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TwitterIn 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.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides values for ELECTRICITY PRICE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
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TwitterHousehold electricity prices vary significantly around the world. In March 2025, the price of electricity was below 0.1 U.S. dollars per kilowatt-hour in countries which rely on nationally produced fossil fuels for electricity generation, while it exceeded 0.4 U.S. dollars per kilowatt-hour where the power sector is dependent on energy imports.
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Graph and download economic data for Global price of Energy index (PNRGINDEXM) from Jan 1992 to Jun 2025 about energy, World, indexes, and price.
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TwitterIn September 2024, industrial electricity prices in the European countries of Germany, Italy, and the United Kingdom were among the highest in the world, at around **** U.S. dollars per kilowatt-hour. Singapore was the Asian country with the highest electricity bill worldwide at that time. Lowest electricity prices in the world The average retail electricity price in the United States was considerably lower than in most of Europe. Iceland was the European country with one of the lowest electricity bills for enterprises that month. At the bottom of the ranking were also Russia, Iraq, Qatar, Argentina, and Libya. In these countries, commercial electricity prices amounted to less than *** U.S. dollars per kilowatt-hour. Household electricity prices In addition, European countries had the highest household electricity prices worldwide that month, with Italy at the top of the ranking. By comparison, Iran and Ethiopia had the lowest residential electricity prices in the world.
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TwitterMiddle Eastern and African countries had the cheapest electricity prices worldwide in December 2024. Namely, the electricity price for Iran's households was only 0.4 U.S. cents per kilowatt-hour of electricity. Ethiopia, Syria, Cuba, and Sudan also had some of the lowest electricity prices worldwide that month.
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TwitterElectricity prices in Europe are expected to remain volatile through 2025, with Italy projected to have some of the highest rates among major European economies. This trend reflects the ongoing challenges in the energy sector, including the transition to renewable sources and the impact of geopolitical events on supply chains. Despite efforts to stabilize the market, prices still have not returned to pre-pandemic levels, such as in countries like Italy, where prices are forecast to reach ****** euros per megawatt hour in September 2025. Natural gas futures shaping electricity costs The electricity market's future trajectory is closely tied to natural gas prices, a key component in power generation. Dutch TTF gas futures, a benchmark for European natural gas prices, are projected to be ***** euros per megawatt hour in July 2025. The reduced output from the Groningen gas field and increased reliance on imports further complicate the pricing landscape, potentially contributing to higher electricity costs in countries like Italy. Regional disparities and global market influences While European electricity prices remain high, significant regional differences persist. For instance, natural gas prices in the United States are expected to be roughly one-third of those in Europe by March 2025, at **** U.S. dollars per million British thermal units. This stark contrast highlights the impact of domestic production capabilities on global natural gas prices. Europe's greater reliance on imports, particularly in the aftermath of geopolitical tensions and the shift away from Russian gas, continues to keep prices elevated compared to more self-sufficient markets. As a result, countries like Italy may face sustained pressure on electricity prices due to their position within the broader European energy market. As of August 2025, electricity prices in Italy have decreased to ****** euros per megawatt hour, reflecting ongoing volatility in the market.
