Energy Data

Energy data refers to historical, real-time, and predictive analytics on aspects such as energy consumption and possible power outages. It can be used to plan and optimize the application of renewable energy sources and smart energy management among other things. Learn more →
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1 country covered
4 years of historical data
Monthly with 2 month lag. Contains monthly state-level generation by energy source. for India. Energy sources include: Conventional (coal, gas, diesel, hydro...
Meteomatics Weather API
by Meteomatics
Meteomatics
288 updates daily
249 countries covered
41 years of historical data
The Weather API delivers fast, direct, simple access to an extensive range of global weather and environmental data. It allows the integration of high qualit...
249 countries covered
40 years of historical data
Hourly, historical solar data for any global location dating back to 1980
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CustomWeather
Based in USA
CustomWeather
We provide industry-leading weather solutions to a wide range of industries that value quality, customer service, and data accuracy. As a leader in technolog...
85
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Over 80K
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20 Years
of Industry Leadership
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Meteomatics
Based in Switzerland
Meteomatics
Meteomatics weather API delivers fast, direct, simple access to an extensive range of global weather and environmental data. A single API endpoint to acce...
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Earthmetry
Based in India
Earthmetry
Earthmetry accelerates the transition to sustainable use of our planet’s resources by enabling data-driven decision-making. Through our Signals platform, we ...
15+
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100%
ESG focused
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The Ultimate Guide to Energy Data 2021

Learn about energy data analytics, sources, and collection.

What is Energy Data?

Energy Industry data provides information about energy generation, distribution and consumption. Energy data can encompass various sources of energy, including electrical, gas, oil, renewable and nuclear. It is collected using a range of methods, from domestic meter readings to satellite imagery of electricity grids. You might buy energy data to forecast power outages and surges, or to track trends in the energy industry, such as the increased use of bio-fuels and green vehicles.

Who uses Energy Data and for what use cases?

Energy data is useful for both private and public organisations to ensure their energy consumption is as efficient as possible. Governments can use it to digitalise a country’s electricity grid, and to incentivise responsible energy usage by benchmarking one organisation’s consumption against another. Energy data is crucial in planning the construction of power stations or solar and wind farms, where land and climate conditions must be taken into account.

Increasingly, renewable energy suppliers and ‘green’ start-up companies rely on data from the extractive industry so that they can quantify how much of our energy is generated from oil and gas, and ensure that their sustainable alternatives can meet that demand.

What are typical Energy Data attributes?

Attributes of Energy Data can include, but are not limited to:

  • Source of energy (e.g. oil, gas, electrical, renewable)
  • Electricity transmission
  • Solar potential
  • Payments taken for mineral resources
  • Frequency of power outages
  • Building efficiency

How is Energy Data typically collected?

In short, this depends entirely on what information the data provides. For example, household meter readings and supplier bills are sufficient to collect domestic energy data. To collect data from a solar farm, however, solar radiation measurements, solar potential data and previous photovoltaic output statistics have to be collated daily for an extended period of time. Collection methods depend on the technology required to collect the data, and whether collection can be carried out by citizens or is restricted to government institutes.

How can the quality of Energy Data be assessed?

The first step in ascertaining the quality of an energy dataset is to establish where the data vendor got the data from. For example, only companies working in EU countries, the UK, Norway and Canada are legally required to disclose all extractive industry payments, meaning data about oil and gas mining provided by companies working elsewhere may not be accurate.

Likewise, even the data collected from public records is subject to the data vendor’s analysis, so the reliability of the vendor should also be assessed. This can be done by researching how thoroughly they consider external factors. For data about hydroelectric energy, this would mean considering rainfall and temperature measurements, the possibility of natural debris in the dam, how often the generator is maintained and the demand for power in that vicinity. The more factors considered, the better quality the data is likely to be!

Even if all of these steps to ensure quality data are taken, data can always run out of date. With global climates experiencing increasingly frequent and extreme changes, it’s vital that datasets affected by weather conditions and changing landscapes are updated regularly. Similarly, energy data from developing countries may not be representative of the current situation unless it has been collected very recently.

How is Energy Data typically priced?

Again, this normally depends on what information the data provides! In general, pricing models for energy tend to be in the form of a licence or subscription service more often than CPM, meaning data buyers should consider what kind of licence or level of subscription they would need to buy. The cost of energy data increases if the buyer intends to re-use or re-sell the data. A commission fee may also apply if the transaction is facilitated by a data marketplace, although some marketplaces, like ElectriCChain, are decentralised, and so their data is openly available.

What are the common challenges when buying Energy Data?

Oil and gas companies generate trillions of dollars annually. As such, it’s not always in their best interest to disclose data which might threaten profitable extractive projects, which causes obvious problems for anyone who wants access to energy industry data.

Elsewhere, energy data collection often relies on citizen contributions. Unless citizens have access to the required technology, like satellite imagery, this data can be of limited use to a buyer who needs detailed, high-quality data.

What should you ask Energy Data providers?

  • Which sources of energy does your data cover?
  • Which technology is required to collect this data, and has it been used?
  • How current is the data?
  • What are the disclosure laws in the country where the data has come from?
  • To what level can the data be subdivided?
  • Which other organisations and businesses use this data?
  • What level of subscription/type of licence is needed to implement the data into your own business?

    Who are the best Energy Data providers?

    Finding the right Energy Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular Energy Data providers that you might want to buy Energy Data from are CustomWeather, Meteomatics, Earthmetry, and SETLD.

    Where can I buy Energy Data?

    Data providers and vendors listed on Datarade sell Energy Data products and samples. Popular Energy Data products and datasets available on our platform are India Electricity State Monthly Generation by Energy Source by Earthmetry, Meteomatics Weather API by Meteomatics, and CustomWeather Historical Hourly Solar Data by CustomWeather.

    How can I get Energy Data?

    You can get Energy Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Energy Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Energy Data APIs, feeds and streams to download the most up-to-date intelligence.

    What are similar data types to Energy Data?

    Energy Data is similar to Environmental Data, B2B Data, Real Estate Data, Geospatial Data, and Commerce Data. These data categories are commonly used for Analytics and Energy Data analytics.

    What are the most common use cases for Energy Data?

    The top use cases for Energy Data are Analytics and Energy Usage Management.