This dataset is restricted, for more information please contact the author. Data were collected from multiple sources:The Electricity & Co-Generation Regulatory AuthoritySaudi Electricity companyWeb news article (2015, December 28). Increase of Fuel, Electricity and Water prices. Retrieved from https://akhbaar24.argaam.com/article/detail/255091accessed on March 22, 2018.In October 1984, the government adopted a Tariff that increased with increasing consumption. The changes of Tariffs started in November 1984.Tariff approved by Council of Ministries 170 and become effective in October 2000. This Tariff remained effective for approximately ten years The residential, agricultural, mosques, and charitable societies remained unchanged till 2018In 2010, a new tariff for government, commercial, and industrial consumption came into force, this was adopted by a decision of ECRA's board, to set tariffs for non-residential consumption with an upper limit of SR0.26/kWh.In 2015, the total value of electricity consumed by the residential sector was worth about 38 billion U.S. dollars.In 2018, the Council of Ministers has approved gradual revision of energy prices in the Kingdom including changes to electricity tariffs effective from Jan. 1. 2018, the Electricity and Cogeneration Regulatory Authority (ECRA) announced that new prices will take effect on January 1st, 2018.source: ECRACitation: Alghamdi, Abeer. 2018. “Changes in Saudi Arabia Electricity Prices.” [dataset]. https://datasource.kapsarc.org/explore/dataset/electricity-prices-in-saudi-arabia/information/.

In 2022/23, the government of the United Kingdom spent approximately 20 billion British pounds on the energy price guarantee policy, the most out of any other support policy announced to combat the Cost of Living crisis.

Prices of the components used to calculate the imbalance price. At the specified time, the most recent available data are collected and displayed as quickly as technically possible. Notice that in this report we only provide non-validated data for the current hour. This report contains data for the current hour and is refreshed every minute.This dataset contains data from 22/05/2024 (MARI local go-live) on.

This report contains data for the current hour and is refreshed every minute. Marginal prices of energy activated to maintain a balance in Elia’s control area, as well as the strategic reserve activated to ensure adequacy in the Elia control area. The cumulative prices per minute are indicated for every product category (if the product was actually used).Only regulation-related measures requested by Elia with a view to offsetting imbalances in the control area are included. At the specified time, the most recent available data are collected and displayed as quickly as technically possible. Notice that in this report we only provide non-validated data for the current hour.

The average gas price in Great Britain in May 2025 was 82.59 British pence per therm. This was seven pence higher than the same month the year prior and follows a trend of increasing gas prices. Energy prices in the UK Energy prices in the UK have been exceptionally volatile throughout the 2020s. Multiple factors, such as a lack of gas storage availability and the large share of gas in heating, have exacerbated the supply issue in the UK that followed the Russia-Ukraine war. This has also led to many smaller suppliers announcing bankruptcy, while an upped price cap threatened the energy security of numerous households. The United Kingdom has some of the highest household electricity prices worldwide. How is gas used in the UK? According to a 2023 survey conducted by the UK Department for Energy Security and Net Zero, 58 percent of respondents used gas as a heating method during the winter months. On average, household expenditure on energy from gas in the UK stood at some 24.9 billion British pounds in 2023, double the amount spent just two years prior.

This repository includes python scripts and input/output data associated with the following publication:

[1] Brown, P.R.; O'Sullivan, F. "Spatial and temporal variation in the value of solar power across United States Electricity Markets". Renewable & Sustainable Energy Reviews 2019. https://doi.org/10.1016/j.rser.2019.109594

Please cite reference [1] for full documentation if the contents of this repository are used for subsequent work.

Many of the scripts, data, and descriptive text in this repository are shared with the following publication:

[2] Brown, P.R.; O'Sullivan, F. "Shaping photovoltaic array output to align with changing wholesale electricity price profiles". Applied Energy 2019, 256, 113734. https://doi.org/10.1016/j.apenergy.2019.113734

All code is in python 3 and relies on a number of dependencies that can be installed using pip or conda.

Contents

pvvm/*.py : Python module with functions for modeling PV generation and calculating PV energy revenue, capacity value, and emissions offset.

