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The US switched its China and Taiwan anti-dumping duties to uniform tariffs on all imports of solar panels in January 2018. This research uses an Equilibrium Displacement Model (EDM) to determine the relative effects of these two tariffs on domestic consumer and producer welfare, employment, government revenue, and environmental costs. The results indicate that uniform tariffs are more effective than the specific-country tariffs because of higher welfare for domestic manufacturers and higher government revenue. However, the uniform tariffs hurt American consumers, employees, and the environment more than the other because of higher domestic price and larger domestic demand reduction. Therefore, if a policy aims to create more jobs and have less effect on consumers and the environment, a specific-country tariff might be preferable. However, uniform tariffs are better if the administration intends to support domestic manufacturers and increase government revenue.

The idea that energy is not consumed for its own sake but for the services that it provides has become axiomatic. However, the implications are not worked through into energy policy nor into most analyses of energy demand. Instead, energy service demand is usually isolated from its dynamic and varied socio-cultural basis, rendering it inappropriately static and neglecting the core quality of usefulness that definitions of ‘energy service’ share. To address these limitations, this paper revisits and extends a sociological conceptualisation of services, referred to here as meta-services. These are composite and cross-cutting formations of convention, expectation and experience and the means of achieving them. Meta-services are more-than-energy services and are shaped not only through energy consumption, provision and governance but also by a range of other non-energy providers and organisations. This calls for demand reduction policies to engage wider coalitions of service ‘stakeholders’. In addition, because energy-services co-constitute meta-services, aspirations to deliver the same levels of service but more efficiently risk entrenching, rather than reducing, levels of service demand. Implications for service-based business models (servicizing) and policies are discussed.

Our analysis of policy options was motivated by an inexplicable under-investment in demand response (DR) in the U.S. state of Georgia. In addition to estimating the size of the DR gap, we identify its causes and consequences. By modifying parameters of the U.S. flagship National Energy Modeling System (NEMS), we generate a baseline DR forecast with a default 4% maximum on-peak demand reduction, an achievable case with a DR limit of 20%, and a technical scenario that also halved the cost of storage. The results document many benefits of DR including a demand-reduction induced price effect (DRIPE), which makes DR more equitable than many other clean-energy policies that shift costs to non-participants. Our modeling results, literature review, and focus group analysis enable identification of DR barriers and motivators related to financial costs, electricity rates, consumer bills, pollution emissions, public health, energy equity, and inclusion. Our results suggest that the DR gap is caused less by technology limitations than by the need for financing initiatives, market innovations, infrastructure modernization, and enablers of socio-economic inclusion. By studying a state that lags in DR implementation, other countries and sub-national entities where DR is under-utilized can learn from our findings and methods.

The coronavirus pandemic (COVID-19) has led to a massive collapse in economic activity and energy demand, with the result of significant emissions reductions at a global scale. However, the existing literature investigating abatement from COVID-19 mainly overlooked the overwhelming emissions reduction in Europe's power sector. We address this by assessing the intricate relationship between electricity demand shocks and heterogeneous generation technologies in the power sectors of 16 major European economies during January to March 2020. We apply an econometric model in an instrumental-variables framework. In a first step, we assess the impact of COVID-19 infections on electricity demand, and in a second step how this translates into emissions abatement. We find that, during full lockdown, COVID-19 reduced electricity demand by 19% and carbon emissions by an astonishing 34% per hour, whereas there is severe country heterogeneity depending on the electricity supply structure and demand shock intensity. From our estimates, we predict that power sector emissions fell by 18.4% in 2020. Our results reveal the importance of a carbon price, so that a demand reduction can offset large amounts of emissions by displacing coal at the margin. We derive several policy implications from our analysis to draw lessons from the pandemic.

A transition to a more efficient heat energy system requires the consideration of drivers covering behavioural change, upgrades of the building stock and substitution or improvements in technologies in use. Sweden has set the target to reduce total energy demand per heated area in buildings by 50% by 2050 compared to 1995. This study aims to estimate the potential for reducing heat energy demand in the Swedish residential building stock taking into account behavioural, structural and technological categories of drivers. A combination of bottom-up energy modelling with scenario methodology informed by socio-technical analysis of barriers was used. Our results show that the target can be achieved by combining at least two of the categories of drivers. However, it is noteworthy that the technological category, which has by far the lowest level of barriers, almost reaches the target largely owing to the high impact for single-family houses, showing the crucial role of changes in the technology mix. However, as the same drivers have different demand reduction potential in the two main building types in Sweden, single and multi-family houses, this calls for policymakers to lead on initiatives that foster a combination of technological, behavioural and structural improvements for the latter.

