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The Evolution of Rural Household Electricity Demand in Grid-Connected Communities in Developing Countries: Result of a Survey

Authors:

Salisu Isihak ,

Rural Electrification Agency, Rural Electrification Fund, NG
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Uduak Akpan,

Sustainability, Policy, and Innovative, Development Research (SPIDER) Solutions Nigeria, Uyo, Akwa Ibom State, NG
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Sanusi Ohiare

Rural Electrification Agency, Rural Electrification Fund, NG
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Abstract

The expected electricity demand level of unelectrified communities is one of the variables that guide rural electrification planners and electricity distribution utilities in making the choice of extending electricity grid to such communities and in using appropriate sizes of distribution assets such as transformers. This study presents the result of a survey to determine the level of household electricity demand in two villages in South-West Nigeria. The electricity demand is determined using a bottom-up approach which traces the household electricity demand through the purpose of use, the type and number of electrical appliance, and the duration of use. The result shows that most respondents will use bulbs for up to 8 hours per day but those who own refrigerators will power it for over 16 hours per day. The level of electricity consumption in the households sampled range from 0.38–20.56 kWh/day. Policy implications are discussed.
How to Cite: Isihak, S., Akpan, U. and Ohiare, S., 2020. The Evolution of Rural Household Electricity Demand in Grid-Connected Communities in Developing Countries: Result of a Survey. Future Cities and Environment, 6(1), p.10. DOI: http://doi.org/10.5334/fce.96
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  Published on 16 Oct 2020
 Accepted on 30 Sep 2020            Submitted on 28 Jul 2020

1. Introduction

In many developing countries especially those in sub-Saharan Africa (SSA), a large percentage of the population is poor and resides in rural areas where there is substantial lack of basic amenities and social infrastructures such as good transport network, water, modern energy services, etc. Of the modern energy services, access to electricity is the most crucial because electricity is the most versatile energy carrier. The International Energy Agency estimates that about 789 million people were without access to electricity in 2018 and most of them were in SSA (IEA et al. 2020). Nigeria contributes substantially to the number of people without access to electricity in SSA. The National Population Commission (of Nigeria) puts Nigeria’s electricity access rate in 2018 at 56.5%, with rural and urban access rate being 37.1% and 81.7% respectively (National Population Commission, 2019). Access to electricity has been noted to be an important driver of the socio-economic transformation of rural areas in different facets of development such as health care, water supply, education, etc. (Kanagawa & Nakata, 2007, 2008; Sokona et al., 2012). Consequently, investment in the provision of electricity services and ensuring the availability of electricity in rural communities has the potential to raise the productivity and profitability of rural micro-enterprises thereby providing rural dwellers additional disposable income that may be used to improve their standard of living (Akpan et al., 2013).

Given the importance of electricity access to rural development and the lack of it in many rural areas, the Nigerian government through the Electric Power Sector Reform Act had established the Rural Electrification Agency and saddled it with the responsibility of developing a Rural Electrification Strategy and Plan to minimize the cost of achieving universal electricity access in Nigeria. Most communities are powered by extending the existing grid. However, electricity distribution utilities are often reluctant to make such investment because of the concern that the demand from such communities may be low thereby leading to underutilization of electricity, and by extension, monetary losses. The expected electricity demand level of unelectrified communities is one of the variables that guide rural electrification planners and electricity distribution utilities in making the choice of extending electricity grid to such communities and in using appropriate sizes of distribution assets such as transformers.

The level of electricity demand of a rural household in an unelectrified community may be estimated in two ways: (a) by examining the present end-use of energy in the household (whether for lighting, cooking, motive use, etc.) and making assumptions regarding the expected level of switch in energy source from the present energy source to electricity, and adding the demand for electricity that will arise gradually due to the availability of electricity; and (b) by examining the level of electricity demand in other rural households which have access to electricity and assuming the electricity demand patterns will be similar for the households in the unelectrified community. Both methods have their pros and cons. However, the latter is more applicable in our situation because it provides insights on the evolution of the electricity demand in a rural community within a given period after electricity has been provided to such a rural community. This latter option may be achieved in two ways:

  • - first, one may obtain from the utility servicing the area the average meter reading of households. This approach will provide precise data on the electricity demand; however, it will not be feasible in households that are not properly metered whereby electricity bills are usually estimated or in households that connect to the grid informally. In addition, because the meter reading shows the total consumption of the households within a period, it shields the consumption pattern and the likelihood of households to own certain appliances or to imbibe demand-side management behaviors by switching off unused appliances;
  • - second, by conducting household survey on electricity use.

