NATIONAL INSTITUTE OF STATISTICS ROMANIA

DEVELOPMENT OF DETAILED STATISTICS ON ENERGY CONSUMPTION IN HOUSEHOLDS (SECH Project)

GRANT AGREEMENT No. 30304.2009.003 - 2009.707

FINAL REPORT GRANT AGREEMENT No. 30304.2009.003 - 2009.707

FINAL REPORT

ENERGY CONSUMPTIONS IN HOUSEHOLDS

1. General presentation

In order to comply with the requirements of Regulation 1099/2008 on Energy Statistics, Member States have to develop further energy statistics related to energy consumption and renewable energy. These detailed statistics are an important tool in the assessment of energy efficiency/ energy savings of each country. In the “Energy Statistics Working Party”, held in June 2008, it was recognised that surveys of the industry are common practise in EU, therefore improvement of energy consumption statistics in other sectors, such as households, were considered high priority. Although the Romanian National Institute of Statistics has a long experience in computing the national energy balance, we also considered that there were domains (such as households consumption) that have to be developed and improved for more accurate and reliable results. Currently, some information on the households consumption of energy commodities were estimated based on data from Household Budget Surveys and other administrative sources. The obtained data were good, but only for a few main energy commodities (such as electricity, natural gas and fuel wood) and too general, with a low (or zero) degree of detailed information regarding other energy carriers and the purpose of the consumption (space heating, water heating, cooking, etc). The survey dedicated to energy consumption in households, along with the already existing annual surveys in energy statistics carried out by the Romanian NIS, will be an important source of information for policies and other bodies interested in promoting energy efficiency/ energy savings programs. This project, implemented within the framework of the European Statistical System (ESS), helped us to develop further detailed statistics on energy consumption in the households sector and the data will substitute the estimated data currently used to compute the national energy balance.

2. Scope of work

The objective of this project was to develop further detailed statistics on energy consumption in the households sector, using the coverage recommended by the June 2009 ESWP as a basis, and taking

2 into account the national priorities- that arise from policies pursued at national level- and the current national practices. The project was performed using a dedicated survey, with face to face interviews of households on a sampling basis, to determine the energy consumption, related costs and type/age of energy consuming appliances, for the reference year 2009. The data are significant at national level (NUTS 0) and on urban and rural areas. Based on modelling, the consumption on major end uses was determined (space heating, water heating, cooking, space cooling, lighting and electrical appliances).

3. Description of the work

The project was based on a data collection exercise, by way of a survey of households, based on a sample of dwellings and a survey questionnaire. Data were collected with the help of 780 interviewers, specialised in collection of data from households, the interviewers being used constantly by NIS for this type of surveys. Interviewers were briefed by the NIS experts working in regional statistical offices, in order to have a good knowledge of energy units (kWh, GJ, etc) and local distribution and sale of energy commodities. Interviewers were also required to regularly report all problems experienced with the questionnaire or the interviewing process to the county offices. Throughout the data collection stage questionnaire responses were checked for completeness and internal consistency. The data were keyed-in on line in a data base that permits additional checks and electronic treatment of data in preparing the necessary report tables at national level.

4. Main activities

4.1. Documentation and project preparations The project has started in January 2010 with the preparation of the survey, documentation regarding the objectives of the project and the actions to be performed. It was necessary to read and get familiar with the methodological issues presented in the Recommended Coverage and the definitions sent by Eurostat. The questionnaire, methodological instructions and guidelines and the results of a previous survey, performed in 1996, were also studied, as well as the documents presented on CIRCA as results of Task Force “Final Energy Consumption in Households” from October 2008.

3 An important mission of the project leader was to train the staff (including the experts from the regional statistical offices) involved in this project and to prepare the programme of the territorial network. Also, in order to inform the population about the purpose and schedule of this survey and to allow householders to prepare past invoices and accept the interviewer more readily in their home, NIS created a Press Release and an official notification (Annex 1) that was printed and sent to the households comprised in the sample.

4.2. Questionnaire and Instructions design Based on the methodological requirements of Eurostat and on past experience of questionnaire and methodology, as well as the experience of other Member States, NIS has designed the national household consumption statistical questionnaire (CEnG) for 2009 (Annex 2; the English version of the indicators are presented in Annex 2_English). As a guide for interviewers and staff as well, the fill-in Instructions were designed; they contain the main check keys and informative descriptions and pictures (Annex 3). The statistical instruments (questionnaire and instructions) were printed and distributed to the county statistical offices.

