Wholesale electricity prices in the United Kingdom hit a record-high in 2022, reaching **** British pence per kilowatt-hour that year. Projections indicate that prices are bound to decrease steadily in the next few years, falling under **** pence per kilowatt-hour by 2030.

UK Electricity decreased 23.24 GBP/MWh or 22.68% 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.

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.

Electricity 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.

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.

The price of gas in the United Kingdom was *** British pence per therm in the fourth quarter of 2024. It is anticipated gas prices will increase to *** pence in the second quarter of 2025 before gradually falling to just under ** pence by the second quarter of 2027.
Surging energy costs and the cost of living crisis At the height of the UK's cost of living crisis in 2022, approximately ** percent of UK households were experiencing rising prices compared with the previous month. It was during 2022 that the UK's CPI inflation rate reached a peak of **** percent, in October of that year. Food and energy, in particular, were the main drivers of inflation during this period, with energy inflation reaching **** percent, and food prices increasing by **** percent at the height of the crisis. Although prices fell to more expected levels by 2024, an uptick in inflation is forecast for 2025, with prices rising by *** percent in the third quarter of the year. Global Inflation Crisis The UK was not alone in suffering rapid inflation during this time period, with several countries across the world experiencing an inflation crisis. The roots of the crisis began as the global economy gradually emerged from the COVID-19 pandemic in 2021. Blocked-up supply chains, struggled to recover as quickly as consumer demand, with food and energy prices also facing upward pressure. Russia's invasion of Ukraine in February 2022 led to Europe gradually weening itself of cheap Russian energy exports, while for several months Ukraine struggled to export crucial food supplies to the rest of the World.

A survey conducted by the UK Department for Energy Security and Net Zero (DESNZ) in 2023 found that some 91 percent of UK residents were concerned about energy price hikes. Between 2012 and 2023, the level of concern increased. For instance, in 2012, 34 percent of the respondents were not very concerned or not concerned at all about steep rises in energy price in the future.

In 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.

UK Gas fell to 72.60 GBp/thm on December 2, 2025, down 1.67% from the previous day. Over the past month, UK Gas's price has fallen 11.75%, and is down 40.33% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. UK Natural Gas - values, historical data, forecasts and news - updated on December of 2025.

Spain Electricity decreased 65.44 EUR/MWh or 48.17% 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.

UK Wind Power Market size was valued at USD 39.3 Billion in 2024 and is projected to reach USD 95.3 Billion by 2032, growing at a CAGR of 11.7% from 2025 to 2032.

Key Market Drivers:

Rising Electricity Demand: Rising electricity demand is pushing the UK wind energy market. The growing electrification of transportation and heating is raising renewable energy demand. According to National Grid’s Future Energy Scenarios 2023, the UK’s annual power demand might increase by up to 70% by 2035, reaching 460-500 TWh.

Cost Reduction in Wind Technology: Cost reductions in wind technologies will propel the UK Wind Power Market. Wind power technology has become more competitive with traditional energy sources as its costs have decreased. According to the UK Department for Business, Energy, and Industrial Strategy (BEIS), the strike price for offshore wind in Contract for Difference (CfD) auctions has plummeted from £114.39/MWh in 2015 to £37.35/MWh in 2022, a 67% decrease.

