This table expresses the use of renewable energy as gross final consumption of energy. Figures are presented in an absolute way, as well as related to the total energy use in the Netherlands. The total gross final energy consumption in the Netherlands (the denominator used to calculate the percentage of renewable energy per ‘Energy sources and techniques’) can be found in the table as ‘Total, including non-renewables’ and Energy application ‘Total’. The gross final energy consumption for the energy applications ‘Electricity’ and ‘Heat’ are also available. With these figures the percentages of the different energy sources and applications can be calculated; these values are not available in this table. The gross final energy consumption for ‘Transport’ is not available because of the complexity to calculate this. More information on this can be found in the yearly publication ‘Hernieuwbare energie in Nederland’.

Renewable energy is energy from wind, hydro power, the sun, the earth, heat from outdoor air and biomass. This is energy from natural processes that is replenished constantly.

The figures are broken down into energy source/technique and into energy application (electricity, heat and transport).

This table focuses on the share of renewable energy according to the EU Renewable Energy Directive. Under this directive, countries can apply an administrative transfer by purchasing renewable energy from countries that have consumed more renewable energy than the agreed target. For 2020, the Netherlands has implemented such a transfer by purchasing renewable energy from Denmark. This transfer has been made visible in this table as a separate energy source/technique and two totals are included; a total with statistical transfer and a total without statistical transfer.

Figures for 2020 and before were calculated based on RED I; in accordance with Eurostat these figures will not be modified anymore. Inconsistencies with other tables undergoing updates may occur.

Data available from: 1990

Status of the figures: This table contains definite figures up to and including 2022, figures for 2023 are revised provisional figures and figures for 2024 are provisional.

Changes as of July 2025: Compiling figures on solar electricity took more time than scheduled. Consequently, not all StatLine tables on energy contain the most recent 2024 data on production for solar electricity. This table contains the outdated data from June 2025. The most recent figures are 5 percent higher for 2024 solar electricity production. These figures are in these two tables (in Dutch): - StatLine - Zonnestroom; vermogen en vermogensklasse, bedrijven en woningen, regio - StatLine - Hernieuwbare energie; zonnestroom, windenergie, RES-regio Next update is scheduled in November 2025. From that moment all figures will be fully consistent again. We apologize for the inconvenience.

Changes as of june 2025: Figures for 2024 have been added.

Changes as of January 2025 Renewable cooling has been added as Energy source and technique from 2021 onwards, in accordance with RED II. Figures for 2020 and earlier follow RED I definitions, renewable cooling isn’t a part of these definitions.
The energy application “Heat” has been renamed to “Heating and cooling”, in accordance with RED II definitions. RED II is the current Renewable Energy Directive which entered into force in 2021

Changes as of November 15th 2024 Figures for 2021-2023 have been adjusted. 2022 is now definitive, 2023 stays revised provisional. Because of new insights for windmills regarding own electricity use and capacity, figures on 2021 have been revised.

Changes as of March 2024: Figures of the total energy applications of biogas, co-digestion of manure and other biogas have been restored for 2021 and 2022. The final energy consumption of non-compliant biogas (according to RED II) was wrongly included in the total final consumption of these types of biogas. Figures of total biogas, total biomass and total renewable energy were not influenced by this and therefore not adjusted.

When will new figures be published? Provisional figures on the gross final consumption of renewable energy in broad outlines for the previous year are published each year in June. Revised provisional figures for the previous year appear each year in June.

In November all figures on the consumption of renewable energy in the previous year will be published. These figures remain revised provisional, definite figures appear in November two years after the reporting year. Most important (expected) changes between revised provisional figures in November and definite figures a year later are the figures on solar photovoltaic energy. The figures on the share of total energy consumption in the Netherlands could also still be changed by the availability of adjusted figures on total energy consumption.

In this dataset the anther's analysis is based on data from NREL about Solar & Wind energy generation by operation areas.

NASA Prediction of Worldwide Energy Resources

Solar

Monthly averages for global horizontal radiation over 22-year period (Jul 1983

• Jun 2013)

Wind

Monthly average wind speed at 50m above the surface of earth over a 30-year period (Jan 1984 - Dec 2013)Year: Averaged Over 10 to 15 years

COA = central operating area.

EOA = eastern operating area.

SOA = southern operating area.