The CA-TIMES optimization model of the California Energy System (v1.5) is used to understand how California can meet the 2050 targets for greenhouse gas (GHG) emissions (80% below 1990 levels). This model represents energy supply and demand sectors in California and simulates the technology and resource requirements needed to meet projected energy service demands. The model includes assumptions on policy constraints, as well as technology and resource costs and availability. Multiple scenarios are developed to analyze the changes and investments in low-carbon electricity generation, alternative fuels and advanced vehicles in transportation, resource utilization, and efficiency improvements across many sectors. Results show that major energy transformations are needed but that achieving the 80% reduction goal for California is possible at reasonable average carbon reduction cost ($9 to $124/tonne CO2e at 4% discount rate) relative to a baseline scenario. Availability of low-carbon resources such as nuclear power, carbon capture and sequestration (CCS), biofuels, wind and solar generation, and demand reduction all serve to lower the mitigation costs, but CCS is a key technology for achieving the lowest mitigation costs.

A reduction of energy service demand is a climate mitigation option, but its effectiveness has never been quantified. We quantify the effectiveness of energy service demand reduction in the building, transport, and industry sectors using the Asia-Pacific Integrated Assessment/Computable General Equilibrium (AIM/CGE) model for the period 2015–2050 under various scenarios. There were two major findings. First, a 25% energy service demand reduction in the building, transport, and basic material industry sectors would reduce the GDP loss induced by climate mitigation from 4.0% to 3.0% and from 1.2% to 0.7% in 2050 under the 450 ppm and 550 ppm CO 2 equivalent concentration stabilization scenarios, respectively. Second, the effectiveness of a reduction in the building sector׳s energy service demand would be higher than those of the other sectors at the same rate of the energy service demand reduction. Furthermore, we also conducted a sensitivity analysis of different socioeconomic conditions, and the climate mitigation target was found to be a key determinant of the effectiveness of energy service demand reduction measures. Therefore, more certain climate mitigation targets would be useful for the decision makers who design energy service demand reduction measures.

Endogenous demand responses for energy services, resulting from changing prices, have long been characterised in energy systems models. However, the uncertainty associated with such demand responses, modelled through the use of price elasticities, has often been ignored. This is problematic for two key reasons – elasticity factors used in models are highly uncertain due to the limited evidence base, while at the same time, demand response has been observed as a critical mechanism for meeting long term climate mitigation targets. This paper makes two important contributions for improving the understanding of the role of price-induced demand response. Firstly, it attempts to address the problem of unsatisfactory elasticity input assumptions by undertaking an up-to-date review of the literature. Secondly, the role of demand response under uncertainty is assessed using a probabilistic approach, focusing on its contribution to mitigation. The paper highlights that demand response does play a critical role in mitigation, ensuring a more cost-effective transition to a low carbon energy system. Crucially, the uncertainties associated with price elasticities do not weaken this finding. The transport sector is the driver of this demand response leading to important implications for policy and the focus of demand side interventions.

Japan׳s Fukushima nuclear disaster, triggered by the March 11, 2011 earthquake, has led to calls for shutting down existing nuclear plants. To maintain resource adequacy for a grid׳s reliable operation, one option is to expand conventional generation, whose marginal unit is typically fueled by natural-gas. Two timely and relevant questions thus arise for a deregulated wholesale electricity market: (1) what is the likely price increase due to a nuclear plant shutdown? and (2) what can be done to mitigate the price increase? To answer these questions, we perform a regression analysis of a large sample of hourly real-time electricity-market price data from the California Independent System Operator (CAISO) for the 33-month sample period of April 2010–December 2012. Our analysis indicates that the 2013 shutdown of the state׳s San Onofre plant raised the CAISO real-time hourly market prices by $6/MWH to $9/MWH, and that the price increases could have been offset by a combination of demand reduction, increasing solar generation, and increasing wind generation.

Axon et al., (2012) argue that maximizing the potential for energy efficiency and demand reduction in tenanted commercial properties requires a “building communities” approach. This paper develops and extends Axon et al.′s proposed framework in two ways. First, by extending its applicability from tenanted to owner-occupied properties. Second, by situating it within the literature related to organizational culture, occupant behaviours, and technology adoption. The paper begins with a brief review of the existing research on people, energy and commercial buildings. This literature tends to address either organizational choices, or occupant behavior, but it rarely crosses the analytical boundaries between these two groups. The paper then explores these different levels of analysis within a 3Cs – “concern, capacity, and conditions” – framework, which was developed to describe and distinguish organizational responses to an energy crisis. The combination of the “building communities” and 3Cs frames reveals gaps and grey areas between organizational culture, occupant behaviour, and technology adoption where further conservation opportunities may lie. These understudied areas suggest that there may be “social potential” for change that is between and beyond the frames used by previous research in the field.