4.3. Sampling The Romanian Households Energy Survey is based on a two-stage sampling design, with the stratification in the first stage. The sample size is 10920 dwellings with permanent occupancy. Keeping in mind the proposed survey design and the expected response rate (80%), the sample was being design to produce reliable estimates for each area of residence (urban / rural) as well as national estimates for main variables. First Stage Sampling (master sample EMZOT) The master sample EMZOT was designed on the basis of the Census of the Population and Dwellings from 2002. Even if the use of a master sample makes the estimation process more complicated, it is the only way to carry out household surveys at the time being. EMZOT contains 780 Primary Sampling Units (territorial areas), selected separately on the 88 strata. Criteria by which the stratification has been made are county (NUTS-3 level) and area of residence, resulting a number of 88 strata (in Bucharest the selection was done separately for each of the six sectors). The 780 PSU are distributed in the master sample as follows: 427 PSU in urban area and 353 PSU in rural area. On the first stage, probabilities of inclusion proportional with the size were calculated in each stratum. The size criterion was the number of permanent dwellings of the PSU. Second Stage Sampling

4 Within each PSU, 14 dwellings are sampled using a systematic algorithm of selection with random start. The second-stage inclusion probability is the inverse of the sampling interval inside a PSU. At the end, the probability of selection of a dwelling in the sample is calculated as product of two inclusion probabilities: the first-stage inclusion probability and the second-stage inclusion probability.

4.4. Study visit to Statistics Austria Romanian NIS asked, and it was granted, to use the Austrian experience in households energy consumption surveys. The main topics of the agenda were: -Presentation of the Romanian SECH project: expected results of the action, the questionnaire. -Presentation of Austrian “Domestic energy consumption survey” and “Survey on electricity and natural gas consumption by purposes” -Presentation of interviewer training elements, validation of primary data, non-response imputation, validation of final data. -The butt for data adjustment; types of data adjustment; -Modelling procedures in order to determine energy consumption by end use. The questionnaire designed by NIS Romania was first discussed, along with the expected results of SECH project. The surveys conducted by Statistics Austria were presented and discussed: data processing, modeling procedures, data validation and especially the target determination of a household’s thermal energy consumption were the most important items explained during the discussions; the plausibility checks (both during and after the interview), item non response imputation and the shares’ modelling of energy needs for space heating, water heating and cooking was given. An important discussion was about how to adjust the Austrian average energy consumption values to the Romanian specific energy situation and where to obtain further relevant information in order to build up the target. The Austrian questionnaires used were discussed in detail and special attention was paid to potential problems in collecting the data. The results of the IEE project “REMODECE” were analysed with focus on the Romanian results; their applicability for future calculations of electricity consumption was declared to be acceptable.

4.5. Design of IT software for data entry and control of primary data The IT software was designed, based on the questionnaire and the specifications necessary for data entry and control, and afterwards for imputations. There were discussions between project team and IT experts of NIS, for a better understanding of the terminology, the sense of the questions and the check keys.

5 The on-line IT software permitted data entry and check for completeness and internal consistency, eliminating the errors at unit level, simultaneously with data checking at central level.

4.6. Data collection and data entry The period for data collection was April- May 2010 and by the end of June 2010 the data entry was finished. At regional level working teams were established for data collection, comprising the coordinating staff and the operating staff. The statistical instruments were distributed and the local working groups assisted the interviewers in identifying the households and provided technical assistance when needed. The whole activity of statistical data collection, carried out under the supervision of NIS, complied with the legal provisions. The results of data collection, in terms of response rate, are as follows:  14 dwellings were inhabited by two households and 1 dwelling by three households.  The total response rate is 88.5%.The urban response rate is 85.9% and the rural response rate is 91.6%.

6 Total Urban Rural Number of dwellings 10920 5978 4942 in the sample Number of dwellings 9661 5135 4526 with valid data Number of households 9676 5141 4535 with valid data

4.7 Validation and data processing at national level Validation of data at national level was a long and time consuming process. The team verified to the highest possible extent if the reported data respected the prescribed methodology.

In phase one, the errors that occurred at questionnaire level (and failed to be solved by the county statistical offices) have been dealt with; they were mainly partial non-responses and inconsistencies in data reporting (for example, the relation between fuel and the device using that fuel, unrealistic quantities or values reported, considering the size of the household and type of the dwelling, etc); the county offices were contacted and asked to solve these errors.