WOA = western operating area. Source: NRELSource Link

The data has been sourced from the International Renewable Energy Agency (https://pxweb.irena.org/pxweb/en/IRENASTAT). The indicators on energy transition have been formulated to help users understand the progress in the adoption of renewable energy sources vis-à-vis the increasing energy requirements.Sources: International Renewable Energy Agency (IRENA) (2022), Renewable Energy Statistics 2022, https://pxweb.irena.org/pxweb/en/IRENASTAT; IMF Staff Calculations.Category: Mitigation,Transition to a Low-Carbon Economy Data series: Electricity GenerationElectricity Installed Capacity Metadata:Electricity generation: The gross electricity produced by electricity plants, combined heat and power plants (CHP) and the distribution generators measured at the output terminals of generation. It includes on-grid and off-grid generation, and it also includes the electricity self-consumed in energy industries; not only the electricity fed into the grid (net electricity generation). The indicator is expressed in the Dashboard in Gigawatt hours (GWh).Electricity Installed Capacity: The maximum active power that can be supplied continuously (i.e., throughout a prolonged period in a day with the whole plant running) at the point of outlet (i.e. after taking the power supplies for the station auxiliaries and allowing for the losses in those transformers considered integral to the station). This assumes no restriction of interconnection to the network. It does not include overload capacity that can only be sustained for a short period of time (e.g., internal combustion engines momentarily running above their rated capacity). For most countries and technologies, the data on installed capacity on the Dashboard reflects the capacity installed and connected at the end of the calendar year and are expressed in Mega Watts (MW). The renewable power capacity data shown in these tables represents the maximum net generating capacity of power plants and other installations that use renewable energy sources to produce electricity. For most countries and technologies, the data reflects the capacity installed and connected at the end of the calendar year. Pumped storage is included in total capacity but excluded from total generation. The capacity data are presented in megawatts (MW) and the generation data are presented in gigawatt-hours (GWh). All the data are rounded to the nearest one MW/GWh, with figures between zero and 0.5 shown as a 0.

Global consumption of renewable energy has increased significantly over the last two decades. Consumption levels nearly reached ***** exajoules in 2024. This upward trend reflects the increasing adoption of clean energy technologies worldwide. However, despite its rapid growth, renewable energy consumption still remains far below that of fossil fuels. Fossil fuels still dominate energy landscape While renewable energy use has expanded, fossil fuels continue to dominate the global energy mix. Coal consumption reached *** exajoules in 2023, marking its highest level to date. Oil consumption also hit a record high in 2024, exceeding *** billion metric tons for the first time. Natural gas consumption has remained relatively stable in recent years, hovering around **** trillion cubic meters annually. These figures underscore the ongoing challenges in transitioning to a low-carbon energy system. Renewable energy investments The clean energy sector has experienced consistent growth over the past decade, with investments more than doubling from *** billion U.S. dollars in 2014 to *** billion U.S. dollars in 2023. China has emerged as the frontrunner in renewable energy investment, contributing *** billion U.S. dollars in 2023. This substantial funding has helped propel the renewable energy industry forward.

Content

4 of these datasets outline the quantity of terawatt hours (TWh) produced through various sources of energy, comparing both renewable and non-renewable sources, while highlighting the renewable use of the top 20 countries. The Renewables Power Generation dataset includes a 1997-2017 timeline that outlines the progress of the main renewable energy sectors : Hydro, Wind, Biofuel, Solar PV, and Geothermal. Additionally, the Top 20 Countries Power Generation dataset includes the national data for each of the renewable categories as outlined above. The last 2 datasets include the global TWh generated from renewable and non-renewable sources.

In the latest version, I added two datasets which contain the global consumption figures on national and continental/international group levels, which help provide context about the quantity of energy required, how that is changing over time, and how we are doing in terms of transitioning from non-renewable to renewable energy use.

Source

Renewable Energy: Reddy, Vamsi., Kalananda, Aala., Komanapalli, Narayana. "Nature Inspired Optimization Algorithms for Renewable Energy Generation, Distribution and Management - A Comprehensive Review. 2021.

Consumption: https://yearbook.enerdata.net/total-energy/world-consumption-statistics.html (data converted from mTOE to TWh)

Inspiration

As temperatures rise and storms grow more fierce, improving the efficiency and increasing the use of renewable energy sources is critical. In turn, understanding which nations are leading the way and which require more immediate transformations will help target efforts and hopefully, reach global goals.

