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Asia, the world's highest emitting region with surging electricity demand, must transition to clean energy sources for sustainable development. Despite significant progress in solar power deployment, its penetration in the electricity mix remains relatively low. This study employs process tracing to compare solar power development in China and Thailand from 2000 to 2023, representing state-driven and society-centered governance approaches. By analyzing data from secondary sources and conducting online stakeholder interviews, we assess the role of energy governance in fostering resilience during the low-carbon transition. We find state-driven governance exhibits resilience in addressing immediate crises, while society-centered governance drives societal transformation towards a low-carbon future. While state-centric governance suits large-scale centralized renewables, society-centered governance is crucial for distributed renewable projects. Path-dependent governance determines how the energy sector takes in niche innovation, and the reinforced governance structure constrains energy resilience given the interaction within and of the sector with other societal actors. The findings provide insights to inform evidence-based policies and interventions for renewable deployment.

Photovoltaic-powered drip irrigation is a vital approach to address the irrigation requirements in regions with limited water resources and energy deficiencies, thereby ensuring the provision of sustenance and horticultural produce for local inhabitants. However, the susceptibility of the drip irrigation system to clogging as well as the fluctuations in photovoltaic output can significantly impact irrigation quality. Moreover, conventional storage methods commonly employed in photovoltaic-powered drip irrigation systems, such as elevated water tanks and batteries, exhibit notable technological, economic, and environmental limitations. The present study introduces a novel photovoltaic drip irrigation technology (CAES-PVDI) that utilizes solar energy as the exclusive source of power, enabling stable and cost-effective high-quality drip irrigation. This technology actively regulates solar energy through compressed air energy storage, employing a cyclic pulse discharge method to ensure uniformity in irrigation outflow and significantly enhance the anti-clogging performance of the drip irrigation system. The proposed technology was implemented in a solar greenhouse for drip irrigation, and subsequent tests were conducted to assess its hydraulic performance and anti-clogging properties The results demonstrated that the system achieved a discharge uniformity of no less than 91.76 %. Furthermore, there was no blocked emitter in CAES-PVDI system, and the sedimentation inside the capillary tube decreased by 78.95 %-93.36 % compared to traditional drip irrigation system. In comparison to existing photovoltaic-powered drip irrigation technology, the CAES-PVDI system exhibited exceptional technical indicators and offered significant economic and environmental benefits, thereby presenting a novel approach to promote environmentally friendly and efficient operation of drip irrigation systems.

Summary: Transitioning to renewable energy is crucial for meeting net-zero targets to tackle the climate crisis. Although wind and solar are the main generation methods being pursued, they risk exacerbating future land-use challenges. Here, we explore the UK’s land capacity to accommodate two levels of increased future onshore wind and solar energy capacity. We quantify the impact on breeding bird habitat, food production, and net greenhouse gas flux in the presence and absence of a range of nature-based climate change mitigation measures. We find that even the highest onshore renewable energy ambitions require only a small fraction of the suitable land area, with little cost to food production, greenhouse gas sequestration, or breeding birds, even under pessimistic modeling assumptions. Therefore, the UK could boost onshore renewables without contributing substantially to future land competition, especially if potential synergies between multiple land uses, such as cropping and solar, are realized. Science for society: A transition to renewable energy can help mitigate global climate change. However, the widespread deployment of wind and solar technologies raises concerns about their impacts, from visual amenity to food production. Further, the renewable transition alone is insufficient to reach net-zero greenhouse gas emissions. We need active removal of greenhouse gases from the atmosphere as well as emissions reductions. Such removals can be enabled by nature-based solutions, such as habitat creation and restoration, which concurrently help biodiversity. In a UK case study, we show that ambitious renewable deployment targets require little land, in addition to what is needed for nature-based solutions, and can avoid the most productive farmland to minimize the impact on food production. Even in such a densely populated country with many competing land-use interests, integrated land-use decisions could help to simultaneously achieve net-zero targets, nature recovery, and maintenance of food production.

