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As electricity demand increases, especially in transportation, renewable sources such as solar energy become more important. The direct integration of solar energy in rail transportation mostly involves utilizing station roofs and track side spaces. This paper proposes a novel approach by proposing the integration of photovoltaic systems directly on the roofs of trains to generate clean electricity and reduce dependence on the main grid. Installing solar photovoltaic (PV) systems on train rooftops can reduce energy costs and emissions and develop a more sustainable and ecological rail transport system. This research focuses on the Milan Cadorna-Saronno railway line, examining the feasibility of installing PV panels onto train rooftops to generate power for the train's internal consumption, including lighting and air conditioning. In addition, it is a solution to reduce the power absorbed by the train from the main supply. Simulations conducted using PVSOL software 2023 (R7) indicate that equipping a train roof with PV panels could supply up to almost 10% of the train's auxiliary power needs, equating to over 600 MWh annually. Implementing the suggested system may also result in a decrease of more than 27 tons of CO2 emissions per year for one train. To optimize the performance of PV systems and maximize power output, the gravitational search algorithm (GSA) as an evolutionary-based method is proposed alongside a DC/DC boost converter and its performance is compared with two other main maximum power point tracking (MPPT) methods of perturb and observe (PO), and incremental conductance (INC). The accuracy of the suggested algorithm was confirmed utilizing MATLAB SIMULINK R2023b, and the results were compared with those of the PO and INC algorithms. The findings indicate that the GSA performs better in terms of accuracy, while the PO and INC algorithms demonstrate greater robustness and dynamic response. [ABSTRACT FROM AUTHOR]

This paper takes a cursory look at the problem of inadequate power supply in the rural healthcare centres of a developing country, specifically Nigeria, and proffers strategies to address this issue through the design of hybrid renewable energy systems combined with the existing unreliable grid in order to meet the healthcare load demand, thus ensuring higher reliability of available energy sources. The simulations, analysis and results presented in this paper are based on meteorological data and the load profiles of six selected locations in Nigeria, using which hybrid grid-connected systems integrating diesel, solar and wind energy sources are designed with configurations to give optimum output. The optimised design configurations in the considered case study, Ejioku, Okuru-Ama, Damare-Polo, Agbalaenyi, Kadassaka and Doso, produce very low energy costs of of 0.0791 $/kWh, 0.115 $/kWh, 0.0874 $/kWh, 0.0754 $/kWh, 0.0667 $/kWh and 0.0588 $/kWh, respectively, leveraging solar and wind energy sources which make higher percentage contributions at all sites. The load-following-dispatch strategy is adopted at all sites, ensuring that at every point in time, there is sufficient power to meet the needs of the healthcare centres. Further works on this topic could consider other strategies to optimise general energy usage on the demand side. [ABSTRACT FROM AUTHOR]

As offline control photovoltaic (PV) plants are not equipped with online communication and remote control systems, they cannot adjust their power in real-time. Therefore, in a distribution network saturated with offline control PVs, the distribution system operator (DSO) should schedule the distributed energy resources (DERs) considering the uncertainty of renewable energy to prevent curtailment due to overvoltage. This paper presents a day-ahead network operation strategy using a mobile energy storage system (MESS) and offline control PVs to minimize power curtailment. The MESS model efficiently considers the transportation time and power loss of the MESS, and models various operating modes, such as the charging, discharging, idle, and moving modes. The optimization problem is formulated based on mixed-integer linear programming (MILP) considering the spatial and temporal operation constraints of MESSs and is performed using chanced constrained optimal power flow (CC-OPF). The upper limits for offline control PVs are set based on the probabilistic approach, thus mitigating overvoltage due to forecasting errors. The proposed operation strategy was tested in the IEEE 33-node distribution system coupled with a 15-node transportation system. The test results show the effectiveness of the proposed method for minimizing curtailment in offline control PVs. [ABSTRACT FROM AUTHOR]

Rapid industrialization is consuming too much energy, and non-renewable energy resources are currently supplying the world's majority of energy requirements. As a result, the global energy mix is being pushed towards renewable and sustainable energy sources by the world's future energy plan and climate change. Thus, hydrogen has been suggested as a potential energy source for sustainable development. Currently, the production of hydrogen from fossil fuels is dominant in the world and its utilization is increasing daily. As discussed in the paper, a large amount of hydrogen is used in rocket engines, oil refining, ammonia production, and many other processes. This paper also analyzes the environmental impacts of hydrogen utilization in various applications such as iron and steel production, rocket engines, ammonia production, and hydrogenation. It is predicted that all of our fossil fuels will run out soon if we continue to consume them at our current pace of consumption. Hydrogen is only ecologically friendly when it is produced from renewable energy. Therefore, a transition towards hydrogen production from renewable energy resources such as solar, geothermal, and wind is necessary. However, many things need to be achieved before we can transition from a fossil-fuel-driven economy to one based on renewable energy. [ABSTRACT FROM AUTHOR]

Users ought to decide how to operate and manage power systems in order to achieve various goals. As a result, many strategies have been developed to aid in this regard. Optimal power flow management is one such strategy that assists users in properly operating and managing the supply and demand of power in an optimal way under specified constraints. However, in-depth research on optimal power flow management is yet to be explored when it comes to the supply and demand of power for the bulk of standalone renewable energy systems such as solar photovoltaics, especially when it comes to specific applications such as powering military soldier-level portable electronic devices. This paper presents an optimal power flow management modelling and optimisation approach for solar-powered soldier-level portable electronic devices. The OPTI toolbox in MATLAB is used to solve the formulated nonlinear optimal power flow management problem using SCIP as the solver. A globally optimal solution was arrived at in a case study in which the objective function was to minimise the difference between the power supplied to the portable electronic device electronics and the respective portable electronic device power demands. This ensured that the demand for solar-powered soldier-level portable electronic devices is met at all times in spite of the prohibitive case scenarios' circumstances under the given constraints. This resolute approach underscores the importance placed on satisfying the demand needs of the specific devices while navigating and addressing the limitations posed by the existing conditions or constraints. Soldiers and the solar photovoltaic user fraternity at large will benefit from this work as they will be guided on how to optimally manage their power systems' supply and demand scenarios. The model developed herein is applicable to any demand profile and any number of portable electronic device and is adaptable to any geographical location receiving any amount of solar radiation. [ABSTRACT FROM AUTHOR]

The use of renewable energy sources is becoming increasingly widespread around the world due to various factors, the most relevant of which is the high environmental friendliness of these types of energy resources. However, the large-scale involvement of green energy leads to the creation of distributed energy networks that combine several different generation methods, each of which has its own specific features, and as a result, the data collection and processing necessary to optimize the operation of such energy systems become more relevant. Development of new technologies for the more optimal use of RES is one of the main tasks of modern research in the field of energy, where an important place is assigned to the use of technologies based on artificial intelligence, allowing researchers to significantly increase the efficiency of the use of all types of RES within energy systems. This paper proposes to consider the methodology of application of modern approaches to the assessment of the amount of energy obtained from renewable energy sources based on artificial intelligence technologies, approaches used for data processing and for optimization of the control processes for operating energy systems with the integration of renewable energy sources. The relevance of the work lies in the formation of a general approach applied to the evaluation of renewable energy sources such as solar and wind energy based on the use of artificial intelligence technologies. As a verification of the approach considered by the authors, a number of models for predicting the amount of solar power generation using photovoltaic panels have been implemented, for which modern machine-learning methods have been used. As a result of testing for quality and accuracy, the best results were obtained using a hybrid forecasting model, which combines the joint use of a random forest model applied at the stage of the normalization of the input data, exponential smoothing model, and LSTM model. [ABSTRACT FROM AUTHOR]