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
Dataset comprising data from five day-ahead electricity markets:
Nord pool: The Nord pool day-ahead electricity market, one of the largest European power market. PJM: The zonal prices of the COMED area in the Pennsylvania-New Jersey-Maryland (PJM) market. EPEX-FR: The French day-ahead electricity market. EPEX-BE: The Belgian day-ahead electricity market. EPEX-DE: The German day-ahead electricity market. Each market contains 6 years of data (we consider a year to be 364 days to have an integer number of weeks). The specific dates are:
Nord pool: 01.01.2013 – 24.12.2018 PJM: 01.01.2013 – 24.12.2018 EPEX-FR: 09.01.2011 – 31.12.2016 EPEX-BE: 09.01.2011 – 31.12.2016 EPEX-DE: 09.01.2012 – 31.12.2017 Each dataset comprises historical prices and two relevant exogenous inputs based on day-ahead forecasts of price drivers. The day--ahead forecast representing other exogenous inputs are market dependent:
Nord pool: System load + Wind power generation. PJM: System load + Zonal load in the COMED area. EPEX-FR: System load + Generation in France EPEX-BE: System load in France + Generation in France EPEX-DE: Zonal load in the TSO Amprion zone + Aggregated Wind and Solar power generation All datasets are given using the local timezone:
Nord pool: Central European Time (CET) PJM: Eastern Time (ET) EPEX-FR: Central European Time (CET) EPEX-BE: Central European Time (CET) EPEX-DE: Central European Time (CET) For all five datasets, the daylight saving times (DST) are pre-processed by interpolating the missing values in Spring and averaging the values corresponding to the duplicated time indices in Autumn.
DISCLAIMER
We do not own the data, but we simply have gathered it so other researchers can easily test their methods on multiple day-ahead markets. The data has been gathered using the respective websites of each day-ahead market where these data are freely available. The websites we used to gather the data are:
Nord Pool: Nord pool website PJM: PJM website EPEX-FR: ENTSO-E transparency platform + RTE website (French TSO) EPEX-BE: ENTSO-E transparency platform + RTE website (French TSO) + Elia website (Belgian TSO) EPEX-DE: ENTSO-E transparency platform + Amprion TSO website + TenneT website + 50Hertz website
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TwitterEnergy 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 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
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Dataset Description Title: Electricity Market Dataset for Long-Term Forecasting (2018–2024)
Overview: This dataset provides a comprehensive collection of electricity market data, focusing on long-term forecasting and strategic planning in the energy sector. The data is derived from real-world electricity market records and policy reports from Germany, specifically the Frankfurt region, a major European energy hub. It includes hourly observations spanning from January 1, 2018, to December 31, 2024, covering key economic, environmental, and operational factors that influence electricity market dynamics. This dataset is ideal for predictive modeling tasks such as electricity price forecasting, renewable energy integration planning, and market risk assessment.
Features Description Feature Name Description Type Timestamp The timestamp for each hourly observation. Datetime Historical_Electricity_Prices Hourly historical electricity prices in the Frankfurt market. Continuous (Float) Projected_Electricity_Prices Forecasted electricity prices (short, medium, long term). Continuous (Float) Inflation_Rates Hourly inflation rate trends impacting energy markets. Continuous (Float) GDP_Growth_Rate Hourly GDP growth rate trends for Germany. Continuous (Float) Energy_Market_Demand Hourly electricity demand across all sectors. Continuous (Float) Renewable_Investment_Costs Investment costs (capital and operational) for renewable energy projects. Continuous (Float) Fossil_Fuel_Costs Costs for fossil fuels like coal, oil, and natural gas. Continuous (Float) Electricity_Export_Prices Prices for electricity exports from Germany to neighboring regions. Continuous (Float) Market_Elasticity Sensitivity of electricity demand to price changes. Continuous (Float) Energy_Production_By_Solar Hourly solar energy production. Continuous (Float) Energy_Production_By_Wind Hourly wind energy production. Continuous (Float) Energy_Production_By_Coal Hourly coal-based energy production. Continuous (Float) Energy_Storage_Capacity Available storage capacity (e.g., batteries, pumped hydro). Continuous (Float) GHG_Emissions Hourly greenhouse gas emissions from energy production. Continuous (Float) Renewable_Penetration_Rate Percentage of renewable energy in total energy production. Continuous (Float) Regulatory_Policies Categorical representation of regulatory impact on electricity markets (e.g., Low, Medium, High). Categorical Energy_Access_Data Categorization of energy accessibility (Urban or Rural). Categorical LCOE Levelized Cost of Energy by source. Continuous (Float) ROI Return on investment for energy projects. Continuous (Float) Net_Present_Value Net present value of proposed energy