AUTHOR]

Most regions of the world have seen tremendous growth in distributed energy resources, especially photovoltaic (PV) generation. The penetration of PV generation into the power grid is high and hence it has a major impact in power system. The integration of solar PV plant into the power system has both negative as well as positive impacts on transient stability of the power system during faults. In this work, the proposed current amplitude limiting based Fault Ride Through (FRT) control algorithm is implemented in large scale power systems and enhancement of transient stability is also studied in terms of synchronous machine side and grid side parameters namely rotor speed deviation, load angle, relative rotor angle, active and reactive power. The transient stability of large-scale Grid Connected solar PV (GCPV) system is discussed in this article, when the system is incorporated with the proposed FRT control strategy. The large scale GCPV system is said to be stable, if the angular displacement between the machines in the system stays within predetermined limits. The parameters considered for transient analysis on the synchronous machine side are the rotor angle, rotor speed, and Critical Clearing Time. The proposed model is simulated in MATLAB Simulink and validated in 1 kW hardware setup of grid connected PV system which performs satisfactorily in terms of system parameters and transient stability improvement. [ABSTRACT FROM AUTHOR]

A solar tower system is a nonpolluting solar thermal power plant that utilizes a combination of a wind turbine and generator to convert thermal energy generated from a solar collector into electrical energy. The study focuses on a system comprising a solar collector that transforms solar energy into thermal energy, a chimney that converts thermal energy into kinetic energy, and a wind turbine that further converts kinetic energy into electrical energy. The system's performance is evaluated through the implementation of a numerical model, which is validated by comparing it with experimental data. Four different types of meshes are tested to determine the most suitable mesh for the system. The discrete ordinate radiation model is used to solve the radiative transfer equation, and the RNG k‐휀 turbulence model is implemented to calculate turbulence. In a subsequent study, the effect of absorber configuration on the system's performance is investigated. Three different absorber configurations—sinusoidal, square, and triangular—are proposed, and the numerical results showed that the system's performance is affected by the absorber configuration. The velocity in the chimney inlet increases for all proposed configurations compared to the standard configuration, with the triangular configuration showing the highest velocity increase. Additionally, the newly proposed configurations enhance the thermal efficiency of the system, leading to a thermal efficiency of 12.18%, 12.2%, and 13.65% for the sinusoidal, triangular, and square configurations, respectively. Overall, the solar tower system demonstrates its potential as a clean and efficient source of electrical power. [ABSTRACT FROM AUTHOR]

The current study focuses on the modeling and analysis of an industrial‐scale solar chimney power plant (SCPP) with the storage system. Rating and sizing estimations are time‐consuming and difficult to get since sun radiation is diffuse and imprecise; as a result, a theoretical technique is used to gather the necessary data. The generator is assumed to be fully loaded for the sake of the computations. Considerations including chimney height, collector radius, and storage thickness are made in order to get the appropriate generator rating and daily energy output. The optimum sizing assessment has also been obtained based on the input criteria. To get the required results, weather information for Mumbai, India has been taken into account. Based on the findings, the technical feasibility was researched and presented. [ABSTRACT FROM AUTHOR]

Ground‐mounted photovoltaic sites are often treated as impervious surfaces in stormwater permits. This ignores the pervious soils beneath and between solar arrays and leads to an overestimation of runoff. Our objective was to improve solar farm stormwater hydrology models by explicitly considering the disconnected impervious nature of solar design and site characteristics. Experimental sites established on utility scale solar farms in Colorado, Georgia, Minnesota, New York, and Oregon had perennial vegetative plantings with mean precipitation ranging from 40.6 to 124.5 cm, and soil texture ranging from loamy sand to clay. Soil moisture measurements were collected beneath arrays, under drip edges, and in the vegetated area between arrays at each site. Hydrus‐3D models for soil moisture and stormwater hydrology were developed that accounted for precipitation falling on solar panels, drip edge redistribution of rainfall, infiltration, and runoff in the pervious areas between solar arrays and beneath panels. Drip edge runoff averaged 3‐ to 10‐times incident precipitation at the New York and Minnesota sites, respectively. Root mean square error values between measured sub‐hourly soil moisture and predicted moisture for large measured single storm events averaged 0.029 across all five sites. Predicted runoff depths were strongly affected by precipitation depth, soil texture, soil profile depth, and soil bulk density. Runoff depths across the five experimental sites averaged 13%, 25%, and 45% of the 2‐, 10‐, and 100‐year design storm depths, clearly showing that these solar farms do not behave like impervious surfaces, but rather as disconnected impervious surfaces with substantial infiltration of runoff in the vegetated areas between and beneath solar arrays. Core Ideas: Hydrus‐3D accurately estimated soil moisture and infiltration beneath and between solar arrays.Solar panel drip edge runoff averaged from 3X to 10X precipitation depth falling on panels.Design storm depth, soil texture and depth, and soil bulk density had a large impact on solar farm runoff.Solar farm runoff on coarse‐textured, deep soils was much less than runoff from fine‐textured, shallow soils.Solar farm hydrology is accurately represented with a disconnected impervious modeling framework. [ABSTRACT FROM AUTHOR]

