The agricultural demand for electricity in the united states

This study looks at how farmers adjust their consumption of electricity in response to changes in the price of energy. A demand model is specified and estimated. The conclusions suggest that the price of electricity is a factor impacting the quantity of electricity demanded by farmers for irrigation and for other (non-irrigation) uses, but there is no indication that other types of energy are substitutes for electricity. Additionally, the number of acres irrigated is an important factor driving the demand for electricity for irrigation and the number of acres planted is a factor determining the demand for electricity for other uses. Finally, the estimated models of electricity for irrigation and electricity for other uses are structurally stable over the period 1971–92.     

Estimating the agricultural demand for natural gas and liquefied petroleum gas in the presence of measurement error in the data

The paper begins by discussing the importance of accurate estimates of the price elasticity of demand and some of the problems frequently encountered in obtaining these estimates. To these problems is added that associated with inaccuracy in the measurement of the dependent variable and one or more of the independent variables that affect the quantity demanded. Two diagnostics, i.e. the regression coefficient bounds and the bias correction factor, have been introduced to assess the effect that such measurement error has on the estimated coefficients of demand relationships. The use of these diagnostics will aid in assessing the integrity of the estimates obtained. In considering the demand for natural gas and the demand for liquefied petroleum gas by farmers in the USA, both the quantity demanded and the price data available for demand model estimation purposes contain measurement error. The regression coefficient bounds diagnostic was used to indicate a range over which the true price responsiveness of farmers to changes in energy prices lies. The results suggest that each 1% increase (decrease) in the price of energy will result in a decrease (increase) of between 0.41 and 0.17% in the quantity of natural gas demanded and a decrease (increase) of between 0.48 and 0.07% in the quantity of liquefied petroleum gas demanded. The bias correction factor was computed to evaluate the magnitude of the underestimation of the responsiveness of the quantity of natural gas and liquefied petroleum gas demanded to a change in the number of acres irrigated. For natural gas, the under-estimation was 26.5%, whereas, for liquefied petroleum gas, it was 9.5%.     

A note on energy demand estimation

This study is concerned with the assessing the impact that inaccuracy in the measurement of the dependent variable and one or more of the independent variables has on the estimate of the price elasticity of demand for diesel fuel by farmers in the United States. Two diagnostics – the regression coefficient bounds and the bias correction factor — are introduced to assess the effect that such measurement errors have on the estimated coefficients of the diesel fuel demand relationship.     

Demand for gasoline and diesel fuel by farmers in the USA

This study endeavours to determine whether farmers in the USA adjust their consumption of gasoline and diesel fuel in response to changes in the relative prices of different types of energy. A demand model is specified and estimated. The conclusions suggest that the price of gasoline (diesel fuel) is a factor impacting the quantity of gasoline (diesel fuel) demanded by farmers, but there is no indication that other types of energy are substitutes for gasoline (diesel fuel). Additionally, the level of farming activity is a very important factor driving the demand for gasoline (diesel fuel). Finally, the estimated models of gasoline and diesel fuel demand are structurally stable over the period 1971–1988.     

The demand for residential electricity in South Africa

This paper examines the residential demand for electricity in South Africa as a function of real gross domestic product per capita, and the price of electricity during the period 1978–2005. We make use of the bounds testing approach to cointegration within an autoregressive distributed framework, suggested by Pesaran et al. [2001. Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics 16(3) 289–326]. Following the literature, we use a linear double-logarithmic form using income and price as independent variables in the empirical analysis. In the long run, we find that income is the main determinant of electricity demand, while electricity price is insignificant.     

Regionally-varying and regionally-uniform electricity pricing policies compared across four usage categories

The objective of our research is to predict how electricity demand varies spatially between status quo regionally-uniform electricity pricing and hypothetical regionally-varying electricity pricing across usage categories. We summarize the empirical results of a case study of electricity demand in South Korea with three key findings and their related implications. First, the price elasticities of electricity demand differ across usage categories. Specifically, electricity demands for manufacturing and retail uses are price inelastic and close to unit elastic, respectively, while those for agricultural and residential uses are not statistically significant. This information is important in designing energy policy, because higher electricity prices could reduce electricity demands for manufacturing and retail uses, resulting in slower growth in those sectors. Second, spatial spillovers in electricity demand vary across uses. Understanding the spatial structure of electricity demand provides useful information to energy policy makers for anticipating changes in demand across regions via regionally-varying electricity pricing for different uses. Third, simulation results suggest that spatial variations among electricity demands by usage category under a regionally-varying electricity-pricing policy differ from those under a regionally-uniform electricity-pricing policy. Differences in spatial changes between the policies provide information for developing a realistic regionally-varying electricity-pricing policy according to usage category.     

