The Bureau of National Statistics, Agency for Strategic Planning and Reforms conducts the Household Survey on Fuel and Energy Consumption every five years. The purpose of the survey is to collect data on household fuel and energy consumption, end-use categories (heating, cooling, lighting, cooking, water heating, use of electrical appliances) and energy sources (fuel, electricity, renewable energy) used by households in Kazakhstan.

The 2018 survey was a random sampling, conducted by interviewing households and recording information on the survey questionnaires. The sample survey covered 21 000 households, and 437 interviewers helped collect, verify and transmit data. The sampling addressed 68 940 people from all of Kazakhstan’s 16 regions, covering 0.37% of the total population of 18.4 million in 2018.

Aggregated survey results are available in the statistical publication “Fuel and Energy Consumption by Households in the Republic of Kazakhstan, 2018” on the website of The Bureau of National Statistics, Agency for Strategic Planning and Reforms. The tables below present characteristics and dwelling information for urban and rural households. 

This roadmap’s methodology involves using primary data from the Household Survey to extrapolate at the national level and to further construct projections using scenario assumptions. Fuel use per surface area (by house type and region) among surveyed households was first analysed. Then, national-level household energy use (by house type and region) was estimated by combining data from the survey results with national-level housing stock data. Four future energy consumption scenarios were developed based on current policies and measures, with the addition of best policy practices of other countries.

1. This study obtained and analysed primary data from the Household Survey on Fuel and Energy Consumption (H-070) conducted by the Bureau of National Statistics, Agency for Strategic Planning and Reforms among 21 000 households. Analysis was based on:

• 4 house types (urban/rural and detached/apartment) in 16 regions (14 administrative regions and the 2 cities of Almaty and Nur-Sultan).
• Fuel consumption by each of the 4 house types (urban/rural and detached/apartment) in the 16 regions.
• Energy consumption by house type and region, leading to national-level estimates of corresponding surface area, energy consumption per surface area by house type and by region.

Probable reporting errors were identified (i.e. exceedingly high levels of fuel consumption reported by a few households) and were omitted from the analysis of fuel consumption per surface area. Excluded from analysis were households that reported using more than 10 000 m³ of natural gas (213 households); more than 10 t of coal (310 households); and more than 3 t of propane (23 households). These households constitute 2.6% of surveyed households. The table below presents the total consumption of surveyed households by fuel type regardless of house type, after exclusions.

2. National-level statistics on surface area were obtained from the statistical publication “About Housing Stock of the Republic of Kazakhstan in 2017”.

3. Residential energy consumption by house type and region (except for district heating) was estimated by applying fuel consumption per surface area from the survey and surface area data from “About Housing Stock of the Republic of Kazakhstan in 2017” using the following formula:

National estimated residential fuel consumption = fuel consumption per surface area by house type and region (from survey) × surface area by house type and region.

The residential energy consumption estimates were then compared with the values reported in the statistical publication “Energy Balance of the Republic of Kazakhstan”.

4. Housing stock surface area projections (for the BaU scenario) were made using average annual growth rates published in “About Housing Stock of the Republic of Kazakhstan in 2017”. Annual average national-level growth rates were obtained through analysis of historical values of surface area of the housing stock for 2013-17: 0.25% for an urban apartment, 2.77% for an urban detached house, -1.95% for a rural apartment and 1.3% for a rural detached house. These growth rates were applied for surface areas of all regions equally to obtain surface area projections up to 2030.

5. Residential energy consumption in the BaU scenario was estimated using energy consumption per surface area by house type and region from the Household Survey. It is assumed that energy consumption per surface area will be maintained at the current level.

The figure below provides a simplified schematic illustrating the main steps for estimating national residential energy consumption in the base year (2018) and by 2030 (BaU case).

6. This study employed the emissions coefficients applied by the European Environment Agency (2019).

7. According to ISO 13790:2009 (“Energy performance of buildings. Calculation of energy use for space heating and cooling”), annual energy use for heating, Q_H,sys including system losses is determined as a function of the energy needs for heating: 

Q_(h,sys)=Q_(h,n)/η_(H,sys) 

Where:

Q_h,sys is the energy used by the heating system including system losses.

Q_h,n is the energy needed for heating.

η_H,sys is the overall system efficiency for heating, including generation, transport, storage, distribution and emission losses.