The modernization, efficiency, and decarbonization of the energy supply systems are among the new challenges to be faced in the coming decades to achieve the targets and objectives dictated by European strategic policies. Despite the countless benefits related to renewable energy sources (RES) integration, this brings key challenges to the power system, such as the risk of imbalance between energy generation and demand, sudden changes in flows in transmission lines with a need for expensive and time-consuming upgrades, and the withdrawal of conventional generation systems with consequent demands for new solutions and innovation to support grid services. A potential solution to limit the huge intermittence and fluctuation in power generation from RES is Concentrated Solar Power (CSP) technology integrated with thermal energy storage. The aim of this paper is to discuss the potential benefits related to the use of CSP technology by presenting innovative industrial solutions developed in the Italian SOLARGRID Project, namely the hybridization of CSP–PV systems and the solar thermo-electric system developed by MAGALDI, the parabolic trough collector of Eni, and the new linear Fresnel reflector configuration of IDEA S.r.l. These plant and component solutions are developed for improving the technical performance of CSP technology and reducing the levelized cost of electricity, thereby fostering an effective and massive deployment and encouraging the creation of new business models. [ABSTRACT FROM AUTHOR]

Solar hydrogen production technology is a key technology for building a clean, low-carbon, safe, and efficient energy system. At present, the intermittency and volatility of renewable energy have caused a lot of "wind and light". By combining renewable energy with electrolytic water technology to produce high-purity hydrogen and oxygen, which can be converted into electricity, the utilization rate of renewable energy can be effectively improved, while helping to improve the solar hydrogen production system. This paper summarizes and analyzes the research status and development direction of solar hydrogen production technology from three aspects. Energy supply mode: the role of solar PV systems and PT systems in this technology is analyzed. System control: the key technology and system structure of different types of electrolytic cells are introduced in detail. System economy: the economy and improvement measures of electrolytic cells are analyzed from the perspectives of cost, consumption, efficiency, and durability. Finally, the development prospects of solar hydrogen production systems in China are summarized and anticipated. This article reviews the current research status of photovoltaic-photothermal coupled electrolysis cell systems, fills the current research gap, and provides theoretical reference for the further development of solar hydrogen production systems. [ABSTRACT FROM AUTHOR]

Hybrid Renewable Energy Sources (HRES) integrated into a microgrid (MG) are a cost-effective and convenient solution to supply energy to off-grid and rural areas in developing countries. This research paper focuses on the optimization of an HRES connected to a stand-alone microgrid system consisting of photovoltaics (PV), wind turbines (WT), batteries (BT), diesel generators (DG), and inverters to meet the energy demand of fifteen residential housing units in the city of Djelfa, Algeria. In this context, the multiobjective salp swarm algorithm (MOSSA), which is among the latest nature-inspired metaheuristic algorithms recently introduced for hybrid microgrid system (HMS) optimization, has been proposed in this paper for solving the optimization of an isolated HRES. The proposed multiobjective optimization problem takes into account the cost of energy (COE) and loss of power supply probability (LPSP) as objective functions. The proposed approach is applied to determine three design variables, which are the nominal power of photovoltaic, the number of wind turbines, and the number of battery autonomy days considering higher reliability and minimum COE. In order to perform the optimum size of HMG, MOSSA is combined with a rule-based energy management strategy (EMS). The role of EMS is the coordination of the energy flow between different system components. The effectiveness of using MOSSA in addressing the optimization issue is investigated by comparing its performance with that of the multiobjective dragonfly algorithm (MODA), multiobjective grasshopper optimization algorithm (MOGOA), and multiobjective ant lion optimizer (MOALO). The MATLAB environment is used to simulate HMS. Simulation results confirm that MOSSA achieves the optimum system size as it contributed 0.255 USD/kW h of COE and LPSP of 27.079% compared to MODA, MOGOA, and MOALO. In addition, the optimization results obtained using the proposed method provided a set of design solutions for the HMS, which will help designers select the optimal solution for the HMS. [ABSTRACT FROM AUTHOR]

The precise prediction of power estimates of wind–solar renewable energy sources becomes challenging due to their intermittent nature and difference in intensity between day and night. Machine-learning algorithms are non-linear mapping functions to approximate any given function from known input–output pairs and can be used for this purpose. This paper presents an artificial neural network (ANN)-based method to predict hybrid wind–solar resources and estimate power generation by correlating wind speed and solar radiation for real-time data. The proposed ANN allows optimization of the hybrid system's operation by efficient wind and solar energy production estimation for a given set of weather conditions. The proposed model uses temperature, humidity, air pressure, solar radiation, optimum angle, and target values of known wind speeds, solar radiation, and optimum angle. A normalization function to narrow the error distribution and an iterative method with the Levenberg–Marquardt training function is used to reduce error. The experimental results show the effectiveness of the proposed approach against the existing wind, solar, or wind–solar estimation methods. It is envisaged that such an intelligent yet simplified method for predicting wind speed, solar radiation, and optimum angle, and designing wind–solar hybrid systems can improve the accuracy and efficiency of renewable energy generation. [ABSTRACT FROM AUTHOR]

In this twenty-first century, energy shortages have become a global issue as energy demand is growing at an astounding rate while the energy supply from fossil fuels is depleting. Thus, the urge to develop sustainable renewable energy to replace fossil fuels is significant to prevent energy shortages. Solar energy is the most promising, accessible, renewable, clean, and sustainable substitute for fossil fuels. Third-generation (3G) emerging solar cell technologies have been popular in the research field as there are many possibilities to be explored. Among the 3G solar cell technologies, perovskite solar cells (PSCs) are the most rapidly developing technology, making them suitable for generating electricity efficiently with low production costs. However, the toxicity of Pb in organic–inorganic metal halide PSCs has inherent shortcomings, which will lead to environmental contamination and public health problems. Therefore, developing a lead-free perovskite solar cell is necessary to ensure human health and a pollution-free environment. This review paper summarized numerous types of Sn-based perovskites with important achievements in experimental-based studies to date. [ABSTRACT FROM AUTHOR]

Renewable energy resources have gained considerable attention in recent years due to their efficiency and economic benefits. Their proportion of total energy use continues to grow over time. Photovoltaic (PV) cell and wind energy generation are the least-expensive new energy sources in most countries. Renewable energy technologies significantly contribute to climate mitigation and provide economic benefits. Apart from these advantages, renewable energy sources, particularly solar energy, have drawbacks, for instance restricted energy supply, reliance on weather conditions, and being affected by several kinds of faults, which cause a high power loss. Usually, the local PV plants are small in size, and it is easy to trace any fault and defect; however, there are many PV cells in the grid-connected PV system where it is difficult to find a fault. Keeping in view the aforedescribed facts, this paper presents an intelligent model to detect faults in the PV panels. The proposed model utilizes the Convolutional Neural Network (CNN), which is trained on historic data. The dataset was preprocessed before being fed to the CNN. The dataset contained different parameters, such as current, voltage, temperature, and irradiance, for five different classes. The simulation results showed that the proposed CNN model achieved a training accuracy of 97.64% and a testing accuracy of 95.20%, which are much better than the previous research performed on this dataset. [ABSTRACT FROM AUTHOR]

The ship's power system is one of the most important systems on board. It is designed for uninterrupted power supply to all ship consumers under different conditions of exploitation. When designing a ship, various optimizations are conducted to build the ship as economically and environmentally friendly as possible. The paper aims to analyze the possibility of applying renewable energy sources (RES), particularly solar and wind energy, on an existing vessel by conducting technical and economic analysis. Data for the solar hour's number and wind distribution are gathered from the six locations in the Adriatic Sea over 32 years period. Firstly, it was investigated if data were position dependent or independent. Performing a Pearson correlation coefficient and an ANOVA analysis with F-test, it was concluded that the RES analysis is position-independent (p > 0.05, p = 0.826). Secondly, the energy system model created in Simulink was used for the analysis of the electrical network fundamental parameters. Finally, the object of the analysis is the total costs of procurement, installation, and maintenance of the system within a period of 25 years. Consequences are savings in the cost of exploitation and reduction of harmful gas emissions. The use of solar energy would result in savings of 111,556 L of diesel fuel, while the savings from wind energy would be 170,274 L of diesel fuel for 25 years. [ABSTRACT FROM AUTHOR]

