US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach

This paper estimates a US ‘frontier’ residential aggregate energy demand function using panel data for 48 ‘states’ over the period 1995 to 2006 using stochastic frontier analysis (SFA). Utilizing an econometric energy demand model, the (in) efficiency of each state is modelled and it is argued that this represents a measure of the inefficient use of residential energy in each state (i.e. ‘waste energy’). This underlying efficiency for the US is therefore observed for each state as well as the relative efficiency across the states. Moreover, the analysis suggests that energy intensity is not necessarily a good indicator of energy efficiency, whereas by controlling for a range of economic and other factors, the measure of energy efficiency obtained via this approach is. This is a novel approach to model residential energy demand and efficiency and it is arguably particularly relevant given current US energy policy discussions related to energy efficiency.Energy demand; US residential energy demand; efficiency and frontier analysis; state energy efficiency.

Demand-Response Based Energy Advisor for Household Energy Management

Home energy management systems (HEMS) are set to play a key role in the future smart grid (SG). HEMS concept enables residential customers to actively participate in demand response programs (DR) to control their energy usage, reduce peak demand and therefore contribute to improve the performance and reliability of the grid. The aim of this paper is to propose an energy management strategy for residential end-consumers. In this framework, a demand response strategy is developed to reduce home energy consumption. The proposed algorithm seeks to minimise peak demand by scheduling household appliances operation and shifting controllable loads during peak hours, when electricity prices are high, to off-peak periods, when electricity prices are lower without affecting the customer’s preferences. The overall system is simulated using MATLAB/Simulink and the results demonstrate the effectiveness of the proposed control strategy in managing the daily household energy consumption.Peer reviewe

Energy demand models for policy formulation : a comparative study of energy demand models

This paper critically reviews existing energy demand forecasting methodologies highlighting the methodological diversities and developments over the past four decades in order to investigate whether the existing energy demand models are appropriate for capturing the specific features of developing countries. The study finds that two types of approaches, econometric and end-use accounting, are used in the existing energy demand models. Although energy demand models have greatly evolved since the early 1970s, key issues such as the poor-rich and urban-rural divides, traditional energy resources, and differentiation between commercial and non-commercial energy commodities are often poorly reflected in these models. While the end-use energy accounting models with detailed sector representations produce more realistic projections compared with the econometric models, they still suffer from huge data deficiencies especially in developing countries. Development and maintenance of more detailed energy databases, further development of models to better reflect developing country context, and institutionalizing the modeling capacity in developing countries are the key requirements for energy demand modeling to deliver richer and more reliable input to policy formulation in developing countries.Energy Production and Transportation,Energy Demand,Environment and Energy Efficiency,Energy and Environment,Economic Theory&Research

Contract Design for Energy Demand Response

Power companies such as Southern California Edison (SCE) uses Demand Response (DR) contracts to incentivize consumers to reduce their power consumption during periods when demand forecast exceeds supply. Current mechanisms in use offer contracts to consumers independent of one another, do not take into consideration consumers' heterogeneity in consumption profile or reliability, and fail to achieve high participation. We introduce DR-VCG, a new DR mechanism that offers a flexible set of contracts (which may include the standard SCE contracts) and uses VCG pricing. We prove that DR-VCG elicits truthful bids, incentivizes honest preparation efforts, enables efficient computation of allocation and prices. With simple fixed-penalty contracts, the optimization goal of the mechanism is an upper bound on probability that the reduction target is missed. Extensive simulations show that compared to the current mechanism deployed in by SCE, the DR-VCG mechanism achieves higher participation, increased reliability, and significantly reduced total expenses.Comment: full version of paper accepted to IJCAI'1

Battery Capacity of Deferrable Energy Demand

We investigate the ability of a homogeneous collection of deferrable energy loads to behave as a battery; that is, to absorb and release energy in a controllable fashion up to fixed and predetermined limits on volume, charge rate and discharge rate. We derive bounds on the battery capacity that can be realized and show that there are fundamental trade-offs between battery parameters. By characterizing the state trajectories under scheduling policies that emulate two illustrative batteries, we show that the trade-offs occur because the states that allow the loads to absorb and release energy at high aggregate rates are conflicting

Scenarios of energy efficiency and CO2 emissions reduction potential in the buildings sector in China to year 2050

As China’s rapid urbanization continues and urban dwellers become more affluent, energy use in buildings is expected to grow. To understand how this growth can be slowed, we explore four scenarios for Chinese buildings, ranging from a high-energy-demand scenario with no new energy policies to lowest energy demand under a techno-economic-potential scenario that assumes full deployment of cost-effective efficient and renewable technologies by 2050. We show that, in the high energy demand scenario, building energy demand has an average annual growth rate of about 2.8%, with slower growth rates in the other three scenarios. In all scenarios, CO2 emissions grow slower than energy, with building CO2 peaking around 2045 in the high energy demand scenario, and as early as 2030 in the techno-economic-potential scenario. We show that although various technological solutions, systems and practices can be very effective in minimizing building energy use, rigorous policies are needed to overcome multiple implementation barriers

A strategic study of energy efficient and hybrid energy system options for a multi-family building in Korea

This study is to identify performance of energy efficiency measures and to match low-carbon and renewable energy (RE) systems supplies to demands in the context of multi-family residential buildings in Korea. An approach to the evaluation of the hybrid energy systems was investigated, including consideration of heat and power demand profiles, energy system combinations, building design options and strategies for matching supply to demand. The approach is encapsulated within an integrated software environment. Building energy simulation technology was exploited to make virtual energy use data. Low-carbon and RE system modelling techniques were used to predict energy supply profiles. A series of demand/supply matching-based analyses were made to identify the effect of energy efficient demand measures (e.g. roof-top gardens, innovative underfloor heating system) and evaluate the capacity utilisation factor from the hybrid energy systems. On the basis of performance information obtained at the conceptual design stage, the design team can pinpoint the most energy efficient demand/supply combination, and consequently, maximise the impact of hybrid energy systems adoption

OECD Energy Demand: Modelling Underlying Energy Demand Trends using the Structural Time Series Model

Aggregate energy demand functions for 17 OECD countries are estimated with data for 1960-2003 using the Structural Time Series Model (STSM) thus allowing for a stochastic Underlying Energy Demand Trend (UEDT). It is found that the estimated long-run income and price elasticities range from 0.5 to 1.5 and -0.1 to -0.4 respectively. Furthermore the stochastic form for the UEDT is preferred for all countries suggesting a wide variation in the exogenous effects of energy saving technical progress in addition to other pertinent exogenous factors such as economic structure, consumer preferences, and socio-economic influences.OECD Energy Demand, Modelling, Underlying Stochastic Trends