This second method overcomes the setback of the first method as it adopts a bottom-up approach to capture the propensity of households to use electricity as the source of energy for different end uses. The advantage of this approach is evident in the fact that it is often employed in energy-use accounting (Bhattacharyya & Timilsina, 2010) and it is integrated into computer programmes like RETScreen.

Given the increased commitment of government towards increasing access to electricity in rural areas and the amount of information that may be obtained through conducting household electricity demand and load assessment, this study intends to use the bottom-up approach to examine the level of electricity demand of households in two rural communities in Nigeria that have been connected to the grid within the last ten years. This will enable us to understand the evolution of rural household electricity demand within ten years of the community being connected to the grid. This study is important because it fills the data gap on rural household electricity demand in Nigeria and will be useful to rural electrification planners and policy makers especially in assessing the techno-economic viability or otherwise of decentralized electrification options.

Several studies have examined the household electricity consumption and/or it determinants by examining the underlying factors that contribute to electricity consumption such as the stock of appliances owned, socio-economic and lifestyle factors, climatic and cultural factors, etc. (Murthy et al., 2001; Genjo et al., 2005; Ghisi et al., 2007; Zhou & Teng, 2013; Wijaya & Tezuka, 2013). Ghisi et al. (2007) surveyed 17,643 households in 12 states in different bioclimatic zones in Brazil to obtain the electricity consumption of all appliances owned by households. The study observed the largest end-use of electricity are for refrigerator and freezer together which accounted 38–49% of electricity consumption of the dwellings. Murthy et al. (2001) conducted a survey of 1,165 households in four districts of Karnataka State in India to examine the electricity consumption of the households and employed three approaches: the engineering approach, the appliance stock approach, and the appliance census approach. The engineering approach is akin to the bottom-up approach because it examines the end-use of electricity using the appliance, the wattage of each appliance and the duration of use of each appliance. Genjo et al. (2005) conducted a survey of 505 Japanese households to examine the relationship between possession of household appliances and electricity consumption and observed that increase in electricity consumption was due to increased number of appliances. Murata et al. (2008) surveyed households in 13 cities in China to examine end-use of electricity in the households and the ownership of different appliances as well as the potential of electricity savings in the future by improving the efficiency of appliances. Wijaya & Tezuka (2013) examined the electricity consumption characteristics of households in two cities in Indonesia and observed that appliance stock and socio-economic characteristics of households had a significant effect on electricity consumption.

Our study is similar to these studies because it uses household surveys to examine the households’ ownership and use of electrical appliances. However, it is different from most of these studies: they examine the determinants of household electricity consumption using a regression model where actual data on electricity consumption level obtained from electricity bill is the dependent variable and the stock of electrical appliances, socio-economic variables, price of electricity, etc. are explanatory variables (Wijaya & Tezuka, 2013; Zhou & Teng, 2013).

The study is organized as follows: following this brief Introduction will be the Methodology. We will present and discuss the results in the third section and make our Conclusion and Policy recommendations in the fourth section.

2. Methodology

2.1. Study Area

The study was conducted in Oyo State, Nigeria. Oyo State is one of the 36 states in Nigeria located in the South-Western part of the country. The state lies between latitudes 7° 3’ and 9° 12’ North, and longitudes 2° 47’ and 4° 23’East, is bordered by Kwara State to the North, Ogun State to the South, Osun State to the East, and the Republic of Benin to the West. The state is made up of 33 local government areas1 and has several urban areas including Ibadan, Oyo, Ogbomosho, etc. and also has several rural areas. The average household size in the state is 4.0 (NBS, 2009). Agriculture is the predominant economic activity in the rural areas and the climate of the state favors the cultivation of Maize, Yam, Cassava, Millet, Rice, Plantain, Cocoa tree, Palm tree and Cashew. Other non-agricultural economic activities like broom making, tailoring, carpentry, etc. also thrive in the rural areas.

