Modelling and forecasting Turkish residential electricity demand

This research investigates the relationship between Turkish residential electricity consumption, household total final consumption expenditure and residential electricity prices by applying the structural time series model to annual data over the period from 1960 to 2008. Household total final consumption expenditure, real energy prices and an underlying energy demand trend are found to be important drivers of Turkish residential electricity demand with the estimated short run and the long run total final consumption expenditure elasticities being 0.38 and 1.57, respectively, and the estimated short run and long run price elasticities being −0.09 and −0.38, respectively. Moreover, the estimated underlying energy demand trend, (which, as far as is known, has not been investigated before for the Turkish residential sector) should be of some benefit to Turkish decision makers in terms of energy planning. It provides information about the impact of past policies, the influence of technical progress, the impacts of changes in consumer behaviour and the effects of changes in economic structure. Furthermore, based on the estimated equation, and different forecast assumptions, it is predicted that Turkish residential electricity demand will be somewhere between 48 and 80 TWh by 2020 compared to 40 TWh in 2008.     

Electricity end-uses in the residential sector of Brazil

The residential energy consumption has been studied in many countries as it usually accounts for a large percentage of the total energy consumption. Energy end-uses have also been a matter of concern as they can assist energy system planning. The objective of this paper is to assess the actual scenario of electricity consumption and estimate electricity end-uses in the residential sector of Brazil for different bioclimatic zones. The analysis is based on a survey performed by 17 energy utilities enclosing a total of 17,643 houses or flats over 12 states in Brazil. The survey was performed to obtain electricity consumption data for all household appliances found in houses and flats. The electricity end-uses were estimated by performing weighted averages according to the location of the dwellings in each bioclimatic zone. Results indicate that the largest end-uses are for refrigerator and freezer together, which account for about 38–49% of the electricity consumption in dwellings in Brazil. Air-conditioning and electric shower are the end-uses that are more dependent on the climatic conditions. The main conclusion that can be made from the analysis is that air-conditioning should be a major concern in the residential sector of Brazil in the near future as its ownership is still low, but its electricity consumption is already significant mainly over summer.     

Effectiveness of an energy-consumption information system on energy savings in residential houses based on monitored data

Reducing energy demand in the residential sector is an important problem worldwide. This study focused on the awareness of residents to energy conservation and on the potential of reducing energy demand through energy-saving activities. To carry out quantitative analysis, an on-line interactive “energy consumption information system” for motivating energy-saving activities is constructed, and it was installed in nine residential houses. By utilizing data of measured power consumption, ambient and room temperatures before and after installation of the system, and the responses of the residents to the system, its effectiveness was evaluated. Major findings were as follows: (1) installation of the system led to a 9% reduction in power consumption, (2) comparisons of daily-load curves and load-duration curves for each appliance, before and after installation, revealed various energy-saving behaviors of the household members such as the reduction of standby power and better control of appliance operation, and (3) energy-conservation awareness affected not only the power consumption of the appliances explicitly shown on the display monitor, but also other household appliances.     

Effectiveness of an energy-consumption information system for residential buildings

The authors have proposed a method of reducing the energy consumption in residential buildings by providing household members with information on energy consumptions in their own houses. An on-line interactive “energy-consumption information system” that displays power consumptions of, at most, 18 different appliances, power and city-gas consumption of the whole house and room temperature, for the purpose of motivating energy-saving activities has been constructed and the effectiveness of the system investigated by installing it in 10 residential buildings. The experiment showed that energy-saving consciousness was raised and energy consumption was in fact reduced by the energy-saving activities of the household members. In this paper, the system is described in detail and the effectiveness of reducing energy-consumption of the whole house and for space heating will be discussed. Also the energy-saving activities in a certain household are shown by using load duration curves.     