Peer-to-peer (P2P) energy sharing involves novel technologies and business models at the demand-side of power systems, which is able to manage the increasing connection of distributed energy resources (DERs). In P2P energy sharing, prosumers directly trade energy with each other to achieve a win-win outcome. A research paper titled "Evaluation of peer-to-peer energy sharing mechanisms based on a multiagent simulation framework" has been published on Applied Energy regarding this topic. In the paper, a general multiagent framework was established to simulate P2P energy sharing, with two original techniques proposed to facilitate simulation convergence. Furthermore, a systematic index system was established to evaluate P2P energy sharing mechanisms from both economic and technical perspectives.In case studies of the paper, two sets of cases were conducted to validate the proposed simulation and evaluation methods and to give some practical implications on applying P2P energy sharing in Great Britain (GB) at present and in the future. The household demand dataset and electric vehicle (EV) dataset used in the paper has been provided for researchers to reproduce the results in the paper or to conduct further related studies. Also, the original numerical data of the results in the case studies of the paper have been provided, for researchers to better understand the results or to use the results for other purposes.The whole dataset includes 9 excel files in total. The detailed description for them are presented as follows:1. “CREST_Demand_Model_v2.2 (Great Britain).xlsm” is a high-resolution stochastic integrated thermal-electrical domestic demand simulation tool developed by Centre for Renewable Energy Systems Technology (CREST) of Loughborough University (refering to http://www.lboro.ac.uk/research/crest/demand-model/). It contains a lot of sheets and VBA codes, which are used to generate “fake” demand curves of domestic customers sampled from statistical distributions that are based on real-life data. In the “Main Sheet”, input parameters like “day of month”, “month of year”, “latitude”, “longitude”, etc. can be entered, and then the “Run simulation” button can be clicked to start the simulation. After the simulation, daily curves like “occupancy and activity”, “total electrical demand”, “total gas demand”, etc. are generated and visualized, with very high time resolution.2. “Electric_Vehicle_Dataset (Great Britain).xlsx” is a dataset based on the research conducted jointly by Centre for Integrated Renewable Energy of Cardiff University and Key Laboratory of Smart Grid of Ministry of Education of Tianjin University (referring to https://doi.org/10.1016/j.apenergy.2015.10.159). It contains two sheets, which provide the parameters of 1000 typical electric vehicles of Great Britain respectively. For each electric vehicle, the parameters include: (1) “Time starting charging / returning home (hour)”, (2) “Time finishing charging / leaving home (hour)”, (3) “Battery capacity (kWh)”, (4) “Energy consumption due to travel (measured by SOC)”, (5) “Lowerlimit of SOC”, (6) “Upperlimit of SOC”, (7) “Maximum charging/discharging power”, (8) “Charging efficiency”, and (9) “Discharging efficiency”.3. “Numerical results and figures _ Case 1-1.xlsx” provides the numerical results of Case 1-1 of the paper. It contains three sheets, providing the data behind Fig. 6, Fig. 7 and Fig. 8 of the paper respectively. In the “Fig. 6” sheet, the “Total Net Consumption (kWh)” and “Total PV Generation (kWh)” under “SDR mechanism” and “conventional paradigm” are provided. In the “Fig. 7” sheet, the “Net energy cost under SDR mechanism (£)” and “Net energy cost under conventional paradigm (£)” of each prosumer are provided. In the “Fig. 8” sheet, the “Internal selling price (£/MWh)”, “Internal buying price (£/MWh)” and “Total Net Energy Cost (£)” of each iteration are provided.4. “Numerical results and figures _ Case 1-2.xlsx” provides the numerical results of Case 1-2 of the paper. It contains two sheets, providing the data behind Fig. 9, Fig. 10 and Fig. 11 of the paper. In the “Fig. 9 and 10” sheet, for Fig. 9, the “The iteration at which the simulation stopped” given different ramping rates are provided; for Fig. 10, the “Overall Performance Index” with different ramping rates given different demand profiles are provided. In the “Fig. 11” sheet, the “Total net energy cost (ramping rate = 0.3) (£)” and “Total Net Energy Cost (ramping rate = 0.6) (£)” at each iteration are provided.5. “Numerical results and figures _ Case 1-3.xlsx” provides the numerical results of Case 1-3 of the paper. It contains only one sheets, providing the data behind Fig. 12 of the paper. In the “Fig. 12” sheet, the “Overall Performance Index” with different learning rates given different demand profiles are provided.6. “Numerical results and figures _ Case 1-4.xlsx” provides the numerical results of Case 1-4 of the paper. It contains two sheets, providing the data behind Fig. 13 and Fig. 14 of the paper. In the “Fig. 13” sheet, the “Overall Performance Index” with different ramping rates given different initial values are provided. In the “Fig. 14” sheet, the “Overall Performance Index” with different learning rates given different initial values are provided.7. “Numerical results and figures _ Case 1-5.xlsx” provides the numerical results of Case 1-5 of the paper. It contains only one sheet, providing the data behind Fig. 15 and Fig. 16 of the paper. In the “Fig. 15 and 16” sheet, for Fig. 15, the number of iterations when the simulation stopped given different maximum number of iterations and ramping rates are provided; for Fig. 16, the overall performance given different maximum number of iterations and ramping rates are provided.8. “Numerical results and figures _ Case 2-2.xlsx” provides the numerical results of Case 2-2 of the paper. It contains only one sheet, providing the data behind Fig. 17 of the paper. In the “Fig. 17” sheet, the overall performance scores of the three mechanisms (SDR, MMR and BS) and conventional paradigm in scenarios with different PV and EV penetration levels are provided.