Renewable energy resource utilisation is becoming more prevalent in society and can be a sustainable method to meet rising energy demand and consumption. The International Renewable Energy Agency reports that presently, approximately 33% of total electricity output around the world is from renewable energy sources. However, in Nigeria, the World Bank reported this figure as 18.2% in 2015. It is important to understand how Nigeria can raise this average as the world moves towards less use of fossil fuels. Therefore, the aim of this work was to provide a review of the established literature, which can then be used to support the development of renewable energy systems in Nigeria. The methodology employed for the study of the literature involved a systematic review method, including identification, screening, eligibility and inclusion criterium steps. Understanding the national energy landscape is essential to support potential projects, and consequently, energy supply, demand and consumption in Nigeria are observed. The review examined renewable energy sources in Nigeria with a focus on solar and biomass/bioenergy. The levelised cost of electricity from renewable technologies was analysed, and the paper identified and evaluated past projects centered on solar and biomass, presenting three main case studies. The results indicate that solar and biomass have the most potential for energy generation in Nigeria, with 4–6.5 kWh/m2 of solar irradiation available per day and approximately 2.3 × 109 GJ bioenergy potential per year. However, solar PV is currently of most interest in Nigeria due to the lower cost of on-grid solar PV electricity, which can comfortably compete with fossil fuels. Nevertheless, costs still need to be lowered to compete fully. Finally, the findings also indicate that there is an omission in the literature surrounding the existing renewable projects and technologies in Nigeria. [ABSTRACT FROM AUTHOR]

Using renewable energy sources instead of fossil fuels is one of the best solutions to overcome greenhouse gas (GHG) emissions. However, in designing clean power generation microgrids, the economic aspects of using renewable energy technologies should be considered. Furthermore, due to the unpredictable nature of renewable energy sources, the reliability of renewable energy microgrids should also be evaluated. Optimized hybrid microgrids based on wind and solar energy can provide cost-effective power generation systems with high reliability. These microgrids can meet the power demands of the consuming units, especially in remote areas. Various techniques have been used to optimize the size of power generation systems based on renewable energy to improve efficiency, maintain reliability, improve the power grid's resilience, and reduce system costs. Each of these techniques has shown its advantages and disadvantages in optimizing the size of hybrid renewable energy systems. To increase the share of renewable energies in electricity supply in the future and develop these new technologies further, this paper reviews the latest and most efficient techniques used to optimize green microgrids from an economical and reliable perspective to achieve a clean, economical, and highly reliable microgrid. [ABSTRACT FROM AUTHOR]

The penetration rates of intermittent renewable energies such as wind and solar energy have been increasing in power grids, often leading to a massive peak-to-valley difference in the net load demand, known as a "duck curve". The power demand and supply should remain balanced in real-time, however, traditional power plants generally cannot output a large range of variable loads to balance the demand and supply, resulting in the overgeneration of solar and wind energy in the grid. Meanwhile, the power generation hours of the plant are forced to be curtailed, leading to a decrease in energy efficiency. Building demand response (DR) is considered as a promising technology for the collaborative control of energy supply and demand. Conventionally, building control approaches usually consider the minimization of total energy consumption as the optimization objective function; relatively few control methods have considered the balance of energy supply and demand under high renewable energy penetration. Thus, this paper proposes an innovative DR control approach that considers the energy flexibility of buildings. First, based on an energy flexibility quantification framework, the energy flexibility capacity of a typical office building is quantified; second, according to energy flexibility and a predictive net load demand curve of the grid, two DR control strategies are designed: rule-based and prediction-based DR control strategies. These two proposed control strategies are validated based on scenarios of heating, ventilation, and air conditioning (HVAC) systems with and without an energy storage tank. The results show that 24–55% of the building's total load can be shifted from the peak load time to the valley load time, and that the duration is over 2 h, owing to the utilization of energy flexibility and the implementation of the proposed DR controls. The findings of this work are beneficial for smoothing the net load demand curve of a grid and improving the ability of a grid to adopt renewable energies. [ABSTRACT FROM AUTHOR]

Despite the increasing utilization of renewable energy resources, such as solar and wind energy, most residential buildings still rely on conventional energy supply by public utility services. Such utility services often use time-of-use energy pricing, which compels residential consumers to reduce their energy usage. This paper presents a wireless home energy management (HEM) system that enables the automatic control of home appliances to reduce energy consumption to assist such energy users. The system consists of multiple smart sockets that measure the energy that is consumed by the connected appliances and are capable of implementing on/off commands. The system includes other support components for supplying data to a central controller, which utilizes a rule-based HEM algorithm. The control rules were designed, such that the lifestyle of the user would be preserved while the energy consumption and daily energy cost were reduced. The experimental results showed that the central controller could effectively receive data and control multiple devices. The system was also found to afford significant reductions of 23.5 kWh and $2.898 in the total daily energy consumption and bill of the considered household setup, respectively. The proposed HEM system promises to be particularly useful for households with a high daily energy consumption. [ABSTRACT FROM AUTHOR]

By considering the weight penalty of batteries on payload and total vehicle weight, this paper shows that almost all forms of land-based transport may be served by battery electric vehicles (BEV) with acceptable cost and driving range. Only long-distance road freight is unsuitable for battery electrification. The paper models the future Indian electricity grid supplied entirely by low-carbon forms of generation to quantify the additional solar PV power required to supply energy for transport. Hydrogen produced by water electrolysis for use as a fuel for road freight provides an inter-seasonal energy store that accommodates variations in renewable energy supply. The advantages and disadvantages are considered of midday electric vehicle charging vs. overnight charging considering the temporal variations in supply of renewable energy and demand for transport services. There appears to be little to choose between these two options in terms of total system costs. The result is an energy scenario for decarbonized surface transport in India, based on renewable energy, that is possible, realistically achievable, and affordable in a time frame of year 2050. [ABSTRACT FROM AUTHOR]

Flexible DC power grids are widely recognized as an important component of building smart grids. Compared with traditional AC power grids, flexible DC power grids have strong technical advantages in islanding power supplies, distributed power supplies, regional power supplies, and AC system interconnection. In multi-terminal flexible DC power grids containing renewable energy sources such as solar and wind power, due to the instability and intermittency of renewable energy, it is usually necessary to add energy storage units to pre-regulate the power of the multi-terminal flexible DC power grid in islanded operation. Aiming at the important problem of large current impact and serious consequences when the flexible DC distribution network fails, a combined location method combining an improved impedance method (series current-limiting reactors at both ends of the line to obtain a more accurate current differential value) and a particle swarm optimization algorithm is proposed. Initially, by establishing the enhanced impedance model, the differential variables under the conditions of inter-electrode short-circuit and single-pole grounding fault can be obtained. Then tailor-made fitness functions are designed for these two models to optimize parameter identification. Subsequently, the iterative parameters of the particle swarm optimization algorithm are fine-tuned, giving it dynamic sociality and self-learning ability in the iterative process, which significantly improves the convergence speed and successfully avoids local optimization. Finally, various fault types in a six-terminal DC distribution network are simulated and analyzed by MATLAB, and the results show that this method has good accuracy and robustness. This research provides strong theoretical and methodological support for improving the safety and reliability of DC distribution systems. [ABSTRACT FROM AUTHOR]