2.2. Survey design and data collection

To examine the electricity demand of households in rural areas, the study adopted a multistage sampling procedure. First, we select Lagèlu LGA purposively because it is one of the least developed LGAs in Oyo State. The LGA covers a land area of 342.34 sq. km. and has a population of 148,133 based on 2005 census (National Population Commission, Nigeria, 2006). Second, we set out to identify villages in Lagèlu LGA of Oyo State which met the following inclusion criteria: the village must be formally recognized in the official gazette of the state and must have an official village head; must be without some social institutions/infrastructure such as banks, hospital, well tarred roads (apart the connecting road that links several villages) etc; but will have primary schools, microenterprises, churches/mosque, and the grid (400V low voltage distribution line) must have been extended to the village not earlier than 2005. After identifying up to five villages that met the inclusion criteria, we selected two of them randomly, i.e. Adeleye and Adewumi villages. It is important to note that the number of villages that would have met the inclusion criteria would have been higher if we were able to go round the length and breadth of the LGA. In the third stage, we set out to select households connected to the distribution line from each village. It is also important to mention here that the connection of households in rural areas to the distribution lines do not necessary follow the standard connection procedure prescribed by the distribution company covering the geographic area in the sense that some connections are without approvals and households may get connected to the 400V low voltage distribution line informally. Nevertheless, our concern was with households that use electricity in their houses.

Primary data were obtained from the households with the support of a structured questionnaire which was designed to probe the level of electricity use in the homes. We field-tested the questionnaire through a pilot survey to understand how respondents will understand the questions and the questionnaire was finalized on the basis of suggestions and comments obtained from the pilot survey. We included a statement of informed consent in the questionnaire and this was read and explained to all potential respondents. The questionnaire was designed to ensure data protection and was divided into three sections as follows:

  1. Socio-economic profile of households: household information such as age, sex, highest educational qualification, monthly income range of head of household and household size.
  2. Characteristics of home (the number of rooms in the house): a room is defined as an area in the house enclosed by a wall, floor, and ceiling. This includes bedrooms, parlor, dinning, kitchen, bathroom, toilet, etc. A verandah is also regarded as a room because verandahs usually have lighting points.
  3. Purpose of electricity use, stock of appliances, and duration of use of appliances: the questionnaire provided a table which listed several commonly used electrical appliances and respondents were asked to select the appliances they own; to provide the number of each appliance owned and the average duration of use of each selected appliance if electricity is available all day and every day.2 The duration of use of bulbs, television, DVD/VCD, antenna, music player/radio, and refrigerator was expressed as intervals in hours/day as follows: 0.1–3 hours, 4–7 hours, 8–12 hours, 13–16 hours, and above 16 hours. Similarly, the duration of use of electric iron, hot plate, electric kettle, and blender were expressed as intervals in minutes/day as follows: 1–30 minutes, 31–60 minutes, 61–90 minutes, 91–120 minutes, and above 120 minutes. In addition, we note that for some appliances the duration of use may differ significantly depending on the room such appliances are located (e.g. fan, bulb):3 for such appliances, the duration of use of the appliance located in the sitting room or any other room that is most frequented by the members of the household is adopted. The study also acknowledges that duration of use of electrical appliances on weekends is usually different from those on weekdays. Nevertheless, we treat weekday and weekend use equally.

The study set out to cover 200 households in each village and the respondents were recruited through a door-to-door solicitation procedure; however, we encountered a relatively high non-response rate. Many households declined completing the questionnaire citing no personal benefit; in other cases, prospective respondents were not at home even on a Saturday. In all, the study covered 106 and 134 households in Adeleye and Adewumi villages respectively which are statistically large to validate the result of the survey. The survey was carried out in February, 2015.

