Germany Electricity decreased 30.21 EUR/MWh or 26.10% since the beginning of 2025, according to the latest spot benchmarks offered by sellers to buyers priced in megawatt hour (MWh). This dataset includes a chart with historical data for Germany Electricity Price.

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.

France Electricity decreased 6.25 EUR/MWh or 8.95% since the beginning of 2025, according to the latest spot benchmarks offered by sellers to buyers priced in megawatt hour (MWh). This dataset includes a chart with historical data for France Electricity Price.

Italy Electricity decreased 11.30 EUR/MWh or 8.20% since the beginning of 2025, according to the latest spot benchmarks offered by sellers to buyers priced in megawatt hour (MWh). This dataset includes a chart with historical data for Italy Electricity Price.

IMPORTANT! PLEASE READ DISCLAIMER BEFORE USING DATA. This dataset backcasts estimated modeled savings for a subset of 2007-2012 completed projects in the Home Performance with ENERGY STAR® Program against normalized savings calculated by an open source energy efficiency meter available at https://www.openee.io/. Open source code uses utility-grade metered consumption to weather-normalize the pre- and post-consumption data using standard methods with no discretionary independent variables. The open source energy efficiency meter allows private companies, utilities, and regulators to calculate energy savings from energy efficiency retrofits with increased confidence and replicability of results. This dataset is intended to lay a foundation for future innovation and deployment of the open source energy efficiency meter across the residential energy sector, and to help inform stakeholders interested in pay for performance programs, where providers are paid for realizing measurable weather-normalized results. To download the open source code, please visit the website at https://github.com/openeemeter/eemeter/releases D I S C L A I M E R: Normalized Savings using open source OEE meter. Several data elements, including, Evaluated Annual Elecric Savings (kWh), Evaluated Annual Gas Savings (MMBtu), Pre-retrofit Baseline Electric (kWh), Pre-retrofit Baseline Gas (MMBtu), Post-retrofit Usage Electric (kWh), and Post-retrofit Usage Gas (MMBtu) are direct outputs from the open source OEE meter. Home Performance with ENERGY STAR® Estimated Savings. Several data elements, including, Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, and Estimated First Year Energy Savings represent contractor-reported savings derived from energy modeling software calculations and not actual realized energy savings. The accuracy of the Estimated Annual kWh Savings and Estimated Annual MMBtu Savings for projects has been evaluated by an independent third party. The results of the Home Performance with ENERGY STAR impact analysis indicate that, on average, actual savings amount to 35 percent of the Estimated Annual kWh Savings and 65 percent of the Estimated Annual MMBtu Savings. For more information, please refer to the Evaluation Report published on NYSERDA’s website at: http://www.nyserda.ny.gov/-/media/Files/Publications/PPSER/Program-Evaluation/2012ContractorReports/2012-HPwES-Impact-Report-with-Appendices.pdf. This dataset includes the following data points for a subset of projects completed in 2007-2012: Contractor ID, Project County, Project City, Project ZIP, Climate Zone, Weather Station, Weather Station-Normalization, Project Completion Date, Customer Type, Size of Home, Volume of Home, Number of Units, Year Home Built, Total Project Cost, Contractor Incentive, Total Incentives, Amount Financed through Program, Estimated Annual kWh Savings, Estimated Annual MMBtu Savings, Estimated First Year Energy Savings, Evaluated Annual Electric Savings (kWh), Evaluated Annual Gas Savings (MMBtu), Pre-retrofit Baseline Electric (kWh), Pre-retrofit Baseline Gas (MMBtu), Post-retrofit Usage Electric (kWh), Post-retrofit Usage Gas (MMBtu), Central Hudson, Consolidated Edison, LIPA, National Grid, National Fuel Gas, New York State Electric and Gas, Orange and Rockland, Rochester Gas and Electric. 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 ELECTRICITY PRICE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Over the past half a century, the world's electricity consumption has continuously grown, reaching approximately 27,000 terawatt-hours by 2023. Between 1980 and 2023, electricity consumption more than tripled, while the global population reached eight billion people. Growth in industrialization and electricity access across the globe have further boosted electricity demand. China's economic rise and growth in global power use Since 2000, China's GDP has recorded an astonishing 15-fold increase, turning it into the second-largest global economy, behind only the United States. To fuel the development of its billion-strong population and various manufacturing industries, China requires more energy than any other country. As a result, it has become the largest electricity consumer in the world. Electricity consumption per capita In terms of per capita electricity consumption, China and other BRIC countries are still vastly outpaced by developed economies with smaller population sizes. Iceland, with a population of less than half a million inhabitants, consumes by far the most electricity per person in the world. Norway, Qatar, Canada, and the United States also have among the highest consumption rates. Multiple contributing factors such as the existence of power-intensive industries, household sizes, living situations, appliance and efficiency standards, and access to alternative heating fuels determine the amount of electricity the average person requires in each country.

