Modelling time of day substitution using the second moments of demand

Time of day (TOD) rates are a commonly used method for peak load pricing of many services. Such services as; electricity, communications, transportation, shared computer facilities, and computer networks (i.e. the Internet), either use, or will use, some form of TOD pricing. However, TOD rates do not ensure a movement towards economic efficiency unless the patterns of TOD substitution are known. The model presented here provedes a method for estimating TOD substitution without the need for rate experiments that have proven to be both costly and limited by sample selection bias problems. This model employs the estimated second moment of demand to estimate a matrix of relative own- and cross-price elasticities and it can estimate elasticities even when there is no apparent TOD price variation. The low level of computations required for the estimates allows the application of a bootstrap procedure to estimate the covariance matrix of the elasticities. Two applications of this model are presented: a case of aggregate demand for computer services and a case of an individual household's electricity demand.     

Forecasting demand for electricity in Maryland: An econometric approach

Most of the models for forecasting demand for energy are based on simple extrapolations of past trends or on a simple regression equation with price of the energy and the stock of appliances as explanatory variables. In this paper, an attempt has been made to derive static and dynamic multiple regression equations from economic theory of consumption and production (Section II). Historical data were fitted to these theoretical constructs to test the equations in terms of econometric theory and forecast the demand according to “higher order conditional interval forecasts”. The residential demand for electricity is a function of its price, price of its substitute, per capita income and a lagged demand variable for dynamic adjustment of actual demand to equilibrium demand for electricity. The forecasts of residential demand to 1990 are based on projections of exogenous variables such as residential price of electricity, per capita income and the estimated long run elasticity of demand (Section III). The nonresidential demand for electricity is a function of employment in that sector, sectoral prices of electricity and the lagged sectoral demand. The forecasts of nonresidential electricity demand are also based on projections of its independent variables (Section IV). The last section converts the total demand for electricity into the required generating capacities and juxtaposes them against the estimates of expected supplies available from the forecasts of the utilities. The paper concludes that the eighties will be faced with excess supply of electricity in Maryland, in case the assumptions of projections of independent variables hold good. The misallocation of resources inherent in such excess supplies could be avoided if realistic scenerios of future demand, as attempted in this paper, could be predicted.     

中国电力行业减排政策——基于电力需求函数的实证分析

利用2003—2015年中国的省际面板数据,通过估计电力需求函数模拟碳税的政策效果,为电力行业减排政策的制定提供了参考。结果表明:随着中国经济进入新常态,电价对电力需求的影响减弱,产业结构特别是工业内部结构的调整对电力需求和电力消费结构产生一定影响;由于电力需求对电价变动不敏感,因此碳税的减排效果有限;为实现减排目标,政府需要征收高额碳税,但这在现有的电价水平下较难实施;从减排效果和实施难度两个方面来看,当前暂不开征碳税的减排政策具有一定合理性;与碳税相比,加快供给侧结构性改革、降低火力发电比重,能够更有效地实现减排目标;现阶段政府应将调整电源结构作为节能减排工作的重点。     

Estimating and forecasting residential electricity demand in Iran

This study examines the short- and the long-run relationship between electricity demand and its determinants in the Iranian residential sector. The study employs unit root tests, cointegration and error-correction models on annual time series for the period, 1967–2009. The results show that electricity price is insignificant and income elasticity is lower than unity. The most influential factor influencing household electricity demand is cooling degree days. The number of electrified villages (an indicator of economic progress) is statistically significant, showing that economic progress has a positive impact on electricity demand. Electricity demand is forecast until 2020. The results show that under the most probable projection, electricity consumption in the residential sector will grow at an annual rate of 29% and 80% by 2014 and 2020, respectively.     

Household Electricity Demand, Revisited

Recent efforts to restructure electricity markets have renewed interest in assessing how consumers respond to price changes. This paper develops a model for evaluating the effects of alternative tariff designs on electricity use. The model concurrently addresses several interrelated difficulties posed by nonlinear pricing, heterogeneity in consumer price sensitivity, and consumption aggregation over appliances and time. We estimate the model using extensive data for a representative sample of 1300 California households. The results imply a strikingly skewed distribution of household electricity price elasticities in the population, with a small fraction of households accounting for most aggregate demand response. We then estimate the aggregate and distributional consequences of recent tariff structure changes in California, the consumption effects of which have been the subject of considerable debate.     