居住建筑固定资产投资项目节能评估中综合能耗计算方法的分析与比较

结合工作实践,发现西安市居住建筑类项目存在不同评估单位计算的年综合能耗量数值差异很大的现象,经比较分析发现差异的主要原因是建筑物采暖耗能量评估计算依据的标准规范不一致。通过对比两种计算方法的内容与指标,认为《城镇供热管网设计规范》采暖热负荷推荐值与项目具体建筑物体形系数、热工性能参数等数值无关,对单体建筑物而言不具有针对性,不是唯一的。因此,建议以《严寒和寒冷地区居住建筑节能设计标准》为节能评估计算依据,方符合国家推行固定资产投资项目节能评估与审查的目的。     

Identifying electricity-saving potential in rural China: Empirical evidence from a household survey

In recent years, there has been a fast-growing body of literature examining energy-saving potential in relation to electricity. However, empirical studies focusing on non-Western nations are limited. To fill this gap, this study intends to examine the electricity-saving potential of rural households in China using a unique data set from the China Residential Electricity Consumption Survey (CRECS) in collaboration with the China General Social Survey (CGSS), conducted nationwide at the household level in rural China. We use a stochastic frontier model, which allows us to decompose residential electricity consumption into the minimum necessary amount of consumption based on physical characteristics (e.g. house size, house age, number of televisions or refrigerators) and estimate the consumption slack (i.e. the amount of electricity consumption that could be saved), which depends on various factors. We find that rural households in China are generally efficient in electricity saving and the saving potential is affected by (fast) information feedback and social-demographic characteristics, instead of by the (averaged) electricity price, or energy efficiency labelling signals. In addition, we find no evidence of regional heterogeneity on electricity saving potential for rural households. Policy implications are derived.     

Evaluation on energy and thermal performance for residential envelopes in hot summer and cold winter zone of China

As a result of rapid economic growth in the last several decades, energy issue is becoming more and more important in today’s world because of a possible energy shortage in the future; the usage of residential electricity has increased rapidly in China and building energy efficiency is included as one of the 10 key programs targeting energy efficiency improvement in the 11th Five-Year Plan. In response to the growing concerns about energy conservation in residential buildings and its implications for the environment, systematic evaluation on energy and thermal Performance for residential envelops (EETP) is put forward to assess the energy efficiency of envelop designs and to calculate the energy consumption of cooling and heating systems. Hot summer and cold winter zone of China was selected for EETP analysis because of its rigorous climatic and huge energy consumption. The correlations between EETPs and electricity consumptions in cooling season, heating season, and the whole year were built in Shanghai, Changsha, Shaoguan and Chengdu, which represent A, B, C and D subzone of hot summer and cold winter zone in China, respectively. Illustrations indicate that the algorithm is simple and effective, energy and thermal performance of residential envelopes can be evaluated easily. The maximum allowable values of EETPs were determined when just meeting the compulsory indices of Standard JGJ134-2001, the corresponding allowable EETPs were also gained when achieving different energy-saving degrees on basis of it. EETP method can suggest possible ways to improve the energy efficiency for envelope designs of new building and retrofits of existing buildings and provide governments some useful information for the establishment of new policy on energy efficiency buildings. It has important meanings to carry out sustainable residential building designs with high thermal comfort and low energy consumption.     

The optimization of demand response programs in smart grids

The potential to schedule portion of the electricity demand in smart energy systems is clear as a significant opportunity to enhance the efficiency of the grids. Demand response is one of the new developments in the field of electricity which is meant to engage consumers in improving the energy consumption pattern. We used Teaching & Learning based Optimization (TLBO) and Shuffled Frog Leaping (SFL) algorithms to propose an optimization model for consumption scheduling in smart grid when payment costs of different periods are reduced. This study conducted on four types residential consumers obtained in the summer for some residential houses located in the centre of Tehran city in Iran: first with time of use pricing, second with real-time pricing, third one with critical peak pricing, and the last consumer had no tariff for pricing. The results demonstrate that the adoption of demand response programs can reduce total payment costs and determine a more efficient use of optimization techniques.     