This article reflects on the necessity of employing renewable energy sources in the modern era to mitigate the negative environmental impact caused by traditional energy sources and address environmental pollution. Through research conducted in Azerbaijan and Hungary, it analyses the influence of economic growth on the ecological environment and renewable energy production. Due to limitations in the general dataset, the study considers the period of 1997–2022 for CO2 emissions causing environmental pollution, 2007–2022 for renewable energy production in Azerbaijan, and 2000–2021 for the same in Hungary. Information regarding wind and solar energy in Azerbaijan has been available since 2013. Temporal sequences have been utilised in the research, employing Augmented Dickey–Fuller and Phillips–Perron (PP) unit root tests to examine the stationarity of the time series. An Autoregressive Distributed Lag (ARDL) model has been constructed, and the credibility of the model has been verified using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR) models. The findings reveal that in Azerbaijan, the long-term impact of economic growth on hydro-energy has been negative, while dependence on biomass and waste has been insignificant but positive. The influence on wind and solar energy production has also been negative and insignificant, akin to hydro-energy production. However, energy supply from renewable sources has been positively affected by the aggregate indicator of economic growth, albeit insignificantly. The impact of economic growth on carbon dioxide has been significant in two magnitudes, whereas in other cases, it has been insignificant but positive. In Hungary, economic growth has positively affected renewable energy production. However, the impact on carbon dioxide has been negative, meaning that this indicator has decreased as economic growth has increased. The study concludes that the impact of economic growth on indicators of both countries has been more effective in Hungary, which can be attributed to economic development. [ABSTRACT FROM AUTHOR]

The increase in demand for electricity due to industrial development and the growing use of electronic equipment has led to the need for new alternative energy sources, such as photovoltaic solar energy conversion. In this context, organic photovoltaic (OPV) stands out as an efficient way of generating energy indoors. An electrical power supply system (EPS) was developed to power a commercial electronic lock, using OPV as the energy source. The system was designed with a charging control to match the panel voltage to a supercapacitor charge accumulator and a boost converter. Tests on the bench and in a real scenario demonstrated the viability and effectiveness of the system, showing that it is capable of operating self-sufficiently with a minimum daily illuminance of 250 lux for 12 h. The results indicate that the system can be applied to various loads with low energy consumption, promoting energy efficiency in different contexts. [ABSTRACT FROM AUTHOR]

Federal and state governments in the United States (US) are promoting the transition from traditional Diesel School Buses to Electric School Buses (ESBs). This would prevent the emission of deleterious air pollutants that affect students and communities while simultaneously contributing to a reduction in greenhouse gases, aiding in the fight against climate change. However, due to their significant size and long routes, ESBs require large batteries with significant electricity demand. If this additional electricity demand is supplied to hundreds of thousands of EBSs at peak consumption times, the strain on the grid may be detrimental, while transportation costs for schools could dramatically increase. Furthermore, if EBSs are charged using traditional hydrocarbon generation, the environmental benefits of these projects may be significantly reduced. Therefore, applying renewable energy presents a host of synergistic opportunities to reduce emissions while providing inexpensive electricity to schools. Solar energy is abundant in large portions of the US, potentially providing many schools with ample inexpensive and sustainable electricity to power their transportation equipment and meet other requirements at their facilities. This research developed a novel framework to integrate publicly available big data provided by federal and state agencies in the US, as well as National Laboratories, to provide stakeholders with actionable information to develop EBS grid-to-vehicle (V2G) systems across the US. Geographic Information Systems, data analytics and Business Intelligence were applied to assess and characterize solar energy generation and consumption patterns. The novel integration of the systems in the proposed framework provided encouraging results that have practical implications for stakeholders to develop successful and sustainable ESB V2G facilities. These results identified many schools across the US that would significantly benefit from the use of solar energy and be able to supply their local communities during idle times with renewable energy through V2G. The renewable energy resource would be capable of charging ESBs at a low cost for operational availability as required. The results indicate that the proposed ESB V2G system will provide significant benefits to both schools and their local communities. The feasibility of the proposed endeavor was validated by the results of the study, providing both school and solar energy stakeholders with insights into how to better manage such a complex system. [ABSTRACT FROM AUTHOR]

In addition to zero-carbon generation, the plummeting cost of renewable energy sources (RES) is enabling the increased use of distributed-generation sources. Although the RES appear to be a cheaper source of energy, without the appropriate design of the RES with a true understanding of the nature of the load, they can be an unreliable and expensive source of energy. Limited research has been aimed at designing small-scale hybrid energy systems for irrigation pumping systems, and these studies did not quantify the water requirement, or in turn the energy required to supply the irrigation water. This paper provides a comprehensive feasibility analysis of an off-grid hybrid renewable energy system for the design of a water-pumping system for irrigation applications in Sudan. A systematic and holistic framework combined with a techno-economic optimization analysis for the planning and design of hybrid renewable energy systems for small-scale irrigation water-pumping systems is presented. Different hybridization cases of solar photovoltaic, wind turbine and battery storage at 12 different sites in Sudan are simulated, evaluated, and compared, considering the crop water requirement for different crops, the borehole depth, and the stochasticity of renewable energy resources. Soil, weather, and climatic data from 12 different sites in Sudan were used for the case studies, with the key aim to find the most robust and reliable solution with the lowest system cost. The results of the case studies suggest that the selection of the system is highly dependent on the cost, the volatility of the wind speed, solar radiation, and the size of the system; at present, hybridization is not the primary option at most of sites, with the exception of two. However, with the reduction in price of wind technology, the possibility of hybrid generation will rise. [ABSTRACT FROM AUTHOR]

The global tidal energy resource for electricity generation is small, and converting tidal kinetic energy to electricity is expensive compared to solar-photovoltaic or land-based wind turbine generators. However, as the renewable energy content in electricity supplies grows, the need to stabilise these supplies increases. This paper describes tidal energy's potential to reduce intermittency and variability in electricity supplied from solar and wind power farms while lowering the capital expenditure needed to improve dispatchability. The paper provides a model and hypothetical case studies to demonstrate how sharing energy storage between tidal stream power generators and wind or solar power generators can mitigate the level, frequency, and duration of power loss from wind or solar PV farms. The improvements in dispatchability use tidal energy's innate regularity and take account of tidal asymmetry and extended duration low-velocity neap tides. The case studies are based on a national assessment of Australian tidal energy resources carried out from 2018 to 2021. [ABSTRACT FROM AUTHOR]

As more countries seek solutions to their de-carbonization targets using renewable energy (RE) technologies, interconnection standards and national grid codes for distributed energy resources (DER) are being updated to support higher penetrations of RE and improve grid stability. Common grid-code revisions mandate DER devices, such as solar inverters and energy storage systems, ride-through (RT) voltage and frequency disturbances. This is necessary because as the percentage of generation from DER increases, there is a greater risk power system faults will cause many or all DER to trip, triggering a substantial load-generation imbalance and possible cascading blackout. This paper demonstrates for the first time a methodology to verify commercial DER devices are compliant to new voltage, frequency, and rate of change of frequency (ROCOF) RT requirements established in IEEE Std. 1547-2018. The methodology incorporates a software automation tool, called the SunSpec System Validation Platform (SVP), in combination with a hardware-in-the-loop (HIL) system to execute the IEEE Std. 1547.1-2020 RT test protocols. In this paper, the approach is validated with two commercial photovoltaic inverters, the test results are analyzed for compliance, and improvements to the test procedure are suggested. [ABSTRACT FROM AUTHOR]

Multi-Use Platform (MUP) is a new topic addressed, extensively, under the EU funded projects that aim to exploit oceans in a sustainable way in order to reduce the costs of marine energy and to extract seafood. MUP's electrical grid experiences many challenges, being offshore. One of these challenges is that only Alternating Current (AC) systems are considered which are inefficient, expensive and require bulky components. Considering the advantages of Direct Current (DC) systems, this paper aims to study the feasibility of using the DC system to improve the electrical infrastructure of the MUP's grid. Floating energy unit comprising tidal, wind and solar energy resources is considered as a base unit for the MUP's grid. The paper proposes a new distributed controller for grid voltage regulation and minimizing circulating current among parallel-connected floating energy units in an offshore Low Voltage Direct Current (LVDC) microgrid. A mathematical model is derived for n-parallel floating energy units with the proposed controller. Additionally, stability analysis for the overall model of a single floating energy unit is also presented. The analysis and simulation of the proposed DC system demonstrate that the system is stable and fault-rejected at different operating conditions. [ABSTRACT FROM AUTHOR]