Concentrated solar power (CWP) technology has matured sufficiently for large‐scale implementation. In a typical plant, the solar energy is captured by mirrors and directed onto heat‐transfer fluid (HTF), typically a molten salt that is further conveyed to the thermal energy‐storage system before being channeled to power turbines, generating electricity. A major concern about this technology is the need to reduce the levelized cost of electricity, necessitating heightened efficiency to enhance cost competitiveness and foster greater market penetration. One approach to achieve this involves replacing the current nitrate‐based molten salt mixture with nanofluids. They combine nitrate‐based molten salt and small amounts of nanomaterials of different dimensionality. These promising HTFs present a superior performance concerning their physical, thermal, and chemical properties. However, there is a lack of studies related to understanding the effects of nanomaterials and the underlying enhancement theories. Therefore, in this article, a detailed revision of the state of the art in experimental and theoretical studies of nanomaterials in a binary commercial nitrate‐based molten salt (solar salt) as HTF for CWP plants is presented, highlighting the challenges related to their application and future research directions. [ABSTRACT FROM AUTHOR]

The effects of population growth, climate change, and global economic expansion are concerning for food and energy security. For a nation like India, the agrivoltaic system is a center of photovoltaic and agricultural production as it is better suited to achieving the United Nation's sustainable development goals, especially SDG 7 (Affordable and clean energy) and SDG 11 (Sustainable cities and communities). The agrivoltaic solar power plant system generated 12667.15 kWh from September 2017 to August 2018 with a system efficiency of 11.22%. The height of agrivoltaic structure has been determined 3 m to perform agricultural operations underneath it. A shade-tolerant tomato crop has been cultivated in an open field and an agrivoltaic structure using four different types of land treatments in the proposed experimental study. The land equivalent ratio is obtained greater than open field treatments up to 1.65 for all treatments and environments. The benefit/cost ratio has been determined to be as high as 2.59 with the lowest payback period of 7.90 years. Crop productivity under agrivoltaic structures has been higher in all treatments up to 15.09% as compared to open field agriculture. Agrivoltaic technology is a novel and sustainable technology for farmers in the future. [ABSTRACT FROM AUTHOR]

High‐temperature thermochemical energy storage based on metal oxides is the key technology to reducing the levelized costs of electricity of the next‐generation concentrated solar power plants. CuO/Cu2O has wide availability and high energy density, but severe sintering leads to low reactivity. In this study, an innovative approach to modulate the oxygen vacancy content to change the surface properties and crystal structure to enhance the sintering resistance and redox reversibility is proposed. The re‐oxidation degree is increased from 46% to 99%, and the energy release rate is increased by 3.5 times. It remains 99.9% reduction and 97.1% oxidation activity after 3000 cycles, which is very valuable for engineering applications. Cu2MgO3 and Mg0.78Cu0.22O are prone to form oxygen vacancies, which promotes the formation of porous structures. Mg0.78Cu0.22O helps Cu2MgO3/CuO/Cu2O deliver more O through the surface. Mg0.78Cu0.22O is firmly and uniformly dispersed on the CuO/Cu2O surface after long cycling. They have a large binding energy, more charge transfer and enhanced bond energy at the interface. The mechanism of composite in increasing the sintering temperature and long‐term reaction stability is revealed from experimental and theoretical calculations, which provides a new idea for the rational design of thermochemical energy storage materials. [ABSTRACT FROM AUTHOR]