2.3. Data analysis

The study seeks to estimate the electricity consumption of rural households using the bottom-up approach which involves summing up the total electricity consumed by each appliance with a given capacity used for a particular end-use of electricity, for all types of appliances and for all end-use of electricity. Mathematically, this may be expressed as:

(1)
j=1 k=1 l=1 Pjkl*Qjkl*Tjkl

Where: Pjkl is the kth type of appliance with lth capacity used to achieve the jth purpose of electricity use (for example, a 60W [capacity] incandescent bulb [type of appliance] used for lighting [purpose of electricity use]; Qjkl is the number of Pjkl; Tjkl is the duration of use of each Pjkl; while j, k, l, are counters for purposes of electricity use, types of appliance, and capacities of appliances respectively. We present in Figure 1 an example of the approach.

Figure 1 

Representation of the bottom-up approach for examining household electricity demand.

Our pilot survey showed that most respondents do not know the power consumption capacities of the appliances in their homes therefore we assume that the different types of appliances used for different purposes have the same capacities. This implies that Pjkl = Pjk; Qjkl = Qjk; and Tjkl = Tjk. Therefore eqn (1) becomes:

(2)
j=1 k=1 Pjk*Qjk*Tjk

We use the capacities of the appliance that are prevalent in the study area as presented in Table 1.

Table 1

Assumed power consumption capacities of the different electrical appliance.

Appliance Wattage Appliance Wattage

Lighting TV Antenna 15
      Incandescent 60 Music player 100
      Energy saving* 20 Refrigerator** 400
Television (21”) Electric Iron 1000
      Cathode ray tube 100 Hot Plate 1000
      LCD 30 Electric kettle 1000
Electric fan 30 Blender 300
DVD/VCD 15 Washing Machine 500

* This include fluorescent and compact fluorescent lamp (CFL) bulbs.

** Refrigerator will use 500W when it compressor is on and 200W when it is off. We assume that in a 24 hour period, the compressor will be on for two-third of the period. We use the weighted average.

For the duration of use of the appliances, we code the time intervals as follows: 0.1–3 hours = 1.5 hours; 4–7 hours = 5.5 hours; 8–12 hours = 10 hours; 13–16 hours = 14.5 hours, above 16 hours = 18 hours; 0–30 minutes = 0.25 hours; 31–60 minutes = 0.75 hours; 61–90 minutes = 1.25 hours; 91–120 minutes = 1.75 hours; and above 120 minutes = 2.25 hours. A major setback with this approach is that households are not fully conscious of the number of hours or minutes per day each appliance is used and therefore their estimates may not be accurate. Therefore, the accuracy of our result is contingent on the reliability and accuracy of the information provided by the households Murthy et al. (2001). After estimating the electricity consumption for all households in each village, we present the descriptive statistics of the household electricity consumption level for each village.

3. Result and discussion

This segment is divided into two parts: the first part is the summary of results from the questionnaire; and the second presents the summary of estimates of household electricity consumption.

3.1. Summary of results

3.1.1. Socio-economic profile of respondents

The socio-economic characteristics of individuals (age, sex, educational level, income, average time spent at home, etc) may play an important role in their level of electricity consumption (Zhou & Teng, 2013; Wijaya & Tezuka, 2013). The summary of the socio-economic profile of the respondents is presented in Table 2. We observe from Table 2 that the modal age range of heads of households in our study is 41–55 years for respondents in both villages. In terms of the sex of the respondents, 86% of the respondents in Adeleye village was male and 88% of the respondents in Adewumi village was male. The level of education of an individual may play a role in the level of electricity use (Rahut et al., 2014). Individuals with higher educational attainment are likely to have more income, may be aware of many electrical appliances and are likely to purchase and own these appliances if they can afford. About 93.4% and 89.6% of respondents in Adeleye and Adewumi villages respectively have a secondary school certificate.

Table 2

Socioeconomic characteristics of respondents.