Income and price elasticities of electricity demand in Australia: Evidence of state‐specific heterogeneity

This paper estimates country‐wide and state‐level income and price elasticities of electricity demand in Australia for the period 1999Q1–2013Q2 using the National Electricity Market data and the autoregressive‐distributed lag model. The results suggest that the long‐run income and price elasticities are inelastic and are statistically significant with theoretically consistent signs. The country‐wide income and price elasticities are estimated to be 0.41 and ?0.38, respectively. It is also found that there exists state‐specific heterogeneity in both speed and magnitude of the electricity consumption adjustment in response to changes in income and electricity price. These results have important policy implications, including the need to use state‐specific elasticities in the scenario analysis of the energy pricing policy.     

Factors affecting electricity generation in China: Current situation and prospects

China has attracted worldwide attention due to the global economic and environmental effects of its rapid economic growth over the last 20 years, with particular attention given to the country's accelerating energy consumption and resulting greenhouse gas emissions. China's electricity sector is particularly important for both of these issues as it accounts for nearly half of its greenhouse gas emissions and even greater proportions of the country's demands for primary fuel resources. In order to better understand how these issues may progress in an economy changing as fast as China's, this paper develops a framework that can be used to help model the electricity sector's future development. The framework builds upon key technological and socio-economic drivers, including those affecting electricity demand (e.g., economic growth, structure, energy efficiency, urbanization, and change in per capita income) and electricity supply (e.g., deregulation, initiatives to promote natural gas, nuclear and renewable energy, air pollution regulations, price developments for coal and natural gas, and changes in generation technology). The framework serves as a foundation for a scenario exercise on the greenhouse gas and fuel consumption impacts of different developmental paths for China's electricity sector. These scenarios and their implications for emissions and fuel consumption are presented in a subsequent article.     

Rethinking real-time electricity pricing

Most US consumers are charged a near-constant retail price for electricity, despite substantial hourly variation in the wholesale market price. This paper evaluates the first program to expose residential consumers to hourly real-time pricing (RTP). I find that enrolled households are statistically significantly price elastic and that consumers responded by conserving energy during peak hours, but remarkably did not increase average consumption during off-peak times. The program increased consumer surplus by $10 per household per year. While this is only one to two percent of electricity costs, it illustrates a potential additional benefit from investment in retail Smart Grid applications, including the advanced electricity meters required to observe a household’s hourly consumption.     

电力市场中计及实时电价的电力系统运行风险管理新策略

针对电力市场中用户对实时电价的反应,本文提出一种计及实时电价的电力系统运行风险管理新策略。该策略在评估电力系统运行风险的基础上,对实时电价进行调节,并以电价为信号,刺激用户采取合理的用电结构和方式,从而增强电力系统运行的可靠性。该方法只是弥补了传统方法无法考虑系统运行可靠性的不足,而并非颠覆传统的电价管理方法,所以二者具有很好的衔接性。最后,通过对IEEPRTS测试系统的可靠性进行计算分析,验证了所提算法的有效性。     

差别电价传导机制及延迟性的系统动力学模拟

本文以高耗能企业中的电解铝企业为例,运用差别电价政策的系统动力学仿真模型,模拟差别电价对企业的单位产品成本、用电量等指标的影响以及其最终引起企业经营决策的变化。研究表明:差别电价对电解铝企业的"用电量增加"、"生产量"具有明显的降低效果,且随着时间的推移,此影响的效果越来越显现,并且差别电价对高耗能企业的生产决策影响具有延迟效应。     

中国风电产业政策与产业发展——一项基于风电与传统电力替代性的研究

本文从考察风电与传统能源电力的需求替代弹性入手,通过构建社会对电力需求函数,分析了传统能源电力与风电的需求替代关系。政府若能通过政策手段内化传统电力对社会环境的负外部性,提高传统电力的价格,则社会对风电的需求量将会显著增加。在需求拉动下,风电产业会实现快速的增长。笔者的研究结果表明,以2009年为例,传统电力价格每上涨0.01元,社会对风电的需求将最高增加1.03亿千瓦左右。因此,我国政府在制定一系列风电产业支持政策的同时,可以尝试利用碳税或发放污染配额等政策手段,适当提高传统能源电力价格,拉动社会对风电的需求总量,促进风电产业的发展,实现社会福利的优化。     

The price elasticity of electricity demand in South Africa

This paper examines the effects of price on the demand for electricity in South Africa over the period 1950–83. Emphasis is placed on the estimation of the long-run own-price elasticity of electricity demand. An unconstrained distributed lag model is used and the 12 years elasticity is estimated to be –0.90. The policy implications of this finding are discussed.     