Which types of renewables are improving the fastest? Which countries using which types of renewables? At the increasing rate of returns on renewables, how long will it take to meet global demands and eliminate non-renewables, or atleast, break 50%?

UNISOLAR dataset contains high-granularity Photovoltaic (PV) solar energy generation, solar irradiance, and weather data from 42 PV sites deployed across five campuses at La Trobe University, Victoria, Australia. The dataset includes approximately two years of PV solar energy generation data collected at 15-minute intervals. Geographical placement and engineering specifications for each of the sites are also provided to aid researchers in modellin solar energy generation. Weather data is available at 1-minute intervals and is provided by the Australian Bureau of Meteorology (BOM). Apparent temperature, air temperature, dew point temperature, relative humidity, wind speed, and wind direction were provided under the weather data. The paper describes the data collection methods, cleaning, and merging with weather data. This dataset can be used to forecast, benchmark, and enhance operational outcomes in solar sites.

Acknowledgements

Please cite the following paper if you use this dataset:

• S. Wimalaratne, D. Haputhanthri, S. Kahawala, G. Gamage, D. Alahakoon and A. Jennings, "UNISOLAR: An Open Dataset of Photovoltaic Solar Energy Generation in a Large Multi-Campus University Setting," 2022 15th International Conference on Human System Interaction (HSI), 2022, pp. 1-5, doi: 10.1109/HSI55341.2022.9869474.

Usage Policy and Legal Disclaimer

This dataset is being distributed only for Research purposes, under Creative Commons Attribution-Noncommercial-ShareAlike license (CC BY-NC-SA 4.0). By clicking on download button(s) below, you are agreeing to use this data only for non-commercial, research, or academic applications. You may need to cite the above papers if you use this dataset.

Github: https://github.com/CDAC-lab/UNISOLAR

Global primary energy consumption has increased dramatically in recent years and is projected to continue to increase until 2045. Only hydropower and renewable energy consumption are expected to increase between 2045 and 2050 and reach 30 percent of the global energy consumption. Energy consumption by country The distribution of energy consumption globally is disproportionately high among some countries. China, the United States, and India were by far the largest consumers of primary energy globally. On a per capita basis, it was Qatar, Singapore, the United Arab Emirates, and Iceland to have the highest per capita energy consumption. Renewable energy consumption Over the last two decades, renewable energy consumption has increased to reach over 90 exajoules in 2023. Among all countries globally, China had the largest installed renewable energy capacity as of that year, followed by the United States.

Analysis of ‘Global Energy Consumption & Renewable Generation’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/jamesvandenberg/renewable-power-generation on 12 November 2021.

--- Dataset description provided by original source is as follows ---

Content

4 of these datasets outline the quantity of terawatt hours (TWh) produced through various sources of energy, comparing both renewable and non-renewable sources, while highlighting the renewable use of the top 20 countries. The Renewables Power Generation dataset includes a 1997-2017 timeline that outlines the progress of the main renewable energy sectors : Hydro, Wind, Biofuel, Solar PV, and Geothermal. Additionally, the Top 20 Countries Power Generation dataset includes the national data for each of the renewable categories as outlined above. The last 2 datasets include the global TWh generated from renewable and non-renewable sources.

In the latest version, I added two datasets which contain the global consumption figures on national and continental/international group levels, which help provide context about the quantity of energy required, how that is changing over time, and how we are doing in terms of transitioning from non-renewable to renewable energy use.

Source

Renewable Energy: Reddy, Vamsi., Kalananda, Aala., Komanapalli, Narayana. "Nature Inspired Optimization Algorithms for Renewable Energy Generation, Distribution and Management - A Comprehensive Review. 2021.

Consumption: https://yearbook.enerdata.net/total-energy/world-consumption-statistics.html (data converted from mTOE to TWh)

Inspiration

As temperatures rise and storms grow more fierce, improving the efficiency and increasing the use of renewable energy sources is critical. In turn, understanding which nations are leading the way and which require more immediate transformations will help target efforts and hopefully, reach global goals.

Which types of renewables are improving the fastest? Which countries using which types of renewables? At the increasing rate of returns on renewables, how long will it take to meet global demands and eliminate non-renewables, or atleast, break 50%?

