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Applying consumption time analysis to measure fundamental energy needs: A method to quantify households’ energy services


This research utilizes “time use” analysis, rather than the “power” side of energy consumption, to measure households’ fundamental energy needs (FENs) that is helpful for energy poverty alleviation. Households’ FENs contain energy for cooking, cooling, heating, and lighting/entertainment services, which vary in terms of the family size, their lifestyle, weather parameters, and so on. This research monitors and records time usage of FENs activities for a low-income couple family lived in a triplex kind of house in Japan. After fitting statistical distribution for time usage data, simulation model is used to calculate robust results for household energy consumption. The results indicate that the average daily FENs of this family is around 63 Mega Joule. The results also emphasize that for energy poverty reduction, the investment cost should be prioritized for cooking with the highest share of energy service, followed by heating, cooling, and lighting/entertainment service.

Graphical abstract


The results of this study showed that investment on cooking and heating services reduced energy poverty up to 75%. While, the cooling and lighting/entertainment services share was around 25%.


  • Many studies have analyzed the impact of renewable energies in energy poverty reduction in pre-developing countries. However, the cost of supplying 100% of energy demand through renewable energies to reduce energy poverty, is higher than hybrid power system option. Applying diesel generator along with renewable energies is a viable option with lower cost, while the existence of diesel generator is mostly ignored due to its trivial CO2 emissions compared with significant amount of CO2 emissions in developed countries.

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  1. India accounted for 25% of this figure, followed by Sub-Saharan African countries (53%).

  2. It comprised India (29%), China (17%), Sub-Saharan African countries (30%), and the rest of world countries (24%).

  3. Traditional biomass does not belong to clean fuel.

  4. Typical focus of energy poverty in developed countries is on affordability.

  5. Wooden table frame covered by a heavy blanket with a heat source underneath the table.

  6. Leftover meals.

  7. ”D” stands for duration between two times.

  8. The paper utilizes the “Oracle Crystal Ball” program to find the best fitted statistical distribution for each data set. This program is embedded into the Microsoft Excel through the “add-in” tool.

  9. Its square root represents the standard deviation.

  10. Recommended range of maximum water velocity is 1 m/s for copper pipe with diameter between 15 to 50 mm.

  11. Total gas consumption for cooking, boiling water, hot water for dishwashing, hand-washing clothes, and taking bath was 10.59 m3, from April 12 to May 15, 2018. While, the amount of gas usage based on time consumption analysis was 10.80 m3.

  12. “R.STYLE” with model “KGE31NSGR”.

  13. Peak hours vary from one country to another and summer vs winter season. However, in most practical terms, peak hours varies from 6p.m. to 10 p.m., while off-peak times change since 10 p.m. to 7 a.m.

  14. Efficiency of renewable energies such as solar and wind highly depends on location, technology specifications, and raw materials (in case of biomass). However, the efficiency of current wind turbines mostly ranges among 20% to 40%, biomass varies among 10%-20%, or most solar panels efficiency range among 16% to 22% (average 19.7%).[4446]


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Correspondence to Reza Nadimi.


Appendix A

Energy usage for cooking

The amount of burning fuel mass, Mf, in the cooking stove43 is calculated through the following formula:

$$M_{{\text{f}}} = \frac{{P \times t}}{{{\text{HHV}}}} \quad \mathop{{\text{unit}}}\limits^{ \leftrightarrow } \quad {\text{Kg}} = \frac{{{\text{kW}} \times {\text{Sec}}.}}{{{\text{kJ}}/{\text{kg}}}}$$

where t and P represent the usage time and output power of cooking stove, respectively.

Energy usage for hot water

The following equation calculates the amount of energy, E, required to raise up temperature as much as ΔT for water with V volume:44

$$E = S \times V \times \Delta T \times R \times 2.77778 \times 10^{{ - 7}} \quad \mathop{{\text{unit}}}\limits^{ \leftrightarrow } \quad {\text{KWh}} = \frac{{{\text{Joule}}}}{{{\text{gram}} \,^\circ{\text{C}}}} \times {\text{gram}} \times \,^\circ{\text{C}}$$

where S and R represent the water specific heat capacity (equals with 4.186) and the heater performance ratio (default 0.9), respectively. The desired hot water temperature is assumed 42 °C, while the ambient temperature indicates the amount of ΔT. The constant value (2.77778 × 10–7) in Eq. (17) implies the conversion unit from Joule to kWh. The water volume used for a particular activity is calculated through flow rate Eq. (13) and consumption time of the activity.

Appendix B

See Table 7.

Table 7 Statistical distributions and their parameters for each activity.

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Nadimi, R., Tokimatsu, K. Applying consumption time analysis to measure fundamental energy needs: A method to quantify households’ energy services. MRS Energy & Sustainability (2022).

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  • energy generation
  • statistics/statistical methods
  • renewable
  • simulation
  • sustainability