notebooks/*.ipynb : Jupyter notebooks, including:

pvvm-vos-data.ipynb: Example scripts used to download and clean input LMP data, determine LMP node locations, assign nodes to capacity zones, download NSRDB input data, and reproduce some figures in [1]

pvvm-example-generation.ipynb: Example scripts demonstrating the use of the PV generation model and a sensitivity analysis of PV generator assumptions

pvvm-example-plots.ipynb: Example scripts demonstrating different plotting functions

validate-pv-monthly-eia.ipynb: Scripts and plots for comparing modeled PV generation with monthly generation reported in EIA forms 860 and 923, as discussed in SI Note 3 of [1]

validate-pv-hourly-pvdaq.ipynb: Scripts and plots for comparing modeled PV generation with hourly generation reported in NREL PVDAQ database, as discussed in SI Note 3 of [1]

pvvm-energyvalue.ipynb: Scripts for calculating the wholesale energy market revenues of PV and reproducing some figures in [1]

pvvm-capacityvalue.ipynb: Scripts for calculating the capacity credit and capacity revenues of PV and reproducing some figures in [1]

pvvm-emissionsvalue.ipynb: Scripts for calculating the emissions offset of PV and reproducing some figures in [1]

pvvm-breakeven.ipynb: Scripts for calculating the breakeven upfront cost and carbon price for PV and reproducing some figures in [1]

html/*.html : Static images of the above Jupyter notebooks for viewing without a python kernel

data/lmp/*.gz : Day-ahead nodal locational marginal prices (LMPs) and marginal costs of energy (MCE), congestion (MCC), and losses (MCL) for CAISO, ERCOT, MISO, NYISO, and ISONE.

At the time of publication of this repository, permission had not been received from PJM to republish their LMP data. If permission is received in the future, a new version of this repository will be linked here with the complete dataset.

results/*.csv.gz : Simulation results associated with [1], including modeled energy revenue, capacity credit and revenue, emissions offsets, and breakeven costs for PV systems at all LMP nodes

Data notes

ISO LMP data are used with permission from the different ISOs. Adapting the MIT License (https://opensource.org/licenses/MIT), "The data are provided 'as is', without warranty of any kind, express or implied, including but not limited to the warranties of merchantibility, fitness for a particular purpose and noninfringement. In no event shall the authors or sources be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, arising from, out of or in connection with the data or other dealings with the data." Copyright and usage permissions for the LMP data are available on the ISO websites, linked below.

ISO-specific notes on LMP data:

CAISO data from http://oasis.caiso.com/mrioasis/logon.do are used pursuant to the terms at http://www.caiso.com/Pages/PrivacyPolicy.aspx#TermsOfUse.

ERCOT data are from http://www.ercot.com/mktinfo/prices.

MISO data are from https://www.misoenergy.org/markets-and-operations/real-time--market-data/market-reports/ and https://www.misoenergy.org/markets-and-operations/real-time--market-data/market-reports/market-report-archives/.

PJM data were originally downloaded from https://www.pjm.com/markets-and-operations/energy/day-ahead/lmpda.aspx and https://www.pjm.com/markets-and-operations/energy/real-time/lmp.aspx. At the time of this writing these data are currently hosted at https://dataminer2.pjm.com/feed/da_hrl_lmps and https://dataminer2.pjm.com/feed/rt_hrl_lmps.

NYISO data from http://mis.nyiso.com/public/ are used subject to the disclaimer at https://www.nyiso.com/legal-notice.

ISONE data are from https://www.iso-ne.com/isoexpress/web/reports/pricing/-/tree/lmps-da-hourly and https://www.iso-ne.com/isoexpress/web/reports/pricing/-/tree/lmps-rt-hourly-final. The Material is provided on an "as is" basis. ISO New England Inc., to the fullest extent permitted by law, disclaims all warranties, either express or implied, statutory or otherwise, including but not limited to the implied warranties of merchantability, non-infringement of third parties' rights, and fitness for particular purpose. Without limiting the foregoing, ISO New England Inc. makes no representations or warranties about the accuracy, reliability, completeness, date, or timeliness of the Material. ISO New England Inc. shall have no liability to you, your employer or any other third party based on your use of or reliance on the Material.

Data workup: LMP data were downloaded directly from the ISOs using scripts similar to the pvvm.data.download_lmps() function (see below for caveats), then repackaged into single-node single-year files using the pvvm.data.nodalize() function. These single-node single-year files were then combined into the dataframes included in this repository, using the procedure shown in the pvvm-vos-data.ipynb notebook for MISO. We provide these yearly dataframes, rather than the long-form data, to minimize file size and number. These dataframes can be unpacked into the single-node files used in the analysis using the pvvm.data.copylmps() function.

Usage notes

Code is provided under the MIT License, as specified in the pvvm/LICENSE file and at the top of each *.py file.

Updates to the code, if any, will be posted in the non-static repository at https://github.com/patrickbrown4/pvvm_vos. The code in the present repository has the following version-specific dependencies:

matplotlib: 3.0.3

numpy: 1.16.2

pandas: 0.24.2

pvlib: 0.6.1

scipy: 1.2.1

tqdm: 4.31.1

To use the NSRDB download functions, you will need to modify the "settings.py" file to insert a valid NSRDB API key, which can be requested from https://developer.nrel.gov/signup/. Locations can be specified by passing (latitude, longitude) floats to pvvm.data.downloadNSRDBfile(), or by passing a string googlemaps query to pvvm.io.queryNSRDBfile(). To use the googlemaps functionality, you will need to request a googlemaps API key (https://developers.google.com/maps/documentation/javascript/get-api-key) and insert it in the "settings.py" file.

