Indices of energy consumption: An exploratory analysis of a utility's monthly billing data

Simple weather-sensitive models are derived and applied to monthly energy billing data for a large utility region in New Jersey. Natural gas demand in the residential sector is explored in depth, and the method is applied to other gas and electricity sectors. The results are related to an earlier empirical study of single-family residences.Our findings and hypotheses fall into two classes, those which are specific to the utility's customers and those which pertain to utility data in general. As for the specific utility's residential gas customers, the findings suggest that they reduced their use of gas during the oil embargo of 1973–1974 and the New Jersey natural gas shortage of 1976–1977, and, most likely, the consumption reduction was due to lowered thermostats and reduced use of appliances rather than to retrofitting of dwellings. The more general findings are that utility data can be very valuable for monitoring changes in consumption patterns, and that there is a potential for extracting consumption indices from the data; these indices would not only signal whether consumption patterns are changing but also why. The first of our conclusions needs to be examined for other sample data sets and other regions. The second, our most important hypothesis, merits systematic investigation.     

Measuring household fuel consumption on the Standard Living Cycle

A simple model for monitoring natural gas consumption in large aggregates of houses is developed by extending single-house analyses. The parameters of the model are baseload consumption, rate of fuel use per degree-day for heating, and a reference temperature. Accuracy of the results is assessed by means of confidence intervals derived for the nonlinear model.The meaning of these parameters for the aggregate is investigated using idealized-house data. When applied to actual data for natural gas sales in New Jersey, the model yields parameters which are generally useful indicators but lack the required accuracy for definitive assessments of year-to-year consumption changes. Based on these parameters, a well-determined index representing consumption on a Standard Living Cycle is derived for accurate monitoring of conservation trends. The index calculated from the New Jersey data over the past decade demonstrates interesting changes in the state's consumption patterns.     

Elasticity of demand for gasoline since the 1973 oil embargo

The magnitude E of the price elasticity of gasoline was found to be $\text{E = 0.2054(1 ?}\text{savings due to unemployment and voluntary conservation (per cent of forcast sales)}\text{4.78}\text{± 0.0378}$ within 95% confidence limits. This results holds over a two-year period following the Arab oil embargo in which real prices rose as much as 30%. No discernable change in elasticity was observed over the two-year period. Savings in gasoline consumption due to unemployment and voluntary conservation are almost certainly less than 4.78% of forecast sales. Voluntary conservation may well be closer to 0% than to 4.78%. The methodology of the study was to fit a Box-Jenkins² time series model to 13 years of gasoline sales prior to the embargo, and to use this model to predict what sales would have been had no change in price or other conditions occurred.     

Energy and fuel consumption forecast by retrofitting absorption cooling in Malaysia from 2012 to 2025

Electricity demand in residential and commercial sectors has increased steadily over the past 50 years in Malaysia. The bulk of which is being consumed by air conditioning systems. Absorption cooling systems can be a reasonable alternative to have conditioned spaces in the country. The fuel consumption to produce electricity for cooling purposes in residential and commercial sectors has been forecasted from 2012 to 2025. The paper also investigates the effect of applying five different scenarios on energy and fuel consumption by retrofitting absorption chillers instead of conventional cooling systems. This study found that the consumption of natural gas will be raised by increase in utilized absorption chillers however, the consumption of different fuels such as coal, diesel and fuel oil will decrease in thermal power plants.     

Tests for structural change in US oil consumption, 1967–1982

The purpose of this paper is to test US oil consumption for structural change over the period 1967–1982. A frequently used functional form is posited for total petroleum consumption as well as for gasoline, distillate, and residual fuel. Tests for abrupt change (Chow) and gradual or conservation-like change (Durbin, Brown, Evans and Farley, Hinnich, McGuire) are employed at special break points (1973 embargo, 1979 Iranian crisis, 1980 recession) to check for abrupt changes and across years in general to detect gradual shifts. Both abrupt and gradual changes are found, although the last five years may be the beginning of a new non-changing period.     

The relationship between the price and demand for natural gas: A partially controlled study

Since the onset of the energy crisis, indicated by the start of the Arab oil embargo, the price of natural gas increased for most residential consumers. the relationship between price and monthly demand over five years is examined for a sample of almost identical owner-occupied town houses in a planned community in central New Jersey, USA. It is shown that, since the onset of the energy crisis, the average price, in current dollars, of gas has increased in the USA, and the average demand has decreased, leading to a significant negative estimate of elasticity. However, this disappears if the effects of overall inflation on demand are removed. Closer examination reveals that the relationship between current price and demand is not linear, since the major decrease in demand occurred during the winter immediately following the embargo, but the major increases in current price occurred during subsequent winters. Whether the large reduction in demand is due to price increases, overall inflation, or is a response to conservation appeals by US public officials is an open question. No short-term effects of price on demand are found.     