Technology for “wireless power transfer” (WPT) has advanced greatly in recent years, especially when used for renewable power sources. Environmental issues and the growing need for renewable energy sources have prompted a great deal of study in this area. This report provided an overview of the evolution of WPT technologies for renewable energy systems, including their advantages, disadvantages, and future possibilities. An introduction to WTP’s foundational ideas is provided, including techniques such as resonant pairing, capacitive connection, and microwave-based approaches. It delves into how these systems have been modified and improved to facilitate the long-distance transmission of renewable energy sources like wind and solar power. The study emphasizes the benefits of WPT in renewable energy systems, such as improved convenience, lower maintenance costs, and the opportunity to lessen negative effects on the environment. Problems with WPT technology in renewable energy applications are also analyzed critically. Power loss in transmission, misalignment, and electromagnetic interference are all examples of technical difficulties, and these are on top of the financial and legal obstacles. WPT’s effects on humans and animals are also explored since they must be taken into account before broad use of the technology.

Photo-galvanic cells are liquid electrolyte-based dye-sensitized solar cells. Chemically, the dye/pigment photo-sensitizer, reductant, surfactant, and alkali materials are the main fabrication components of these cells. Most dye/pigment materials are more soluble and stable at high pH. The pH of Potassium hydroxide (an alkali of plant nutrient ‘potassium’ element) is very high. Therefore, Potassium hydroxide is supposed to be the best eco-friendly and effective alkali medium for photogalvanics. As far as alkali is concerned, NaOH has been exploited extensively in photo-galvanics. Although, the NaOH-based photo-galvanics show good electrical output, it is plagued with some drawbacks like shorter shelf life, high cost, unsafe for skin, low conductivity, low water solubility, etc. Therefore, in the present research, the KOH has been exploited as an alkali material for harvesting solar energy using the Sunset Yellow FCF dye sensitizer-Ascorbic acid reductant-CTAB surfactant cylindrical cell designed photo-galvanic system.In the present study, the observed optimum cell performance is as follows-open-circuit potential 777 mV, maximum current 25000 μA, short-circuit current 5600 μA, power 733.6 μW, fill factor 0.16, and efficiency is 19.77 % at pH 14.30. The Sunset Yellow FCF dye shows very high photostability and photo-absorption with KOH alkali. The power storage capacity is sufficiently robust, as the cell is capable of supplying power at its ∼36.16 % capacity after a very long time of 24 h. The KOH-Sunset Yellow FCF dye sensitizer-Ascorbic acid reductant-CTAB surfactant photo-galvanics in the present study show improved results over the reported results for the NaOH-Sunset Yellow FCF dye sensitizer-Ascorbic acid reductant-CTAB surfactant photo-galvanics. The reasons for the good photo-galvanics with KOH alkali may be attributed to some peculiar chemical and physical properties of KOH vis-à-vis the chemical and physical properties of NaOH.

Today, the growing demand for hydroponic greenhouses is driven by the limitations of fertile land and water. In light of the imperative for sustainable development, particularly in energy usage within these greenhouses, the integration of clean energy sources, especially solar power, is essential. This study aims to assess the energy and environmental aspects, as well as the practicality of employing photovoltaic cells to meet the energy requirements of a commercial hydroponic greenhouse in Alborz province. Data was gathered from a 3000 m2 strawberry hydroponic greenhouse through on-site visits, surveys, and measurements. The findings revealed that the total input energy during a production period amounts to 8652.20 GJ ha−1. The energy ratio, net energy, and energy productivity were calculated as 0.03, -8424.20 GJ ha−1, and 0.20 kg GJ−1, respectively. Natural gas accounted for the highest input energy use, followed by electricity, while biocides, human labor, and chemical fertilizers had the lowest energy consumption. According to the LCA results, the damage categories for resources amount to 724.69 USD2013 per 1 ton of strawberries, with natural gas exerting the greatest impact on this measure. The feasibility assessment for solar energy implementation in the greenhouse indicated that approximately 120 m2 of solar cells would be required to generate electricity from solar radiation, covering about 4 % of the greenhouse roof. Furthermore, the use of solar cells was found to enhance energy and environmental indicators.