--- Original source retains full ownership of the source dataset ---

The POWER Project contains over 380 satellite-derived meteorology and solar energy Analysis Ready Data (ARD) at four temporal levels: hourly, daily, monthly (by year 12 months + annual averages), and climatology. The POWER Data Archive provides data at the native resolution of the source data products. The data is updated nightly to maintain Near Real Time (NRT) availability (2-3 days for meteorological parameters and 5-7 days for solar). The POWER Project targets three specific user communities: Renewable Energy (RE), Sustainable Buildings (SB), and Agroclimatology (AG). The POWER Projects provides community specific parameters, output formats, naming conventions, and units that are commonly employed by each user community. The POWER Services Catalog consists of a series of RESTful Application Programming Interfaces (API), geospatial enabled image services, and a web mapping Data Access Viewer (DAV). These three different service offerings support data discovery, access, and distribution to our user base as ARD and as direct application inputs to decision support tools.

Top Countries' Share of Global Solar Energy Consumption, 2016 Discover more data with ReportLinker!

Developed by SOLARGIS and provided by the Global Solar Atlas (GSA), this data resource contains photovoltaic power potential (PVOUT) in kWh/kWp covering the globe. Data is provided in a geographic spatial reference (EPSG:4326). The resolution (pixel size) of solar resource data (GHI, DIF, GTI, DNI) is 9 arcsec (nominally 250 m), PVOUT and TEMP 30 arcsec (nominally 1 km) and OPTA 2 arcmin (nominally 4 km). The data is hyperlinked under 'resources' with the following characteristics: PVOUT LTAy_AvgDailyTotals (GeoTIFF) Data format: GEOTIFF File size : 3.6 GB There are two temporal representation of solar resource and PVOUT data available: • Longterm yearly/monthly average of daily totals (LTAym_AvgDailyTotals) • Longterm average of yearly/monthly totals (LTAym_YearlyMonthlyTotals) Both type of data are equivalent, you can select the summarization of your preference. The relation between datasets is described by simple equations: • LTAy_YearlyTotals = LTAy_DailyTotals * 365.25 • LTAy_MonthlyTotals = LTAy_DailyTotals * Number_of_Days_In_The_Month For individual country or regional data downloads please see: https://globalsolaratlas.info/download (use the drop-down menu to select country or region of interest) For data provided in AAIGrid please see: https://globalsolaratlas.info/download/world. For more information and terms of use, please, read metadata, provided in PDF and XML format for each data layer in a download file. For other data formats, resolution or time aggregation, please, visit Solargis website. Data can be used for visualization, further processing, and geo-analysis in all mainstream GIS software with raster data processing capabilities (such as open source QGIS, commercial ESRI ArcGIS products and others).

This dataset contains the GIS data used in the report, "Global Photovoltaic Power Potential by Country" generated by Solargis (https://solargis.com) with funding provided by the Energy Sector Management Assistance Program (ESMAP). The study summarizes global solar resource and PV power potential on a country and regional basis. Analysis is based on Solargis's high-resolution datasets, and GIS mask layers which are downloadable via the 'resources' tab. A country comparison spreadsheet is also provided as an additional download, which provides indicators of PV power potential for all countries as described in the study. The study provides: • Ranking and comparison of countries and regions according to their PV potential; • Approximate levelized cost of electricity (LCOE) relevant to current PV projects; • Cross-correlation with the socio-economic indicators relevant to PV development. Data information: Format: raster (GeoTIFF) size: 5.3 GB Zip file contains README.txt

Load, wind and solar, prices in hourly resolution. This data package contains different kinds of timeseries data relevant for power system modelling, namely electricity prices, electricity consumption (load) as well as wind and solar power generation and capacities. The data is aggregated either by country, control area or bidding zone. Geographical coverage includes the EU and some neighbouring countries. All variables are provided in hourly resolution. Where original data is available in higher resolution (half-hourly or quarter-hourly), it is provided in separate files. This package version only contains data provided by TSOs and power exchanges via ENTSO-E Transparency, covering the period 2015-mid 2020. See previous versions for historical data from a broader range of sources. All data processing is conducted in Python/pandas and has been documented in the Jupyter notebooks linked below.

This table contains figures on the supply and consumption of energy broken down by sector and by energy commodity. The energy supply is equal to the indigenous production of energy plus the receipts minus the deliveries of energy plus the stock changes. Consumption of energy is equal to the sum of own use, distribution losses, final energy consumption, non-energy use and the total net energy transformation. For each sector, the supply of energy is equal to the consumption of energy.