结构变化、效率改进与能源需求预测——以中国电力行业为例

本文利用宏观经济学的方法提出一个长期电力需求模型以分析影响中国电力需求的主要因素。如预期的一样 ,当各种因素受市场力量的进一步约束时 ,影响需求的各项变量之间的关系在中国经济改革以后更加稳定也更为显著。一个误差修正模型为预测中国电力总需求的短期波动提供了适合的框架。 1 978年经济改革以后 ,需求的GDP弹性估计为 0 .8左右 ,低于改革前 (1 978年以前 )。结果表明 ,虽然GDP仍是影响电力需求的最重要因素 ,但电力需求与中国的结构变化及效率改进是负相关的。这意味着对于一个快速增长的经济来说 ,GDP的高速增长并不总是伴随着高的电力需求 ,并解释了为什么 1 998年经济增长率为 7 8% ,但电力消费却只增长了 2 8%。     

UNCERTAINTY AND THE COST OF ACID RAIN CONTROL

This paper uses a utility capacity planning and dispatch model to examine the robustness of acid rain mitigation policies. The model meets electricity demand at the lowest economic cost while it responds to price or quantity signals for controlling emissions. The model is unique since it is couched in a risk analysis framework that captures the uncertainty in other economic parameters determining the utility's strategic choices–e.g., demand level and fuel prices. This permits one to compare various institutional settings for pollution control for both a world with perfect foresight and one with imperfect foresight. This exercise provides quantitative results on the cost of pollution control with price and quantity controls. It also provides a measure of the response of these cost functions to the uncertainty in other key parameters.
Exploring the performance of various pollution control mechanisms has led to three findings: (i) that the performance of a price control mechanism is dependent on the level of emission reductions that one seeks, (ii) that regionally traded emission permits and emission fees are equally efficient regardless of the level of foresight, and (Hi) that emission fees lead to more stable electricity generation prices. Finally, the sensitivity analysis of the results under imperfect foresight suggest that uncertainties in the level of demand and load management success play an important role in determining future pollution control costs.     

Incentive properties of coincident peak pricing

Coincident peak pricing is used in several electricity markets to recover the embedded cost of infrastructure, such as transmission. In this approach, measured consumption at the time of the peak is used to set charges for that pricing period or a subsequent period. If transmission costs are truly sunk, then such a recovery is unlikely to be efficient. However, in the context of growing peak demand, new additions must be built. We consider the incentive properties of coincident peak pricing when related investments are not considered to be sunk, finding that it can reproduce the incentive properties of an ideal time-varying price. We also consider several variations on this assumption.     

Aggregate cigarette demand and regional differences in China

National educational level, final consumption expenditure, average propensity to cigarette consumption (APCC) and cigarette price are adopted to research the regional and national aggregate cigarette demand of China. Under the condition that the effects of anti-smoking education in the Chinese current educational system are not remarkable, the theoretical model shows that cigarette demand will increase with the increase of national educational level. Empirical analysis points out that cigarette demand increases with the increase of educational level. Estimates also suggest that cigarette price, consumption expenditure and APCC will affect cigarette demand significantly, and that there are great differences for cigarette demand by region.     

论产品价格、劳动力价格与消费需求

价格高水平变动与消费需求变动的关系比较间接。劳动力相对其他商品的价格不断提高，是经济发展表现出的普遍规律。劳动力价格对产品价格不断提高是消费需求持续增长的必要条件。通过企业之间的竞争来实现劳动生产率的提高和非农产业就业人数的增长，是实现大众消费良性循环的根本措施。     

基于水资源需求侧管理的水价制度探讨

价格是调整水资源供需平衡的重要经济杠杆,是引导用户合理用水和节约用水最为重要的经济手段。面对我国水资源日益紧缺的严峻形势,本文借鉴电力部门用电管理采用的需求侧管理技术,探讨了实施水资源需求侧管理的水价制度,着重分析了高峰负荷定价、论质水价在水资源需求侧管理中的作用,同时指出建立水资源需求侧管理的水价制度应该注意的几个问题。     

The behavioral response to voluntary provision of an environmental public good: Evidence from residential electricity demand

This paper develops a theory of voluntary provision of a public good in which a household's decision to engage in a form of environmentally friendly behavior is based on the desire to offset another behavior that is environmentally harmful. The model generates predictions about (1) participation in a green-electricity program at the extensive and intensive margins, and (2) changes in electricity consumption in response to participation. We test the theory using billing data for participants and nonparticipants in a green-electricity program in Memphis, Tennessee. High-consumption households are more likely to participate, and they participate at higher levels. In terms of a behavioral response, households participating above the minimum threshold level do not change electricity consumption, but those participating at the minimum threshold increase electricity consumption 2.5 percent after enrolling in the program. The result is based on identification strategies that exploit before–after differences between participants and nonparticipants, and differences in the timing of enrollment among participants only. Despite the increase in electricity demand upon the purchase of green electricity for the households with a “buy-in” mentality, the net effect for the buy-in households is a reduction in pollution emissions, as the behavioral response is not large enough to offset the environmental benefit of the green-electricity purchase.