Note that many of the ISO websites have changed in the time since the functions in the pvvm.data module were written and the LMP data used in the above papers were downloaded. As such, the pvvm.data.download_lmps() function no longer works for all ISOs and years. We provide this function to illustrate the general procedure used, and do not intend to maintain it or keep it up to date with the changing ISO websites. For up-to-date functions for accessing ISO data, the following repository (no connection to the present work) may be helpful: https://github.com/catalyst-cooperative/pudl.

The size of the Renewable Energy Market was valued at USD 1.32 Trillion in 2023 and is projected to reach USD 3.14 Trillion by 2032, with an expected CAGR of 7.09% during the forecast period. It focused on sustainable energy sources, such as solar, wind, and biomass, characterized by reducing dependency on fossil fuel-based energy with low environmental impacts. It has the main characteristics of a varied range of technologies involved and high capital investment. These find applications in the residential, commercial, and industrial sectors, which guarantee more security related to energy and reduction of carbon emissions. The benefits in this sector include environmental sustainability, generation of jobs, and energy independence. Nevertheless, the high upfront investment cost remains a big drawback, and accessibility may be limited, more so in emerging economies. Recent developments include: April 2023: ArcelorMittal announced that the company's Brazilian entity, ArcelorMittal Brazil, formed a joint venture with the Brazilian renewable energy company Casa dos Ventos to develop the 554 MW Babilonia wind power project. The project is expected to be developed at a cost of USD 800 million and will be located in the central region of Bahia, northeast Brazil. ArcelorMittal is anticipated to hold a 55% share in the joint venture, and the remaining share will be held by Casa dos Ventos., January 2023: Cepsa announced that it would build three new solar power projects in Castilla-La Mancha, Spain. The total capacity of the three solar energy farms is expected to be 400 MW. The projects are expected to be developed with an investment of USD 305 million in the towns of Campo de Criptana and Arenales de San Gregorio., May 2022: NJR Clean Energy Ventures (CEV) started construction on an 8.9-MW floating solar installation in Millburn, New Jersey, which is expected to be the largest floating array in the United States. The project uses a floating racking system, and 16,510 solar panels are expected to be installed on a reservoir located at the New Jersey American Water Canoe Brook Water Treatment Plant. The clean power generated by the array is anticipated to provide approximately 95% of the facility's annual power needs through a power purchase agreement with CEV.. Key drivers for this market are: 4., Favorable Government Policies for Renewable Energy4.; The Declining Price of Solar Panels and Wind Turbine Installations4.; Increasing Investments in Hydropower and Pumped Storage Hydropower Projects4.; Growing Emphasis on Geothermal Energy. Potential restraints include: 4., Increasing Penetration of Natural Gas for Power Generation​. Notable trends are: Hydropower Segment is Expected to Dominate the Market during the Forecast Period.

The average wholesale electricity price in July 2025 in Ireland is forecast to amount to******* euros per megawatt-hour. During the period in consideration, figures reached a record high in March 2022, at over *** euros per megawatt-hour.

About the Project The objective of this project is to assess potential economic and technical gains that could be realized by utilizing the GCC Interconnector to deliver electricity at least-cost across the GCC. Summary This paper presents datasets that support economic and policy analyses of countries in the Gulf Cooperation Council (GCC). The objective is to provide an overview of the GCC energy systems and serve as a reference for researchers performing quantitative modeling and analysis. The following data have been collected from public sources, using the most recent complete datasets available. We begin by describing the GCC in terms of electricity systems specific to each country. For each system, we compile and present information about how electricity and water are supplied in terms of technologies and fuels. A key point is the linkage of electricity and water production in the GCC. Power plants typically produce a combination of electricity and water, primarily through desalinating seawater using waste heat. This linkage must be considered when analyzing how energy is transformed in the GCC. An assessment of fossil and renewable resources follows in the third section. The GCC states are well endowed with fossil and renewable resources. To date, fossil energy has been exploited for export and domestic consumption while the use of renewable resources has been negligible in terms of total primary energy supply. The fourth section presents government administered fuel prices and electricity tariffs. These provide a context for understanding the composition of the energy and water sectors. Regulated energy prices are a characteristic of the GCC. Administered prices on the supply (electricity production) and demand side (electricity consumption) have been, and continue to be, a key barrier to electricity trade and greater penetration of renewable technologies in the power and water sectors. Ongoing price reforms are expected to improve the prospects of electricity trade and cost-effectiveness of renewables. Existing energy policies, future targets and power sector reforms are covered in the fifth section. GCC countries have announced plans to both diversify electricity production (by deploying renewables and nuclear capacity) and to reduce demand (through efficiency measures). Recently announced targets in all six GCC states suggest that renewable resources and nuclear energy will be a prominent component of the region’s future energy systems. Almost 80 GW of renewables will be installed, around four times the amount of nuclear power that is planned in the region. The accompanying datasets are available on the OpenKAPSARC data portal and will be updated as new data are available.