This study investigates the potential for renewable energy-based electricity generation using existing wave, wind, and solar energies in Türkiye. A significant part of Türkiye's energy needs is still met using fossil fuels. Considering the country's resources, renewable energy sources appear as an alternative source to meet these needs. The objective of this study is to find an effective, efficient, economical, environmentally friendly, and sustainable way to produce electricity to reach net-zero targets and transition towards low-carbon and carbon-free energy systems. To be able to make a deep investigation about the relevant issue, six provinces from different regions of Türkiye (Antalya, Çanakkale, İstanbul, İzmir, Kırklareli, and Muğla) are assessed in terms of wave, wind, and solar energy potential, including wave data, wind speeds, sunshine duration, and global radiation values. Wind, wave, and solar energy data of the selected regions were taken from the ERA5 database, which is the weather forecast model of the European Center for Medium-Term Weather Forecasts (ECMWF), and the Ministry of Energy and Natural Resources of the Republic of Türkiye and the General Directorate of Meteorology. Calculations were made using monthly data for the last 5 years. Considering the coastal lengths in the determined regions, the annual total electrical power produced from wave, solar, and wind energies was calculated. In these calculations, the coastal length parameter was assumed to be uniform across all cities, and the electrical power potential from these energy sources was analyzed. Within the framework of these analyses, the number of houses in the selected regions whose electricity needs can be met was calculated. As a result, the potential electrical power and the amount of affordable housing units in the selected regions were compared. As an important result of the studies, it was determined that the characteristic features of the selected regions, such as wavelength, wave height, and wind speed, were directly related to the applicable coast length. The power obtained from wave energy was higher than that from other renewable energy sources, considering the determined coast lengths. Wave energy was followed by parabolic solar collector, wind, and photovoltaic solar energy systems. According to the model, the power obtained from renewable energy systems was at the highest level in the Kırklareli/Demirköy province compared to other locations. Kırklareli was followed by İstanbul, Antalya, İzmir, Muğla, and Çanakkale. It was also found that the electricity needs of 763,578 houses were met in the Kırklareli/Demirköy region, and the electricity needs of 470,590 houses were met in the Çanakkale/Ayvacık region. The statistically optimized factors using the Response Surface Methodology (RSM) for wind, photovoltaic, parabolic solar collector, and wave power were reported as 995.278, 4529.743, 2264.546, and 276,495.09, respectively. The optimal factors aim to achieve a total electricity generation rate of 2.491 × 109 (kWh/year), a total number of houses of 682,590.55 (number/year), and a total cost of USD 813,940,876. In line with the results obtained, the Kırklareli/Demirköy region becomes favorable when considering wave and wave-integrated wind and solar energies. The proposed system has the potential to meet the entire electricity demand of the Kırklareli province based on data from the Republic of Türkiye Energy Market Regulatory Authority (EMRA). [ABSTRACT FROM AUTHOR]

Climate change poses a significant threat to humanity. Achieving net-zero emissions is a key goal in many countries. Among various energy resources, solar power generation is one of the prominent renewable energy sources. Previous studies have demonstrated that post-processing techniques such as bias correction can enhance the accuracy of solar power forecasting based on numerical weather prediction (NWP) models. To improve the post-processing technique, this study proposes a new day-ahead forecasting framework that integrates weather research and forecasting solar (WRF-Solar) irradiances and the total solar power generation measurements for five cities in northern, central, and southern Taiwan. The WRF-Solar irradiances generated by the Taiwan Central Weather Bureau (CWB) were first subjected to bias correction using the decaying average (DA) method. Then, the effectiveness of this correction method was verified, which led to an improvement of 22% in the forecasting capability from the WRF-Solar model. Subsequently, the WRF-Solar irradiances after bias correction using the DA method were utilized as inputs into the transformer model to predict the day-ahead total solar power generation. The experimental results demonstrate that the application of bias-corrected WRF-Solar irradiances enhances the accuracy of day-ahead solar power forecasts by 15% compared with experiments conducted without bias correction. These findings highlight the necessity of correcting numerical weather predictions to improve the accuracy of solar power forecasts. [ABSTRACT FROM AUTHOR]

With the rapidly evolving mobile technologies, the number of cellular base stations (BSs) has significantly increased to meet the explosive demand for mobile services and applications. In turn, this has significantly increased the capital and operational expenses, due to the increased electricity prices and energy consumption. To generate electricity, power plants mainly rely on fossil fuels, which are non-renewable energy resources. As a result, CO 2 emissions also increase, which adversely affect health and environment. For wireless access technologies and cellular networks, BSs are the largest power consumer, and the network energy consumption is mainly dominated by the network infrastructure, which makes the telecommunications sector liable for energy consumption as well as CO 2 emissions around the globe. Alternatively, solar energy is considered as an eco-friendly and economically attractive solution, due to its cost-effectiveness and sustainability. In this paper, the potentials of photovoltaic (PV) solar power to energize cellular BSs in Kuwait are studied, with the focus on the design, implementation, and analysis of off-grid solar PV systems. Specifically, system components, such as the number of PV panels, batteries, and converters needed for the design are determined and evaluated via HOMER software, with the focus on minimizing the net present cost (NPC). A comparison between various PV, diesel generator (DG), and battery bank (BB) system configurations is also performed. Moreover, a comparison of system deployment area will be presented for different PV panels that have different output power and panel sizes, in addition to utilizing a solar tracking system. It is revealed that utilizing a hybrid system configuration (i.e., PV-DG-BB) decreases fuel consumption per year by almost 95% in comparison to the conventional DG-only based electric systems. Not only that, but utilizing a pure off-grid solar PV system (i.e., PV-BB) can significantly reduce the total NPC while completely eliminating CO 2 emissions; however, at the expense of more land. [ABSTRACT FROM AUTHOR]

This manuscript presents a thorough review of unitized regenerative fuel cells (URFCs) and their importance in Remote Area Power Supply (RAPS). In RAPS systems that utilize solar and hydrogen power, which typically include photovoltaic modules, a proton exchange membrane (PEM) electrolyzer, hydrogen gas storage, and PEM fuel cells, the cost of these systems is currently higher compared to conventional RAPS systems that employ diesel generators or batteries. URFCs offer a potential solution to reduce the expenses of solar hydrogen renewable energy systems in RAPS by combining the functionalities of the electrolyzer and fuel cell into a single unit, thereby eliminating the need to purchase separate and costly electrolyzer and fuel cell units. URFCs are particularly well-suited for RAPS applications because the electrolyzer and fuel cell do not need to operate simultaneously. In electrolyzer mode, URFCs function similarly to stand-alone electrolyzers. However, in fuel cell mode, the performance of URFCs is inferior to that of stand-alone fuel cells. The presented review summarizes the past, present, and future of URFCs with details on the operating modes of URFCs, limitations and technical challenges, and applications. Solar hydrogen renewable energy applications in RAPS and challenges facing solar hydrogen renewable energy in the RAPS is discussed in detail. [ABSTRACT FROM AUTHOR]

The World Energy Council, in its 2019 World Energy Scenarios Report, advised policymakers to identify innovative opportunities for the integration of renewable energy resources into existing electrical power systems to achieve a fast and affordable solution. However, large-scale industries with cogeneration units are facing problems in handling the higher penetration levels of intermittent renewable energies. This paper addresses large-size photovoltaic power integration problems and their optimal operation. This work considers the case of a chemical industry having both cogeneration power and solar photovoltaics. Here, a modified firefly algorithm and a hybrid power resource optimization solver are proposed. The results of the proposed method are compared with other benchmark techniques, to confirm its advantages. The proposed techniques can be used in industries having cogeneration power plants with photovoltaics for better optimization and to meet the guidelines specified in IEEE 1547. The voltage ramp index is proposed to determine the voltage ramp up and down with intermittent solar irradiance. Additionally, a machine learning technique is used to predict the cogeneration plant efficiency at different loads and the solar irradiance under varying weather conditions. Finally, this paper proposes the effectiveness of the modified heuristic technique and certain guidelines, including solvers for industrial use. [ABSTRACT FROM AUTHOR]