Solar energy is a rapidly growing industry, and the performance analysis and maintenance of solar farms are crucial for ensuring their photovoltaics efficiency and longevity. In this context, many solar farms are established and it is crucial for energy producers to operate these farms efficiently. However, control of solar degradation panels locally takes time and control procedures are a challenge for the producers particularly for large farms. In recent years, the use of unmanned aerial vehicles equipped with thermal imaging sensors has emerged as a promising technique for monitoring solar farms. Herein, degradation inspection and efficiency analyses of the solar panels can be effectively conducted by mapping thermal orthomosaic data. In this study, thermal images were obtained for orthomosaic data production by conducting photogrammetric flights with a real time kinematic enabled unmanned aerial vehicles on a solar farm. The solar panels were divided into segments by the segmentation process and photovoltaics efficiency was calculated for each panel based on solar energy. The photovoltaics efficiency was monitored to vary at most 1.22 % throughout the day with the maximum efficiency reaching 18.25 % in the afternoon, and the minimum efficiency dipping to 17.03 % midday. Close efficiency values were acquired in the morning and afternoon with a difference not exceeding 0.12 %. As such, the damage conditions of panels can be identified by designating the ones with the lowest efficiency. Thus it can be deduced that rapid, cost effective and feasible assessment of solar farms may be possible by unmanned aerial vehicle-based thermal monitoring while bringing forth more sensitive future predictions.

This research aims to design and test automatic auxiliary heating unit for solar dryer cabinets to improve drying performance. The auxiliary heating unit utilizes an infrared furnace with cooking gas, a fin heat exchanger, and a blower. It is equipped with an automatic control system to regulate the temperature of the dryer. An agricultural product used in the experiment was fresh pineapple slides. The experimental test was divided into three cases; using (i) solar dryer, (ii) hot air dryer from the automatic auxiliary heating unit and, (iii) combined solar dryer with auxiliary heating unit. Temperature of the automatic auxiliary heating unit was controlled at 55.0 ± 3.0 °C and the air flow speed in the dryer cabinet was 1.5 ± 0.2 m/s. The thermal output from the automatic auxiliary heating unit was more than 2700 W. From the tests, it was shown that the drying time could be reduced to 12.5 h from 32 h, when the solar dryer was combined with the automatic auxiliary heating unit, compared to using only solar dryer. Dried pineapple products showed good quality. Comparative analysis of CIELAB color properties indicated low pigmentation. From a simple economic analysis, return on investment was less than 3.0 months. The use of automatic auxiliary heating units to the solar dryer enabled reduction in drying time and improved product quality.

The need to reduce global carbon emissions has led to a significant increase in clean energy globally. While renewable energy penetration into energy grids and power systems is increasing in many countries, the intermittency and stochastic nature of wind and solar energy resources is still a major challenge. These can affect the safety, stability, and reliability of the energy grid. In existing works of literature, the forecast and prediction of wind energy, solar power, wind power, and solar energy with various models have been considered independently. However, with the rise in solar power and wind power penetration, there exists a gap in literature on the development of models that can simultaneously forecast solar and wind power production. In this paper, two deep hybrid neural networks (DHN-Net) models are developed for the simultaneous forecast of wind and solar power. The novelty of this study is further strengthened as a minute-level timestep is considered for the application of the models developed. The models are trained and tested with data collected from Zone 1 of four different power system operators in the USA. The two DHN-Net models are built on the foundation of artificial, convolutional, and recurrent neural networks (ANN, CNN, and RNN). Results from this study show that the two DHN-Nets can accurately forecast solar and wind power with an R-squared (r2) value of 0.9915, RMSE of 0.01920, and MAE of 0.00736 for data collected from PJM_Zone1. The DHN-Net models recorded a better performance when compared to the benchmark results in literature.

In this paper, we develop several predictive models pertaining to Electric Vehicles in the United States. We set out to understand three phenomena: Public Charging Units, Electric Vehicle Jobs, and Electric Vehicle Registrations. To model them, we include variables from various categories – demographics, economics, education, environment, finance, geographics, public health, and technographics – in the timespan of 2010–2020. We integrate data from multiple data sources and use them to understand, explain, and predict the Electric Vehicle phenomena combining state and county level data. We obtain three random effects linear regression models having variance explained of 51.5–62.4%. We also fit several machine learning models to improve the accuracy of the models, highlighting nonlinearities, to provide additional insights. The overall predictive accuracy of each Gradient Boosted Tree model is far superior to that of each linear regression model and significantly better than the other machine learning models. Our core contribution is that, spanning all three phenomena, the three most important predictor variables are solar generation of electricity, high school graduation rates, and air quality. We interpret the models and discuss their implications for research and practice.