The size of the Argentina Oil and Gas Upstream Market was valued at USD XX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 3.50">> 3.50% during the forecast period. The upstream oil and gas sector in Argentina represents a vital component of the nation's energy framework, distinguished by its exploration and production endeavors. The country is endowed with substantial hydrocarbon reserves, notably within the Vaca Muerta shale formation, recognized as one of the largest unconventional oil and gas reserves globally. This positioning has established Argentina as a significant participant in the international energy arena, drawing considerable investment into upstream activities. The expansion of this market is propelled by both local and foreign enterprises keen to exploit these resources. Innovations in hydraulic fracturing and horizontal drilling have facilitated more effective extraction methods, thereby enhancing production rates. However, the sector encounters obstacles such as volatile global oil prices, regulatory ambiguities, and limitations in infrastructure. In response, the Argentine government has introduced a range of initiatives aimed at fostering investment and development, including tax benefits and favorable regulatory frameworks. Furthermore, there is an increasing focus on sustainability and environmental stewardship within the sector. As Argentina advances in harnessing its oil and gas assets, the upstream market is anticipated to be instrumental in bolstering the country's energy security and economic development. The interplay of abundant reserves, technological progress, and supportive governmental policies underscores the considerable promise of Argentina’s upstream oil and gas industry. Recent developments include: In October 2022, Vista Energy and Trafigura Argentina announced that the companies would invest around USD 150 million into the Vaca Muerta Shale formation. This announcement comes after the companies formed a joint venture in 2021 to jointly develop 20 wells in Vista's main oil development concessions in Vaca Muerta., In September 2022, TotalEnergies SE approved the final investment decision for the Fenix gas development project, located 60 km off the coast of Tierra del Fuego in southern Argentina. TotalEnergies operates the project with a 37.5% interest in partnership with Pan American Sur (25%) and WintershallDea (37.5%). The FID amount for the project is USD 706 million, which is expected to come online in 2025.. Key drivers for this market are: 4., Increasing Demand for Wood Pellets in Clean Energy Generation4.; Growing Wood Pellet Manufacturing Infrastructure. Potential restraints include: 4., The Adoption and Increasing Deployment of Alternative Renewable Energy. Notable trends are: Onshore Segment to Dominate the Market.

Renewable Energy Pilot ProgramThe State Corporation Commission (SCC) accepts notices of intent by non-utility owners of solar or wind-powered generation who are interested in selling electricity to utility customers under a power purchase agreement. Under a purchase power agreement, a non-utility developer installs a solar or wind generating facility on a customers’ property and then sells the electricity generated by them back to that customer at a price that is usually less than electricity provided by the utility company.

The global Testing, Inspection, and Certification (TIC) market within the energy and power industry is experiencing robust growth, projected to reach a substantial size. Driven by stringent regulatory compliance mandates, increasing emphasis on safety and reliability of energy infrastructure, and the global transition toward renewable energy sources, this market is poised for significant expansion. The 4% Compound Annual Growth Rate (CAGR) indicates a consistent upward trajectory throughout the forecast period (2025-2033), fueled by factors such as the rising adoption of smart grids, expanding electricity demand globally, and the need for thorough quality control across the entire energy value chain. Key market segments include testing and inspection services, certification services, and various applications such as power generation, storage, distribution, and sales. Geographically, regions like China, the United States, and India are expected to dominate the market due to rapid industrialization, significant investments in energy infrastructure development, and growing awareness of safety protocols. The competitive landscape is marked by the presence of established global players, including DNV Group AS, SGS SA, Bureau Veritas SA, and Intertek Group PLC, vying for market share through strategic partnerships, technological advancements, and service diversification. The continued expansion of renewable energy projects (solar, wind, etc.) is a primary growth driver, demanding rigorous TIC services for quality assurance and grid integration. Further, the increasing complexity of energy infrastructure, coupled with growing cybersecurity concerns, is leading to a surge in the demand for specialized TIC services. While certain challenges remain, such as fluctuating energy prices and economic uncertainties, the long-term outlook for the TIC market in the energy and power sector remains exceptionally positive, indicating strong investment opportunities and considerable future growth potential. The market's evolution will likely involve technological integrations, such as AI and big data analytics, improving efficiency and accuracy of testing and inspection processes. Recent developments include: November 2023 - ScottishPower Renewables awarded DNV a three-year contract to provide integrated East Anglia Three project inspection services. The agreement would see DNV conduct various services, including site inspection, vendor inspection, and quality management services across project and vendor locations globally until 2026. As per the Managing Director for the East Anglia Hub, East Anglia THREE is set to be the world’s second-largest wind farm when it comes into operation in 2026 and is anticipated to play a vital role in enhancing the United Kingdom's energy security and providing clean, renewable energy that would facilitate it to reach net zero., November 2023 - Intertek announced the expansion of its quality, safety, and sustainability solution offering with the launch of Intertek Hydrogen Assurance, an end-to-end advisory and assurance platform providing companies with access to hydrogen expertise and engineering resources for their projects and processes. Assurance solutions help facilitate the adequate progress and implementation of projects based on hydrogen while also addressing safety concerns and complying with intricate regulatory standards.. Key drivers for this market are: Government Regulations and Mandates to Ensure Product Safety and Environmental Protection, Rising Investments in Energy Efficiency Process and Increasing Usage of Smart Grids in the Energy and Power Sector. Potential restraints include: Government Regulations and Mandates to Ensure Product Safety and Environmental Protection, Rising Investments in Energy Efficiency Process and Increasing Usage of Smart Grids in the Energy and Power Sector. Notable trends are: Power Generation to Witness Significant Growth.

