Graph and download economic data for Global price of Energy index (PNRGINDEXM) from Jan 1992 to Jun 2025 about energy, World, indexes, and price.

New York Energy Prices presents retail energy price data. Energy prices are provided by fuel type in nominal dollars per million Btu for the residential, commercial, industrial, and transportation sectors. This section includes a column in the price table displaying gross domestic product (GDP) price deflators for converting nominal (current year) dollars to constant (real) dollars. To convert nominal to constant dollars, divide the nominal energy price by the GDP price deflator for that particular year. Historical petroleum, electricity, coal, and natural gas prices were compiled primarily from the Energy Information Administration. How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

Energy price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations.
This data set includes energy price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

The dataset contains the evolution of electricity prices in Spain for the period 2020-11-01 to 2022-10-31. The average energy prices (in MWh) as a function of the market, the produced energy (in MW), as well as the renewable energy produced (in MW) by type (wind, solar, hydroelectric, etc.) are provided with a granularity of hours for the period of time mentioned above.

The data has been obtained from the webpage: https://www.esios.ree.es/es/.

Disclaimer: Express consent was provided by Red Eléctrica de España (source and proprietary of the data) to gather the data using web scraping under the framework of a practicum from the Master in Data Science from the Universitat Oberta de Catalunya (UOC). Under no circumstance do they support the reuse of the data. We express our intention to use the data for the purpose of the activity and decline any commercial interest in the use of the data extracted.

Success.ai’s LinkedIn Data for Energy Professionals Worldwide provides a powerful dataset tailored to businesses and organizations aiming to connect with key decision-makers and professionals in the global energy sector. Covering roles such as energy consultants, project managers, engineers, and executives, this dataset offers verified LinkedIn profiles, work emails, professional histories, and actionable insights.

With access to over 700 million verified global profiles, Success.ai ensures your marketing, outreach, and partnership strategies are driven by accurate, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution empowers you to excel in the dynamic and evolving energy landscape.

Why Choose Success.ai’s LinkedIn Data?

1. Verified Contact Data for Precision Engagement

   • Access verified LinkedIn profiles, work emails, and professional histories of energy professionals worldwide.
   • AI-driven validation ensures 99% accuracy, minimizing inefficiencies and boosting engagement rates.

2. Comprehensive Coverage of the Global Energy Sector

   • Includes professionals from top energy hubs such as North America, Europe, the Middle East, and Asia-Pacific.
   • Gain insights into renewable energy initiatives, oil and gas operations, and emerging energy technologies.

3. Continuously Updated Datasets

   • Real-time updates ensure profiles remain accurate and reflect the latest career moves and industry changes.
   • Stay ahead of energy trends and capitalize on new opportunities effectively.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

• 700M+ Verified Global Profiles: Access LinkedIn profile data for energy professionals and decision-makers worldwide.
• Leadership Insights: Connect with energy executives, project managers, and consultants driving industry advancements.
• Verified Contact Details: Gain work emails and phone numbers for targeted outreach.
• Professional Histories: Understand career trajectories, areas of expertise, and contributions to the energy sector.

Key Features of the Dataset:

1. Comprehensive Energy Professional Profiles

   • Identify and connect with professionals involved in renewable energy, oil and gas, utilities, and energy infrastructure projects.
   • Target decision-makers responsible for sustainability initiatives, technology adoption, and operational efficiency.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by industry focus (solar, wind, oil and gas, utilities), geographic location, or job function.
   • Tailor campaigns to align with specific energy market needs, such as efficiency improvements or regulatory compliance.

3. Regional and Industry Insights

   • Leverage data on global energy trends, consumption patterns, and technological innovations.
   • Refine marketing strategies and business outreach based on actionable insights specific to energy markets.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data enable personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Lead Generation

   • Design targeted campaigns to promote energy solutions, renewable technologies, or consultancy services to energy professionals globally.
   • Use verified contact data for multi-channel outreach, including email, phone, and social platforms.