This paper presents a trustworthy unit commitment study to schedule both Renewable Energy Resources (RERs) with conventional power plants to potentially decarbonize the electrical network. The study has employed a system with three IEEE thermal (coal-fired) power plants as dispatchable distributed generators, one wind plant, one solar plant as stochastic distributed generators, and Plug-in Electric Vehicles (PEVs) which can work either loads or generators based on their charging schedule. This paper investigates the unit commitment scheduling objective to minimize the Combined Economic Emission Dispatch (CEED). To reduce combined emission costs, integrating more renewable energy resources (RER) and PEVs, there is an essential need to decarbonize the existing system. Decarbonizing the system means reducing the percentage of CO2 emissions. The uncertain behavior of wind and solar energies causes imbalance penalty costs. PEVs are proposed to overcome the intermittent nature of wind and solar energies. It is important to optimally integrate and schedule stochastic resources including the wind and solar energies, and PEVs charge and discharge processes with dispatched resources; the three IEEE thermal (coal-fired) power plants. The Water Cycle Optimization Algorithm (WCOA) is an efficient and intelligent meta-heuristic technique employed to solve the economically emission dispatch problem for both scheduling dispatchable and stochastic resources. The goal of this study is to obtain the solution for unit commitment to minimize the combined cost function including CO2 emission costs applying the Water Cycle Optimization Algorithm (WCOA). To validate the WCOA technique, the results are compared with the results obtained from applying the Dynamic Programming (DP) algorithm, which is considered as a conventional numerical technique, and with the Genetic Algorithm (GA) as a meta-heuristic technique. [ABSTRACT FROM AUTHOR]

Among developing countries in Asia, Indonesia has realized the importance of transitioning from fossil fuels to renewable energy sources such as solar power. Careful consideration must be given to the strategic placement of solar power installations to fully leverage the benefits of solar energy. This study proposes a methodology to optimize the site selection of solar power plants in Indonesia by integrating Data Envelopment Analysis (DEA), Fuzzy Analytic Hierarchy Process (F-AHP), and Fuzzy Measurement of Alternatives and Ranking according to Compromise Solution (F-MARCOS) models. The proposed methodology considers quantitative and qualitative criteria to evaluate potential locations for solar power plants. In the first stage, DEA is used to identify the most efficient locations based on quantitative measures such as solar radiation, land availability, and grid connectivity. In the second stage, qualitative factors such as technological, economic, environmental, and socio-political aspects are evaluated using F-AHP to prioritize the most important criteria for site selection. Finally, F-MARCOS ranks potential locations based on the selected criteria. The methodology was tested using data from Indonesia as a case study. The results show that the proposed hybrid model optimizes Indonesia's solar power plant site selection. The optimal locations can contribute to a cost-effective long-term renewable energy supply nationwide. The findings from this study are relevant to policymakers, industry stakeholders, and researchers interested in renewable energy development and site selection. However, to promote sustainable solar energy development, governments and local authorities must also enact supportive policies and mechanisms that encourage the adoption and growth of renewable energy technologies in Indonesia. [ABSTRACT FROM AUTHOR]

Solar photovoltaic systems will play a key role in the country's energy mix thanks to their ability to meet increasing energy needs while reducing greenhouse gas emissions. Despite the potential of solar photovoltaic energy, several criticalities remain, such as the intermittent nature and the need for significant land use for its implementation. In this regard, this work aimed at evaluating the photovoltaic potentiality in a national context by 2030 and 2050, considering only installations on the roof surfaces of existing buildings, i.e., without consuming additional land. This study has allowed the answering of three key points: (i) the roof surface could represent a valuable and alternative solution for new installations, since it could amount to around 450 km2, (ii) the national target cannot be reached by only using installations on existing buildings, although some regions could get close to the target by 2050, and (iii) long-term energy incentives should be implemented branching out to each national region, considering their photovoltaic potential. Finally, a regional potential index was also defined, capable of evaluating the photovoltaic potential in each region, helping policymakers to adopt the most suitable energy strategies. [ABSTRACT FROM AUTHOR]

Energy consumption is increasing rapidly; hence, the energy demand cannot be fulfilled using traditional power resources only. Power systems based on renewable energy, including solar and wind, are effective and friendly for the environment. Islanded hybrid microgrid systems (IHMS) are relatively new in this industry and combine two or more sustainable sources, such as wind turbines, solar photovoltaic (PV), and other renewable alternatives, ocean, wave, and geothermal energy, etc. While sustainable, long-lasting power sources are the best choice to satisfy the growing energy demands, they are still not yet ready to be used on a large scale due to their stochastic characteristics. Furthermore, integrating these sources into the existing energy system can cause high technical difficulties, due to the stochastic nature of solar and wind in the conventional grid system and common stand-alone framework. A review of research and applications of the effective hybridization of renewable energy sources is therefore essential to address those technical and economic issues and ensure system stability, reliability, and cost-effectiveness. This article discusses the challenges that might arise when a PV plant and a wind power station are combined to produce power for the conventional main grid or in a stand-alone system. In addition, this analysis provides light on optimization approaches for improving power quality and cost-effectiveness in a solar and wind integrated IHMS. Voltage fluctuation, frequency deviation, and the uncertain nature of solar irradiation and wind sources are significant challenges for both grid-connected and standalone hybrid systems. This study then provides an overview of the control strategies which might help enhance the integration of the IHMS in producing electricity for distribution to the grid-connected load and the islanded load. In this study, the possible issues that can hinder the smooth integration of these renewable sources have been discussed. Finally, this study discusses the recent platforms being used in IHMS as well as the potential of dispatch strategies on solar and wind-integrated IHMS. [ABSTRACT FROM AUTHOR]

Europe is currently facing the potentially biggest energy crisis in history. There are many reasons for this, and the current geopolitical situation makes it clear that we are being forced to take immediate action to ensure sufficient energy supplies to consumers. Until recently, the European Union was dependent on Russian energy resources (mainly oil and gas). For many years, the EU countries had been shutting down their own production and importing much cheaper raw material from Russia. The threat of a blackout is becoming increasingly possible. European governments are preparing businesses and households for the energy crisis in various ways, but there is also a great deal of mobilization to accelerate the development of renewable energy sources (RES). The aim of this study was to identify the barriers and prospects for RES development in Poland in the current geopolitical conditions. The reasons for insufficient grid HC were analyzed. Additionally, the article aimed to assess the prospects for solar energy development in Poland. Wind power was discussed only in general terms because the development of wind farms is inhibited by the regulatory framework. Particular attention was paid to hosting capacity (HC) and the condition of the power infrastructure as the main determinants of RES development in Poland. Numerous documents developed by power companies and government agencies responsible for implementing and managing energy in Poland were analyzed. Special attention was paid to legal regulations and the need for legislative changes. As a country, Poland has one of the highest growth rates in photovoltaic (PV) installations. The forecasts for increasing HC, as a prerequisite for RES development in Poland, are not promising. [ABSTRACT FROM AUTHOR]

Bangladesh is blessed with abundant solar resources. Solar power is considered the most desirable energy source to mitigate the high energy demand of this densely populated country. Although various articles deal with solar energy applications in Bangladesh, no detailed review can be found in the literature. Therefore, in this study, we report on the current scenario of renewable energy in Bangladesh and the most significant potential of solar energy's contribution among multiple renewable energy resources in mitigating energy demand. One main objective of this analysis was to outline the overall view of solar energy applications in Bangladesh to date, as well as the ongoing development of such projects. The technical and theoretical solar energy potential and the technologies available to harvest solar energy were also investigated. A detailed techno-economic design of solar power applications for the garment industry was also simulated to determine the potential of solar energy for this specific scenario. Additionally, renewable energy policies applied in Bangladesh to date are discussed comprehensively, with an emphasis on various ongoing projects undertaken by the government. Moreover, we elaborate global insight into solar power applications and compare Bangladesh's current solar power scenario with that of other regions worldwide. Furthermore, the potential of artificial intelligence to accelerate solar energy enhancement is delineated comprehensively. Therefore, in this study, we determined the national scenarios of solar power implementation in Bangladesh and projected the most promising approaches for large-scale solar energy applications using artificial intelligence approaches. [ABSTRACT FROM AUTHOR]