The Iranian wind power industry is poised for significant growth, driven by the country's ambitious renewable energy targets and increasing energy demand. With a current market size (estimated 2025) in the tens of millions of USD (precise figure unavailable, but logically derived considering a CAGR of >7% and a value unit of millions USD), the sector exhibits substantial potential. Governmental support for renewable energy initiatives, including favorable policies and incentives, is a major catalyst. Furthermore, Iran's vast geographical area with considerable wind resources presents a significant untapped opportunity. While challenges such as initial investment costs and grid integration remain, the long-term outlook is positive. The participation of major international players like Vestas, Siemens Gamesa, and General Electric, alongside domestic companies such as MAPNA and MahTaab, signifies growing confidence in the market's prospects. This competitive landscape fosters innovation and accelerates technological advancements, further propelling market expansion. The projected CAGR of over 7% from 2025 to 2033 indicates a substantial increase in market value over the forecast period. Segmental analysis, encompassing production, consumption, import, export, and price trends, offers a nuanced understanding of market dynamics. Analyzing these segments will provide actionable insights into investment opportunities and market entry strategies. The historical period (2019-2024) serves as a valuable benchmark for understanding market evolution and informing future projections. Future growth will likely be fueled by further policy support, technological progress, and a greater focus on sustainable energy sources. Recent developments include: In November 2022, the Iranian government increased private companies' guaranteed purchase prices for solar and wind power generated by 20-60% compared to 2021. Iran's Ministry of Energy announced a new directive to raise tariffs (for private sector producers) to encourage investment. The Ministry's new portal cited the press release issued by the state-run Renewable Energy and Energy Efficiency Organization (SATBA). The Ministry also noted that the latest prices for generating electricity from small-scale solar power stations (with less than 20-kilowatt capacity) have risen by 20% per kilowatt, reaching 6 cents/kWh., In January 2022, Iran's Ministry of Energy and the Energy Efficiency Organization (SATBA) signed an MoU (Memorandum of understanding) to carry out the plan to install an additional 10 GW of renewable energy capacity within the span of four years to deliver 30 GW of power generation capacity.. Notable trends are: Onshore to Dominate the Market.

The announcement is amended "Integrated power industry purchases electricity rates for qualified cogeneration systems" general qualified cogeneration system surplus electricity purchase electricity rates

This shapefile represents annual average net power estimates.

The OTEC Plant model predicts the net power production at a specific location, given three inputs: surface temperature (°C), depth (m), and difference between warm surface water temperature and cold deep sea water temperature (ΔT in °C) at the given depth, relative to the surface temperature.

In order to normalize values for the purposes of visualization of the OTEC resource around the world, a baseline plant design was used. The baseline 100MW Net Power design has been optimized for conditions indicative of the Hawai‘i OTEC resource. As such, power output as described by the results of this study is not optimized for local conditions (except in parts of Hawai’i), but does provide guidance for site selection. Given the nominal plant power output of 100MW based on a competitive cost of electricity (Hawai’i), any output exceeding this value represents significant potential. A large area of predicted 100 MW+ net power exists in many locations around the world, especially in areas with high energy costs.

Data were processed and converted to shapefile format by NREL for the Ocean Thermal Extractable Energy Visualization

License Info

This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify, alter, enhance and distribute this data for any purpose whatsoever, provided that this entire notice appears in all copies of the data. Further, the user of this data agrees to credit NREL in any publications or software that incorporate or use the data.