In order to reduce energy demand, building integrated photovoltaics (BIPV) are getting more publicity as a possible solution that could meet the energy needs for buildings. This paper aims to comparatively review the visual comfort indices and the multi-aspect impact of using semi-transparent BIPV on visual comfort indoors. It was found that there was no direct correlation that could be simply detected between the energetic and the visual performance of the photovoltaic semi-transparent windows, moreover, special attention should be paid to the local climate and GHI in the optimization process. Semi-transparent BIPV glazing systems may reduce the level of illuminance indoors, especially in locations with low GHI and with a specified distance from the façade. Meanwhile, these systems could significantly reduce the glare indoors in all locations during the periods when the illuminance is oversupplied and improve daylight quality.

Irrigation expansion is critical for agricultural and rural development, food and nutrition security, and climate change adaptation in Sub-Saharan Africa (SSA). Lack of accessible energy for irrigation development due to limited off- and on-grid infrastructure and the resulting dependence on costly fuel-based irrigation have been key inhibiting factors for irrigation expansion in the region. Off-grid solar-powered irrigation pumps (SIPs) can overcome many of the energy access and other challenges in the region, but their uptake has been slow. Given the nascent development of the solar irrigation sector in SSA, this paper combines a review of the peer-reviewed and grey literature with key informant interviews to identify systemic barriers to the adoption and growth of solar-powered irrigation. We identify uncovered risks, lack of incentives, and lack of capacity as the key factors limiting the adoption of solar-powered irrigation. Moreover, despite significant global cost reductions, solar-powered irrigation systems remain costly in SSA due to limited market development and geographical constraints. Lack of regulation and low investment in building local institutions and value chains further affect uptake and inhibit leveraging the energy transition for ensuring food security and agriculture-led poverty alleviation in SSA. We propose a move away from thinking of SIPs as “silver bullets” and towards a systems approach and the design of context-specific solutions to address risks, incentives and capacity challenges.

In a very dense urban landscape, incorporating renewables becomes challenging due to a lack of space, planning, and mindset. Utilization of already existing large infrastructures in combination with existing technology and necessary adaptation can create the right synergy for harnessing renewables like solar. This paper proposes the installation of a solar power plant in Dhaka, Bangladesh, using available space on Metro Rail Line 6 to meet the increasing demand for clean and renewable energy. The proposed system involves the selection of suitable space, and PV panels, the calculation of annual electricity generation, and performing financial and environmental analyses. The proposed on-grid/grid-tied system offers the advantage of reducing dependence on power supplied to the grid, resulting in lower energy costs, and promoting the use of green energy. The system has a payback period of 7.7 years and a return on investment of 45.7 %. It is estimated that the system saves 14,053.203 tons of CO2 emissions per year and 281,064.06 tons of CO2 emissions over its lifetime. Also, the grid life cycle emission is 584 gCO2/kWh, and the system life cycle emission is 39,119.4 tCO2, which further proves that it is a feasible solution to meeting energy demands while reducing the dependency on fossil fuels and promoting sustainable energy utilization. The results of simulations run using PVsyst and HOMER confirm the economic viability of the proposed solar power station, supporting its viability. The levelized energy cost (LCOE), as projected by PVsyst, is $0.09 per kWh, nearly matching HOMER's prediction of $0.0835. This convergence of results from several simulation tools supports the solar power plant's predicted cost-effectiveness, demonstrating its potential as a key player in the effort to create a greener and more affordable energy landscape.

