Datasets

Commercial Datasets

Energy Exemplar® provides commercial datasets for modelling in the regions of North and South America, Europe, Asia, Oceania, and Africa using the PLEXOS® Integrated Energy Model software. These include:

Eastern Interconnect (US)

The Eastern Interconnect dataset is founded from the EREG MMWG database as well as data from the public domain which are all referenced. Each dataset comes pre-loaded into PLEXOS for the particular NERC region purchased. Packages of multiple NERC regions are available (ISO-NE, NYISO, PJM, MISO, SPP, SERC, FRCC, EISO, Hydro Quebec, etc.). All surrounding intertie flows are modelled within PLEXOS. Each dataset includes, a) Dataset pre-loaded into PLEXOS, b) Relevant CSV files, c) List of References. General Dataset Properties included are: A. Generators (Name, Fuel Type, and Registered Maximum Capacity). Generators are provided with common empirical operational attributes (e.g. Average Heat Rates, Ramp Up/Down Rate, Min Stable Level, Forced Outage Rate, Maintenance Rates, Mean time to Repair, Variable Operating & Maintenance Costs (VOM)) based on the generator characteristics using trusted US databases & reports. For a given NERC region, the sum of the power plants capacity by technology is compared to the aggregated capacity of each technology, usually given in separate documents, B. Fuels (Price for Coal, Gas, Oil Monthly and Daily), CO2, SO2, and NOX emission factors which are regional-independent emission factors of fuels). Fuel prices used in the datasets correspond to well-known indices (CME & ICE) and an escalator can be used to adjust for taxes, transmission and distribution costs, C. Demand (Load Zone at hourly resolution).

Please contact us about this dataset.

ERCOT (US)

The ERCOT dataset is founded from the ERCOT Planning & Operations database as well as data from the public domain which are all referenced. The ERCOT dataset comes pre-loaded into PLEXOS. All surrounding intertie flows are modelled within PLEXOS. Each dataset includes, a) Dataset pre-loaded into PLEXOS, b) Relevant CSV files, c) List of References. General Dataset Properties included are: A. Generators (Name, Fuel Type, and Registered Maximum Capacity). Generators are provided with common empirical operational attributes (e.g. Average Heat Rates, Ramp Up/Down Rate, Min Stable Level, Forced Outage Rate, Maintenance Rates, Mean time to Repair, Variable Operating & Maintenance Costs (VOM)) based on the generator characteristics using trusted US databases & reports. For a given zone, the sum of the power plants capacity by technology is compared to the aggregated capacity of each technology, usually given in separate documents, B. Fuels (Price for Coal, Gas, Oil Monthly and Daily), CO2, SO2, and NOX emission factors which are regional-independent emission factors of fuels). Fuel prices used in the datasets correspond to well-known indices (CME & ICE) and an escalator can be used to adjust for taxes, transmission and distribution costs, C. Demand (Load Zone at hourly resolution).

Please contact us about this dataset.

WECC (US)

The Western Interconnect (WECC) database in PLEXOS was translated from the WECC TEPPC 2020 and 2022 databases. After the translation, many revisions are introduced based on many stakeholder meetings from a few consulting assignments. The major changes include:

  • Thermal Generator Heat Rates,
  • CT, Coal and Steam generator minimum generation capacities,
  • Nuclear minimum generation capacities,
  • Hydro minimum generation capacities,
  • Pumped-storage hydro generators minimum pumping and generating capacities,
  • The generator ramp rates,
  • The introduction of renewable generations for the high renewable penetration levels,
  • Regulation up and down reserves,
  • Demand Response minimum capacities and exercise prices,
  • The eligibilities of generator provisions to reserves.

Please contact us about this dataset.