In phase two, the data have been subjected to the following treatment:  the missing heated floor space was imputed by the total living floor;  if no light lamps were reported, 2 incandescent light lamps / room were imputed;  the missing quantities of fuel consumption were calculated from the monetary values by applying average prices and vice-versa;  the missing quantities and values were replaced with the average data from donors belonging to the same area of residence with ±10% deviation of characteristic keys (type of building, heated surface and number of persons in household);  the quantities of fuel reported in secondary measure unit have been transformed in primary measure unit;  quantitative consumption checks against an upper and lower level of fuel consumption (these levels are based on information from various sources, such as REMODECE studies, Statistics Austria, internet, etc) ;  quantitative consumption checks against an interval (-50%, +100%) of default values (based on Statistics Austria information) for annual energy use for heating, in GJ/m2;  quantitative consumption checks against an interval (-50%, +50%) of default values (based on Statistics Austria information) for: - annual energy use for water heating, in GJ/person; - annual energy use for cooking, in GJ/person; 7 4.8 Weighting and calibration of data Weighting is a three step procedures: a) Basic weight calculation. The corresponding basic weight of a sampled dwelling is the inverse of the probability of selection. Each household belonging to a sampled dwelling takes the basic weight of the dwelling. b) Unit Non-Response Adjustment. To cover the non-respondent sampled households the respondent units are re-weighted. Response Homogeneity Groups are constructed by crossing the following variables: county and residence area. The basic weight of each respondent household belonging to such a group is adjusted with the inverse of the corresponding response rates of the group. c) Calibration. The final weights are obtained by calibrating the weights issued from the previous steps on certain variables of interest, for which totals are known for the entire population. Demographic variables (population on gender, age groups), locating variables (population on residence area, region (NUTS2 classification)) and number of households for every region are used for this final adjustment. The structure of the population for the above-mentioned variables is known from the legal population, available at 1st of July 2009. The calibration is carried out within each region, by means of CALMAR SAS macro. At the end of this step, the final weights are obtained.

4.9 Final data checking and analyse The final data have been computed applying the weighting coefficients to all variables, obtaining two sets of data: one at the level of household (in 2009 were 7395749 households) and one at the level of dwelling (7383643 occupied dwellings in 2009). Due to the small number of dwellings with two or three households (12106), the comparative analysis of these two sets of data revealed differences of less than 0.3% in terms of fuel consumption. For this reason, and because of the doubts concerning the correct split of ownership regarding the appliances in dwellings with more than one household, we have decided to analyse all data at the level of dwelling. The aggregated data have been checked against the available information from previous energy surveys and administrative sources, such as: the 2002 Population and Dwelling Census, the Annual reports of the national energy regulator (ANRE), the Household Survey for 2009, the Household Energy Survey for 1996, the Energy balance for 2009.

The energy consumption in households in 2009 is with 9.8% lower than in 1996, according to the similar survey performed then, due to the decrease with 5.0% of the Romanian population and with

8 6.6% of the number of households and, perhaps, of a self-imposed reduction in energy consumption due to the high energy prices compared to the family income. Compared with the data from the Energy balance for 2009, we can conclude that the residential consumption for some fuels was underestimated in the energy balance, especially fire wood, LPG and coal.

Household energy Household energy Energy balance HES 2009/ HES 2009/ Energy balance Fuel consumption survey (HES) 1996 survey (HES) 2009 2009 HES 1996 2009 TJ TJ TJ % % Electricity 26884 40869 39719 152.0 102.9 Natural gas 64575 95018 90790 147.1 104.7 Coal/other solid fuel 11294 1584 553 14.0 286.4 LPG 19272 17342 12842 90.0 135.0 Liquid fuels 2661 45 524 1.7 8.5 Fire wood (incl. biomass) 192351 199158 142124 103.5 140.1 District heating 129466 48669 49497 37.6 98.3 Total 446503 402684 336049 90.2 119.8