1. “Numerical results and figures _ Appendix B.xlsx” provides the numerical results of the cases in Appendix B of the paper. It contains two sheets, providing the data behind Fig. B1, Fig. B2, Fig. B3 and Fig. B4 of the paper. In the “Fig. B1 and B2” sheet, for Fig. B1, the EWH power consumption (kW) at t=1 and t=2 for each iteration without any techniques for convergence are provided; for Fig. B2, the Internal buying price (pence/kWh) at t=1 and t=2 without any techniques for convergence are provided. In the “Fig. B3 and B4” sheet, for Fig. B1, the EWH power consumption (kW) at t=1 and t=2 for each iteration with a limitation for its power change are provided; for Fig. B2, the Internal buying price (pence/kWh) at t=1 and t=2 with a limitation for its power change are provided.Research results based upon these data are published at https://doi.org/10.1016/j.apenergy.2018.02.089

According to Cognitive Market Research, the global Electricity Generation market size was USD 2154.2 million in 2024. It will expand at a compound annual growth rate (CAGR) of 9.80% 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 861.68 million in 2024 and will grow at a compound annual growth rate (CAGR) of 8.0% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 646.26 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 495.47 million in 2024 and will grow at a compound annual growth rate (CAGR) of 11.8% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 107.71 million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.2% 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 43.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.5% from 2024 to 2031.
Thermal Generation is the market leader in the Electricity Generation industry

Market Dynamics of Electricity Generation Market

Key Drivers for Electricity Generation Market

Rising need for cooling boosts the electricity generation market: The increased demand for cooling is projected to drive the electricity generating market in the future years. Cooling is the process of lowering the temperature of an object or environment, which is usually accomplished by transporting heat away from the intended location, typically utilizing air or a cooling medium. Power generation can be utilized to cool by running air conditioning (AC) and fans to keep indoor temperatures comfortable. For instance, According to the International Energy Agency, an autonomous intergovernmental body located in France, in July 2023, more than 90% of households in the United States and Japan had an air conditioner. Cooling accounts for around 10% of global electricity use. In warmer countries, this might result in a more than 50% increase in power demand during the summer months. As a result, increased demand for cooling is likely to drive expansion in the power generating industry.

Increasing applications of electricity in the transportation industry: The growing use of energy in the transportation industry is predicted to increase demand for electricity, hence pushing the power generation market. The electrification of railways in underdeveloped and developing countries, the establishment of public transportation networks such as rapid metro transit systems, and the growing use of electric vehicles in developed countries will all create significant market opportunities for power generation companies. For instance, in order to achieve net-zero carbon emissions, the Office of Rail and Road (ORR) predicts that 13,000 track kilometers - or roughly 450 km per year - of track in the UK will need to be electrified by 2050, with 179 km electrified between 2020 and 2021. According to the Edison Electric Institute (EEl), yearly electric car sales in the United States are estimated to exceed 1.2 million by 2025. Electric vehicles are projected to account for 9% of worldwide electricity demand by 2050.

Restraint Factor for the Electricity Generation Market

High initial capital investment for renewable projects: The high initial capital for renewable projects is indeed a limiting factor for the market growth of the electricity generation sector, as most such technologies, infrastructure, and installation depend on significant up-front funding. For instance, most renewable energy technologies are highly capital intensive-solar, and wind, in particular, scares investors away from taking action, especially if they are small or developing firms. There is thus an economic limitation that restricts competition and contributes toward slower development of cleaner energy solutions. Moreover, funding can be quite tricky and challenging-especially for a poor economic climate. The payback times attached to these investment options are long, leading to uncertainty and making stakeholders reluctant to commit. These financial constraints are, therefore, blighting the transition to renewable energy as well as, more broadly, the overall electricity generation market

Trends for the Electri...

Energy consumption readings for a sample of 5,567 London Households that took part in the UK Power Networks led Low Carbon London project between November 2011 and February 2014.

Readings were taken at half hourly intervals. Households have been allocated to a CACI Acorn group (2010). The customers in the trial were recruited as a balanced sample representative of the Greater London population.

The dataset contains energy consumption, in kWh (per half hour), unique household identifier, date and time, and CACI Acorn group. The CSV file is around 10GB when unzipped and contains around 167million rows.

Within the data set are two groups of customers. The first is a sub-group, of approximately 1100 customers, who were subjected to Dynamic Time of Use (dToU) energy prices throughout the 2013 calendar year period. The tariff prices were given a day ahead via the Smart Meter IHD (In Home Display) or text message to mobile phone. Customers were issued High (67.20p/kWh), Low (3.99p/kWh) or normal (11.76p/kWh) price signals and the times of day these applied. The dates/times and the price signal schedule is availaible as part of this dataset. All non-Time of Use customers were on a flat rate tariff of 14.228pence/kWh.

The signals given were designed to be representative of the types of signal that may be used in the future to manage both high renewable generation (supply following) operation and also test the potential to use high price signals to reduce stress on local distribution grids during periods of stress.

The remaining sample of approximately 4500 customers energy consumption readings were not subject to the dToU tariff.

More information can be found on the Low Carbon London webpage

Some analysis of this data can be seen here.

