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The annual State of the Sector report is a dataset about the community energy sector. It has always covered England and Wales, and in 2021 include Scottish data for the first time. Reports detail the data from the community energy sector in the previous year.

The European Environment Agency provides sound, independent information on the environment for those involved in developing, adopting, implementing and evaluating environmental policy, and also the general public. The site includes interactive data viewers for datasets. There are also visualizations on specific topics such as Progress on Energy Efficiency in Europe, and publications. A major information source for those involved in developing, adopting, implementing and evaluating environmental policy, and also the general public. Currently, the EEA has 33 member countries. The website is available in a wide range of languages. There is a Semantic Data Service, allowing access to datasets using APIs, but datasets can also be downloaded as zip files and INSPIRE-compliant metadata sets. No registration is needed, but on download, some usage feedback is requested.

Levelised unit cost data (£/MWh 2006) for electricity generation from various primary energy sources in various countries. Unit cost“relevance” rating. Plant types comprise: Coal, Nuclear, Gas, Wind, Coal (other), CHP, PV, Gas (other), Biomass & Energy Crops, Hydro, Waste, Wind (offshore), Geothermal, Solar Thermal, Wave & Tidal Stream, Fossil Fuel (other), Fuel cell, Nuclear (other). The database is in Heptonstall2007_LevelisedElectricityCostData.xls
Contains information for Australia, Austria, Belgium, Brazil, Canada, China, Czech Republic, Denmark, Finland, France, Germany, Greece, India, Indonesia, Italy, Japan, Mexico, Netherlands, New Zealand, Portugal, Spain, Romania, Slovakia, South Africa, South Korea, Sweden, Switzerland, Turkey, UK, USA
A full list of references with links to original documents is provided in "A Review of Electricity Unit Cost Estimates" (PDF 300 KB)

A forecast of electricity use in the UK in the next ten years, with different scenarios base on different assumptions about demand, supply and European interconnection. Published annually. The PDF report gives the overview and scenario forecasts. All the supporting data is downloadable to Excel.

As well as linking to the OECD Data statistics, this includes statistics from other sources such as the IEA, Nuclear Energy Agency and EUROSTAT, indicator information, factbook and yearbook series and other analyses and syntheses. Differs from the OECD Data offering as it draws on more sources and covers a wider range of countries. Acts as a federated search rather than holding its own datasets. However, there are far more books, papers, factbooks and so on accessible from here.

The Renewable Energy Planning Database (REPD) and the Heat Networks Planning Database are updated and published every quarter. The Renewable Energy Planning Database tracks the progress of renewable electricity and heat networks projects. The Heat Networks Planning Database covers district as well as communal heat network projects. The Renewable Energy Planning Database tracks the progress of renewable electricity and heat networks projects. It provides as accurate and comprehensive a snapshot as possible of projects in both areas, and of progress across the technology sectors.The Heat Networks Planning Database covers district as well as communal heat network projects.It aims to provide a more complete picture of heat network deployment across the UK.
The databases are: updated during the month following the end of each quarter; and are provided in 2 separate CSV files, and on separate worksheets within a single XLSX file.

The Electricity Pool operated from 1st April 1990 to 26th March 2001, controlling the trading of electricity within England and Wales. The Electricity Pool data contains system demand and transmission losses plus the price information (/MWh) within the trading pool, comprising the three main prices: Pool purchase price (PPP), the basis of payments to generators; Pool selling price (PSP), the basis of payments by suppliers; and system marginal price (SMP), the highest offered price for any generating set scheduled by the Pool to run before system constraints are taken into account. The Electricity Pool system was replaced by the New Electricity Trading Arrangements (NETA/BETTA) from 27 March 2001. (Note : It is mandatory to acknowledge the UKERC EDC and the data owner Poolit Ltd when any use of this data is made in publications) Explanation of parameters and pool operation
PSP : Pool Selling Price, is the price paid mostly by RECs purchasing electricity from the Pool to sell to their final commercial, industrial and residential customers; this value is determined for two distinct price-rule regimes referred to as Table A and Table B periods, such that: PSP = SMP + CC + UPLIFT = PPP + UPLIFT
SMP : System Marginal Price is the highest offered price for any generating set scheduled by the Pool before system constraints are taken into account
LOLP : Loss Of Load Probability, a decreasing function of the expected amount of excess capacity available during each half-hour period, determined for each half-hour as the probability of a supply interruption due to generation capacity being insufficient to meet demand (the greater the amount of capacity available relative to expected demand in any half-hour, the lower the LOLP and therefore the lower the capacity charge per KWH paid to generators)
VOLL : Value Of Lost Load, representing the per kWh willingness of customers to pay to avoid supply interruptions; it was set by the Director General of the Office of Electricity Regulation (OFFER) at 2,000 per megawatt-hour (MWH) for 1990/91 and was then increased annually by the growth in the RPI
PPP : Pool Purchase Price, is the price paid to generators for electricity purchased into the Pool
CC : Capacity Charge: CC = LOLP * (VOLL - SMP) is a signal to generators of the necessity for additional generation capacity and to consumers that their consumption has a significant probability of requiring the maximum amount of generating capacity available in that load period
UPLIFT : a charge to compensate generators for reserve, plant available but not actually used to meet demand, and startup costs, known only ex post and therefore the only price uncertainty from the day ahead perspective; it is collected over at least 28 Table A pricing periods each day (UPLIFT is zero for Table B pricing periods) according to the formula: Availability Payment/MWh = LOLP*(VOLL - max(SMP, bid price))

This dataset relates to the modelling component of the UKERC Phase 4 Project '4.2a Investment in infrastructure'. The aim is to assess the scale of investment risks in the electricity generation sector associated with uncertainty over the pathway towards net zero. The model comprises three components:1. Input data. Based in Excel, contains the scenario assumptions on the electricity system including generation technologies, wind and solar power availability, demand profiles, interconnector and storage capacities etc.2. Modelling files based on the open-source Antares modelling framework. This requires additional free software to be able to run the model. The model calculates the hourly dispatch of all types of plant included in the system.3. Excel-based financial model, based on post-processing the output of the Antares model.Additional 1_Metadata.xls, Input_ReadMe and Outputs_ReadMe files explain the method for running each step of the modelling process. Software available at https://antares-simulator.org/. Version used 8.0.2

UNSD maintains the Energy Statistics Database, which provides annual statistics on production, trade, transformation and consumption (end-use) for solid, liquid, and gaseous fuels, electricity, and heat. It contains basic statistics for more than 230 countries/territories from 1950 year onwards and is updated annually. The database contains data in their original units (e.g. metric tonnes, GWh) as well as calorific values to allow interfuel comparison in a common energy unit (terajoules).