In this study, energy needed for heating (of a specific energy carrier i) was identified as:

Q_(h,n,i)=Q_(h,sys,i)×η_(H,sys,i)

Overall system efficiency η_H,sys,i was determined as:

〖η_(H,sys,i)=η_(dis,i) η〗_(ac,i) η_(TBM,i) η_(gen,i) η_(em,i)

η_em is emission efficiency.

η_dis is distribution efficiency

η_ac is automatic control efficiency.

η_TBM is operations and maintenance efficiency.

η_gen is generation efficiency.

Total energy need for heating in 2018 (for all energy carriers) Q_h,n was estimated as:

Q_(H,n)=∑Q_(H,n,i) 

The share of fuel in total energy for heating (share of fuel i) in 2018 was estimated as:

Share of fuel i=Q_(H,n,i)/Q_(H,n) 

8. Energy needed for heating in 2030 (by region and house type) was estimated based on the estimated energy needed for heating in 2018 and the surface area in 2030.

9. Assumptions of heat losses in the existing heating system had to be made because there are no studies that characterise the heat losses in Kazakhstan’s residential buildings and provide information on, for example, how many buildings have thermostatic radiator valves or automatic control stations, and the amount of insulated/ pipes/valves. In the scenario that incorporates energy efficiency, heating energy needs in buildings (for both district heating and individual heating systems) are assumed to be 15% lower in 2030 than in 2017 owing to measures such as window replacements and wall insulation.

10. Study limitations and further research:

• When a household reported that it used fuel for “heating and cooking”, “heating and water heating”, “heating, water heating and cooking”, it was assumed that the fuel was used primarily for heating, and it was not possible to break fuel use down further into precise end uses. Additional research should therefore be conducted to survey household stove operation modes, particularly to understand how stoves/boilers are used for multiple end uses, how several stoves/boilers are used within one household, and how the various fuels are used for the multiple purposes mentioned.
• For projections of surface area, this study used national-level average annual growth rates: 0.25% for urban apartments, 2.77% for urban detached houses, -1.95% for rural apartments and 1.3% for rural detached houses. Historically (2013-17), however, regional differences in surface area growth rates have been substantial. The size of urban detached houses increased in all regions except South Kazakhstan (fell by 0.86%) and Nur-Sultan (fell by 0.87%). As Nur‑Sultan is the capital city, the decline in urban detached house size could be associated with the high cost of land, a shortage of available land and severe winter climatic conditions. Meanwhile, substantial growth in urban detached house surface area was observed in Almaty city (+1.53%) and the Aktobe region (+1.61%), and considerable decreases were registered in cold rural regions such as Pavlodar, North Kazakhstan and East Kazakhstan. Importantly, the surface area decreased for all housing types in both urban and rural areas in South Kazakhstan even though there was no decline in the region’s population. Regional differences in growth rates were not taken into consideration because it is not clear whether these trends will continue in the future, as internal migration between regions may not last long term. This interregional migration therefore needs to be investigated further to gain an understanding of the factors and drivers involved.

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This roadmap was written by Aiymgul Kerimray, EU4Energy Country Expert for Kazakhstan, and produced by Talya Vatman (Policy Programme Manager of the EU4Energy Programme). Duncan Millard and Markus Fager-Pintilä provided valuable support.

Thanks goes to Jad Mouawad, Head of the IEA Communications and Digital Office (CDO), and CDO colleagues for their assistance in producing the roadmap, particularly Astrid Dumond, Isabelle Nonain-Semelin, Julie Puech, Clara Vallois, and Therese Walsh. Kristine Douaud carried editorial responsibility. LGND designed the visual brochure.

Special thanks goes to the Bureau of National Statistics, Agency for Strategic Planning and Reforms of the Republic of Kazakhstan for providing primary data from the Households Survey on Fuel and Energy Consumption. We would like to thank Dr Marat Karatayev (Graz University of Technology), Dr Zhanna Kapsalyamova (Nazarbayev University), Dinara Shayakhmetova (Bureau of National Statistics, Agency for Strategic Planning and Reforms of the Republic of Kazakhstan); UNDP experts in Kazakhstan, Zhaksylyk Tokayev (International Green Technologies and Investment Projects Center) and the EU Delegation in Kazakhstan for providing valuable reviews and comments to the report. We would also like to thank Rebecca Gaghen, Simon Bennett, Laura Maiolo and Armin Mayer for their comments.

And a final, invaluable thank you to the European Commission for their support of IEA work on EU4Energy.