Socio-economic characteristics Communities (number of respondents)

Adeleye (n = 106) Adewumi (n = 134)

Age of head of households
    Below 25 years 11 14
    25–40 37 42
    41–55 41 66
    55–70 12 11
    Above 70 years 5 1
    Mean [St. dev.] 2.65 [0.98] 2.57 [0.82]
Sex of head of households
    Female 15 16
    Male 91 118
Highest educational qualification of head of households
    No formal Education 0 0
    Primary school completed 7 14
    Secondary school completed 37 54
    ONDa/NCEb 47 36
    B.Sc./HNDc 15 28
    Post graduate qualification 0 2
Mean [St. dev.] 2.66 [0.80] 2.62 [0.98]
Household size
    1 to 3 12 29
    4 to 6 63 79
    7 to 9 27 22
    10 to 12 4 3
    12 and above 0 1
Mean [St. dev.] 5.57 [1.81] 5.06 [2.14]
Average monthly income*
    Below N10,000 7 19
    N10,001–N25,000 31 40
    N25,000–N40,000 33 32
    N40,00–N55,000 21 25
    N55,000 above 8 10
Mean [St. dev.] 2.92 [1.06] 2.74 [1.17]

a – ordinary national diploma; b – national certificate of education; c – higher national diploma; * not all respondents answered the question.

Household size may play role in the level of household electricity consumption because there will be more people in large households to make use of electricity services than in small households. The modal class for household size for both villages in our study is 4–6, with an average household size of 5.63 in Adeleye village and 5.06 in Adewumi village. The income level of an individual may influence his/her ability to purchase electrical appliances. Persons with higher income are more likely to own more electrical appliance than those with low income. The modal class for monthly income of respondents in Adeleye and Adewumi villages are N25,001–N40,000 and N10,001–N 25,000 respectively.

3.1.2. Number of rooms in the house

The second segment sought to know the number of rooms in the homes of the respondents. As highlighted in the Methodology, a room here is defined as an area in the house enclosed by a wall, floor, and ceiling and it includes bedrooms, parlor, dinning, kitchen, bathroom, toilet, verandah, etc. The number of rooms is directly related to the income level of the households because persons with higher income are likely to live in homes with many rooms. It is also related to the level of electricity consumption because homes with many rooms are likely to have more electrical appliances than those with fewer rooms. For example, it is expected that all rooms in a house will have at least one lighting point. The frequency distributions of the number of rooms for the two villages are presented in Figure 2.

Figure 2 

Frequency distribution of number of rooms in homes of respondents.

3.1.3. Purpose of electricity use, stock of appliances, and duration of use of appliances

We present the summary of the responses for purpose of use and stock of appliance in Table 3.

Table 3

Respondents’ purpose of use of electricity and stock of appliances.

Appliance Stock Adeleye Village (n = 106) Adewumi Village (n = 134)