Caribbean

The Caribbean dataset is founded from data from the public domain which are all referenced. Each dataset comes pre-loaded into PLEXOS for the particular Caribbean Island purchased. Packages of multiple Islands are available including, Antigua and Barbuda, Barbados, Dominica, Dominican Republic, Grenada, Haiti, Jamaica, Martinique, Nevis, Puerto Rico, St Kitts, St Lucia & St Vincent and Grenadines. Each dataset includes, A) Dataset pre-loaded into PLEXOS, B) Relevant CSV files & C) List of References. General Dataset Properties included are: A) Generators (Name, Fuel Type, Registered Maximum Capacity). Generators are provided with common empirical operational attributes (e.g. Average Heat Rates, Ramp Up/Down Rate, Min Stable Level, Forced Outage Rate, Maintenance Rates, Mean time to Repair, Variable Operating & Maintenance Costs (VOM)) based on the generator characteristics using trusted resources & reports. B) Fuels (Price for Coal, Gas, Oil Monthly and Daily). Historical and 40-year fuel price forecasts are pre-loaded into PLEXOS. C) Ancillary Services Regulation (Up & Down) and Spinning (Up & Down) reserves included for all Caribbean Islands. D) Demand (Load Zone at hourly resolution) Historical and 40-year Load Forecast at hourly granularity. E) Sub-Hourly Forecasts – Sub-Hourly Loads, Sub-Hourly wind and solar profiles available for all the Caribbean Islands. F) Stochastics – Stochastic variables defined for loads, solar & wind profiles and fuel prices useful for Risk Analysis studies. G) Capacity Expansion – Expansion candidates have been included for all the Caribbean islands to perform Long-term planning studies.

Europe and Great Britain

European Datasets are based on collected from publicly available sources data which are all referenced. Each Dataset comes pre-loaded into PLEXOS for the particular country purchased. Packages of multiple countries or as separate Markets are available (Nordpool Market, CWE, etc.). All surrounding interconnector flows modelled in PLEXOS with the ability to switch between using NTC or actual flows. Each dataset includes, a) Dataset pre-loaded into PLEXOS, b) Relevant CSV files, c) List of References. General Dataset Properties included are: A. Generators (Name, Fuel Type, and Registered Maximum Capacity). Generators are provided with common empirical operational attributes (e.g. Average Heat Rates, Ramp Up/Down Rate, Min Stable Level, Forced Outage Rate, Maintenance Rates, Mean time to Repair, Fixed Operating & Maintenance Costs (FOM), Variable Operating & Maintenance Costs (VOM)) based on the generator characteristics using trusted international databases & reports. For a given country, the sum of the power plants capacity by technology is compared to the aggregated capacity of each technology, usually given in separate documents, B. Fuels (Price for Coal & Gas Daily, for Oil Monthly, CO2 prices 2008 – 2012 (CO2 prices available until the middle of 2012 with latest data available for purchase from third-party provider), CO2 emission factors which are Country-independent emission factors of fuels). Fuel prices used in the datasets correspond to well-known indices (CIF ARA, NBP, Zeebrugge, Baumgarten, Gaspool, PEG, TTF, PSV) and an escalator can be used to adjust for taxes, transmission and distribution costs, C. Interconnectors (Net Transfer Capacities (NTCs) and Physical import/export flow). Hourly physical flow with cross-checks between ENTSO-E and individual TSOs data and NTCs data at hourly resolution where available, lower resolution otherwise (seasonal, annual). D. Demand (Country Load at hourly resolution).

Australian NEM

Based on publically available data, this dataset is benchmarked each year against actual market outcomes. It is suitable for market price, generation, transmission, and other forecasting needs out to 25 years.

Philippines

Based on publically sourced data, the Philippines dataset is developed in-house at Energy Exemplar. It incorporates the bid based spot market regions of Visayas and Luzon giving the user an excellent foundation for both short term forecasting and long term capacity expansion planning. To find out more please contact our Regional Manager for Asia-Pacific, Mr Milorad Zecevic.

Chile

Based on publically available data from Chilean electric system regulator, this information is updated every 6 months and it is suitable to forecast nodal prices, generation dispatch and transmission flows according to different hydrology scenarios using stochastic optimization up to 10 years.