Recent greenhouse gas auctions have resulted in base level prices while remaining significantly concentrated. How do dominant firms receive such a large share of emissions allowances without bidding up the market price? This paper provides a Monte Carlo simulation analysis based on a contemporary regional greenhouse gas market in the United States. It introduces a C # simulation software environment, Oligopsony 1.0 that simulates uniform-price emissions auctions in repeated iterations. The results of these simulations indicate that there can be significant non-linearities between profit and market power as exercised through strategic demand reduction. This analysis finds the optimum point of strategic demand reduction that enables firms to exploit these non-linearities. The use of auctions to distribute tradeable pollution rights to firms in heavily concentrated markets can have significant unintended consequences, as it can exacerbate the problems of market power that exist within those markets.

The use of feed-in tariffs (FITs) is now widespread for renewable energy and under discussion for other low carbon electricity generation, but not for energy efficiency. There is a small literature on FITs for electricity demand reduction, but not energy efficiency more generally. This paper considers the general application of FITs on the demand side and sets out the economic arguments in the context of changing energy markets. It then discusses the implications of some practical issues, including the definitional problems arising from the difference between energy efficiency and demand reduction. Using experience from historical energy efficiency programmes, it considers the public benefits, payment methods and policy scope that need to be considered and how these might affect policy design. It makes some provisional estimates of economically justified payments in the context of the proposed UK energy market reform. It concludes that FITs for energy saving might be a powerful tool for incentivising energy efficiency.

Smart meters are being rolled out in large numbers throughout the world, with proponents claiming they are a critical step in the transition to a low-carbon economy. Yet there are significant unresolved negative reactions to smart meters, principally based on the concern that smart meters might be used to infer the private activities that occur within a dwelling. Though smart meter data is classified as personal data, and as such protected under existing data protection frameworks in the EU, there are relevant exceptions, notably where the data is required for legitimate applications associated with the performance of 'regulated duties'. This paper contributes to this debate by examining the data requirements for some of the proposed applications of smart meter data within the electricity supply industry, and investigates whether the use of personal data can be minimized or even avoided. The discussion includes system balancing, demand reduction, demand response and distribution network operation and planning, and indicates that, for most of these applications, the requirements for personal data can indeed be minimized. 'Privacy friendly' alternatives are discussed.

In order to reduce energy-related CO 2 emissions different options have been considered: energy efficiency improvements, structural changes to low carbon or zero carbon fuel/technologies, carbon sequestration, and reduction in energy-service demands (useful energy). While efficiency and technology options have been extensively studied within the context of climate change mitigation, this paper addresses the possible role of price-related energy-service demand reduction. For this analysis, the elastic demand version of the TIAM–UCL global energy system model is used in combination with decomposition analysis. The results of the CO 2 emission decomposition indicate that a reduction in energy-service demand can play a limited role, contributing around 5% to global emission reduction in the 21st century. A look at the sectoral level reveals that the demand reduction can play a greater role in selected sectors like transport contributing around 16% at a global level. The societal welfare loss is found to be high when the price elasticity of demand is low.

Buildings account for almost half of UK carbon dioxide emissions, and energy demand in buildings continues to grow. In the context of economic growth, population growth, increasing demand for homes and commercial floor space, and increasing demand for energy services, energy use and probably carbon emissions look set to continue to increase unless there is significant change. This paper outlines enabling technologies that may permit a step-change reduction in energy demand from buildings through the application of next-generation information metering and control, energy-efficiency products and microgeneration. It covers both residential and non-residential buildings. This wide approach has been adopted because technologies and trends tend to migrate from one building sector to another, as, for example, IT has moved from offices into homes and lighting trends from offices and retail into homes. It covers technologies that can be used in new build or major refurbishment. Much of the need for change involves the better use of known technology, and some involves changing behaviour. Some behaviour depends on new technologies such as metering. Understanding how technological innovations are taken up (e.g. stock turnover issues, as well as how technical change occurs) and the economics of new technologies is as important as the technologies themselves.

A demand reduction strategy is considered in the context of the UK and in the light of the UK Government's 2006 Energy Review. This paper discusses how a mechanism—a Demand Reduction Obligation (DRO)—can be established to achieve radical energy demand reduction targets in electricity and gas use in the industrial, commercial and public administration sectors. A DRO would require energy suppliers to invest in energy-saving measures so as to reduce energy demand in these sectors. The investment for this activity would be funded by energy suppliers who would increase prices in order to cover the cost of achieving the carbon reductions. Public opinion surveys suggest that a large proportion of the public would prefer to support demand reduction measures compared to other energy options. It may be practical to deliver carbon emission reductions equivalent to around 30% of emissions from the UK electricity sector over a 15-year period through a broad-based demand reduction strategy. Demand reduction is considered in the context of an assessment of costs and resources available from other low carbon options including renewable energy and nuclear power.