This study investigates the impact of including (or neglecting) the variable efficiency of hydrogen electrolyzers as a function of operating power in the modelling of green hydrogen produced from variable renewable energy sources. Results show that neglecting the variable electrolyzer efficiency, as is commonly done in studies of green hydrogen, leads to significant overestimation of hydrogen production in the range of 5–24%. The effects of the time resolution used in models are also investigated, as well as the impact of including the option for the electrolyzer to switch to stand-by mode instead of powering down and electrolyzer ramp rate constraints. Results indicate that these have a minor effect on overall hydrogen production, with the use of hour resolution data leading to overestimation in the range of 0.2–2%, relative to using 5-min data. This study used data from three solar farms and three wind in Australia, from which it is observed that wind farms produced 55% more hydrogen than the solar farms. The results in this study highlight the critical importance of including the variable efficiency of electrolyzers in the modelling of green hydrogen production. As this industry scales, continuing to neglect this effect would lead to the overestimation of hydrogen production by tens of megatonnes. • Variable efficiency electrolyzers are compared to fixed efficiency electrolyzers. • Fixed efficiency can lead to overestimation in hydrogen production by up to 24%. • Low fidelity time resolution has a modest impact on modelling hydrogen production. • Fixed efficiency electrolyzers underestimate the optimal size of hydrogen plant. • Results are validated using data from six renewable energy sites in Australia. [ABSTRACT FROM AUTHOR]

To easily control distributed photovoltaic power stations and provide fast responses for their regulation, this paper proposes an optimal cluster partitioning method based on a graph-based genetic algorithm (GA). In this approach, a novel structure utilizing a graph model is designed for chromosomes, and enhancements are made to the selection, crossover, and mutation models of the evolutionary to generate a search population for dividing distributed photovoltaic (PV) power grids into clusters. Moreover, the modularity and active power balance degree of the classic Girvan–Newman algorithm are employed as optimal objectives to establish a basis and evaluation system for cluster partitioning. Additionally, a Simulink simulation platform is established for the IEEE 33-bus time-varying scenario to validate its performance. A comparative analysis with some classic PV cluster partitioning algorithms demonstrates that the proposed method can achieve a more accurate and stable division of distributed PV units. [ABSTRACT FROM AUTHOR]

Solar photovoltaic (PV) panels are projected to become the largest contributor of clean electricity generation worldwide. Maintenance and cleaning strategies are crucial for optimizing solar PV operations, ensuring a satisfactory economic return of investment. Nanocoating may have potential for optimizing PV operations; however, there is insufficient scientific evidence that supports this idea. Therefore, this study aims to investigate the effectiveness of nanocoating on the performance of solar photovoltaic (PV) panels installed in Al Seeb, Oman. A further study was also carried out to observe the influence of coating layers on the performance of PV panels. One SiO2 nanocoated solar panel, another regularly cleaned PV panel, and a reference uncleaned panel were used to carry out the study. The site of the study was treeless and sandy, with a hot and dry climate. A data logger was connected to the solar PV panel and glass panel to record the resulting voltage, current, temperature, and solar radiation. It was observed that nanocoated PV panels outperformed both regular PV panels and uncleaned PV panels. Nanocoated PV panels demonstrated an average efficiency of 21.6%, showing a 31.7% improvement over uncleaned panels and a 9.6% improvement over regularly cleaned panels. Although nanocoating displayed high efficiency, regular cleaning also contributes positively. Furthermore, even though nanocoated PV panels outperformed the other two panels, it is important to note that the performance difference between the regular cleaned PV panels and the nanocoated PV panels was small. This indicates that regular cleaning strategies and nanocoating can further contribute to maintaining a more efficient solar PV system. Coating in many layers was also observed to influence the performance of PV panels insignificantly, mainly the fourth layer coating appeared to have formed sufficient mass to retain heat. [ABSTRACT FROM AUTHOR]