Path Analysis of Energy-Saving Technology in Yangtze River Basin Based on Multi-Objective and Multi-Parameter Optimisation

The Yangtze River Basin in China is characterised by hot-and cold-humid climates in summer and winter, respectively. Thus, increased demand for heating and cooling energy according to the season, as well as poor indoor thermal comfort, are inevitable. To overcome this problem, this study focused on the influence of passive design and heating, ventilation, and air conditioning equipment performance on the energy performance of residential buildings, and explored potential energy-saving technology paths involving passive design and improved coefficient of performance through a multi-objective and multi-parameter optimisation technique. A large-scale questionnaire survey covering a typical city was first conducted to identify family lifestyle patterns regarding time spent at home, family type, air conditioner use habits, indoor thermal comfort, etc. Then, the actual heating and cooling energy consumption and information of model building were determined for this region. Subsequently, the design parameters of an individual building were simulated using Energyplus to investigate the cooling and heating energy consumption for a typical residential building with an air conditioner. The results indicated an improvement of approximately 30% in energy efficiency through optimisation of the external-wall insulation thickness and the external-window and shading performance, and through use of appropriate ventilation technology. Thus, a multi-objective and multi-parameter optimisation model was developed to achieve comprehensive optimisation of several design parameters. Experimental results showed that comprehensive optimisation could not only reduce cooling and heating energy consumption, but also improve the thermal comfort level achieved with a non-artificial cooling and heating source. Finally, three energy-saving technology paths were formulated to achieve a balance between indoor thermal comfort improvement and the target energy efficiency(20 kWh/(m2?a)). The findings of this study have implications for the future design of buildings in the Yangtze River Basin, and for modification of existing buildings for improved energy efficiency.     

Responsiveness of low-income households to hybrid price/non-price policies in the presence of energy shortages: evidence from Colombia

At the beginning of 2016, Colombia was experiencing an energy shortage, and in order to avoid mandatory power cuts, the government launched an unexpected hybrid price/non-price energy-saving policy. In this paper, I evaluate how low-income households in a major Colombian city respond to this policy. Using hourly household electricity consumption data, I find that, on average, households reduce electricity consumption by 4.5% as a result of the policy. It is striking that even low-income households, who consume relatively small amounts of electricity, respond to energy-saving policies and engage in conservation behaviors in the short term. In my analysis, I also find that the effect is stronger the higher the household pre-treatment electricity consumption levels and smaller among poorer households. However, the heterogeneity in terms of income level vanishes once I control for household pre-program electricity consumption levels. Finally, my point estimates are comparable to the impact estimates of policies that are similar to the one I analyze in this paper.     

Evaluation of city-scale impact of residential energy conservation measures using the detailed end-use simulation model

Energy conservation policies for the residential sector are evaluated by a model that simulates city-scale energy consumption in the residential sector by considering the diversity of household and building types. In this model, all the households in the city are classified into 380 categories based on the household and building type. The energy consumption for each household category is simulated by the dynamic energy simulation model, which includes an energy use schedule model and a heating and cooling load calculation model. Since the energy usage of each appliance is simulated for every 5 min according to the occupants’ energy usage activity, this model can evaluate not only the energy conservation measures by improving the buildings and appliances but also the measures that involve changing the occupants’ activities. The accuracy of the model is verified by comparing its results with the statistical and the measured data on Osaka City, Japan. Various types of energy conservation measures planned by the Japanese government for the residential sector are simulated and their effects on Osaka City are evaluated quantitatively. The future effects of these combined measures on the energy consumption are also predicted.     

Electricity consumption and energy savings potential of video game consoles in the United States

Total energy consumption of video game consoles has grown rapidly in the past few decades due to rapid increases in market penetration, power consumption of the devices, and increasing usage driven by new capabilities. Unfortunately, studies investigating the energy impacts of these devices have been limited and potential responses, such as ENERGY STAR requirements, have been difficult to define and implement. We estimate that the total electricity consumption of video game consoles in the US was around 11?TWh in 2007 and 16?TWh in 2010 (approximately 1?% of US residential electricity consumption), an increase of almost 50?% in 3?years. However, any estimate of total game console energy consumption is highly uncertain, and we have determined that the key uncertainty is the unknown consumer behavior with regards to powering down the system after use. Even under this uncertainty, we demonstrate that the most effective energy-saving modification is incorporation of a default auto power down feature, which could reduce electricity consumption of game consoles by 75?% (10?TWh reduction of electricity in 2010), saving consumers over $1 billion annually in electricity bills. We conclude that using an auto power down feature for game consoles is at least as effective for reducing energy consumption as implementing a strict set of energy efficiency improvements for the devices, is much easier to implement given the nature of the video game console industry, and could be applied retroactively to currently deployed consoles through firmware updates.     