Bulbs % of households that use electricity for lighting 100.0% 100.0%
% of Households that owned:
(i) only energy savings bulbs 16.0% 10.4%
(ii) only incandescent bulbs 45.3% 54.5%
(iii) both energy savings and incandescent bulbs 38.7% 34.3%
(iv) 1–3 incandescent bulbs 39.6% 29.1%
(v) 4–6 incandescent bulbs 27.4% 27.6%
(vi) 7–9 incandescent bulbs 9.4% 20.1%
(vii) more than 9 incandescent bulbs 7.5% 11.9%
(viii) 1–3 energy saving bulbs 32.1% 32.1%
(ix) 4–6 energy saving bulbs 10.4% 9.0%
(x) 7–9 energy saving bulbs 0.9% 3.7%
(xi) more than 9 energy saving bulbs 11.3% 0.0%
Television % of households that use electricity for television 94.3% 86.6%
% of Households that owned:
(i) only cathode ray tube 83.0% 73.9%
(ii) only LCD 5.7% 10.4%
(iii) both cathode ray tube and LCD 5.7% 2.2%
(iv) only one cathode ray tube 83.0% 66.4%
(v) more than one cathode ray tube 5.7% 9.7%
(vi) only one LCD 11.3% 11.2%
(vii) more than one LCD 0.0% 1.5%
Fan % of households that use electricity for fan 81.1% 82.1%
% of Households that owned:
(i) only one fan 29.2% 45.5%
(ii) 2–4 fans 49.1% 30.6%
(iii) more than 4 fans 2.8% 6.0%
DVD/VCD % of households that use electricity for DVD/VCD 91.5% 83.6%
% of Households that owned:
(i) only one DVD/VCD 72.6% 64.2%
(ii) more than one DVD/VCD 18.9% 19.4%
TV antenna % of households that use electricity for antenna 46.2% 52.2%
% of Households that owned:
(i) only one TV antenna 40.6% 47.0%
(ii) more than one TV antenna 5.7% 5.2%
Music player/radio % of households that use electricity for music player/radio 29.2% 44.8%
% of Households that owned:
(i) only one music player/radio 25.5% 27.6%
(ii) more than one music player/radio 3.8% 17.2%
Refrigerator % of households that use electricity for refrigeration 41.5% 41.0%
% of Households that owned:
(i) only one refrigerator 41.5% 39.6%
(ii) more than one refrigerator 0.0% 1.49%
Electric Iron % of households that use electricity for ironing clothes 69.8% 70.9%
% of Households that owned:
(i) only one electric iron 69.8% 70.9%
(ii) more than one electric iron 0.0% 0.0%
Hot plate % of households that use electricity for cooking 8.5% 11.9%
% of Households that owned:
(i) only one hot plate 8.5% 11.9%
(ii) more than one hot plate 0.0% 0.0%
Electric kettle % of households that use electricity for heating water 21.7% 22.4%
% of Households that owned:
(i) only one electric kettle 20.8% 22.4%
(ii) more than one electric kettle 0.9% 0.0%
Blender % of households that use electricity for blending food items 10.4% 15.7%
% of Households that owned:
(i) only one blender 10.4% 15.7%
(ii) more than one blender 0.0% 0.0%

We observe from Table 3 that all the respondents in both villages use electricity for lighting. Most respondents in both villages also use electricity to power television, DVD/VCD, electric fans and to iron clothes. We expected that the number of households that use electricity for playing music/radio will also be high, however this is not the case. The likely reason for this is that most DVD/VCD players can also be used for playing music and for radio therefore households may not see the need to purchase a separate music player/radio. A substantial percentage of households also own refrigerator and a few of them own more than one. The least end-use of electricity highlighted by the respondents in both communities is for cooking and blending food items. In addition, electricity is also used for pumping water by two households in Adeleye village and to power a computer by one and two households in Adeleye and Adewumi village respectively.

In terms of ownership of energy-saving appliances (bulbs and television), we observe from Table 3 that a substantial percentage of the respondents do own energy saving bulbs and 16.0% and 10.4% of respondents in Adeleye and Adewumi villages respectively use only energy saving bulbs. Similarly, 5.7% and 10.4% of the respondents in Adeleye and Adewumi villages own only liquid crystal display (LCD) televisions and 1.5% of the respondent in Adewumi village has more than one LCD television. The motivations for owning the energy saving appliances may be diverse: higher quality of output, durability, lower electricity consumption, etc. We did not probe the respondents further to determine their real motivations for owning the low energy appliances; however, the lower energy consumption of the appliances will likely be a motivation if the household owns a backup generator and not because of saving electricity from the grid. We may also deduce from Table 3 the propensity of households to switch energy sources. The percentage of respondents that use electricity for lighting and cooking re-echoes the findings from literature that access to electricity may cause a switch in energy source for lighting but not necessarily for cooking (IEA, 2010). The percentage of respondents that own blenders also shows that rural households are not likely to switch the source of blending food items. In contrast, the percentage of households that own electric irons shows that rural households are likely to switch from using charcoal irons to electric irons if they have access to electricity.

We present the summary of the duration of use of the appliances in Adeleye and adewumi villages in Tables 4 and 5 respectively.

Table 4

Distribution of duration of use of electric appliances in homes of respondents in Adeleye village (in %).