Estimating runoff at ground-mounted solar photovoltaic (PV) installations is challenging because of the disconnected nature of impervious solar panels and the pervious ground surface underneath and between panel rows. There is a need for improved tools to estimate how low impact development practices at these solar installations affect stormwater runoff. The objective of this study was to develop an innovative spreadsheet-based runoff calculator that rapidly estimates stormwater runoff from ground-mounted solar PV sites. The calculator is built on a 2-D hydrologic model (Hydrus-2D/3D) calibrated and validated using experimental data from five commercial solar farms in Colorado, Georgia, Minnesota, New York, and Oregon. The Hydrus-2D/3D hydrologic model was then used to generate nomographs for stormwater runoff that were incorporated into an easy-to-use Excel-based solar farm runoff calculator. This calculator allows for rapid estimation of NRCS stormwater runoff curve number (CN) values at solar farms by considering several complex factors unique to PV installations including: soil and topographic characteristics, surface cover, disconnected impervious surface factors associated with various solar panel designs, and climatic factors. The solar farm runoff calculator quickly estimates runoff CN for pre- and post-construction scenarios, and can estimate actual depth of runoff based on a user-specified 24-h design storm depth. Factors that have the most significant impact on stormwater runoff include design storm return frequency, soil texture, soil bulk density, and soil depth. Ground surface cover has a moderate impact on stormwater runoff, and factors that have a lesser impact on stormwater runoff include slope and array size, spacing and orientation on the landscape. The runoff calculator allows for accurate estimates of runoff generated by disconnected impervious surfaces and low impact development practices at solar farms as affected by a wide range of site-specific conditions. [ABSTRACT FROM AUTHOR]

In response to the challenges faced by solar power plants in Kupang, Indonesia -- particularly during the peak of the rainy season -- this study aims to enhance the WRF-Solar (Weather Research and Forecasting--Solar) numerical weather prediction model. Accurate short-term solar radiation forecasting is crucial for managing electricity supply disruptions and controlling operational costs in the City of Kupang and its surroundings. The unpredictable weather patterns -- characterized by intense cloud activity during these seasons -- pose significant challenges for reliable solar energy generation, thereby making precise weather modeling an essential tool for effective power plant management. Spanning 2020-2022, the research focused on the peak rainy seasons, utilizing a specifically configured WRF-Solar model to simulate solar radiation. Validation of the WRF-Solar model using observational data from the Automatic Solar Radiation Stations at the Kupang Climatological Station showed correlation values consistently above 0.50. However, the model exhibited a tendency to overestimate radiation intensity for GHI and DNI parameters (correlation 0.78 and 0.54) and underestimate for DHI (correlation 0.80), with RMSE values ranging from 47-320 W/m² and MBE values from -41.84 to 116.34 W/m². The model's accuracy was notably higher under clear conditions, with lower RMSE and MBE values but decreased significantly under overcast conditions, hence indicating sensitivity to cloud cover. This study highlights the WRF-Solar model's capability in capturing the diurnal pattern and hourly fluctuations of solar radiation while also underscoring the need for improved cloud representation to enhance accuracy under diverse climatic conditions. [ABSTRACT FROM AUTHOR]

Climate change has become a global issue and is predicted to impact less-developed regions, such as sub-Saharan Africa, severely. Innovative, sustainable renewable energy systems are essential to mitigate climate change's effects and unlock the region's potential, especially with the increasing energy demands and population growth. The region relies heavily on fossil fuels, which calls for urgent action towards energy security and expansion. Hybrid floating solar photovoltaic-hydropower (FPV-HEP) technology has emerged as a cost-effective and transformative solution to accelerate the low-carbon energy transition in sub-Saharan Africa. The technology combines solar panels with existing hydropower infrastructure, ensuring energy security while reducing carbon emissions. This technology offers several benefits over conventional ground-mounted solar systems, including efficient land utilization, energy generation, and water conservation. However, its adoption remains challenging due to technical complexities and evolving regulatory frameworks. Despite these challenges, Nigerian energy professionals have preferred renewable alternatives, mainly distributed solar PV and FPV-HEP plants. This collective embrace of FPV and renewables reflects a growing understanding of their critical role in mitigating climate change through sustainable energy practices. This research aims to contribute to the existing body of knowledge and assist policymakers in making informed decisions on adopting this technology. It also stimulates further research on this topic, offering a new potential solution to the ever-increasing demand for green energy in the region to meet their sustainable development needs. [ABSTRACT FROM AUTHOR]