Decarbonization of the energy sector to mitigate the consequences of climate change is possible by incorporating a greater share of electricity from renewable sources and thus reducing the share of fossil fuels in the energy mix, improving energy efficiency in general and increasing energy storage capacities. Renewable energies are increasingly permeating energy systems, causing significant shifts in the energy production mix. The success of transforming the electricity mix is dependent on the variability of renewable energy sources such as solar photovoltaic, wind, biomass, and hydro. The share of renewable sources in Romania’s energy mix was determined based on real data on electricity generation and consumption in 2019. However, the current electricity consumption has significantly surpassed the electricity produced from renewable sources. Specifically, the combined contribution of hydro, solar photovoltaic, wind, and biomass energy accounted for 39.86% of the total electricity consumption.

A supercapacitor (SCap)/Battery combination leads to development of an efficient energy storage system (ESS). This combination further enhances the performance of the battery by reducing the burden, especially at peak load conditions. In this work, the Energy Management (EM) based model is developed and implemented to the basic solar power-based (SPB) electric vehicle (EV) model. In any type of EM model predicting the driver cycle of EV is one of the main obstacles. The basic structure has been developed with Solar panels, SCap, Battery, DC-DC Converters, and proper control models. Irradiance and temperature are the main sources of power for the solar panel to generate, to run the connected load. In this, static load with constant power has been considered and three different case studies are examined as per the proposed control method. The Battery feeds the load and SCap since there is no power available from two sources, this will be done in case one. In the second case study, PV only supplies power to two sources and the load. In the third case, no power is considered until a certain period, so the battery only sends power to the load when PV and SCap cannot provide power. In order to accomplish this, MATLAB/Simulation models are obtained and validated for the power-sharing between solar panel, battery, and SCap in relation to the power availability conditions at the source level.

The investment in renewable energies like solar power became a priority in order to protect the world from an environmental crisis caused by greenhouse gas emissions. Over the past few decades, human activities like burning fossil fuels for energy have increased greenhouse emissions to an unprecedented level which warn to increase the global average temperature up to 1.5 °C above pre-industrial levels. Such increase in global temperature would cause massive environmental damage and affect people’s lives. Currently, around 65% of the total CO2 emissions are related to fossil fuel burning activities, thus it is necessary to find alternative sources of energy that are environmentally friendly. Renewable energy like solar power is considered one of the most reliable sources of energy as it covers a wide range of the earth’s surface and is constantly available. Several research studies focused on concentrated solar power (CSP) which revealed its high performance in producing electric power. Thus, this paper aims to study the feasibility of constructing a100 MW CSP Linear Fresnel solar power in Riyadh city to support meeting the energy demand in Saudi Arabia and reduce the dependence on fossil fuels. In this study, the National Renewable Energy Laboratory (NREL) System Advisor Model (SAM) was used to design, simulate, and analyze the system. The system was designed based on CSP LF technology, and it was tested with two types of thermal fluid namely molten salt and liquid sodium to examine the potential of each fluid to generate competitive energy at a lower cost. The thermal fluids serve as heat transfer fluids (HTF) and thermal energy storage (TES), where TES supplies the power cycle with needed energy during sunset time. The system simulation shows the capability to produce enough solar power throughout the year. The model achieved a high level of energy production with a capacity factor exceeding 90% during summer for both operating fluids. It was also found that liquid sodium yields higher energy as compared to molten salt with a capacity factor exceeding 0.5–1.2%. During the summertime, it was shown that Saudi Arabia has a high potential to adopt the CSP LF technology to produce sustainable solar power.

Photogalvanic cells are solar power and storage devices. Extensive study on the photo-stability and durability aspect of these cells has not attracted the attention of the researchers. With this aim, the present work reports the electrical output and stability study of the Titan Yellow sensitized photo-galvanic cells. The observed electrical output is 823 mV potential, 2800 μA current, and 511.10 μW power. The observed potential decay rate over 52.18 h is very low (i.e., 1.59 mV/h only) during illumination. This observation shows quite good photo-stability of the cell with respect to the open-circuit potential. The observed current decay rate over 52.18 h is very high (i.e., 15.67 μA/h) during illumination. This observation shows less photo-stability of the cell with respect to the short-circuit current. From initial charging to 1st re-charging to 2nd re-charging of the same cell, the power output decreases under experimental conditions. Overall, the power decay is observed with time in both dark and illuminated conditions. The trend of fall of power is suggestive of the inverse relation between half change time and initial power, and the power decay is of non-zero and non-first order decay. The dye decay and temperature rise in the electrolyte is observed. The power decay may be attributed to the photo-induced degradation of the dye electro-active species and high temperature induced aggregation (precipitation) of the Titan Yellow dye molecules. Despite this power decay, the Titan Yellow dye based photogalvanic cells are capable of producing solar power for sufficiently long hours.