Estimating energy savings due to conservation programmes: The BPA residential weatherization pilot programme

The Bonneville Power Administration operated a residential weatherization pilot programme from 1980 to 1982. The programme provided free home energy audits to more than 7000 electrically heated homes in the Pacific Northwest and gave zero-interest loans to weatherize over 4000 of these homes. The total cost of the programme was $11 million. This paper describes several mehtods used to estimate the net energy-saving effect of the BPA programme (ie the electricity saving that could be directly attributed to the programme). The simplest method ivolves estimation of weather adjusted annual electricity consumption for each household. The second approach uses this weather adjusted consumption as the dependent variable in a pooled time-series cross-section regression model of electricity use. The third approach involves estimation of qualitative choice models of the decisions to retrofit and to participate in the BPA programme. Results from these models are used to define Mills ratio terms that are then used as explanatory variables in the regression model of the second approach. The range in estimated programme saving, given the diversity of analytical methods used, is surprisingly small — 3100–3300 kWh/year per average programme participant.     

Residential energy demand in the United States: Analysis using static and dynamic approaches

The residential sector is the main consumer of energy in the United States, and reducing energy consumption is an important goal for policymakers in each state. To know how reducing residential energy demand could be achieved, this study develops a set of static and dynamic models to investigate and identify the impact of socio-economic and demographic characteristics, building age, energy prices, and weather conditions on residential energy demand at the state level from 2005 to 2013. Next, this study proposes two alternative scenarios to reduce residential energy demand based on the most precise model. For every 10,000 dollars of per capita income in each state: (1) increasing residential electricity price by 1 cent per kW h and (2) decreasing average building age by 1%. In the first scenario, the findings indicate that annual residential electricity demand would decrease by 7.3% on average, with the highest reductions in Washington (11.9%), North Dakota (10.9%), and Idaho (9.7%). In the second scenario, residential gas demand would decrease by an average of 15.8% annually, with the highest reduction in Connecticut (33.2%) followed by New York (33.0%) and Massachusetts (30.7%). These proposed scenarios assist policymakers in optimizing decisions and investments to reduce residential energy consumption.     

The effect of sociodemographic diversity of residential customers on the financial risk experienced in the retail electricity market

The sociodemographic diversity of residential customers can affect the level of financial risk that an electricity provider experiences in the retail market. To demonstrate the relationship between sociodemographic diversity and financial risk, electricity consumption data drawn from the United Kingdom Power Networks ‘Low Carbon London’ project was analyzed to explore the relationship between sociodemographic diversity and financial risk experienced by electricity retailers. The results show that when increasing the sociodemographic diversity amongst a group of residential customers the effect on financial risk depends on the electricity consumption patterns of individual customers and the relationship of consumption patterns between residential customers. Increasing sociodemographic diversity amongst residential customers with very distinct energy consumption patterns can decrease the overall financial risk associated with the aggregated revenue received from these customers. However, the results showed that adding customers to a customer base without consideration for their sociodemographic background can cause the overall financial risk associated with the aggregated revenue received to change erratically. Whilst previous studies have considered customer diversity and its influence on peak electricity demand, this research advances the state-of-the-art by showing the importance of customer diversity to the financial quantity risk experienced by electricity retailers. This finding has serious implications for electricity providers seeking to mitigate financial risk in the retail electricity market.     

Assessment of hydrogen as a potential energy storage for urban areas’ PV-assisted energy systems - Case study

The world is experiencing unprecedented development in the clean energy sector in residential and industrial applications. This paper provides a case study assessing different scenarios of greenizing the electrical energy demand in El-Mostakbal city in Egypt. Three scenarios are studied with consideration of a photovoltaic (PV) system integrated with the grid-connected city with different integrated system configurations. The scenarios for the grid-connected city are scenario-I: only PV, scenario-II: PV with batteries for electricity storage along with grid electricity, and scenario-III: PV with hydrogen production, storage, and utilization for covering the electric demand along with grid electricity, these scenarios are assessed technoeconomically, and the results show an optimized case where the electricity demand of the city can be met with 64.3% produced from solar energy, at $71.7 M of the net present cost.     