This paper presents a machine learning (ML)-based approach for the intelligent control of Autonomous Vehicles (AVs) utilized in solar panel cleaning systems, aiming to mitigate challenges arising from uncertainties, disturbances, and dynamic environments. Solar panels, predominantly situated in dedicated lands for solar energy production (e.g., agricultural solar farms), are susceptible to dust and debris accumulation, leading to diminished energy absorption. Instead of labor-intensive manual cleaning, robotic cleaners offer a viable solution. AVs equipped to transport and precisely position these cleaning robots are indispensable for the efficient navigation among solar panel arrays. However, environmental obstacles (e.g., rough terrain), variations in solar panel installation (e.g., height disparities, different angles), and uncertainties (e.g., AV and environmental modeling) may degrade the performance of traditional controllers. In this study, a biologically inspired method based on Brain Emotional Learning (BEL) is developed to tackle the aforementioned challenges. The developed controller is implemented numerically using MATLAB-SIMULINK. The paper concludes with a comparative analysis of the AVs' performance using both PID and developed controllers across various scenarios, highlighting the efficacy and advantages of the intelligent control approach for AVs deployed in solar panel cleaning systems within agricultural solar farms. Simulation results demonstrate the superior performance of the ML-based controller, showcasing significant improvements over the PID controller. [ABSTRACT FROM AUTHOR]

This article introduces a novel analytical equation for computing the Nusselt number within the macroporous structures of channel absorbers utilized in high-temperature solar receivers. The equation incorporates heat and mass transfer processes occurring within boundary layers as fluid flows through complex-shaped macroporous absorber channels. The importance of accounting for the length of the thermodynamic boundary layer within channel-type macroporous media when calculating heat transfer coefficients using the Nusselt equation is demonstrated. By incorporating proposed indicators of porosity and flow characteristics, this method significantly enhances the accuracy of heat transfer coefficient calculations for such media. Discrepancies observed in existing calculation relationships and experiments are attributed to the omission of certain proposed values in the Nusselt number for macroporous media. To address this, empirical coefficients for the Nusselt number are derived using statistical methods. The resulting semi-empirical equation is applied to macroporous absorbers in solar receivers. The findings enable more accurate predictions of future absorber characteristics, enhancing their efficiency. The derived equation is successfully validated against numerical data across various geometric structures of absorbers in concentrated solar power plants. [ABSTRACT FROM AUTHOR]

Small islands in Indonesia usually have a million beauty and extraordinary natural wealth. However, the development of remote islands is prolonged due to the limited electricity supply on these islands. This limitation occurs because the island is far from the primary power grid or uses a diesel generator (DG). Using the DG will increase the cost of shipping fuel oil through limited sea transportation. Therefore, this study aims to conduct a feasibility study of a solar power plant to meet the electricity needs of Sebesi Island, South Lampung, Indonesia. The availability of solar Energy and limited battery life are the main challenges in providing solar Energy today. Therefore, this study also considers the uncertainty of resources by using the sensitivity factor. This research uses HOMER software. This study assumes operating reserve peak, operating reserve, solar reserve, and lifetime battery life to account for resource uncertainty. This method is very effective in overcoming operational limitations and problems. The research results show that the optimal peak operating reserve, operating reserve, solar reserve, and lifetime battery are 10%, 10%, 10–30%, and 5 years, respectively. To meet the daily electrical energy needs of 505.1 kWh, the minimum net current cost (NPC) and energy cost (COE) are $1.26 million and 0.346 $/kWh, respectively. Therefore, this research succeeded in finding a scenario that takes into account sensitivity factors that are more economical. Compared with a diesel generator (DG) with a capacity of 100 kW, the NPC and COE values are $1.29 million and 0.397 $/kWh. Meanwhile, in terms of technology, solar power systems produce much more energy than DG. This system has an energy of 583,316 kWh/year, while the DG system can produce an energy of 268,469 kWh/year. As a result, this system can also reduce CO2 emissions by 241,812 kg/year. [ABSTRACT FROM AUTHOR]