For some energy commodities, the total of the observed domestic deliveries is not exactly equal to the sum of the observed domestic receipts. For these energy commodities, a statistical difference arises that can not be attributed to a sector.

The breakdown into sectors follows mainly the classification as is customary in international energy statistics. This classification is based on functions of various sectors in the energy system and for several break downs on the international Standard Industrial Classification (SIC). There are two main sectors: the energy sector (companies with main activity indigenous production or transformation of energy) and energy consumers (other companies, vehicles and dwellings). In addition to a breakdown by sector, there is also a breakdown by energy commodity, such as coal, various petroleum products, natural gas, renewable energy, electricity and heat and other energy commodities like non renewable waste.

The definitions used in this table are exactly in line with the definitions in the Energy Balance table; supply, transformation and consumption. That table does not contain a breakdown by sector (excluding final energy consumption), but it does provide information about imports, exports and bunkering and also provides more detail about the energy commodities.

Data available: From: 1990.

Status of the figures: Figures up to and including 2022 are definite. Figures for 2023 and 2024 are revised provisional.

Changes as of July 2025: Compiling figures on solar electricity took more time than scheduled. Consequently, not all StatLine tables on energy contain the most recent 2024 data on production for solar electricity. This table contains the outdated data from June 2025. The most recent figures are 5 percent higher for 2024 solar electricity production. These figures are in these two tables (in Dutch): - StatLine - Zonnestroom; vermogen en vermogensklasse, bedrijven en woningen, regio - StatLine - Hernieuwbare energie; zonnestroom, windenergie, RES-regio Next update is scheduled in November 2025. From that moment all figures will be fully consistent again. We apologize for the inconvenience.

Changes as of June 2025: Figures for 2024 have been updated.

Changes as of March 17th 2025: For all reporting years the underlying code for 'Total crudes, fossil fraction' and 'Total kerosene, fossiel fraction' is adjusted. Figures have not been changed.

Changes as of November 15th 2024: The structure of the table has been adjusted. The adjustment concerns the division into sectors, with the aluminum industry now being distinguished separately within the non-ferrous metal sector. This table has also been revised for 2015 to 2021 as a result of new methods that have also been applied for 2022 and 2023. This concerns the following components: final energy consumption of LPG, distribution of final energy consumption of motor gasoline, sector classification of gas oil/diesel within the services and transfer of energy consumption of the nuclear industry from industry to the energy sector. The natural gas consumption of the wood and wood products industry has also been improved so that it is more comparable over time. This concerns changes of a maximum of a few PJ.

Changes as of June 7th 2024: Revised provisional figures of 2023 have been added.

Changes as of April 26th of 2024 The energy balance has been revised for 2015 and later on a limited number of points. The most important is the following: 1. For solid biomass and municipal waste, the most recent data have been included. Furthermore data were affected by integration with figures for a new, yet to be published StatLine table on the supply of solid biomass. As a result, there are some changes in receipts of energy, deliveries of energy and indigenous production of biomass of a maximum of a few PJ. 2. In the case of natural gas, an improvement has been made in the processing of data for stored LNG, which causes a shift between stock changes, receipts of energy and deliveries of energy of a maximum of a few PJ.

Changes as of March 25th of 2024: The energy balance has been revised and restructured. This concerns mainly the following: 1. Different way of dealing with biofuels that have been mixed with fossil fuels 2. A breakdown of the natural gas balance of agriculture into greenhouse horticulture and other agriculture. 3. Final consumption of electricity in services

1. Blended biofuels Previously, biofuels mixed with fossil fuels were counted as petroleum crude and products. In the new energy balance, blended biofuels count for renewable energy and petroleum crude and products and the underlying products (such as gasoline, diesel and kerosene) only count the fossil part of mixtures of fossil and biogenic fuels. To make this clear, the names of the energy commodities have been changed. The consequence of this adjustment is that part of the energy has been moved from petroleum to renewable. The energy balance remains the same for total energy commodities. The aim of this adjustment is to make the increasing role of blended biofuels in the Energy Balance visible and to better align with the Energy Balances published by Eurostat and the International Energy Agency. Within renewable energy, biomass, liquid biomass is now a separate energy commodity. This concerns both pure and blended biofuels.