The inputs for this calculation are described in the following points:

  • Load forecasting for a 10 years period.
  • Actual and planned transmission system for 10 years.
  • Actual and planned generation plants for 10 years.
  • Price indexation of fossil combustibles.
  • Maintenance of all generators along the horizon of simulation.
  • Forced outage rates of thermal units.
  • 4 cascading hydro networks.
  • Irrigation settlements of two main cascading hydro networks.
  • 52 historical inflow samples.
SAPP (Africa)

The Southern African Power Pool (SAPP) PLEXOS® Integrated Energy Model (“PLEXOS”) Dataset has been developed with country level granularity to allow the user to assess a range of issues as they relate to Southern African energy markets. The Dataset is based on public domain information and generally accepted industry practice. The Dataset includes all mainland Southern African nations (Angola, Botswana, DRC, Lesotho, Malawi, Mozambique, Namibia, South Africa, Swaziland, Tanzania, Zambia and Zimbabwe). Users of the Dataset could include inter alia regional utilities, regulators, IPPs, ISMOs, TransCos, GenCos, Consultants and universities or research institutions.
In summary, the Dataset contains the following:

  • One node per country with associated demand and demand profiles with seasonality and associated annual energy from 2010 to 2025
  • One Zone per control area within the SAPP (including countries not interconnected with the SAPP system i.e. Angola, Malawi and Tanzania
  • Existing transmission lines including maximum/minimum flows, resistance/reactance and existing SAPP interconnector flows
  • Planned transmission lines including typical technical characteristics (as modelled for existing transmission lines) as well as financial parameters including maximum number of units built, build cost, technical and economic life as well Weighted Average Cost of Capital (WACC)
  • Country specific fuel prices (forecasted up to 2025) with emission intensities
  • Existing major generators connected to the national power systems of each country inclusive of major technical characteristics such as number of units, maximum capacity, heat rates, variable operations & maintenance costs, firm annual energy constraints (for hydro generators), typical wind and solar profiles (with annual energy yields), minimum stable factors, maximum ramp-up and ramp-down rates, minimum up/down time, Forced Outage Rates (FORs), Unforced Outage Rates (UFOR), Mean Time to Repair (MTTR), pump load and pump efficiency (for pumped storage units) and date of commissioning (selected plants)
  • Candidate generation projects for Southern Africa in each SAPP nation. Properties modelled include the typical technical and economic parameters (as is the case for existing generators) with additional parameters including maximum number of units built, build cost, technical and economic life, Weighted Average Cost of Capital (WACC)

Download the V1.2 SAPP Dataset Flyer

EAPP (Africa)

The Eastern African Power Pool (EAPP) PLEXOS Dataset has been developed by Energy Exemplar (Africa) with the aim of helping various market participants analyse and assess critical energy industry issues in Eastern Africa. These range from security constrained short term unit commitment and energy dispatch to medium term fuel forecasting, hydro-thermal co-ordination and maintenance optimisation to integrated generation and transmission long term capacity expansion planning. Users of the Dataset could include inter alia utilities, regulators, IPPs, ISMOs, TransCos, GenCos, distributors, consultants, universities and research institutions.

The PLEXOS EAPP Dataset is defined with granularity at a country level based on public domain information and generally accepted industry practice with demand (hourly resolution) from 2010-2038. Supply is modelled via 232 power stations linked to country specific fuel price forecasts from 2010-2038 and all pertinent technical properties e.g. max capacity, number of units, annual energy constraints (hydro), wind/solar profiles for renewable plants, heat rates (average), VO&M costs, fixed annual costs, minimum stable factor, maximum ramp-up/ramp-down rates, minimum up/down time and reliability data (forced/unforced outage rates as well as mean time to repair). Interconnectors between all countries are modelled including key technical properties e.g. maximum/minimum transfer capacity, line impedances, forced outage rates, mean time to repair and expected dates of commissioning (for planned lines). With recent significant discoveries of natural gas and coal, the development of geothermal power, wind and solar this PLEXOS Dataset will prove to be invaluable to energy market participants in Eastern Africa and will give insights into the fast developing energy markets in each country of the EAPP.