Access to and use of the GIS data shall further impose the following obligations on the User. The names DOE/NREL may not be used in any advertising or publicity to endorse or promote any product or commercial entity using or incorporating the GIS data unless specific written authorization is obtained from DOE/NREL. The User also understands that DOE/NREL shall not be obligated to provide updates, support, consulting, training or assistance of any kind whatsoever with regard to the use of the GIS data.

THE GIS DATA IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DOE/NREL BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF DATA OR PROFITS, WHICH MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT OF OR IN CONNECTION WITH THE ACCESS OR USE OF THE GIS DATA.

The User acknowledges that access to the GIS data is subject to U.S. Export laws and regulations and any use or transfer of the GIS data must be authorized under those regulations. The User shall not use, distribute, transfer, or transmit GIS data or any products incorporating the GIS data except in compliance with U.S. export regulations. If requested by DOE/NREL, the User agrees to sign written assurances and other export-related documentation as may be required to comply with U.S. export regulations.

The Generative AI market in the energy sector is poised for exponential growth, driven by the increasing need for data-driven insights and automation in the industry. With a market size of $19,942.01 million in 2025, the market is projected to expand at a CAGR of 24.1% during the forecast period of 2025-2033, reaching a value of $67,100 million by 2033. Key drivers fueling this growth include the increasing adoption of renewable energy sources, the need for grid modernization and optimization, and the rising demand for personalized energy offerings. Generative AI technologies empower energy companies to enhance demand forecasting accuracy, optimize energy trading and pricing, and improve customer engagement through personalized recommendations. With leading players such as SmartCloud Inc, Siemens AG, and General Electric investing heavily in this space, the market is expected to witness significant innovation and advancements in the coming years. Recent developments include: June 2023, Government acquisition specialists and business executives came together in a lively discussion at the first Unison Connect event, which was successfully conducted by Unison, a leading provider of software solutions and analytics in government purchases. With a demonstration of its generative AI prototype, Unison had also demonstrated the promise of large language models' (LLMs') capacity to change acquisition procedures. During presentation, Unison's AI-powered search was on display. This generative AI experience provides precise acquisition-related responses based on reliable regulatory sources. By incorporating generative AI into Unison's solutions, consumers are guided to take action utilizing a wide range of tools that Unison offers., April 2023, Utilizing the Siemens Teamcenter software, Microsoft Teams, and Azure OpenAI Service, Siemens and Microsoft integrated generative AI to improve innovation and efficiency in industrial goods through cross-functional collaboration., October 2022, A strategic agreement was announced by Tupl, a US-based provider of AI solutions, and Torsa, a Spanish business with expertise in the heavy industrial, logistics, and renewable energy sectors. Through AI-based automation technologies, Tupl seeks to hasten the digital transformation process.. Key drivers for this market are: . Increasing use of microgrids, . Increasing demand for energy across the globe; . Driver impact analysis. Potential restraints include: . Regulatory Concern, . Restraint impact analysis. Notable trends are: Growing number of wholesalers are adopting cloud-native software is expected to drive market growth..

According to Cognitive Market Research, the global Renewable Energy Source market size will be USD 915245.5 million in 2024. It will expand at a compound annual growth rate (CAGR) of 17.20% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 366098.20 million in 2024 and will grow at a compound annual growth rate (CAGR) of 15.4% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 274573.65 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 210506.47 million in 2024 and will grow at a compound annual growth rate (CAGR) of 19.2% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 45762.28 million in 2024 and will grow at a compound annual growth rate (CAGR) of 16.6% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 18304.91 million in 2024 and will grow at a compound annual growth rate (CAGR) of 16.9% from 2024 to 2031.
The Solar Energy category is the fastest growing segment of the Renewable Energy Source industry

Market Dynamics of Renewable Energy Source Market

Key Drivers for Renewable Energy Source Market

Increasing awareness of climate change to Boost Market Growth

Increasing awareness of climate change is significantly driving the renewable energy source market as individuals and organizations recognize the urgent need to transition away from fossil fuels. Public concern over environmental issues has led to heightened demand for sustainable energy solutions that can mitigate climate impacts. This awareness has influenced governments to implement supportive policies and incentives to promote renewable technologies, encouraging investments in clean energy projects. Additionally, corporations are increasingly adopting sustainability goals, driving further investment in renewable energy sources. As consumers demand greener products and practices, the market is shifting towards cleaner energy alternatives, reinforcing the commitment to combat climate change and ensuring a more sustainable future. For instance, ArcelorMittal announced that its Brazilian division, ArcelorMittal Brazil, has partnered with Casa dos Ventos, a Brazilian renewable energy firm, to create a joint venture for the Babilonia wind power project, which has a capacity of 554 MW. This initiative is projected to require an investment of USD 800 million and will be situated in Bahia’s central region in northeastern Brazil. ArcelorMittal is expected to retain a 55% stake in the joint venture, with Casa dos Ventos owning the remaining share.