Assessing the need for power : A regional econometric model

The growing controversy over nuclear power has demanded a critical evaluation of the need for power to justify proposed nuclear power plants. This paper discusses the use of an econometric model developed for the US Nuclear Regulatory Commission to conduct an independent assessment of electricity demand forecasts related to the licensing of nuclear power plants. The model forecasts electricity demand and price by sector and by state. The estimation and forecasting results for the New England region are presented as a case in point where an econometric model has been used to analyse alternative fuel price scenarios and to aid substantive public decision making regarding new nuclear power plant decisions.     

考虑短期负荷影响的DeepESN电力市场实时电价预测研究

精准的电价预测有助于宏观调控的实施.但能源结构转型导致大规模可再生能源并网,因此会导致电价降低和产生波动,降低时序预测序列的相关性,加大实时电价的预测难度.针对这一问题,采用自相关函数和最大信息数计算电价自身和电价与电量关联性,为模型输入提供依据,并在此基础上应用具有深度储备池特性的深度回响网络进行实时电价预测.研究结...     

Development of a numerical simulation system toward comprehensive assessments of urban warming countermeasures including their impacts upon the urban buildings'' energy-demands

One of the detrimental effects caused by the urban warming phenomena is the increase of energy consumption due to the artificial air-conditioning of buildings in summer. In greater Tokyo, the temperature sensitivity of the peak electricity demand reaches up to 3%/°C in recent years, and about 1.5 GW of new demand is required as the daily maximum temperature increases by 1.0 °C. This huge demand for summer electricity is considered to be one of the common characteristics of big cities in Asian countries. In order to simulate this increase in cooling energy demands and to evaluate urban warming countermeasures from the viewpoint of buildings' energy savings, a numerical simulation system was developed adopting a new one-dimensional urban canopy meteorological model coupled with a simple sub-model for the building energy analysis. Then, the system was applied to the Ootemachi area, a central business district in Tokyo. Preliminary verification of the simulation system using observational data on the outdoor and indoor thermal conditions showed good results. Simulations also indicated that the cut-off of the anthropogenic heat from air-conditioning facilities could produce a cooling energy saving up to 6% with the outdoor air-temperature decrease by more than 1 °C in the summer urban canopy over Ootemachi area.     

The residential demand for electricity in Australia: an application of the bounds testing approach to cointegration

This paper reports estimates of the long- and short-run elasticities of residential demand for electricity in Australia using the bounds testing procedure to cointegration, within an autoregressive distributive lag framework. In the long run, we find that income and own price are the most important determinants of residential electricity demand, while temperature is significant some of the time and gas prices are insignificant. Our estimates of long-run income elasticity and price elasticity of demand are consistent with previous studies, although they are towards the lower end of existing estimates. As expected, the short-run elasticities are much smaller than the long-run elasticities, and the coefficients on the error-correction coefficients are small consistent with the fact that in the short-run energy appliances are fixed.     

Natural gas demand by agriculture in the USA

This study sets out to determine whether agricultural consumers of natural gas are responsive to changes in the relative prices of different types of energy. A demand model is specified and estimated. The conclusions strongly suggest that not only is the price of natural gas a factor having an impact on the quantity of natural gas demanded by agriculture, but that other types of energy are substitutes for natural gas and that income and weather (measured by heating degree days) likewise affect natural gas demand.     

Impacts of residential electricity subsidy reform in China

China’s rapid economic growth causes a sharp increase in the demand for electricity. Electricity price in China is generally controlled at a low level by the government, leading to a substantial electricity subsidy. Electricity subsidy is the focus of energy price reform. It is also most closely linked with residential life and is a very sensitive issue to residents. This paper adopts the price-gap approach to estimate the scale of electricity subsidy and finds that in 2010, residential electricity subsidy in China amounted to 467.17 billion CNY (Chinese yuan), accounting for 1.17 % of GDP in that year. Subsequently, the paper estimates the impacts of residential electricity subsidy reform on the welfare of residents using the compensating variation (CV) measurement. The results show that if residential electricity price rises by 50, 100, 150, and 191 %, the CV should be 288.5, 394.2, 451.1, and 467.2 billion CNY, respectively. The residential electricity subsidy reform also has a moderating role in the rebound effect of electricity consumption. The direct rebound effect in China’s residential electricity consumption is 20 %. Electricity subsidy reform will raise terminal electricity price and restrain residential electricity consumption. Therefore, electricity subsidy reform should be an effective measure to mitigate the rebound effect.     