Total number of respondents (n = 106)

Appliance Number of respondents who own appliance Number of hours of use of appliance/day

0–3 4–7 8–12 13–16 above 16

Bulb 106 0.0% 14.2% 67.9% 17.9% 0.0%
Television 100 39.0% 49.0% 12.0% 0.0% 0.0%
Fan 86 17.4% 30.2% 30.2% 20.9% 1.2%
DCD/VCD 97 37.1% 54.6% 8.2% 0.0% 0.0%
Antenna 49 34.7% 57.1% 8.2% 0.0% 0.0%
music player/radio 31 48.4% 38.7% 12.9% 0.0% 0.0%
Refrigerator 44 0.0% 0.0% 2.3% 15.9% 81.8%
Number of minutes of use of appliance/day

0–30 31–60 61–90 91–120 above 120

Electric Iron 74 63.5% 36.5% 0.0% 0.0% 0.0%
Hot plate 9 0.0% 33.3% 55.6% 11.1% 0.0%
Boiler 23 95.7% 4.3% 0.0% 0.0% 0.0%
Blender 11 100.0% 0.0% 0.0% 0.0% 0.0%

Table 5

Distribution of duration of use of electric appliances in homes of respondents in Adewumi village (in %).

Total number of respondents (n = 134)

Appliance Number of respondents who own appliance Number of hours of use of appliance/day

0–3 4–7 8–12 13–16 above 16

Bulb 134 0.0% 29.1% 61.9% 7.5% 1.5%
Television 116 30.2% 48.3% 18.1% 0.0% 3.4%
Fan 110 6.4% 18.2% 60.9% 10.0% 4.5%
DCD/VCD 112 48.2% 32.1% 14.3% 0.9% 4.5%
Antenna 70 41.4% 35.7% 14.3% 1.4% 7.1%
music player/radio 60 31.7% 38.3% 26.7% 0.0% 3.3%
Refrigerator 55 0.0% 3.6% 12.7% 20.0% 63.6%
Number of minutes of use of appliance/day

0–30 31–60 61–90 91–120 above 120

Electric Iron 95 45.3% 49.5% 2.1% 3.2% 0.0%
Hot plate 16 62.5% 25.0% 0.0% 0.0% 12.5%
Boiler 30 86.7% 13.3% 0.0% 0.0% 0.0%
Blender 21 76.2% 19.0% 4.8% 0.0% 0.0%

We observe from Tables 4 and 5 that if electricity is available all day and every day, many households in both villages are likely to be putting on light in their homes for 8–12 hours daily. A large percentage of households in both communities also noted that they will use entertainment/relaxation appliances (television, DVD/VCD, radio/music player, antenna) for up to eight hours daily. When probed further, some of the respondents noted that the entertainment/relaxation appliances are connected to the same socket and all will be powered whenever the socket is on, albeit some may be on standby. In addition, a large percentage of respondents in both villages noted that they will use refrigerator for more than 16 hours/day; and electric kettle and blender for less than 30mins/day respectively.

3.2. Household electricity consumption

We present in Table 6 the summary of the household electricity consumption from our bottom-up analysis and in Table 7 the distribution of electricity consumption by appliances for selected households in both villages.

Table 6

Household electricity consumption level in the selected villages.

Consumption level/day (kWh) Adeleye (n = 106) Adewumi (n = 134)

Minimum 0.58 0.38
Maximum 18.06 20.56
Average 7.36 7.48
Standard deviation 4.80 5.17
Percentage distribution

0–5 45.3% 44.8%
5.01–10 22.6% 20.1%
10.01–15 24.5% 24.6%
15.01–20 7.5% 9.7%
20.01–25 0.0% 0.7%

Table 7

Distribution of electricity consumption by appliances for selected households in both villages.

Appliance Share of appliance consumption

Adeleye Adewumi

Bulbs 39.8% 38.9%
Television 6.1% 11.2%
Fan 6.1% 6.1%
DCD/VCD 1.0% 1.1%
Antenna 0.5% 0.5%
Music player/radio 0.9% 1.7%
Refrigerator 38.9% 34.6%
Electric Iron 4.2% 5.1%
Hot plate 1.6% 0.1%
Electric kettle 0.8% 0.4%
Blender 0.2% 0.3%
Total 100% 100%