Download the V1.0 EAPP Dataset Flyer

WAPP (Africa)

The PLEXOS Western African Power Pool (WAPP) Dataset is defined with granularity at a country level to allow the user to assess a range of issues as they relate to West African energy markets. The dataset is based on only public domain information and generally accepted industry practice. Users of the dataset could include inter alia utilities, regulators, IPPs, ISMOs, TransCos, GenCos, distributors, consultants, universities and research institutions. All data included in the dataset is completely referenced and thus completely transparent and traceable by the end user. The countries included in the EAPP dataset are Benin, Burkina Faso, Cote d’Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Niger, Nigeria, Senegal, Sierra Leone and Togo. In summary, the dataset contains demand forecasts (hourly resolution) from 2010-2025, major existing power stations including a range of technical and economic properties, country specific fuel price forecasts from 2010-2038 as well as CO2 emission intensities, existing interconnectors between all countries including key technical properties as well as explicit modelling of gas supply, gas nodes and pipelines related to the West African gas Pipeline (WAGP) project.

Download the V1.0 WAPP Dataset Flyer

Comité Maghrébin de l’Electricité (COMELEC)

The PLEXOS COMELEC Dataset is defined with granularity at a country level to allow the user to assess
a range of issues as they relate to North African energy markets. The Dataset is based on only public
domain information and generally accepted industry practice.

The COMELEC Dataset is pre-loaded into PLEXOS with the supporting *.csv data files for demand,
renewables generation profiles and fuel prices along with the full listing of data references used to
develop the COMELEC Dataset. An example of the visualisation of the COMELEC PLEXOS Dataset is
shown in Figure 1.

Users of the dataset could include inter alia utilities, regulators, IPPs, ISMOs, TransCos, GenCos,
distributors, consultants, universities and research institutions.

The dataset is based on public domain information and generally accepted industry practice where
information is not available. All data included in the dataset is completely referenced and thus
completely transparent and traceable by the end user.

The countries included in the COMELEC dataset are:

  • Algeria
  • Libya
  • Mauritania
  • Morocco
  • Tunisia

In summary, the dataset contains:

  • Country level granularity with demand (hourly resolution) from 2010-2025 including
    associated annual energy.
  • Major existing power stations including technical and economic properties:
    • Number of units
    • Max capacity
    • Annual energy constraints (hydro)
    • Wind/solar profiles for renewable plants
    • Heat rates (average)
    • VO&M costs o Fixed annual costs
    • Minimum stable factor
    • Maximum ramp-up/ramp-down rates
    • Minimum up/down time
    • Forced Outage Rates (FORs)
    • Unforced Outage Rates (UFORs)
    • Mean time to repair
  • Country specific fuel price forecasts from 2010-2025 as well as CO2 emission intensities
  • Existing interconnectors between all countries are modelled including key technical technical
    properties e.g. maximum/minimum transfer capacity, line impedances, forced outage rates,
    mean time to repair.

Contact us to find out more

 

Public Datasets

A significant number of public datasets are available in PLEXOS format free-of-charge, including:

Europe Integrated Power & Gas Model

An integrated gas and electricity model of the 2030 European energy system is developed using PLEXOS by the University College Cork in Ireland. The model is built using publicly available data and with several different scenarios. Each scenario looks at a projection of the European energy system for the year 2030 with alterations to the gas system.

This will provide a good platform to fully explore the potential impacts of gas supply interruptions on the electricity system, and to identify challenges which might arise when studying the gas – electricity co-optimisation in the EU region.

Download the 2030 EU Integrated Power Gas Model

Australian NEM

Australian NEM

The Australian Electricity Market Operator (AEMO) has recently released a copy of 2012 NTNDP Database. PLEXOS was used to solve the Least-Cost Expansion Modelling requirements as part of their long term planning analyses. For more information, click here or visit the AEMO Planning Assumptions page to download the 2014 PLEXOS LT Model and Traces database.

Download the Dataset

Northwest Europe

The Western European PLEXOS model is an academic research model developed by the Energy Policy and Modelling Group in University College Cork, Ireland. This is an hourly electricity market model for the year 2020 covering the countries of Belgium, Denmark, France, Germany, Great Britain, Ireland, Luxembourg, Netherlands, Portugal and Spain. The model details more than 1100 individual generators and renewable energy capacities are derived from submitted member state National Renewable Energy Action Plans (NREAP) for the year 2020. A description of the model is also given in this publication.

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