Low-voltage (LV) and high-voltage (HV) DC distribution systems are being investigated as alternatives due to the growth of DC distribution energy resources (DER), DC loads such as solar and wind power systems, and energy storage sources (ESSs). Furthermore, an HV/LV DC distribution system offers various advantages, including lower conversion losses, an easier connecting strategy for DC DERs, and less complex power management techniques. As renewable energy sources are increasingly incorporated into the electrical grid, it is important to create novel, effective approaches for connecting such sources and loads. It would hence be effective to merge DC distribution with AC distribution to fulfill the energy demands of both DC and AC consumers. To this end, this study proposes a multizone design with four buses: low-voltage direct current (LVDC), high-voltage direct current (HVDC), low-voltage alternating current (LVAC), and an electrical grid. A model of this system that covers crucial elements, including power systems, DER systems, and power electronic devices, to serve as a foundation for the analysis and design of this architecture is proposed. MATLAB/Simulink is used to conduct a simulation study to verify the performance of the proposed design. In this study, a hybrid electrical grid with an LVDC, HVDC, and LVAC distribution network test is used and implemented. Additionally, a transient and steady-state characteristic analysis of the test system is performed. [ABSTRACT FROM AUTHOR]

Research and innovation in renewable energy, such as wind and solar, have been supporting the green transformation of energy systems, the backbone of a low-carbon climate-resilient society. The major challenge is to manage the complexity of the grid transformation to allow for higher shares of highly variable renewables while securing the safety of the stability of the grid and a stable energy supply. A great help comes from the ongoing digital transformation where digitisation of infrastructures and assets in research and industry generates multi-dimensional and multi-disciplinary digital data. However, a data user needs help to find the correct data to exploit. This has two significant facets: first, missing data management, i.e., datasets are neither findable because of missing community standard metadata and taxonomies, nor interoperable, i.e., missing standards for data formats; second, data owners having a negative perception of sharing data. To make data ready for data science exploitation, one of the necessary steps to map the existing data and their availability to facilitate their access is to create a taxonomy for the field's topics. For this, a group of experts in different renewable technologies such as photovoltaics, wind and concentrated solar power and in transversal fields such as life cycle assessment and the EU taxonomy for sustainable activities have been gathered to propose a coherent and detailed taxonomy for renewable energy-related data. The result is a coherent classification of relevant data sources, considering both the general aspects applicable to electricity generation from selected renewable energy technologies and the specific aspects of each of them. It is based on previous relevant work and can be easily extended to other renewable resources not considered in this work and conventional energy technology. [ABSTRACT FROM AUTHOR]

Renewable energy supply is essential for carbon neutrality; however, technologies aiming to optimally utilize renewable energy sources remain insufficient. Seasonal variability in renewable energy is a key issue, which many studies have attempted to overcome through operating systems and energy storage. Currently, hydrogen is the only technology that can solve this seasonal storage problem. In this study, the amount of hydrogen required to circumvent the seasonal variability in renewable energy supply in Korea was quantified. Spatiotemporal analysis was conducted using renewable energy resource maps and power loads. It was predicted that 50% of the total power demand in the future will be met using solar and wind power, and a scenario was established based on the solar-to-wind ratio. It was found that the required hydrogen production differed by approximately four-times, depending on the scenarios, highlighting the importance of supplying renewable energy at an appropriate ratio. Spatially, wind power was observed to be unsuitable for the physical transport of hydrogen because it has a high potential at mountain peaks and islands. The results of this study are expected to aid future hydrogen research and solve renewable energy variability problems. [ABSTRACT FROM AUTHOR]

Tracking the trend of restricted access to natural fossil energy resources determines the need to search for alternative energy sources, introducing energy-efficient technologies, and optimizing the energy supply system based on intelligent networks. Understanding district heating enterprises' readiness to work with innovative renewable resources based on climate neutrality plays a unique role. Thus, this article is devoted to the study of the features of providing and determining the district heating enterprises' capacity to integrate climate management of innovative resources to produce green thermal energy. The research methodology is based on a combination of systemic, process and cybernetic approaches to determining the resource sustainability of district heating enterprises for implementing climate innovations. The scientific novelty of the study lies in a comprehensive assessment of the ability of district heating enterprises to use renewable resources (biomass, waste, hydropower, solar energy, wind energy) for the production of thermal energy according to such indicators as: an indicator of balanced resource use, an indicator of climate neutrality and an indicator of economic feasibility. The results became the basis to apply the set-theoretical approach to calculate the district heating enterprises' coefficient of resource sustainability, based on the climate management of innovative resources to produce green thermal energy. The innovation of the fuzzy sets method lies in achieving the set goal without the deep formation of a data dynamics series, particularly interval models. The added scientific value of the method to determine the resource sustainability of district heating enterprises is used to justify the feasibility of integrating climate management with the use of innovative resources through the diversification of renewable energy sources for thermal energy production. The prospects for such results are the basis for future research to develop intersectoral clustering enterprises in the green energy production chain based on a closed cycle of renewable energy resources. [ABSTRACT FROM AUTHOR]

Under the European Union (EU) energy efficiency targets that Romania has assumed, increasing the share of solar energy has been one of the main points to be considered. The most important solar energy resources are found in the lowlands and low hills in southern and south-eastern parts of the country. The current paper is focused on the Romanian Plain, which has the best environmental conditions to support the development of photovoltaic (PV) farms. One hundred and ten PV farms have been identified and mapped which cover a total area of 1393 hectares. Although it provides a clean and sustainable energy source, the related environmental implications of PV farms could be either positive or negative. In this study, some of the main categories of impacts have been selected for identification and analysis of their environmental consequences. Several indicators have been computed: the share of PV farms from the main land use/cover categories and main soil types, and the distance of PV farms to forests, water bodies, or protected areas. The overall results of the study reveal the current and potential impacts of PV farms in order to understand the interactions between the environment and the use of renewable energy sources and further support science-based solutions for sustainable development. [ABSTRACT FROM AUTHOR]

Small hydropower (SHP) and pumped hydropower storage (PHS) are ideal members of power systems with regard to integrating intermittent power production from wind and PV facilities in modern power systems using the high penetration of renewable energy. Due to the limited capacity of SHP and the geographic restrictions of PHS, these power sources have not been adequately utilized in multi-energy integration. On the one hand, rapidly increasing wind/PV power is mostly situated in remote areas (i.e., mountain and rural areas) and is delivered to core areas (i.e., manufacturing bases and cities) for environmental protection and economic profit. On the other hand, SHP is commonly dispersed in remote areas and PHS is usually located in core areas. This paper proposes a strategy to take advantage of the distribution and regulation features of these renewable energy sources by presenting two models, which includes a remote power system model to explore the potential of SHP to smooth the short-term fluctuations in wind and PV power by minimizing output fluctuations as well as a core power system model to employ PHS to shift the surplus power to the peak period by maximizing the income from selling regenerated power and minimizing output fluctuations. In the proposed first model, the cooperative regulation not only dispatches SHP with a reciprocal output shape to the wind/PV output to smooth the fluctuations but also operates the reservoir with the scheduled total power production by adjusting its output in parallel. The results of a case study based on a municipal power system in Southwestern China show that, with the proposed method, SHP can successfully smooth the short-term fluctuations in wind and PV power without influencing the daily total power production. Additionally, SHP can replace the thermal power production with renewable power production, smooth the thermal output, and further reduce the operation costs of thermal power. By storing the surplus power in the upper reservoir and regenerating the power during the peak period, PHS can obtain not only the economic benefit of selling the power at high prices but also the environmental benefit of replacing non-renewable power with renewable power. This study provides a feasible approach to explore the potential of SHP and PHS in multi-energy integration applications. [ABSTRACT FROM AUTHOR]