United States Electricity: Average Retail Price: EIA: Residential data was reported at 13.300 0.01 USD/kWh in Aug 2018. This records an increase from the previous number of 13.130 0.01 USD/kWh for Jul 2018. United States Electricity: Average Retail Price: EIA: Residential data is updated monthly, averaging 8.590 0.01 USD/kWh from Jul 1976 (Median) to Aug 2018, with 434 observations. The data reached an all-time high of 13.300 0.01 USD/kWh in Aug 2018 and a record low of 3.600 0.01 USD/kWh in Jan 1977. United States Electricity: Average Retail Price: EIA: Residential data remains active status in CEIC and is reported by Energy Information Administration. The data is categorized under Global Database’s United States – Table US.P002: Energy Price.

Indonesia Electricity: Average Price: Total data was reported at 1,123.010 IDR/kWh in 2018. This records an increase from the previous number of 1,105.110 IDR/kWh for 2017. Indonesia Electricity: Average Price: Total data is updated yearly, averaging 628.140 IDR/kWh from Dec 1994 (Median) to 2018, with 25 observations. The data reached an all-time high of 1,123.010 IDR/kWh in 2018 and a record low of 154.280 IDR/kWh in 1994. Indonesia Electricity: Average Price: Total data remains active status in CEIC and is reported by State Electricity Company. The data is categorized under Global Database’s Indonesia – Table ID.RBH001: Average Price: Electricity.

Japan JP: Residential Electricity Price: USD per kWh data was reported at 0.330 USD/kWh in 2022. This records an increase from the previous number of 0.260 USD/kWh for 2021. Japan JP: Residential Electricity Price: USD per kWh data is updated yearly, averaging 0.220 USD/kWh from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 0.330 USD/kWh in 2022 and a record low of 0.190 USD/kWh in 2002. Japan JP: Residential Electricity Price: USD per kWh data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Japan – Table JP.OECD.GGI: Environmental: Environmental Policy, Taxes and Transfers: OECD Member: Annual.

Spain Electricity decreased 36.23 EUR/MWh or 26.67% since the beginning of 2025, according to the latest spot benchmarks offered by sellers to buyers priced in megawatt hour (MWh). This dataset includes a chart with historical data for Spain Electricity Price.

Note: Find data at source. ・ Federal and state decarbonization goals have led to numerous financial incentives and policies designed to increase access and adoption of renewable energy systems. In combination with the declining cost of both solar photovoltaic and battery energy storage systems and rising electric utility rates, residential renewable adoption has become more favorable than ever. However, not all states provide the same opportunity for cost recovery, and the complicated and changing policy and utility landscape can make it difficult for households to make an informed decision on whether to install a renewable system. This paper is intended to provide a guide to households considering renewable adoption by introducing relevant factors that influence renewable system performance and payback, summarized in a state lookup table for quick reference. Five states are chosen as case studies to perform economic optimizations based on net metering policy, utility rate structure, and average electric utility price; these states are selected to be representative of the possible combinations of factors to aid in the decision-making process for customers in all states. The results of this analysis highlight the dual importance of both state support for renewables and price signals, as the benefits of residential renewable systems are best realized in states with net metering policies facing the challenge of above-average electric utility rates.This dataset is intended to allow readers to reproduce and customize the analysis performed in this work to their benefit. Suggested modifications include: location, household load profile, rate tariff structure, and renewable energy system design.

Brazil Energy: Average Current Prices: Source: Electricity: Industry data was reported at 268.117 USD/BOE in 2023. This records an increase from the previous number of 261.376 USD/BOE for 2022. Brazil Energy: Average Current Prices: Source: Electricity: Industry data is updated yearly, averaging 93.215 USD/BOE from Dec 1973 (Median) to 2023, with 51 observations. The data reached an all-time high of 300.176 USD/BOE in 2015 and a record low of 36.812 USD/BOE in 1973. Brazil Energy: Average Current Prices: Source: Electricity: Industry data remains active status in CEIC and is reported by Ministry of Mining and Energy. The data is categorized under Global Database’s Brazil – Table BR.PE001: Average Current and Constant Price. In order to keep the series, is adopted boe based on higher heating value of the source.