2. Greenhouse horticulture separately The energy consumption of agriculture in the Netherlands largely takes place in greenhouse horticulture. There is therefore a lot of attention for this sector and the need for separate data on energy consumption in greenhouse horticulture. To meet this need, the agriculture sector has been divided into two subsectors: Greenhouse horticulture and other agriculture. For the time being, we only publish separate natural gas figures for greenhouse horticulture.

3. Higher final consumption of electricity in services in 2021 and 2022. The way in which electric road transport is treated has improved, resulting in an increase in the supply and final consumption of electricity in services by more than 2 PJ in 2021 and 2022. This also works through the supply of electricity in sector H (Transport and storage).

Changes as of November 14th 2023: Figures for 2021 and 2022 haven been adjusted. Figures for the Energy Balance for 2015 to 2020 have been revised regarding the following items: - For 2109 and 2020 final consumption of heat in agriculture is a few PJ lower and for services a few PJ higher. This is the result of improved interpretation of available data in supply of heat to agriculture. - During the production of geothermal heat by agriculture natural gas is produced as by-product. Now this is included in the energy balance. The amount increased from 0,2 PJ in 2015 to 0,7 PJ in 2020. - There are some improvements in the data for heat in industry with a magnitude of about 1 PJ or smaller. - There some other improvements, also about 1 PJ or smaller.

Changes as of June 15th 2023: Revised provisional figures of 2022 have been added.

Changes as of December 15th 2022: Figures for 1990 up to and including 2019 have been revised. The revision mainly concerns the consumption of gas- and diesel oil and energy commodities higher in the classification (total petroleum products, total crude and petroleum produtcs and total energy commodities). The revision is twofold: - New data for the consumption of diesel oil in mobile machine have been incorporated. Consequently, the final energy consumption of gas- and diesel oil in construction, services and agriculture increases. The biggest change is in construction (+10 PJ from 1990-2015, decreasing to 1 PJ in 2019. In agriculture the change is about 0.5-1.5 PJ from 2010 onwards and for services the change is between 0 and 3 PJ for the whole period. - The method for dealing with the statistical difference has been adapted. Earlier from 2013 onwards a difference of about 3 percent was assumed, matching old data (up to and including 2012) on final consumption of diesel for road transport based on the dedicated tax specifically for road that existed until 2012. In the new method the statistical difference is eliminated from 2015 onwards. Final consumption of road transport is calculated as the remainder of total supply to the market of diesel minus deliveries to users other than road transport. The first and second item affect both final consumption of road transport that decreases consequently about 5 percent from 2015 onwards. Before the adaption of the tax system for gas- and diesel oil in 2013 the statistical difference was positive (more supply than consumption). With the new data for mobile machines total consumption has been increased and the statistical difference has been reduced and is even negative for a few years.

Changes as of 1 March 2022: Figures for 1990 up to and including 2020 have been revised. The most important change is a different way of presenting own use of electricity of power-generating installations. Previously, this was regarded as electricity and CHP transformation input. From now on, this is seen as own use, as is customary in international energy statistics. As a result, the input and net energy transformation decrease and own use increases, on average about 15 PJ per year. Final consumers also have power generating installations. That's why final consumers now also have own use, previously this was not so. In the previous revision of 2021, the new sector blast

In 2024, renewable energy consumption in China reached *****exajoules, more than any other country in the world. Renewable sources such as geothermal, wind, solar, biomass, and waste were included in this measurement, while cross-border electricity trade was not taken into account. Hydropower in China China is by far the leading consumer of hydropower, with over ***** times the consumption of other leading countries such as Canada and Brazil. Several of the world’s hydroelectric dams with the highest generating capacity are located in China, many of which were constructed in the past two decades. The **************** on the Yangtze River was completed in 2012 to become the largest in the world. Energy consumption in the United States After China, the United States was the second-highest consumer of renewable energy in the world. Both countries also consumed the most primary energy overall. The United States strives to achieve energy independence in order to reduce imports of foreign energy sources. As renewable energy gains momentum in a fossil-fuel dominated industry, renewable production in the United States has slightly exceeded the country’s consumption in recent years, and additionally, have both more than doubled since 1975.