2. Partnership Development and Collaboration

   • Build relationships with energy companies, renewable energy providers, and utilities seeking strategic alliances.
   • Foster collaborations that enhance energy efficiency, expand renewable adoption, or improve grid resilience.

3. Market Research and Competitive Analysis

   • Analyze energy trends and technology adoption to refine product offerings, marketing strategies, and development plans.
   • Benchmark against competitors to identify growth opportunities and high-demand solutions.

4. Recruitment and Talent Acquisition

   • Target HR professionals and hiring managers in the energy sector recruiting for roles in engineering, project management, or sustainability.
   • Provide workforce optimization platforms or training solutions tailored to the energy industry.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality LinkedIn data at competitive prices, ensuring strong ROI for your marketing, outreach, and development efforts.

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   • Integrate verified LinkedIn data into CRM systems, analytics tools, or marketing platforms via APIs or downloadable formats, enhancing productivity and streamlining workflows.

3. Data Accuracy with AI Validation

   • Trust in 99% accuracy to guide data-driven decisions, refine targeting, and boost conver...

Abstract

Energy price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes energy price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

Geographic coverage notes

The data cover the following sub-national areas: Badakhshan, Badghis, Baghlan, Balkh, Bamyan, Daykundi, Farah, Faryab, Paktya, Ghazni, Ghor, Hilmand, Hirat, Nangarhar, Jawzjan, Kabul, Kandahar, Kapisa, Khost, Kunar, Kunduz, Laghman, Logar, Wardak, Nimroz, Nuristan, Paktika, Panjsher, Parwan, Samangan, Sar-e-pul, Takhar, Uruzgan, Zabul, Market Average, Armavir, Ararat, Aragatsotn, Tavush, Gegharkunik, Shirak, Kotayk, Syunik, Lori, Vayotz Dzor, Yerevan, Kanifing Municipal Council, Central River, Upper River, West Coast, North Bank, Lower River, Bafata, Tombali, Cacheu, Sector Autonomo De Bissau, Biombo, Oio, Gabu, Bolama, Quinara, Anbar, Babil, Baghdad, Basrah, Diyala, Dahuk, Erbil, Ninewa, Kerbala, Kirkuk, Missan, Muthanna, Najaf, Qadissiya, Salah al-Din, Sulaymaniyah, Thi-Qar, Wassit, Attapeu, Louangnamtha, Champasack, Bokeo, Bolikhamxai, Khammouan, Oudomxai, Phongsaly, Vientiane, Xiengkhouang, Louangphabang, Salavan, Savannakhet, Sekong, Vientiane Capital, Houaphan, Xaignabouly, Akkar, Mount Lebanon, Baalbek-El Hermel, North, Beirut, Bekaa, El Nabatieh, South, Nimba, Grand Kru, Grand Cape Mount, Gbarpolu, Grand Bassa, Rivercess, Montserrado, River Gee, Lofa, Bomi, Bong, Sinoe, Maryland, Margibi, Grand Gedeh, Abia, Borno, Yobe, Katsina, Kano, Kaduna, Gombe, Adamawa, Jigawa, Kebbi, Oyo, Sokoto, Zamfara, Lagos, Shabelle Hoose, Juba Hoose, Bay, Banadir, Shabelle Dhexe, Gedo, Hiraan, Woqooyi Galbeed, Awdal, Bari, Juba Dhexe, Togdheer, Nugaal, Galgaduud, Bakool, Sanaag, Mudug, Sool, , Warrap, Unity, Jonglei, Northern Bahr el Ghazal, Upper Nile, Eastern Equatoria, Central Equatoria, Western Bahr el Ghazal, Western Equatoria, Lakes, Aleppo, Dar'a, Quneitra, Homs, Deir-ez-Zor, Damascus, Ar-Raqqa, Al-Hasakeh, Hama, As-Sweida, Rural Damascus, Tartous, Idleb, Lattakia, Al Dhale'e, Aden, Al Bayda, Al Maharah, Lahj, Al Jawf, Raymah, Al Hudaydah, Hajjah, Amran, Shabwah, Dhamar, Ibb, Sana'a, Al Mahwit, Marib, Hadramaut, Sa'ada, Amanat Al Asimah, Socotra, Taizz, Abyan