Effects of demand side management on Chinese household electricity consumption: Empirical findings from Chinese household survey

China’s residential electricity demand has grown rapidly over the last three decades and given the expected continued growth, demand side management (DSM) can play an important role in reducing electricity demand. By using micro-level data collected from 1450 households in 27 provinces in the first-ever China Residential Energy Consumption Survey in 2012, this study estimates the effects of three DSM measures empirically: tiered household electricity pricing, China Energy Label program, and information feedback mechanisms. We find these measures have contributed to moderating residential electricity demand growth but additional policy reform and tools are needed to increase their effectiveness and impact. Residential electricity demand is found to be price- and income- inelastic and tiered pricing alone may not be as effective in electricity conservation. The statistically significant relationship between China Energy Label efficient refrigerators - but not televisions - and lowered residential electricity consumption reflect mixed program effectiveness. Lastly, of the information feedback currently available through electricity bills, payment frequency and meters, only meter reader is estimated to be statistically significant. Important policy implications and recommendations for improving each of these three DSM measures to expand their impact on reducing residential electricity consumption are identified.     

Life-cycle energy of residential buildings in China

In the context of rapid urbanization and new construction in rural China, residential building energy consumption has the potential to increase with the expected increase in demand. A process-based hybrid life-cycle assessment model is used to quantify the life-cycle energy use for both urban and rural residential buildings in China and determine the energy use characteristics of each life cycle phase. An input–output model for the pre-use phases is based on 2007 Chinese economic benchmark data. A process-based life-cycle assessment model for estimating the operation and demolition phases uses historical energy-intensity data. Results show that operation energy in both urban and rural residential buildings is dominant and varies from 75% to 86% of life cycle energy respectively. Gaps in living standards as well as differences in building structure and materials result in a life-cycle energy intensity of urban residential buildings that is 20% higher than that of rural residential buildings. The life-cycle energy of urban residential buildings is most sensitive to the reduction of operational energy intensity excluding heating energy which depends on both the occupants' energy-saving behavior as well as the performance of the building itself.     

Prediction of greenhouse gas reduction potential in Japanese residential sector by residential energy end-use model

A model is developed that simulates nationwide energy consumption of the residential sector by considering the diversity of household and building types. Since this model can simulate the energy consumption for each household and building category by dynamic energy use based on the schedule of the occupants’ activities and a heating and cooling load calculation model, various kinds of energy-saving policies can be evaluated with considerable accuracy. In addition, the average energy efficiency of major electric appliances used in the residential sector and the percentages of housing insulation levels of existing houses is predicted by the “stock transition model.” In this paper, energy consumption and CO₂ emissions in the Japanese residential sector until 2025 are predicted. For example, as a business – as-usual (BAU) case, CO₂ emissions will be reduced by 7% from the 1990 level. Also evaluated are mitigation measures such as the energy efficiency standard for home electric appliances, thermal insulation code, reduction of standby power, high-efficiency water heaters, energy-efficient behavior of occupants, and dissemination of photovoltaic panels.     

Analysis and modeling of active occupancy of the residential sector in Spain: An indicator of residential electricity consumption

The growing energy consumption in the residential sector represents about 30% of global demand. This calls for Demand Side Management solutions propelling change in behaviors of end consumers, with the aim to reduce overall consumption as well as shift it to periods in which demand is lower and where the cost of generating energy is lower. Demand Side Management solutions require detailed knowledge about the patterns of energy consumption. The profile of electricity demand in the residential sector is highly correlated with the time of active occupancy of the dwellings; therefore in this study the occupancy patterns in Spanish properties was determined using the 2009–2010 Time Use Survey (TUS), conducted by the National Statistical Institute of Spain. The survey identifies three peaks in active occupancy, which coincide with morning, noon and evening. This information has been used to input into a stochastic model which generates active occupancy profiles of dwellings, with the aim to simulate domestic electricity consumption. TUS data were also used to identify which appliance-related activities could be considered for Demand Side Management solutions during the three peaks of occupancy.