Information strategies for energy conservation: A field experiment in India

Little is known about the effectiveness of information strategies on energy conservation in developing countries. In this study, we conduct a field experiment in an apartment complex in India to test how information about electricity usage impacts the electricity consumption of urban middle class households. Our results, based on fifteen-minute electricity readings over an academic year, show that non-monetary messages that framed electricity consumption in terms of environmental and health impacts were more effective than messages emphasizing the monetary savings of reducing electricity consumption. Households in the environmental/health group accessed the online energy-monitoring dashboard more frequently and reduced their electricity usage by 18.4% relative to the control group. Households in the monetary group did not significantly alter their usage. These results about revealed preferences are contrasted with stated preferences disclosed in a survey of urban Indians who describe money, not health, as the main motivation for energy conservation. Our findings have important implications for the development non-monetary strategies for energy conservation in developing countries.     

Energy rebound effect in China's Industry: An aggregate and disaggregate analysis

Considering the crucial role of industrial sectors in energy conservation, this paper investigates the impact of output growth on energy consumption in China's industrial sectors with an index decomposition model and the energy rebound effect in the industrial sectors with a panel data model using the annual data during 1994–2012. The empirical results indicate that: first, industrial output growth is proved to be the major factor in promoting industrial energy consumption, while energy intensity reduction and structure shifts across industrial sub-sectors play the dominant roles in slowing down industrial energy consumption. Second, there does exist energy rebound effect in China's aggregate Industry, which ranges from 20% to 76% during 1995–2012 (or 39% on average). In particular, the energy rebound effect in Manufacturing is relatively smaller during the sample period (i.e., 28% on average). Finally, the energy rebound effect in both China's aggregate Industry and Manufacturing exhibit an overall decreasing trend over time.     

Structural breaks, energy consumption, and economic growth revisited: Evidence from Taiwan

This paper studies the stability between energy consumption and GDP for Taiwan during 1954–2003. We use aggregate as well as various disaggregate data of energy consumption, including coal, oil, gas, and electricity, to employ the unit root tests and the cointegration tests allowing for structural breaks. Our main findings are: First, though gas consumption seems to have structural breaks in the 1960s, after considering the structural breaks, the series is a stationary variable when Taiwan adopted its expansionary export trade policy. Second, we find that different directions of causality exist between GDP and various kinds of energy consumption. The empirical result shows unanimously in the long run that energy acts as an engine of economic growth, and that energy conservation may harm economic growth. Third, the cointegration between energy consumption and GDP is unstable, and some economic events may affect the stability. Overall, we do find the structural breakpoints, and they look to match clearly with the corresponding critical economic incidents.     

The dieselization of American agriculture

This study investigates the increase in the relative importance of diesel fuel in terms of aggregate farm energy consumption over the 1971–1989 period coupled with the decline in the absolute quantity of diesel fuel consumed over the 1978–1989 period in the USA. Four factors are identified as being central to the observed trend. These include the relative efficiency of diesel-powered equipment versus gasoline-powered equipment, the technological changes in dieselpowered equipment that have impacted energy efficiency, the trend towards larger farms, and the enhanced energy conservation by farmers as a result of the adoption of reduced tillage practices.     

Electricity and natural gas use for residential space heating: U.S. experience, 1976–1980

Energy consumption for residential space heating has been studied for households using electricity and natural gas, based on aggregate sales data for 1976–1980. The ratio of average end-use energy consumption with electricity to that with natural gas was found to be 0.44 ± 0.06, despite little use of electric heat pumps. Together with the results of other studies, this estimate suggests that electric space heating can be used in future construction without requiring more primary input energy (including generation losses) than the average input energy used for gas space heating in existing residences, assuming modest conservation measures. While these results do not establish the relative fuel consumption in future gas-heated and electrically-heated households, they do provide a rough ceiling on the amount of energy required if electricity is used.     

What can we learn from high-frequency appliance-level energy metering? Results from a field experiment

This study uses high-frequency appliance-level electricity consumption data for 124 apartments over 24 months to provide a better understanding of appliance-level electricity consumption behavior. We conduct our analysis in a standardized set of apartments with similar appliances, which allows us to identify behavioral differences in electricity use. The Results show that households' estimations of appliance-level consumption are inaccurate and that they overestimate lighting use by 75% and underestimate plug-load use by 29%. We find that similar households using the same major appliances exhibit substantial variation in appliance-level electricity consumption. For example, households in the 75th percentile of HVAC usage use over four times as much electricity as a user in the 25th percentile. Additionally, we show that behavior accounts for 25–58% of this variation. Lastly, we find that replacing the existing refrigerator with a more energy-efficient model leads to overall energy savings of approximately 11%. This is equivalent to results from behavioral interventions targeting all appliances but might not be as cost effective. Our findings have important implications for behavior-based energy conservation policies.     

Residential energy conservation: Analysis of US federal programmes

The authors examine three residential energy conservation programmes under study and development by the US government. These programmes include setting appliance efficiency targets, developing new thermal standards for housing, retrofitting existing houses to improve thermal performance and a stronger energy conservation programme. The programmes are compared using a model developed for the FEA and ERDA which projects consumption up to the year 2000. The major conclusion is that the programmes can save both energy for the USA and money for individual households.     