The retail price for electricity in the United States stood at an average of ***** U.S. dollar cents per kilowatt-hour in 2024. This is the highest figure reported in the indicated period. Nevertheless, the U.S. still has one of the lowest electricity prices worldwide. As a major producer of primary energy, energy prices are lower than in countries that are more reliant on imports or impose higher taxes. Regional variations and sector disparities The impact of rising electricity costs across U.S. states is not uniform. Hawaii stands out with the highest household electricity price, reaching a staggering ***** U.S. cents per kilowatt-hour in September 2024. This stark contrast is primarily due to Hawaii's heavy reliance on imported oil for power generation. On the other hand, states like Utah benefit from lower rates, with prices around **** U.S. cents per kilowatt-hour. Regarding U.S. prices by sector, residential customers have borne the brunt of price increases, paying an average of ***** U.S. cents per kilowatt-hour in 2023, significantly more than commercial and industrial sectors. Factors driving price increases Several factors contribute to the upward trend in electricity prices. The integration of renewable energy sources, investments in smart grid technologies, and rising peak demand all play a role. Additionally, the global energy crisis of 2022 and natural disasters affecting power infrastructure have put pressure on the electric utility industry. The close connection between U.S. electricity prices and natural gas markets also influences rates, as domestic prices are affected by higher-paying international markets. Looking ahead, projections suggest a continued increase in electricity prices, with residential rates expected to grow by *** percent in 2024, driven by factors such as increased demand and the ongoing effects of climate change.

In the third quarter of 2025, Bermuda had the highest household electricity prices worldwide, followed by Ireland, Italy, and Germany. At the time, Irish households were charged around 0.44 U.S. dollars per kilowatt-hour, while in Italy, the price stood at 0.42 U.S. dollars per kilowatt-hour. By comparison, in Russia, residents paid almost 10 times less. What is behind electricity prices? Electricity prices vary widely across the world and sometimes even within a country itself, depending on factors like infrastructure, geography, and politically determined taxes and levies. For example, in Denmark, Belgium, and Sweden, taxes constitute a significant portion of residential end-user electricity prices. Reliance on fossil fuel imports Meanwhile, thanks to their great crude oil and natural gas production output, countries like Iran, Qatar, and Russia enjoy some of the cheapest electricity prices in the world. Here, the average household pays less than 0.1 U.S. dollars per kilowatt-hour. In contrast, countries heavily reliant on fossil fuel imports for electricity generation are more vulnerable to market price fluctuations.

New York Energy Prices presents retail energy price data. Energy prices are provided by fuel type in nominal dollars per specified physical unit for the residential, commercial, industrial, and transportation sectors. This section includes a column in the price table displaying gross domestic product (GDP) price deflators for converting nominal (current year) dollars to constant (real) dollars. To convert nominal to constant dollars, divide the nominal energy price by the GDP price deflator for that particular year. Historical petroleum, electricity, coal, and natural gas prices were compiled primarily from the Energy Information Administration. How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

This dataset provides values for ENERGY PRICES. reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This table shows the average prices paid for natural gas and electricity. The total prices represent the sum of energy supply prices and network prices.

The total price is the price paid by an end-user, for instance a household or an industrial company consuming energy in their production process. Natural gas used for non-energy purposes or for electricity generation is excluded from the data.

Data available from: 1st semester of 2009

Status of the figures: The figures in this table are provisional for the two most recent semesters, and the annual figures follow the status of the second semester of the relevant reporting year. The remaining figures are final.

Changes as of September 30: Figures for the first half of 2025 have been added.

The network prices for final non-household customers will from now on, and dating back to 2009, be derived from administrative data sources. This now follows the methodology for households. Consumption data can be combined with tariffs that are published on the websites of the network companies, providing the necessary data to compile the prices. The change in methodology is carried out for the full time-series, making sure the network prices are consistent and price changes are not the result of varying measurement approaches.

When will new figures be published? New provisional figures will be published three months after the semesters end, at the end of September and at the end of March.