The limited availability of fossil fuel, ecosystem consideration and economic factor stimulates interest in alternative energy provision and thermal energy enhancement. Utilization of solar radiation and nanofluids with solid tiny particle provides a platform to optimize renewable solar thermal system performance. Owing to its usages, this study examines thermal transfer and current density of electromagnetic gravity driven Casson hybridized nanofluid flow through partially filled porous media with Ohmic heating. A mixture of cobalt ferrite (CoFe2O4) and titanium dioxide (TiO2) is considered for the nanoparticles thermal propagation in base solvent ethylene-glycol+water (C2H6O2+H2O). A parabolic concentrated solar collector is used for the solar radiation absorption with a continuous energy supply. An invariant transformation of the partial derivative model is obtained using similarity variables. A semi-analytical shifted Chebyshev method coupled with the integrated collocation scheme has been adopted to provide theoretical solutions to the model. The study revealed that concentrated solar power current density is raised as the electric field factor and medium porosity is increased. The fluid velocity is damped while the temperature distribution is enhanced as the nanoparticle volume fraction is boosted. Thus, this investigation will improve the efficiency of thermal engineering products and enhance industrial performance.

The automobile sector is rising rapidly at a global level. In the current scenario, emphasis is given on electric vehicles (EVs) to reduce conventional energy demand and minimize greenhouse gasses. Most work has been done on solar-powered vehicles used for the transportation of people rather than agricultural transport such as labor, tools, and farm production. Therefore solar-powered farm rickshaw were tailored to Indian farm conditions. A three-wheel rear-driven 450-watt capacity solar-powered farm rickshaw was designed, developed, and evaluated in Indian climatic conditions. The developed rickshaw were comprised of three 150-watt polycrystalline solar modules. The produced electricity is stored in a 48-volt 30 Ah lithium-ion battery. A maximum power point tracking (MPPT) system was also incorporated to access the maximum power from solar panels. Statistical analysis was made with ANOVA tool and FCRD-test. The results were tested at the 5% significant level. The developed rickshaw has a cargo capacity of 300 kg and can be used to transport labor and farm produce. It reduces annual fossil fuel demand by approximately 350 liters and annual CO2 emissions by approximately 837 kg. The developed solar-powered farm rickshaw not only reduces fossil fuel demand but also reduces the emission of greenhouse gasses at large. The main goal behind the design and development of a solar-powered farm rickshaw is to do farm work at low-cost and pollution-free.

Liquid metals are good potential heat transfer materials for thermoclinic heat storage (THS) systems and will play an important role in the next generation solar thermal power system with higher operating temperature. This paper presents a comparative research work on the charging, discharging and mechanical performances of THS tanks based on four different liquid metal materials, which are lead (Pb), lead-bismuth alloy (PbBi), sodium (Na) and sodium-potassium alloy (NaK). The analysis results indicate that for both the charging and discharging processes, the lead-based THS tank can have the shortest operating duration, largest charging and discharging quantities (9.78 × 109 J and 9.21 × 109 J) as well as the highest discharging efficiency (94.17%), revealing its best operating performance. Relatively acceptable operating performances of lead-bismuth-based and sodium-based THS tanks are also demonstrated. Furthermore, in contrast with other three liquid metals, the lead-based THS tank also has the best mechanical performance. It has the smallest peak maximum mechanical stress of the steel wall (58.6 MPa). In summary, the lead-based THS tank has both the best heat storage and mechanical performances.