UK Electricity decreased 29.45 GBP/MWh or 28.75% since the beginning of 2025, according to the latest spot benchmarks offered by sellers to buyers priced in megawatt hour (MWh). This dataset includes a chart with historical data for the United Kingdom Electricity Price.

Context

These data were collected and disseminated according to this publication: https://www.nature.com/articles/s41597-020-00582-3

All descriptors below are taken from this publication and are copyright of the authors.

Abstract

This paper describes the release of the detailed building operation data, including electricity consumption and indoor environmental measurements, of the seven-story 11,700-m2 office building located in Bangkok, Thailand. The electricity consumption data (kW) are that of individual air conditioning units, lighting, and plug loads in each of the 33 zones of the building. The indoor environmental sensor data comprise temperature (°C), relative humidity (%), and ambient light (lux) measurements of the same zones. The entire datasets are available at one-minute intervals for the period of 18 months from July 1, 2018, to December 31, 2019. Such datasets can be used to support a wide range of applications, such as zone-level, floor-level, and building-level load forecasting, indoor thermal model development, validation of building simulation models, development of demand response algorithms by load type, anomaly detection methods, and reinforcement learning algorithms for control of multiple AC units.

Background

The global energy consumption of the building sector, which includes both commercial and residential buildings, is about 20%. With the rapid increase in population as well as economic growth, energy consumption in buildings is projected to increase at the rate of 1.3% per year from 2018 to 2050; this growing energy demand has raised significant concerns worldwide of its negative impact on the environment. In order to meet the rising electricity demand, an efficient and cost effective operation is needed.

The uniqueness of the CU-BEMS dataset described in this paper is the breakdown of building-level electricity consumption (kW) into each zone and each floor of the building. The CU-BEMS dataset captures the operation of individual AC units, lighting, and plug loads in each zone of the building at one-minute intervals. These are three major loads in commercial buildings. In addition, corresponding indoor environmental sensor data (temperature, humidity, and ambient light) are also measured in each zone at one-minute intervals.

Methods

In mid-2018, CU-BEMS –the building energy management system, developed at Chulalongkorn University using an open standard IEEE1888, was installed at the seven-story academic office building located at Chulalongkorn University. The building has an area of around 11,700 square meters (126,000 sqft) with a peak load of about 700 kW. The overall CU-BEMS system comprises Energy Monitoring Units (EMU), digital meters, multi-sensors, gateways and a CU-BEMS server.

Energy Monitoring Unit (EMU) An EMU is a communicating electrical meter that can measure power consumption of up to 36 circuits and communicate via Ethernet LAN with Modbus protocol. An EMU comprises potential transformers, a microcontroller module and an Ethernet-based communication module. An EMU can connect to up to 36 external current transformers (CT, rating up to 60 Ampere). Based on current and voltage readings, the built-in microcontroller unit calculates power consumption (Watts). Then, the Ethernet module transfers the calculated electricity consumption to the CU-BEMS server using an open standard IEEE 1888 protocol.

Digital Meter Each digital meter used is a commercial off-the-shelf product (Siemens SENTRON PAC3100), which provides basic metering and monitoring applications. It provides open communications using Modbus RTU over RS485 interface. It measures current, voltage, and provides real, reactive power measurements, meeting ANSI C12.16 (accuracy class 1.0, i.e., typical error of 1%) specification for revenue meters.

Multi-sensors Multi-sensors have been designed to measure temperature (0 °C − 90 °C ± 0.4 °C), humidity (0–100%RH ± 2%RH) and ambient light (0.11 − 10000lux). Hence, it comprises temperature, humidity and ambient light sensors, as well as a Wi-Fi communication module.

Gateway CU-BEMS gateways have been developed in house to gather data from multi-sensors. Each gateway comprises a microprocessor and an Ethernet module. It has been designed to collect data at one-minute intervals.

Data Records

The entire datasets are divided into 14 comma-separated value (csv) files according to the floor and year of the data recorded. Note that one CSV file is provided for each floor of the building. This makes the total of seven CSV files for each year. Since each file does include data of each zone on a single floor, a user has the flexibility to work with any individual zones, which can be extracted (based on the column names) from the CSV files.

Each file combines the measurements available in each zone on the same floor of the building in a parti...

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.

Data available from: January 2021

Status of the figures: When first published, the figures are provisional. These will become definitive with the following month’s publication.

Changes compared with previous version: Data on the most recent period have been added and/or adjustments have been implemented.

When will new figures be published? New figures will usually be published between the first and second Thursday of the month.