projects. Continuous (Float) Population_Growth Population growth rate trends impacting energy demand. Continuous (Float) Optimal_Energy_Mix Suggested optimal mix of renewable, non-renewable, and nuclear energy. Continuous (Float) Electricity_Price_Forecast Predicted electricity prices based on various factors. Continuous (Float) Project_Risk_Analysis Categorical analysis of project risks (Low, Medium, High). Categorical Investment_Feasibility Indicator of the feasibility of energy investments. Continuous (Float) Use Cases Electricity Price Forecasting: Utilize historical and projected price trends to predict future electricity prices. Project Risk Classification: Categorize projects into risk levels for better decision-making. Optimal Energy Mix Analysis: Analyze the balance between renewable, non-renewable, and nuclear energy sources. Policy Impact Assessment: Study the effect of regulatory and market policies on energy planning. Long-Term Strategic Planning: Provide insights into investment feasibility, GHG emission reduction, and energy market dynamics. Acknowledgment This dataset is based on publicly available records and market data specific to the Frankfurt region, Germany. The dataset is designed for research and educational purposes in energy informatics, computational intelligence, and long-term forecasting.
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TwitterAs of December 2024, Guatemala had the highest household electricity price among Latin American countries, with an average of **** U.S. dollars per kilowatt-hour. Argentina reported the lowest rate among the countries displayed, at less than **** U.S. dollars per kilowatt-hour. Electricity prices across the American continent Electricity prices vary considerably across the American continent. The Caribbean country of Jamaica accounted for the highest household electricity price on the continent, after Guatemala and Uruguay, at **** U.S. dollars per kilowatt-hour. In comparison, the residential electricity price in the United States amounted to approximately **** U.S. dollars per kilowatt-hour, like in Brazil. Global electricity prices After recovering from the global energy crisis, global electricity prices fell in most countries worldwide. The wildest price spikes occurred in countries that heavily rely on fossil fuels and energy imports, like the European countries. In some cases, price caps set by governmental institutions kept domestic electricity prices under a certain threshold, such as in Brazil.
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TwitterHistorical electricity data series updated annually in July alongside the publication of the Digest of United Kingdom Energy Statistics (DUKES).
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TwitterTable comparing electricity prices per kWh and their annual changes in France, Germany, Spain, and Italy, highlighting the variations across European countries. Source: Eurostat.
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TwitterQuarterly statistical publication containing tables, charts and commentary covering energy prices to domestic and industrial consumers for all the major fuels, as well as presenting comparisons of fuel prices in the EU and G7 countries.
Annexes A to D are now included in the main publication.
We no longer publish a separate copy of the combined tables: we have included links to the QEP tables from the main document.
If you have questions about this content, please email: energyprices.stats@energysecurity.gov.uk
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Comparison of average electricity prices for residential and industrial use in various countries
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TwitterAnnual national average electricity prices, in euro per kWh, charged to medium size households (annual consumption between 2500 and 5000 kWh) and medium size non-household consumers (annual consumption between 500 MWh and 2000 MWh). Prices include energy, supply and network costs, plus VAT and the rest of taxes.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
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Twitterhttps://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/
This report analyses the electricity prices paid by industrial consumers in the United Kingdom. The data is sourced from the Department for Energy Security and Net Zero in addition to estimates by IBISWorld. The data is presented as the average price paid during a financial year (April to March) by a medium-sized industrial consumer (an industrial company with an annual consumption between 2000 and 20000 MWh). This price includes environmental taxes and levies but excludes VAT.
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TwitterIn 2024, Germany recorded the highest residential electricity price for users within Europe, at 44.11 euro cents per kilowatt-hour. This was followed by Ireland, at 36.11 euro cents per kilowatt-hour. Italy, Cyprus, Belgium, Denmark and Czechia were also among the countries with the highest electricity costs.
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TwitterIn 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.