Globally, over quarter of population experiences energy crisis, particularly those living in rural communities of developing countries. Many of such victims are the people within the Africa continent. More than 600 million people lives in Africa without access to electricity. Energy use is a requirement for physical and socio-economic development of every country. Bioenergy and solar energy has currently seen an increase in its development in many countries in Africa. However, their major concern is its technological development and finance as well as impact on the environment. The study evaluates the solar and bioenergy potential utilization and future prospects in Africa. It also discusses some of the principal challenges negatively influencing its development. Conclusions are drawn on the need for effective international cooperation on inputs from financial, resources and technological advance mechanisms for solar and bio energies development in Africa. For example Development of new businesses should be linked with solar PV and bioenergy infrastructure to promote effective rural electrification. This study provides beneficial information, which will serve as a reference to help improve bioenergy and solar power development.

The Raspberry Pi is a credit card sized single board computer that finds its use in very diverse projects. Being a computer it runs on a full operating system and can be interfaced with a wide range of hardware. Its ability to collect and store data and its superior processing capabilities gives it an edge over other microprocessors. When used to collect data away from the grid, alternative methods of powering the Raspberry Pi have to be used. An ideal powering system should be autonomous, allowing the Raspberry Pi to be deployed indefinitely without the need to check on the system due to power shortcomings. In this paper we introduce the DSAIL Power Management Board that is used to power the Raspberry Pi autonomously. We have developed a prototype and used it to collect ecological data from a conservancy in Central Kenya.

Due to the low access rate of electricity in Africa and unreliable power supply in the grid. It is difficult for smallholder farmers that have incubators to use their egg incubators for reproduction, which constrains their businesses and imports day-old chicks from other continents. Farmers who have incubators face low productivity due to poor performance in their hatcheries that have human beings monitoring and controlling processes in incubation. Minimizing human contact in incubation can boost the income levels of smallholder farmers. Remote monitoring and control of the egg incubator parameters from a distant location may be cost-effective and efficient for bird reproduction in modern times. The abundant solar resources on the continent can eliminate the challenge of low access rates and unreliable power supply farmers face and guarantee income from hatcheries. The main objective of this paper is to design and construct an intelligent solar-powered egg incubator based on GSM/IoT that limits human contact in the incubation cycle to meet global protein needs. The paper seeks to build an innovative egg incubator whose supply is from a standalone photovoltaic system. After the physical product construction, several tests were conducted on the developed incubator to evaluate its performance. The recorded hatchability rates were 97.14%, 95.45%, 95.6%, and 95.24%.

The aim of the SOLETE dataset is to support researchers in the meteorological, solar and wind power forecasting fields. Particularly, co-located wind and solar installations have gained relevance due to the rise of hybrid power plants and systems. The dataset has been recorded in SYSLAB, a laboratory for distributed energy resources located in Denmark. A meteorological station, an 11 kW wind turbine and a 10 kW PV array have been used to record measurements, transferred to a central server. The dataset includes 15 months of measurements from the 1st June 2018 to 1st September 2019 covering: Timestamp, air temperature, relative humidity, pressure, wind speed, wind direction, global horizontal irradiance, plane of array irradiance, and active power recorded from both the wind turbine and the PV inverter. The data was recorded at 1 Hz sampling rate and averaged over 5 min and hourly intervals. In addition, there are three Python source code files accompanying the data file. RunMe.py is a code example for importing the data. MLForecasting.py is a self-contained example on how to use the data to build physics-informed machine learning models for solar PV power forecasting. Functions.py contains utility functions used by the other two.

In cold regions, traditional air source heat pumps are easily frosted in heating state. The frosting problem can be effectively overcome by the direct-expansion solar/air-assisted heat pump (DX-SASIHP). One of the most critical components in the DX-SASIHP system is the collector/evaporator, whose performance hinges on its structure and material. To improve the heating performance of DX-SASIHP, this paper attempts to optimize the structure and material of the collector/evaporator by the Computational Fluid Dynamics (CFD) method. Specifically, key parameters like tube diameters, rib height, rib thicknesses, and tube material were examined under the same weather conditions. On this basis, the heat collection capacity and heat collection efficiency of the collector/evaporator were evaluated. Finally, the collector/evaporator structure was optimized in the light of heat collection capacity, heat collection efficiency and manufacturing cost. The key parameters were optimized as follows: 23 mm for tube diameter, 45 mm for rib height, 4 mm for rib thickness, and aluminum for tube material. The research results lay a theoretical basis for the collector/evaporator design of DX-SASIHP in heating state.