Codes and Datasets for “A global assessment of the effects of solar farms on albedo, vegetation, and land surface temperature using remote sensing"Contacts: Zhengjie Xu (xuzj@mail.bnu.edu.cn); Yan Li* (yanli.geo@gmail.com)*Correspondance: Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.Abstract:This document describes the codes and datasets for“A global assessment of the effects of solar farms on albedo, vegetation, and land surface temperature using remote sensing”(Xu et al. 2023 Solar Energy). The data include MODIS Land Surface Temperature (LST), Enhanced Vegetation Index (EVI), albedo data, monthly air temperature and precipitation data from TERRACLIMATE, monthly solar radiation data from ERA5 and the Solar Farm(SF) database from Solar Wiki (wiki-solar.org). Please read this document for more details. The codes and datasets can be used freely under the CCY4.0 License. Users should cite the original paper of Xu et al. (2023) and the dataset (DOI: https://doi.org/10.6084/m9.figshare.24152766) when using it.ReferencesXu, Z., Li, Y., Qin, Y., & Bach, E. (2024). A global assessment of the effects of solar farms on albedo, vegetation, and land surface temperature using remote sensing. Solar Energy, 268, 112198. https://doi.org/10.1016/j.solener.2023.112198

The PowerPulse dataset is a synthetically generated collection of 100,000 records designed to simulate real-world energy usage patterns. It provides insights into household energy consumption, solar energy generation, and environmental impact across various regions and weather conditions. With detailed fields like EnergyConsumed_kWh, SolarEnergyGenerated_kWh, WeatherCondition, and CO2Emissions_kg, this dataset is ideal for exploring energy trends, building predictive models, and analyzing sustainability initiatives.

Key Features:

Comprehensive Coverage: Includes attributes like energy consumption, solar generation, CO2 emissions, and appliance usage. Scalable Insights: Designed to handle large-scale data processing with tools like PySpark. Real-World Relevance: Captures modern energy challenges such as renewable energy optimization and carbon footprint analysis. Flexible Use Cases: Suitable for regression, classification, clustering, and exploratory data analysis.

The leading countries for installed renewable energy in 2024 were China, the United States, and Brazil. China was the leader in renewable energy installations, with a capacity of around 1,827 gigawatts. The U.S., in second place, had a capacity of around 428 gigawatts. Renewable energy is an important step in addressing climate change and mitigating the consequences of this phenomenon. Renewable energy capacity and productionRenewable power capacity is defined as the maximum generating capacity of installations that use renewable sources to generate electricity. The share of renewable energy in the world’s power production has increased in recent years, surpassing 30 percent in 2023. Renewable energy consumption varies from country to country. The leading countries for renewable energy consumption are China, the United States, and Canada.Renewable energy sourcesThere are various sources of renewable energy used globally, including bioenergy, solar energy, hydropower, and wind energy, to name a few. Globally, China and Brazil are the top two countries in terms of generating the most energy through hydropower. Regarding solar power, China, the United States, and Japan boast the highest installed capacities worldwide.

This data provides annual average daily total solar resource averaged over surface cells of 0.038 degrees in both latitude and longitude, or nominally 4 km in size. The solar radiation values represent the resource available to solar energy systems. The data was created using cloud properties which are generated using the AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) algorithms. Fast all-sky radiation model for solar applications (FARMS) in conjunction with the cloud properties, and aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary source are used to estimate direct normal irradiance (DNI) and global horizontal irradiance (GHI). The DNI and GHI are computed for clear skies using the REST2 model. For cloud scenes identified by the cloud mask, the FARMS is used to compute the GHI. The DNI for cloud scenes is then computed using the DISC model. The data are averaged from hourly model output over 19 years (1998-2016). The PATMOS-X model uses half-hourly radiance images in visible and infrared channels from the GOES series of geostationary weather satellites, daily snow cover data from the NSIDC and mixing ratio, temperature and pressure profiles from the Modern Era-Retrospective Analysis (MERRA-2) dataset. The REST2 model uses hourly aerosol optical depth from MERRA-2 to calculate GHI and DNI; water vapor and other inputs for REST 2 are obtained from the MERRA-2. This dataset was derived from the NSRDB and may be used with the following citation: Sengupta, M., Xie, Y., Lopez, A., Habte, A., Maclaurin, G., & Shelby, J. (2018). The national solar radiation data base (NSRDB). Renewable and Sustainable Energy Reviews, 89, 51-60.

European Solar Energy Consumption by Country, 2023 Discover more data with ReportLinker!