Aggregate demand for electricity in South Africa: An analysis using the bounds testing approach to cointegration

Electricity demand in South Africa has grown at a very rapid rate over the past decade. As part of reform initiatives to enhance long-term sustainability of the country's electricity industry, South Africa's authorities have in recent years sought to develop an electricity pricing framework that is cost reflective and forms the cornerstone of demand management schemes meant to foster changes in consumption behaviour and enhance efficiency in resource use. The effects of any pricing policy on aggregate electricity consumption will depend on a useful understanding of the factors that influence electricity demand, and the magnitude to which electricity demand responds to changes in such factors. In this context, this paper applies the bounds testing approach to cointegration within an autoregressive distributed lag framework to examine the aggregate demand for electricity in South Africa during the period 1960–2007. The results indicate that in the long run, income is the main determinant of electricity demand. With electricity prices having an insignificant effect on aggregate electricity demand, future pricing policies will need to ensure that electricity prices are cost reflective and enhance efficiency of electricity supply and use.     

On the dynamics of aggregate output,electricity consumption and exports in Malaysia: Evidence from multivariate Granger causality tests

This paper employs annual data from 1971 to 2006 to examine the causal relationship between aggregate output, electricity consumption, exports, labor and capital in a multivariate model for Malaysia. We find that there is bidirectional Granger causality running between aggregate output and electricity consumption. The policy implication of this result is that Malaysia should adopt the dual strategy of increasing investment in electricity infrastructure and stepping up electricity conservation policies to reduce unnecessary wastage of electricity, in order to avoid the negative effect of reducing electricity consumption on aggregate output. We also find support for the export-led hypothesis which states Granger causality runs from exports to aggregate output. This result is consistent with Malaysia pursuing a successful export-orientated strategy.     

World energy markets and the developing countries

Primary energy consumption in the developing countries has been increasing rapidly in the last ten years, giving rise to the prospect that these countries will play an even greater role in world energy markets. This paper describes the adjustments to higher petroleum prices that have taken place in the developing countries and looks at their likely future role. For the purpose of exposition, the developing countries are divided into oil-exporting and oil-importing groups. Analysis is conducted mostly at the aggregate level but fuel-specific and sectoral trends are also identified. The author notes that the experience of the last ten years suggests that the dramatic increases in international petroleum prices had a relatively minor impact on the developing countries′ total energy consumption. There was, however, a significant degree of substitution for other fuels for petroleum in the oil-importing developing countries. The prognostications for the future presented in this paper are based on the assumption that adjustments to price changes take more time in the developing countries. A reasonable degree of adjustment can be expected for the years ahead.     

Improving the prediction of UK domestic energy-demand using annual consumption-data

The ability to predict how changes in patterns of usage in different types of dwelling can affect energy consumption is important if efforts to reduce demand and carbon emissions are to be effective. This paper describes an approach using a questionnaire survey, supported by annual gas and electricity meter data and floor-area estimates derived from a GIS. Clusters of higher and lower energy consumers were discovered and these were related to indicators of energy consumption. Simple and multiple regression were used to determine the strength of the relationships and identify the most statistically-significant indicators of differences in gas and electricity consumption. Although significant effects of the built-form type were not observable in the data available, the effects of related measurable and countable aspects of form, such as floor-area and numbers of rooms, were seen. Significant relationships were found with the number of bedrooms and regular home working, which may reflect changes in UK households that are expected to drive future energy-consumption. Implications for zonal domestic energy-models are noted.     

A machine learning‐based operational control framework for reducing energy consumption of an amine‐based gas sweetening process

This study proposes a data‐driven operational control framework using machine learning‐based predictive modeling with the aim of decreasing the energy consumption of a natural gas sweetening process. This multi‐stage framework is composed of the following steps: (a) a clustering algorithm based on Density‐Based Spatial Clustering of Applications with Noise methodology is implemented to characterize the sampling space of all possible states of the operation and to determine the operational modes of the gas sweetening unit, (b) the lowest steam consumption of each operational mode is selected as a reference for operational control of the gas sweetening process, and (c) a number of high‐accuracy regression models are developed using the Gradient Boosting Machines algorithm for predicting the controlled parameters and output variables. This framework presents an operational control strategy that provides actionable insights about the energy performance of the current operations of the unit and also suggests the potential of energy saving for gas treating plant operators. The ultimate goal is to leverage this data‐driven strategy in order to identify the achievable energy conservation opportunity in such plants. The dataset for this research study consists of 29 817 records that were sampled over the course of 3 years from a gas train in the South Pars Gas Complex. Furthermore, our offline analysis demonstrates that there is a potential of 8% energy saving, equivalent to 5 760 000 Nm³ of natural gas consumption reduction, which can be achieved by mapping the steam consumption states of the unit to the best energy performances predicted by the proposed framework.     

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.