Declining costs of renewable technologies to Drive Market Growth

The declining costs of renewable technologies are a significant driver of the renewable energy source market, making clean energy solutions more accessible and appealing. Advances in manufacturing processes, economies of scale, and increased competition have led to substantial reductions in the prices of solar panels, wind turbines, and energy storage systems. As these technologies become more affordable, both businesses and consumers are more inclined to invest in renewable energy solutions, resulting in higher adoption rates. Lower costs also enhance the financial viability of renewable projects, attracting investments from various sectors. This trend not only supports the global transition towards sustainable energy but also encourages innovation and development within the industry, fostering further advancements in renewable technologies.

Restraint Factor for the Renewable Energy Source Market

High Initial Costs will Limit Market Growth

High initial costs are a significant restraint on the renewable energy source market, often deterring investment and adoption. Many renewable technologies, such as solar panels, wind turbines, and energy storage systems, require substantial upfront capital for installation and infrastructure development. This financial barrier can be particularly challenging for small businesses and low-income households, limiting their access to renewable energy solutions. While long-term savings on energy bills can offset these costs, the lack of immediate affordability may discourage potential users. Additionally, financing options ma...

Summary

Geojson files used to visualize geospatial layers relevant to identifying and assessing trucking fleet decarbonization opportunities with the MIT Climate & Sustainability Consortium's Geospatial Trucking Industry Decarbonization Explorer (Geo-TIDE) tool.

Relevant Links

Link to the online version of the tool (requires creation of a free user account).

Link to GitHub repo with source code to produce this dataset and deploy the Geo-TIDE tool locally.

Funding

This dataset was produced with support from the MIT Climate & Sustainability Consortium.

Original Data Sources

These geojson files draw from and synthesize a number of different datasets and tools. The original data sources and tools are described below:

Filename(s) Description of Original Data Source(s) Link(s) to Download Original Data License and Attribution for Original Data Source(s)

faf5_freight_flows/*.geojson

trucking_energy_demand.geojson

highway_assignment_links_*.geojson

infrastructure_pooling_thought_experiment/*.geojson

Regional and highway-level freight flow data obtained from the Freight Analysis Framework Version 5. Shapefiles for FAF5 region boundaries and highway links are obtained from the National Transportation Atlas Database. Emissions attributes are evaluated by incorporating data from the 2002 Vehicle Inventory and Use Survey and the GREET lifecycle emissions tool maintained by Argonne National Lab.

Shapefile for FAF5 Regions

Shapefile for FAF5 Highway Network Links

FAF5 2022 Origin-Destination Freight Flow database

FAF5 2022 Highway Assignment Results

Attribution for Shapefiles: United States Department of Transportation Bureau of Transportation Statistics National Transportation Atlas Database (NTAD). Available at: https://geodata.bts.gov/search?collection=Dataset.

License for Shapefiles: This NTAD dataset is a work of the United States government as defined in 17 U.S.C. § 101 and as such are not protected by any U.S. copyrights. This work is available for unrestricted public use.

Attribution for Origin-Destination Freight Flow database: National Transportation Research Center in the Oak Ridge National Laboratory with funding from the Bureau of Transportation Statistics and the Federal Highway Administration. Freight Analysis Framework Version 5: Origin-Destination Data. Available from: https://faf.ornl.gov/faf5/Default.aspx. Obtained on Aug 5, 2024. In the public domain.

Attribution for the 2022 Vehicle Inventory and Use Survey Data: United States Department of Transportation Bureau of Transportation Statistics. Vehicle Inventory and Use Survey (VIUS) 2002 [supporting datasets]. 2024. https://doi.org/10.21949/1506070

Attribution for the GREET tool (original publication): Argonne National Laboratory Energy Systems Division Center for Transportation Research. GREET Life-cycle Model. 2014. Available from this link.

Attribution for the GREET tool (2022 updates): Wang, Michael, et al. Summary of Expansions and Updates in GREET® 2022. United States. https://doi.org/10.2172/1891644

grid_emission_intensity/*.geojson

Emission intensity data is obtained from the eGRID database maintained by the United States Environmental Protection Agency.

eGRID subregion boundaries are obtained as a shapefile from the eGRID Mapping Files database.

eGRID database

Shapefile with eGRID subregion boundaries

Attribution for eGRID data: United States Environmental Protection Agency: eGRID with 2022 data. Available from https://www.epa.gov/egrid/download-data. In the public domain.

Attribution for shapefile: United States Environmental Protection Agency: eGRID Mapping Files. Available from https://www.epa.gov/egrid/egrid-mapping-files. In the public domain.