4.10 The expected results compared with the actual results of the project Expected results Actual results Housing stock characteristics: ownership, dwelling Housing stock characteristics: ownership, dwelling type, age of building, availability of insulation (wall, type, age of building, availability of insulation (wall, roof, window), surface heated, surface air- roof, window), insulation work in 2009, useful conditioned surface, living surface, surface heated, surface air- conditioned Dwellings characteristics: size, intensity of Dwellings characteristics: size, intensity of occupation; occupation; dwellings with adjacent economic activities Consumption/expenditure of energy commodities: Consumption/expenditure of energy commodities: consumption and associated cost (per type) for consumption and associated cost (per type) for electricity, heat and major fuels electricity, heat and major fuels Space heating: fuel type, availability and type of Space heating: fuel type, availability and type of temperature control instruments temperature control instruments; equipment type Hot water: fuel type, tank size, age Hot water: fuel type, tank size, age; equipment type Cooking: fuel type, equipment type and age Cooking: fuel type, equipment type and age Electrical appliances: type, number, age Electrical appliances: type, number, age Air conditioning: type, age Air conditioning: type, age Penetration of energy efficiency technologies: Penetration of energy efficiency technologies: labelled (by appliance type), diffusion of high- labelled (by appliance type), diffusion of high- efficiency light bulbs efficiency light bulbs Energy service demand: intensity of use of heating Energy service demand: intensity of use of heating system, intensity of use of air-conditioning system, intensity of use of air-conditioning Biomass consumption: by type, destination Biomass consumption: by type, destination Energy consumption by end use: space heating, Energy consumption by end use: space heating, water heating, cooking, space cooling, lighting and water heating, cooking, other uses, space cooling, electrical appliances lighting and electrical appliances, share of dwellings by main fuel consumed and end use Additional information 9 penetration of high-efficiency condensing boilers - the use of solar panels (surface/power, by type) - penetration of heat pumps (type/power, electricity - consumption) thermostat set points during heating/cooling period thermostat set points during heating/cooling period 4.11 Difficulties A number of difficulties were encountered during the development of this project, consisting mainly in a poor understanding of various methodological concepts. For example, the difference between central steam/hot water, central warm air, central boiler and CHP boiler had to be explained over and over again, although they were amply presented in the fill- in Instructions brochure. Additional checking had to be performed to ensure quality data for these indicators. Also, the lack of data regarding high-efficiency condensing boilers, solar panels or heat pumps (due to a household sample too small for the intensity of this type of technology), prevented us from achieving the desired information.

Another difficulty occurred, of an unexpected nature: the splitting of biomass by type, in fuel wood consumption and wood waste consumption, has provided unreliable figures for each category. The reason for the poor quality of information in this regard is that, for most of the Romanian population, especially in rural areas, the distinction between the two wood categories is difficult to make. However, the overall figure for biomass consumption is appreciated as accurate.

4.12 Energy consumption by end use - modelling exercise In order to perform de split of fuel consumption by end use, the following steps were followed:  for each dwelling was identified the main fuel used for space heating, water heating and cooking, according to the information provided in chapter 2 of the questionnaire;  for each fuel and dwelling have been computed default consumption values depending on the heated surface and number of persons, using the default values for annual use presented below: Default values Default values Default values Fuel for space heating for water heating for cooking Electricity 0.2903 GJ/m2 All fuels (except electricity) 0.5806 GJ/m2 All fuels 4.59 GJ/person 1 person: 1.35 GJ 2 persons: 1.71 GJ 3 persons: 1.96 GJ 4 persons: 2.57 GJ ≥5 persons: 3.18 GJ

10  for each fuel and dwelling, if this fuel was used only for space heating, the entire amount was attributed to consumption for space heating;  for each fuel and dwelling, if this fuel was used only for water heating, the entire amount was attributed to consumption for water heating;  for each fuel and dwelling, if this fuel was used only for cooking, the entire amount was attributed to consumption for cooking;  for each fuel (except electricity) and dwelling, if the amount of fuel used was higher than the sum of the default consumption values for space heating, water heating and cooking: 1. if the dwelling used the amount of fuel for water heating and cooking but not for space heating, the fuel amount was divided by 2; 1/2 was attributed to water heating and 1/2 to cooking; 2. if the dwelling used the amount of fuel for space heating and water heating and cooking, the default value for water heating was attributed to water heating, the default value for cooking was attributed to cooking and the rest of the fuel amount was attributed to space heating;  for each fuel (except electricity) and dwelling, if the amount of fuel used was smaller than the sum of the default consumption values for space heating, water heating and cooking: 1. if the dwelling used the amount of fuel for water heating and cooking but not for space heating, the fuel amount was divided by 2; 1/2 was attributed to water heating and 1/2 to cooking; 2. if the dwelling used the amount of fuel for space heating and water heating and cooking, the fuel amount was divided by 4; 1/4 was attributed to water heating, 1/4 to cooking and 1/2 to space heating;  for each dwelling and electricity, if the overall electricity consumption was higher than the default consumption values (with floor size and number of persons) the residuum was assumed as other uses; also, for dwellings not using electricity for space and water heating or cooking, the electricity was attributed to other uses;  for each dwelling and electricity, if the overall electricity consumption was smaller than the default consumption values (with floor size and number of persons), 50% of electricity was assumed to space heating, 15% to water heating, 10% for cooking and 25% to other uses;  the same procedures were followed for any secondary fuel used in a dwelling;  finally, the amounts were summarized for each end use.

11 5. Conclusion As an overall estimation, we are satisfied with the results of this project, considering it good and extremely useful the achieved information.

The following annexes are part of this report:

Annex 1 Annex 2 Annex 2_English Annex 3 Annex 4_Romania 2009_SECH project_final tables

Project manager

Adriana Opriş

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