Gas conditioning towers (GCTs) or cooling towers have broad industrial applicability, especially in the cement industry. Most cement factories deal with the same problems faced by other factories. However, the solutions to these problems are barely internationally published and have not received much attention, meaning a lot of time and money is spent on researching previous solutions. Iran is among the top ten cement manufacturing countries in the world. Therefore, many of these problems have occurred in Iranian cement factories. The purpose of this paper is to provide a review of studies in this field over the last couple of decades, with a particular focus on advances in Iran. The most important findings in the literature are summarised in order to suggest the best possible solutions for improving the performance and lifetime of GCTs and decreasing common problems such as dust build-up and wet bottom. Numerical methods for modelling different aspects of GCTs are reviewed. The results can be used to reduce water and energy consumption, air pollution and the repair and maintenance costs of cement factories. [ABSTRACT FROM AUTHOR]

We evaluate the conditions and consequences of union strategies in three industrial transitions in California, all driven by its globally influential climate policies: in construction (solar power plants), electricity (nuclear power retirement), and manufacturing (electric vehicles). Building on recent, global frameworks in environmental labor studies, we grow the field's attention towards unions with workers transitioning between 'sunset' industries like fossil energy and 'sunrise' sectors like clean energy. Using original ethnographic and archival data, we analyze the conditions that shaped union strategies in transitions, and how these in turn impacted union power and coalitions. We argue that union strategies embraced climate transitions when they organized leverage to define a shift on their members' terms, independently from employers, often by turning environmental regulation to the advantage of labor and its allies. [ABSTRACT FROM AUTHOR]

This paper discusses Groningen Airport Eelde's (GRQ) transition to sustainable aviation, emphasising its commitment to minimising environmental impact while enhancing regional connectivity. It details GRQ's initiatives, collaborations and future plans, showcasing how the airport leverages its unique position to spearhead the adoption of sustainable technologies, particularly in hydrogen. Through collaboration, innovation and strategic partnerships, GRQ aims to lead the way towards a more sustainable aviation future. GRQ's commitment to minimising environmental impacts aligns with community interests, maintaining local trust and government support. By 2030, GRQ aims for a fully emission-free ground operation. The airport has successfully implemented a 22MW airside solar park and is now pioneering a comprehensive hydrogen ecosystem, aiming to become Europe's first Hydrogen Valley Airport. Despite challenges in funding and legislation, GRQ advises other airports to build consortia, connect with regional partners and prioritise sustainability. [ABSTRACT FROM AUTHOR]

The integration of renewable energy is rapidly leading the existing grid systems toward modern hybrid power systems. These hybrid power systems are more complex due to the random and intermittent nature of RE and involve numerous operational challenges. This paper presents the operational model for solar integrated power systems to address the issues of economical operation, reliable solar share, energy deficit in case of contingency events, and the allocation of system spinning reserve. A mixed-integer optimization is formulated to minimize the overall cost of the system operation and to maximize the solar share under robust system spinning reserve limits as well as various other practical constraints. A Pareto-optimal solution for the maximization of the number of solar power plants and minimization of the solar cost is also presented for reliable solar share. Further, a decomposition framework is proposed to split the original problem into two sub-problems. The solution of joint optimization is obtained by exploiting a Lagrange relaxation method, a binary search Lambda iteration method, system spinning reserve analysis, and binary integer programming. The proposed model was implemented on an IEEE-RTS 26 units system and 40 solar plants. [ABSTRACT FROM AUTHOR]