US_elec.geojson

US_hy.geojson

US_lng.geojson

US_cng.geojson

US_lpg.geojson

Locations of direct current fast chargers and refueling stations for alternative fuels along U.S. highways. Obtained directly from the Station Data for Alternative Fuel Corridors in the Alternative Fuels Data Center maintained by the United States Department of Energy Office of Energy Efficiency and Renewable Energy.

US_elec.geojson

US_hy.geojson

US_lng.geojson

US_cng.geojson

US_lpg.geojson

Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy. Alternative Fueling Station Corridors. 2024. Available from: https://afdc.energy.gov/corridors. In the public domain.

These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

daily_grid_emission_profiles/*.geojson

Hourly emission intensity data obtained from ElectricityMaps.

Original data can be downloaded as csv files from the ElectricityMaps United States of America database

Shapefile with region boundaries used by ElectricityMaps

License: Open Database License (ODbL). Details here: https://www.electricitymaps.com/data-portal

Attribution for csv files: Electricity Maps (2024). United States of America 2022-23 Hourly Carbon Intensity Data (Version January 17, 2024). Electricity Maps Data Portal. https://www.electricitymaps.com/data-portal.

Attribution for shapefile with region boundaries: ElectricityMaps contributors (2024). electricitymaps-contrib (Version v1.155.0) [Computer software]. https://github.com/electricitymaps/electricitymaps-contrib.

gen_cap_2022_state_merged.geojson

trucking_energy_demand.geojson

Grid electricity generation and net summer power capacity data is obtained from the state-level electricity database maintained by the United States Energy Information Administration.

U.S. state boundaries obtained from this United States Department of the Interior U.S. Geological Survey ScienceBase-Catalog.

Annual electricity generation by state

Net summer capacity by state

Shapefile with U.S. state boundaries

Attribution for electricity generation and capacity data: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data/state/. In the public domain.

electricity_rates_by_state_merged.geojson

Commercial electricity prices are obtained from the Electricity database maintained by the United States Energy Information Administration.

Electricity rate by state

Attribution: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data.php. In the public domain.

demand_charges_merged.geojson

demand_charges_by_state.geojson

Maximum historical demand charges for each state and zip code are derived from a dataset compiled by the National Renewable Energy Laboratory in this this Data Catalog.

Historical demand charge dataset

The original dataset is compiled by the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy (DOE), and the Alliance for Sustainable Energy, LLC ('Alliance').

Attribution: McLaren, Joyce, Pieter Gagnon, Daniel Zimny-Schmitt, Michael DeMinco, and Eric Wilson. 2017. 'Maximum demand charge rates for commercial and industrial electricity tariffs in the United States.' NREL Data Catalog. Golden, CO: National Renewable Energy Laboratory. Last updated: July 24, 2024. DOI: 10.7799/1392982.

eastcoast.geojson

midwest.geojson

la_i710.geojson

h2la.geojson

bayarea.geojson

saltlake.geojson

northeast.geojson

Highway corridors and regions targeted for heavy duty vehicle infrastructure projects are derived from a public announcement on February 15, 2023 by the United States Department of Energy.

The shapefile with Bay area boundaries is obtained from this Berkeley Library dataset.

The shapefile with Utah county boundaries is obtained from this dataset from the Utah Geospatial Resource Center.

Shapefile for Bay Area country boundaries

Shapefile for counties in Utah

Attribution for public announcement: United States Department of Energy. Biden-Harris Administration Announces Funding for Zero-Emission Medium- and Heavy-Duty Vehicle Corridors, Expansion of EV Charging in Underserved Communities (2023). Available from https://www.energy.gov/articles/biden-harris-administration-announces-funding-zero-emission-medium-and-heavy-duty-vehicle.

Attribution for Bay area boundaries: San Francisco (Calif.). Department Of Telecommunications and Information Services. Bay Area Counties. 2006. In the public domain.

Attribution for Utah boundaries: Utah Geospatial Resource Center & Lieutenant Governor's Office. Utah County Boundaries (2023). Available from https://gis.utah.gov/products/sgid/boundaries/county/.

License for Utah boundaries: Creative Commons 4.0 International License.

incentives_and_regulations/*.geojson

State-level incentives and regulations targeting heavy duty vehicles are collected from the State Laws and Incentives database maintained by the United States Department of Energy's Alternative Fuels Data Center.

Data was collected manually from the State Laws and Incentives database.

Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy, Alternative Fuels Data Center. State Laws and Incentives. Accessed on Aug 5, 2024 from: https://afdc.energy.gov/laws/state. In the public domain.

These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

costs_and_emissions/*.geojson

diesel_price_by_state.geojson

trucking_energy_demand.geojson

Lifecycle costs and emissions of electric and diesel trucking are evaluated by adapting the model developed by Moreno Sader et al., and calibrated to the Run on Less dataset for the Tesla Semi collected from the 2023 PepsiCo Semi pilot by the North American Council for Freight Efficiency.

In