Estimation of residential electricity demand function in Seoul by correction for sample selection bias

This paper attempts to estimate the residential electricity demand function in Seoul. To this end, we collected the data from a survey of households in Seoul and employed the bivariate model to rectify the undesirable impacts of non-response data. The results show that the size of family, the size of house, dummy for having a plasma display panel television, dummy for having an air conditioner, and the household's income have positive relationships with the residential electricity demand. On the other hand, electricity price contributes negatively to the residential electricity demand. In addition, the price and income elasticities were estimated as −0.2463 and 0.0593, respectively, implying that residential electricity demand in Seoul is price- and income-inelastic. Such useful information is expected to help policy-makers regulate the residential electricity supply and predict the effect of the price on the residential electricity demand in the future.     

Estimating short and long-term residential demand for electricity: New evidence from Sri Lanka

This study investigates the short-run dynamics and long-run equilibrium relationship between residential electricity demand and factors influencing demand – per capita income, price of electricity, price of kerosene oil and price of liquefied petroleum gas – using annual data for Sri Lanka for the period, 1960–2007. The study uses unit root, cointegration and error-correction models. The long-run demand elasticities of income, own price and price of kerosene oil (substitute) were estimated to be 0.78, ? 0.62, and 0.14 respectively. The short-run elasticities for the same variables were estimated to be 0.32, ? 0.16 and 0.10 respectively. Liquefied petroleum (LP) gas is a substitute for electricity only in the short-run with an elasticity of 0.09. The main findings of the paper support the following (1) increasing the price of electricity is not the most effective tool to reduce electricity consumption (2) existing subsidies on electricity consumption can be removed without reducing government revenue (3) the long-run income elasticity of demand shows that any future increase in household incomes is likely to significantly increase the demand for electricity and (4) any power generation plans which consider only current per capita consumption and population growth should be revised taking into account the potential future income increases in order to avoid power shortages in the country.     

A data‐driven approach to study the role of interconnectors in a future low‐carbon electricity supply system

This paper investigates the potential role of the electricity interconnectors in improving the security of supply in Great Britain (GB) in 2030. Real electricity demand and price data for GB and France in 2016 were used to understand the relationship between power exchange between the two countries and their wholesale electricity prices. A linear programming optimisation model was developed to find the economic power dispatch. Two interconnection links were considered; two‐way trade interconnector with a capacity of 5.4 GW and a 12.3 GW import‐only interconnector between GB and other states. The GB–France link transmits electricity from cheaper system to the more expensive one. The total electricity demand in 2030 will be 406 TWh. Gas‐fired power plants w/wo CCS will provide 83 TWh of the total electricity demand, whereas nuclear power plants will produce 74 TWh. In addition, wind farms and solar PVs are expected to deliver ~120 TWh electricity. CHP units will provide 88 TWh electricity in 2030. The electricity traded between GB and France in 2030 was found to be 33 TWh, which is 160% larger compared with 2016. The power import from France is about 27 TWh and occurs in 59% of the time. For 64% of the time, the interconnector with France is fully loaded. The electricity imported via the 12.3 GW interconnector in 2030 is 1 TWh and mainly occurs during winter‐time when the demand in GB is high. De‐rated capacity margin was calculated based on instantaneous electricity demand and varies between ?2% and 139%. The impact of the price of the imported electricity via the 12.3 GW link was investigated. Increasing the price of the imported electricity via the 12.3 GW link results in a higher capacity factor for all the generation options except the 12.3 GW interconnector link.     