This dataset includes the future CfD generation weighted average strike prices (£/MWh) estimated by LCCC using 2020 real prices. It also includes the weighted average strike prices for the whole CfD portfolio including bespoke contracts, investment contracts, CfDs awarded under different allocation rounds to date and annual forecast market prices estimated by DESNZ (Annex m price growth assumption 16 May 2019) This dataset is updated following the end of each financial year.

The objective of the project was to provide econometric analysis and theory for modelling energy and soft commodity prices. This necessitated data analysis and modelling together with theoretical econometrics, dealing with the specific stylised facts of commodity prices. In order to analyse energy and soft commodity prices, the determination of spot energy prices in regulated markets was first considered, from the point of view of the regulator. Direct data analysis of futures commodity prices was then undertaken, resulting in the collection of an extensive dataset of most traded futures commodity prices at a daily frequency, covering 16 different commodities over a 10-year period.

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Demand Response (DR) Market Size 2025-2029

The demand response (dr) market size is forecast to increase by USD 3.3 billion, at a CAGR of 8.4% between 2024 and 2029.

Major Market Trends & Insights

North America dominated the market and accounted for a 59% growth during the forecast period.
By the Product - Hardware and software segment was valued at USD 4.36 billion in 2023
By the End-user - Industrial segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 87.49 billion
Market Future Opportunities: USD USD 3.3 billion 
CAGR : 8.4%
North America: Largest market in 2023

Market Summary

The market is witnessing significant growth as businesses and utilities seek innovative solutions to address the increasing gap between electricity supply and demand. According to recent studies, the global DR market is projected to reach a value of USD38.3 billion by 2026, expanding at a steady pace. This expansion is driven by the integration of renewable energy sources and the growing adoption of smart grid technologies. DR programs enable energy consumers to adjust their electricity usage in response to changes in the grid's conditions. By reducing peak demand, these programs help prevent power outages and improve grid stability. In the industrial sector, DR has gained traction due to its potential to reduce energy costs and improve operational efficiency. For instance, a study by the Lawrence Berkeley National Laboratory found that DR programs could save the US industrial sector up to USD20 billion annually. Moreover, the advent of the Internet of Things (IoT) is expected to further fuel the growth of the DR market. IoT-enabled devices can provide real-time data on energy usage, enabling utilities to optimize energy distribution and consumers to adjust their usage accordingly. However, the increasing threat of cyberattacks on IoT devices poses a challenge to the market's growth. Despite this, the benefits of DR far outweigh the risks, making it an essential component of modern energy systems.

What will be the Size of the Demand Response (DR) Market during the forecast period?

Explore market size, adoption trends, and growth potential for demand response (dr) market Request Free SampleThe market represents a significant opportunity for businesses to optimize energy usage and reduce costs without fail. According to recent data, approximately 20% of the total electricity consumption in the US is currently managed through DR programs. Looking forward, future growth is anticipated, with expectations of a 15% compound annual increase in DR participation over the next five years. A comparison of key numerical data highlights the potential impact of DR. For instance, DR programs have led to an average of 10% reduction in peak electricity demand, providing essential network congestion relief. Furthermore, DR technology deployment has resulted in an average of 12% system efficiency gains, contributing significantly to grid reliability improvement. These figures underscore the substantial benefits of DR, including emissions reduction, cost savings, and grid service provision. By integrating advanced metering infrastructure, load control devices, and energy management systems, businesses can effectively participate in capacity market bidding and event-driven load control. Additionally, DR aggregator platforms enable real-time data acquisition and building controls optimization, offering energy arbitrage opportunities and industrial automation system enhancements. In conclusion, the DR market offers businesses a valuable opportunity to optimize energy usage, reduce costs, and contribute to grid reliability. With increasing participation rates and continuous technological advancements, the potential for growth and innovation is significant.

How is this Demand Response (DR) Industry segmented?

The demand response (dr) industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ProductHardware and softwareServiceEnd-userIndustrialResidentialCommercialGovernment BuildingsHospitalsData CentersAgricultureSolution TypeResidential DRMSCommercial DRMSIndustrial DRMSDeployment TypeAutomated Demand Response (ADR)Conventional Demand ResponseApplicationPeak Load ManagementGrid BalancingRenewable Energy IntegrationGeographyNorth AmericaUSCanadaEuropeFranceGermanyUKMiddle East and AfricaUAEAPACChinaIndiaJapanSouth AmericaBrazilRest of World (ROW)

By Product Insights

The hardware and software segment is estimated to witness significant growth during the forecast period.

In the market, microgrid optimization and dynamic pricing mechanisms have emerged as key trends. Predictive load forecasting an