Motor Gasoline Price: Premium: EIA: End User: Retail Outlets data was reported at 2.787 USD/gal in Apr 2018. This records an increase from the previous number of 2.649 USD/gal for Mar 2018. Motor Gasoline Price: Premium: EIA: End User: Retail Outlets data is updated monthly, averaging 1.148 USD/gal from Jan 1983 (Median) to Apr 2018, with 424 observations. The data reached an all-time high of 3.833 USD/gal in Jun 2008 and a record low of 0.656 USD/gal in Nov 1986. Motor Gasoline Price: Premium: EIA: End User: Retail Outlets data remains active status in CEIC and is reported by Energy Information Administration. The data is categorized under Global Database’s USA – Table US.P002: Energy Price.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Household Energy in U.S. City Average (CUSR0000SAH21) from Jan 1967 to Sep 2025 about energy, urban, households, consumer, CPI, inflation, price index, indexes, price, and USA.

This table contains consumer prices for electricity and gas. Weighted average monthly prices are published broken down into transport rate, delivery rates and taxes, both including and excluding VAT. These prices are published on a monthly basis. The prices presented in this table were used to compile the CPI up to May 2023. Prices for newly offered contracts were collected. Contract types that are no longer offered, but have been in previous reporting periods, are imputed. The average can therefore diverge from the prices paid for energy contracts by Dutch households.

Data available from January 2018 up to May 2023.

Status of the figures: The figures are definitive.

Changes as of 17 July 2023: This table will no longer be updated. Due to a change in the underlying data and accompanying method for calculcating average energy prices, a new table was created. See paragraph 3.

Changes as of 13 February: Average delivery rates are not shown in this table from January 2023 up to May 2023. With the introduction of the price cap, the average energy rates (delivery rates) of fixed and variable energy contracts together remained useful for calculating a development for the CPI. However, as a pricelevel, they are less useful. Average energy prices from January 2023 up to May 2023 are published in a customized table. In this publication, only data concerning new variable contracts are taken into account

When will new figures be published? Does not apply.

The average wholesale electricity price in September 2025 in the United Kingdom is forecast to amount to*******British pounds per megawatt-hour, a decrease from the previous month. A record high was reached in August 2022 when day-ahead baseload contracts averaged ***** British pounds per megawatt-hour. Electricity price stabilization in Europe Electricity prices increased in 2024 compared to the previous year, when prices stabilized after the energy supply shortage. Price spikes were driven by the growing wholesale prices of natural gas and coal worldwide, which are among the main sources of power in the region.

… and in the United Kingdom? The United Kingdom was one of the countries with the highest electricity prices worldwide during the energy crisis. Since then, prices have been stabilizing, almost to pre-energy crisis levels. The use of nuclear, wind, and bioenergy for electricity generation has been increasing recently. The fuel types are an alternative to fossil fuels and are part of the country's power generation plans going into the future.

Access LinkedIn company data for renewable energy businesses globally with Success.ai. Includes detailed firmographic data, employee counts, and decision-maker profiles. Continuously updated datasets. Best price guaranteed.

This dataset provides a comprehensive time series of natural gas prices with a focus on the U.S. Henry Hub Natural Gas Spot Price, one of the most widely used benchmarks for natural gas pricing.

Data is collected from the U.S. Energy Information Administration (EIA), ensuring high reliability and transparency.

Coverage

• Frequency: Daily and Monthly
• Period: January 1997 – Present
• Units: U.S. Dollars per Million British Thermal Units (nominal)

Applications

This dataset can be useful for:

• Energy market analysis
• Time series forecasting
• Price volatility studies
• Economic and policy research
• Machine learning projects involving energy price prediction

Abstract

Energy price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes energy price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

Geographic coverage notes

The data cover the following sub-national areas: Attapeu, Louangnamtha, Champasack, Bokeo, Bolikhamxai, Khammouan, Oudomxai, Phongsaly, Vientiane, Xiengkhouang, Louangphabang, Salavan, Savannakhet, Sekong, Vientiane Capital, Houaphan, Xaignabouly, Market Average