Electricity demand in Kazakhstan

Properties of electricity demand in transition economies have not been sufficiently well researched mostly due to data limitations. However, information on the properties of electricity demand is necessary for policy makers to evaluate effects of price changes on different consumers and obtain demand forecasts for capacity planning. This study estimates Kazakhstan's aggregate demand for electricity as well as electricity demand in the industrial, service, and residential sectors using regional data. Firstly, our results show that price elasticity of demand in all sectors is low. This fact suggests that there is considerable room for price increases necessary to finance generation and distribution system upgrading. Secondly, we find that income elasticity of demand in the aggregate and all sectoral models is less than unity. Of the three sectors, electricity demand in the residential sector has the lowest income elasticity. This result indicates that policy initiatives to secure affordability of electricity consumption to lower income residential consumers may be required. Finally, our forecast shows that electricity demand may grow at either 3% or 5% per year depending on rates of economic growth and government policy regarding price increases and promotion of efficiency. We find that planned supply increases would be sufficient to cover growing demand only if real electricity prices start to increase toward long-run cost-recovery levels and policy measures are implemented to maintain the current high growth of electricity efficiency.     

Electricity consumption in G7 countries: A panel cointegration analysis of residential demand elasticities

This article applies recently developed panel unit root and panel cointegration techniques to estimate the long-run and short-run income and price elasticities for residential demand for electricity in G7 countries. The panel results indicate that in the long-run residential demand for electricity is price elastic and income inelastic. The study concludes that from an environmental perspective there is potential to use pricing policies in the G7 countries to curtail residential electricity demand, and thus curb carbon emissions, in the long run.     

Residential demand for electricity

Short- and long-run responses by households to changes in the price of electricity are estimated using data which permit measurement of the marginal price of electricity, the infra-marginal demand charge, and estimates of household appliance stocks. The price elasticities of high- and low-level users of electricity are compared. The theoretical bias in price elasticity estimates resulting from neglect of the infra-marginal demand charge is shown to be empirically insignificant.     

Is space heating in offices really necessary?

New office buildings in Sweden are thoroughly insulated due to the Swedish building code. This code, however, does not consider the type of activity occurring in the building. This means that the heating equipment is designed as if no activity at all is going on. In modern offices there is a lot of equipment installed which uses electricity. This electricity is converted into heat which can be utilized for heating the premises, mostly in a direct way but also by the use of exhaust-air heat-pumps or heat exchangers. This paper deals with a modern office building plus office hotel complex located in Linköping, Sweden, about 200 km south of Stockholm. The tenants deal with the design of hard- and software for computers. The lighting and computers in the building use electricity which converts into heat. In this paper, it is shown that this electricity is all that is needed during normal conditions, i.e. when people work in the building. The building is also equipped with a district-heating system, which is designed as if no activity goes on in the building, so subsequently the heating equipment is larger than it need be. In this special case, it might have been better to install an electric heating device for hot-water heating and very cold winter conditions, instead of using district heating. This is so even if district heat is about half the unit price compared with that due to the dissipation of electricity. At present, when district heating is used, no measures for saving heat can be profitable due to the low district-heating price. The fact is that the tenants complain of too much heat instead of too little: the prevailing indoor temperature was about 24° C in January 1990 even though 20° C would have been sufficient. There is subsequently a need for a properly working regulation system. The one currently in use is designed to a modern standard, but is not able to maintain temperatures at a modest level.     

Operational scheduling of responsive prosumer farms for day‐ahead peak shaving by agricultural demand response aggregators

This paper proposes a novel structure to optimize the operational strategies of responsive farms for day‐ahead peak shaving. To achieve the aim, the modern irrigation system of farms, including groundwater, surface water, and booster water pumps, are modeled mathematically. To develop the demand response (DR) potentials of the farms, electrical storage systems, and self‐generation facilities, including thermal distributed generations and on‐farm solar sites, are addressed. In order to facilitate the integration of the agricultural DR programs into the electricity market, a mathematical formulation for agricultural demand response aggregator (ADRA) is suggested. The ADRA participates in the day‐ahead electricity market on behalf of the responsive farms. To overcome the price uncertainty of the electricity market, a robust optimization approach is addressed. This approach determines the robust decisions of farms in the worst‐case realizations of the uncertain electricity price. Regarding on‐farm solar sites located in rural areas, a data‐driven approach is used to estimate the solar power generation of a significant number of sites without needing to install costly communication and measurement infrastructures. Finally, the proposed approach is implemented on agricultural lands in the northeast of Iran. The numerical results show that the suggested approach provides day‐ahead peak shaving for the power systems meeting the crop's water requirements.