Table 6 shows that the daily electricity consumption for the selected households in Adeleye village if electricity is available all day and everyday will range from 0.58 to 18.06 kWh/day, with average and standard deviation of 7.36 kWh/day and 4.8 kWh/day respectively. Similarly, the daily electricity consumption for the selected households in Adewumi village if electricity is available all day will be between 0.38 kWh/day and 20.56 kWh/day, with mean and standard deviation of 7.48 kWh/day and 5.17 kWh/day respectively. The frequency distribution shows that the percentage of respondents in both villages with electricity consumption level of 0–5kWh/day will be highest. In addition, the daily consumption level of 0.7% (i.e. only one) of the respondents in Adewumi village will be between 20.01 kWh/day and 25 kWh/day. We observe from Table 7 that lighting and refrigeration contributes the most to the total electricity consumption of the all the selected households in each village. Most households with higher daily consumptions are those that own refrigerators and plan to use the refrigerators for more than 16 hours a day.

4. Policy Implications and Conclusion

Data on the evolution of household electricity demand in communities that have been connected to the grid are largely unavailable and utilities and planners often rely on assumptions. In some cases, these assumptions are usually that electricity will be used for mainly lighting and to power low energy consuming appliances like televisions, electric fans, etc. as confirmed in Table 3. However, we also observe from Tables 3, 4, 5 that within the initial 10 years of having access to electricity, rural households are likely to use electricity for other purposes such as refrigeration and ironing of clothes which use appliances with relatively high electric power ratings. This is very likely in rural areas such as the ones used for this study where the electricity utility seldom distribute bills and the households seldom pay for the electricity use. Moreover, we observe from Tables 4 and 5 that if electricity is available all day and every day, rural households who own refrigerators are most likely to use them for more than 16 hours.

This finding is in line with the findings of (Xiaohua & Zhenmin, 2001) who noted that high electricity consuming appliances such as refrigerators, washing machines, etc. can be found in homes of relatively wealthy rural households. We observe from Table 6 that some households may consume as low as 0.38 kWh/day which is in line with IEAs assumption of the initial level of electricity consumption of 250 kWh/year, i.e. 0.68 kWh/day (IEA, 2011, p. 12), but we also see that there may be some households in rural communities that may consume up to 20.56 kWh/day. This result is in line with the findings of (Obermaier et al., 2012) that low electricity consumption levels give way to higher consumption levels in rural areas after only a few years of rural electrification. The level of consumption by some households is far beyond the lifeline tariff threshold for rural and low-income consumers in Nigeria (which is consumption below 50 kWh/month) and it results in loss of potential revenue for the distribution company in charge of the area. In addition, the duration of use of some appliances as noted by the respondents shows that many rural households with access to electricity are unaware of the impacts of their electricity consumption pattern on the electricity system which is already overburdened. Therefore, rural electrification programmes need to be accompanied with demand-side management education. Finally, the main motivation of this study was to fill the data gap on rural household electricity consumption in Nigeria – a duty that should normally be carried out by the Rural Electrification Agency and Energy Commission of Nigeria. This study calls on these agencies to conduct a comprehensive survey on household electricity use in Nigeria as this will help planners and researchers in rural electrification.

Notes

1Nigeria is a federal republic made up of 36 federating units and one federal capital territory and each state is further divided into local government areas. The federal, state, and local government areas are the three main tiers of governance. In addition, the LGAs may be further divided into wards and each ward is made up of villages and/or communities. 

2Using the present level of electricity use would have been more appropriate if electricity supply was regular; however, the erratic nature of power supply implies that electricity is used only when available and this will not reflect the level of use of appliances. Therefore we use the expected level of use if electricity is available all day and every day. 

3For example, bulbs in the verandah may be powered all night while those in the bedroom will often be put off; fans in the sitting room may be put on for longer hours than those in the bedroom. 

Ethics and Consent

This data collected in this study were collected with the support of a number of subjects who accepted to complete our questionnaire after agreeing to the Informed Consent statement included at the top of the questionnaire.

Funding Information

This research is funded by the DR YUSUFU BALA USMAN FOUNDATION, located at 24 Hanwa Road, GRA Zaria, Kaduna State, Nigeria with grant number 20212/DYBUF/05.

Competing Interests

The authors have no competing interests to declare.

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