Natural disasters (e.g., hurricanes) can cause widespread power outages within distribution networks and interrupted power supply to critical loads (e.g., grocery stores, hospitals, gas, fire, and police stations) that provide utility services. Microgrids are localized power grids that can incorporate solar/photovoltaic (PV) distributed generators (PV-DGs) and energy storage systems (ESSs) for stand-alone system operations independent of the main grid, known as the island mode. This study investigates a microgrid design problem using PV-DGs and ESSs when facing prolonged power outages in the main grid. We propose a multi-stage stochastic program that holistically considers the techno-economics of microgrid investment and daily operations by optimizing the reliability and resilience of the microgrid during a week-long power outage. The model is designed from a utility perspective that includes budget constraints for investment. Due to the large model size, we develop a nested L-shaped algorithm that solves the problem exactly and analyzes the microgrid’s reliability across different weather scenarios in the entire decision-making horizon. Results from a case study using real-world data show that an islanded utility-scale microgrid can effectively provide uninterrupted power supply to a network of 5 and 10 critical loads, covering 100% and 97% of the demand in all possible future scenarios, with potential investments of $8 million and $15 million, respectively.

This paper describes the hybrid renewable sources, for instance, the wind generator and the photovoltaic modules utilized to produce power to recharge the electric vehicles (EVs) storage system automatically. The current recharging mechanism of EVs requires recharging stations and it will affect the travelling distance for a long travel. This paper presents an automated charging mechanism (ACM) automatically recharges the battery packs, therefore, no need to wait for recharging EVs thereby increases the traveling distance. The proposed ACM is developed using MATLAB-Simulink model. The output voltage of the wind turbine is measured for three dissimilar speed scenarios. The performance of the solar photovoltaic had undergone different irradiance levels in the analysis. A series of studies have been carried out for the developed model of ACM under different load conditions. The total harmonic distortion (THD) of both the output current and voltage, efficiency, and the coverage distance of the vehicle has been studied. For illustrating the capability of ACM it is compared with commercial charging mechanism including different EV brands. The simulation result indicates that the performance of ACM is satisfactory for recharging the batteries of EVs without involving recharging stations. Automatic recharging of EV increases the usage of EVs thereby immensely reduce the fossil fuel vehicles as a result greatly reduced CO2 and CO-related emissions. Therefore the authors strongly believe that the method proposed decreases the complete travel time and as well as in increased EVs usage.

The heat transfer fluid material can affect both the behaviors of a heat storage tank. Based on the Fluid-Solid Coupling method, the influences of five different heat transfer fluids on the thermal and mechanical behaviors of the thermally stratified tank are estimated in this paper, including the binary nitrate (KNO3+NaNO3), binary chloride (KCl + MgCl2), ternary nitrate (KNO3+Ca(NO3)2+LiNO3), liquid lead-bismuth eutectic (LBE) and liquid sodium. The simulation results demonstrate that for the charging process, the tank using the ternary nitrate has the best operation behavior, while for the discharging one, that utilizing the binary nitrate has relatively better operation behavior. The standby behavior comparison results indicate that the thermocline stability of the ternary nitrate is the best, but the tank employing the binary nitrate has the smallest cumulative total heat loss. The mechanical performance comparison results show that the binary nitrate salt and binary chloride salt can lead to the smallest and largest maximum mechanical stress of the tank, which are 96.6 MPa and 168.8 MPa. Therefore, the tank utilizing the binary nitrate has the best mechanical behavior.

The solar power installation on a new broadband seismometer shelter will greatly be affected by the quality of waveform data. The lower power means a physically smaller footprint and a less costly installation for a new station which must be located far from the main power system. In this case, we have installed the solar power system in the new broadband seismometer shelter in the mini region at TKSM station, in Tiganderket, Karo, North Sumatera Indonesia. The main goal of this study, to design, testing the solar cell, and compute the power spectral after installation of the power cell in the new shelter, which located away from roads and cities and human activity. The results presented that the good performance of the solar power system (solar cell, solar charge controller, and battery) for continuous transmission and to collect the waveform data based on the performance TKSM station using power spectral density function methods.