The primary focus is on projecting power consumption (demand) at each model node. Projections include national-level data for 153 countries and sub-national data for 10 additional countries. All data and results are presented on an annual timescale.

For countries represented as national nodes, the methodology begins with a trend analysis of Gross Domestic Product (GDP) growth and population growth data. This analysis identifies the growth line’s shape (linear, exponential, or polynomial), which is then used for regression. Datasets are analysed to quantify their influence on historical demand data. This forms the basis for assigning weighting factors to each dataset, which are applied in regression.

A similar method is applied to countries with sub-national zones. The focus shifts to regional data, specifically Gross Regional Domestic Product (GRDP), regional population statistics, and regional electricity demand. Where granular power demand data is unavailable, a proportional scaling approach is used based on the ratio of GRDP to GDP within each node.

Each node is assessed individually, considering power usage and characteristics within the context of its unique macroeconomic conditions. The top-down approach used in this demand analysis may not capture granular ground-level data with precision. This is due to constraints in obtaining comprehensive socio-economic data for in-depth behavioural analysis that impacts power utilisation. However, this top-down approach is considered an effective way to illustrate power demand growth at the national level.

Power demand projection relies on three primary input variables: GDP, population, and historical electricity demand data.

GDP and population data

The World Bank provides data from 1990 to 2022 on GDP (Purchasing Power Parity in 2017 international USD) and population. For future growth projections (2025-2100), IIASA’s Shared Socioeconomic Pathways (SSP2) dataset is used. The IMF’s GDP growth forecast up to 2025 bridges the gap between the World Bank and SSP2 data.

Historical electricity demand data

Data is sourced from EMBER’s open dataset and validated against IEA’s energy statistics data.

The table below summarises our data sources for GDP, population, and historical electricity demand.

Input VariableData SourceData PeriodUnit of Measurement
GDPWorld Bank1990 - 2022PPP in USD 2017
PopulationWorld Bank1990 - 2022Total population
Short-term GDP growth projectionIMF2022 - 2024Annual percent change
Long-term GDP projectionIIASA SSP22025 - 2100PPP in USD 2017
Historical electricity demandEMBER2000-2022Terawatt hours of electricity demand

For countries represented at the sub-national level, data is collected from the official websites and documents of each country as listed in the table below:

Country/RegionSources
CanadaNational Statistical Agency
USAThe Bureau of Economic Analysis, Energy Information Administration
RussiaFederal State Statistic Service
IndiaMinistry of Statistics and Program Implementation, Central Electricity Authority
ChinaNational Bureau of Statistics of China
IndonesiaRUPTL 2021-2030, Visi Indonesia 2045
VietnamVietnam Statistical Yearbook, Eight National Power Development Plan (PDP8) 2021-2030
MalaysiaThe Department of Statistics Malaysia, Malaysia Energy Statistics Handbook
PhilippinesPhilippine Statistics Authority, Philippine Energy Plan 2020-2040
ThailandOffice of The National Economic and Social Development Council, Electricity Statistic of Energy Policy and Planning Office