Among the renewable energy resources, solar thermal is one of the technologies that significantly contribute to energy supply and reduce global greenhouse gas (GHG) emissions. Solar water heating (SWH) contributes a large proportion of the global solar thermal capacity, with 63% installation for domestic hot water (DHW) systems, 28% for large DHW systems, and the remaining 9% for other applications such as swimming pools heating, solar district heating, and space heating. Still, now, there are many challenges and limitations of those SWH technologies. The present work reviews the current challenges faced in the domestic SWH industry globally. The integration of thermal energy storage (TES) systems for better collector's radiation absorption and overall performance are also highlighted. Many countries worldwide seem to face similar challenges within the SWH technologies and industry. It is proven that these challenges and limitations can hinder the global capacity of solar thermal utilization. [ABSTRACT FROM AUTHOR]

Under the conditions of climate change and energy crisis stemming from the COVID-19 pandemic and the embargo on the supply of raw materials from Russia, high hopes are attached to the development of renewable energy in terms of meeting energy needs. Still, renewable energy has some drawbacks too. In the most dynamically growing solar and wind energy industries, the main problems that are indicated include this energy storage and ensuring the security of supplies. These are supposed to be solved by the digital transformation of renewable power generation plus the entry of market players that implement digital business models in renewable energy. The purpose of the article is to identify a framework "digital compass" of business models in renewable energy within a group of solar and wind energy start-ups, operating in energy storage and supply industries. At the base of this study there were: digital technologies, customer orientation, delivery of value and revenue stream. The research algorithm applied here enabled the identification and classification of startup business models based on secondary data using R software. The results show that the identified startups implement digital business models to a minor extent. Startups dealing with solar energy storage stand out in a quite positive manner. The low digital attractiveness of investing in wind energy storage and supply (which, to a smaller extent applies to solar energy), is also indicated the investment preferences of big-tech. Thus, the future of the digital transformation of these industries should be related to regulatory changes rather than technological ones. [ABSTRACT FROM AUTHOR]

In recent years, environmental and energy issues relating to global warming have become more serious, and there is a need to shift from conventional power generation, which emits an abundance of carbon dioxide, to renewable energy sources without emissions, such as solar and wind. However, solar power generation, which is one of the renewable energies, changes dynamically, depending on real time weather conditions. Thus, power supplied mainly by solar power generation is often unstable, and an appropriate on-demand energy management for demand-to-supply is required to ensure a stable power supply. Demand-to-supply management methods include inventory management analysis and on-demand inventory management analysis. The cumulative-control method has been used as one of the production management methods to visually manage inventory status in factories and warehouses, while the on-demand cumulative-control method is an extension of inventory management analysis. This study models a demand-to-supply management method for a solar power generation system by using the on-demand cumulative-control method in an actual case. First, a demand-to-supply management method is modeled by an on-demand cumulative-control method, using actual power data from a childcare facility in Tokyo. Next, the on-demand cumulative-control method is adopted to the case without batteries, and the amount of electricity to be purchased is estimated. Finally, the effectiveness of the maximum battery capacity and the amount of the initial charge are examined and discussed by sensitivity analysis. [ABSTRACT FROM AUTHOR]

Featured Application: Renewable energy microgrid for a cluster of buildings that avoids the duck curve effects. The reduction of CO2 emissions and the avoidance of Global Climate Change necessitate the conversion of the electricity generation industry to rely on non-carbon sources. Additionally, the mitigation of the duck-curve effects in microgrids requires the development of grid-independent buildings. Computations were performed for a cluster of one thousand grid-independent buildings in the North Texas area, where air-conditioning demand is high in the summer months. The electricity demand is balanced with energy supply generated from wind turbines, photovoltaic cells, or stored energy in hydrogen tanks. The results indicate that with one wind turbine operating, each building must be fitted with 10.2 kW rating photovoltaics capacity and a tank with 5.2 m3 of hydrogen storage capacity to satisfy the hourly demand of the buildings' community. The addition of more wind turbines significantly reduces the needed PV rating but increases the required storage. Investing in energy conservation measures in the buildings significantly reduces both the needed storage capacity and the PV cell ratings. [ABSTRACT FROM AUTHOR]

This study assessed suitable smart grid areas for power generation and distribution from solar and small hydro energy resources in Western Uganda by employing the fuzzy analytic hierarchy process (AHP) based on geographic information system (GIS) data. This was performed based on the selected economic, environmental, and technical criteria by the authors guided by the experts' judgements in the weighing process. The main criteria also included various sub-criteria. The sub-criteria of the economic criterion included distance from transmission lines, topography, and distance to roads. The environmental sub-criteria covered land use, sensitive areas, and protected areas. The technical sub-criteria were on distance from demand centers, available potential energy resources (solar and hydro), and climate (rainfall and sunshine). The weights of the main criteria and the sub-criteria were calculated by using the fuzzy AHP. These weights were then used in the GIS environment to determine both the potential for power generation from the solar energy resource and the smart grid suitable areas. According to the weight results, the economic criteria has the highest weight, followed by environmental and technical criteria. The validation of the experts' judgements for each criterion by comparing the results from fuzzy AHP with AHP confirmed insignificant differences in weights for all criteria. The obtained suitable smart grid areas in Western Uganda have been classified into three parts, that is, the South, North, and Central. Therefore, this is a one-of-a-kind study that, in the authors' view, will provide the initial insights to the government, policymakers, renewable energy practitioners, and researchers to investigate, map, and embrace decarbonization strategies for the electricity sector of Uganda. [ABSTRACT FROM AUTHOR]

Energy demand is steadily growing as society becomes more industrialised. Renewable energy sources (RES) have long been used for various applications by thermal energy systems in the European Union (EU). Biomass and solar energy represent important RES in the development of energy transition in some regions such as coal-mining areas of Europe. Bioenergy is a key renewable energy storage mechanism for solar energy which, when combined, can tackle many of the barriers to the use of solar energy. Against this background, this study evaluates the potential implementation of both biomass and solar energy for energy production in coal-mining areas in Spain as a direct alternative to coal. The shown methodology relies on a comprehensive analysis of existing resources and their conversion to thermal energy from a multi-parametric point of view. The obtained results show that the solar–biomass combination can be used for thermal energy systems as a challenging option. The theoretical total hybrid-modular systems if implemented in the study area are equivalent to 1165 MWth and supply thermal energy for 170,000 single-family houses. [ABSTRACT FROM AUTHOR]

Recently, the resources of renewable energy have been in intensive use due to their environmental and technical merits. The identification of unknown parameters in photovoltaic (PV) models is one of the main issues in simulation and modeling of renewable energy sources. Due to the random behavior of weather, the change in output current from a PV model is nonlinear. In this regard, a new optimization algorithm called Runge–Kutta optimizer (RUN) is applied for estimating the parameters of three PV models. The RUN algorithm is applied for the R.T.C France solar cell, as a case study. Moreover, the root mean square error (RMSE) between the calculated and measured current is used as the objective function for identifying solar cell parameters. The proposed RUN algorithm is superior compared with the Hunger Games Search (HGS) algorithm, the Chameleon Swarm Algorithm (CSA), the Tunicate Swarm Algorithm (TSA), Harris Hawk's Optimization (HHO), the Sine–Cosine Algorithm (SCA) and the Grey Wolf Optimization (GWO) algorithm. Three solar cell models—single diode, double diode and triple diode solar cell models (SDSCM, DDSCM and TDSCM)—are applied to check the performance of the RUN algorithm to extract the parameters. the best RMSE from the RUN algorithm is 0.00098624, 0.00098717 and 0.000989133 for SDSCM, DDSCM and TDSCM, respectively. [ABSTRACT FROM AUTHOR]