Despite the global importance of solar energy, its variability requires energy storage to balance production during peak and off-peak periods. Moreover, the transport sector is undergoing a global transition from internal combustion engines to electric vehicles. Since vehicles are idle 95% of the time, electric vehicle batteries, when connected to a grid, can effectively regulate intermittent photovoltaics using vehicle-to-grid technology. This conceptual study investigates the feasibility of a nationwide energy infrastructure that relies solely on solar energy, replacing other electricity sources, such as solid fuels, petroleum products, and natural gas, and utilizes electric vehicles as the sole battery energy storage system. This study aims to demonstrate the significant potential and benefits of such collaboration. The theoretical study combines historical data, assumptions, and conditions to build a simulation model that is modelled similarly as in previous conceptual studies of nationwide energy systems based solely on photovoltaics and electric vehicles, referenced in this article. In Slovenia, the total surface size suitable for the installation of photovoltaic systems is estimated to be 280 km2. The calculations show that a surface size of 217 km2 for photovoltaic systems can produce enough energy to cover Slovenia's entire energy demand, Slovenia's final energy consumption. However, simulations comparing photovoltaic production, total energy consumption (electricity, solid fuels, etc.), and the capacity of electric vehicle batteries show that a surface size of more than 500 km2 with photovoltaic systems and a 200% share of electric vehicles in the Slovenian vehicle fleet in 2022 will provide satisfactory results. Therefore, for a country like Slovenia, in addition to a solar power plant with a surface size of 280 km2, additional renewable energy sources are needed to cover the total energy demand, as well as additional battery energy storage systems in addition to electric vehicles. [ABSTRACT FROM AUTHOR]

Concentrated solar power (CSP) has gained traction for generating electricity at high capacity and meeting base-load energy demands in the energy mix market in a cost-effective manner. The linear Fresnel reflector (LFR) is valued for its cost-effectiveness, reduced capital and operational expenses, and limited land impact compared to alternatives such as the parabolic trough collector (PTC). To this end, the aim of this study is to optimize the operational parameters, such as the solar multiple (SM), thermal energy storage (TES), and fossil fuel (FF) backup system, in LFR power plants using molten salt as a heat transfer fluid (HTF). A 50 MW LFR power plant in Duba, Saudi Arabia, serves as a case study, with a Direct Normal Irradiance (DNI) above 2500 kWh/m2. About 600 SM-TES configurations are analyzed with the aim of minimizing the levelized cost of electricity (LCOE). The analysis shows that a solar-only plant can achieve a low LCOE of 11.92 ¢/kWh with a capacity factor (CF) up to 36%, generating around 131 GWh/y. By utilizing a TES system, the SM of 3.5 and a 15 h duration TES provides the optimum integration by increasing the annual energy generation (AEG) to 337 GWh, lowering the LCOE to 9.24 ¢/kWh, and boosting the CF to 86%. The techno-economic optimization reveals the superiority of the LFR with substantial TES over solar-only systems, exhibiting a 300% increase in annual energy output and a 20% reduction in LCOE. Additionally, employing the FF backup system at 64% of the turbine's rated capacity boosts AEG by 17%, accompanied by a 5% LCOE reduction. However, this enhancement comes with a trade-off, involving burning a substantial amount of natural gas (503,429 MMBtu), leading to greenhouse gas emissions totaling 14,185 tonnes CO₂ eq. This comprehensive analysis is a first-of-a-kind study and provides insights into the optimal designs of LFR power plants and addresses thermal, economic, and environmental considerations of utilizing molten salt with a large TES system as well as employing natural gas backup. The outcomes of the research address a wide audience including academics, operators, and policy makers. [ABSTRACT FROM AUTHOR]

This study aims to assess potential changes in radiation values at the solar power plant facility in Istanbul using the RegCM. This analysis seeks to estimate the extent of the solar radiation changes and evaluate the production capacity of solar power in Istanbul in the future. The research involved installing an off-grid rooftop solar energy system. Meteorological parameters (temperature, etc.) and the system's outputs were monitored to evaluate the energy production and its relationship with these parameters. The performance of the Regional Climate Model version 5.0 (RegCMv5) in accurately representing surface solar radiation and temperature patterns was assessed by comparing it with measured monocrystalline solar panel output data. The impact of different cumulus convection schemes was examined on the sensitivity of the RegCM by analyzing surface solar radiation data over the initial three months. Long-term simulations were conducted with the representational concentration path (RCP) scenarios of 2.6, 4.5, and 8.5 spanning from 2023 to 2050 with convection schemes yielding the best results. All scenarios project a slight decrease in incoming surface radiation. [ABSTRACT FROM AUTHOR]