The relationship between electricity demand reduction and the consequent change in carbon emissions is central to greenhouse gas emissions policy. This paper examines this relationship for the power system of England and Wales. Previous analysis showed that the commonly used conversion factor based on the system average emission factor significantly underestimates these savings (Hitchin and Pout, 2002. The carbon intensity of electricity: how many kgC per kWhe?. Building Serv. Eng. Res. Technol. 23(4)). Thus any policy analysis based on the system-average emission factor will under-estimate the potential for carbon savings from reductions in electricity demand. The present paper extends the previous analysis by using more detailed modelling to explore differences between demand reductions of differing load shape and magnitude; and the sensitivity of these figures to changes of the fuel mix of the generation system. The new analysis confirms that the carbon savings are consistently greater than those calculated from the annual system average emission factors, and that they vary with end use and scale of demand reduction. However, no systematic differences between end-uses could be discerned. It is therefore recommended that a general incremental carbon emission factor should be used for initial assessments irrespective of end-use. Under current expectations of changes to the generation fuel mix, the incremental carbon intensity will fall more rapidly than the system-average mix. A similar reduction in carbon intensity is also present in the other scenarios explored, but is sometimes more and sometimes less marked.

Iran's demographic profile is sharply youth oriented and this upcoming generation's needs for employment and housing, coupled with low-energy efficiency vectors and consumption patterns, has created a constant rise in energy demand and greenhouse gas (GHGs) emissions in the residential sector. Improved energy efficiency as a national policy lynchpin for demand reduction and GHGs mitigation, has become commonplace. OPEC countries however, Iran included, suffer an obvious lack of consumer incentive because of low fuel prices. This study evaluates the twin impacts of price reform and efficiency programs on energy carriers’ consumption and GHGs mitigation in the Iranian housing sector. For this purpose, the demand functions for energy carriers, has been developed by econometrics process models. The results reveal that price elasticity for electricity demand in the Constant Elasticity Model for the short-run while the long-run is −0.142 and −0.901, respectively. In the Variable Elasticity Model the 250% increase in electricity rates in the short-run resulted in a price elasticity change from −0.02 to −0.475, hence the 250% increase in electricity pricing for the long-run resulted in the price elasticity change from −0.15 to −2.0. Finally, aided by a Scenario-Based Approach the impact of fuel pricing and efficiency improvement in trends of energy demand and GHGs emission were assessed in a Scenarios Base, developed on two different cases of Business-as-Usual (BAU) and Management. The results indicate that in the BAU case between 2000 and 2011, the energy demand and CO2 emission increases with an annual growth rate of 7.5% and 6.8%, respectively. Comparatively, if the energy carriers’ price is increased to border price and energy efficiency programs are implemented, they will stimulate carriers’ demand and CO2 emissions growth rate decreases to 4.94% and 3.1%, respectively.

A demand curve for electricity intensity of the OECD economies is discussed. Based on a 1998 sample, the (long-run) price elasticity of intensity is assessed at 1.17, clearly not smaller than 1, refuting the allegation that lower prices guarantee lower bills. The regression shows that electricity efficiency improvement is stronger than the height of the price, and so that industrial nations with a high price (tax) policy reveal the smaller budget shares of electricity bills in GDP. High end-use prices (taxes) are not harmful to the economies, but a necessity to trigger efficiency, while efficiency seems not feasible without high end-use prices. Nations as an aggregate react on electricity budget shares that they try to keep within acceptable/affordable boundaries. The analysis confirms that there still exist huge unexploited efficiency potentials, but once the physical limits of efficiency are attained, that non-energy policies must take over to limit energy consumption. End-use demand reduction is discussed to be also more efficient and more effective than supply extension for meeting the energy needs. The final question why the better options are overridden by the worse ones, brings us to the discussion of barriers, where the discussion is limited to a distinction between natural and artificial barriers to energy efficiency.

In light of the present debate about the future organization of electricity supply, the relationship between energy conservation and organization of electricity supply in the Netherlands is examined. Three case studies of energy conservation are analysed: the development of industrial cogeneration of heat and power, the development of wind energy and the use of a so-called ‘MAP levy’ as an instrument used by utilities to stimulate demand reduction of end users. The implications of these case studies for the future organization of Dutch electricity supply are discussed. Some measures aimed at reconciling energy conservation and liberalization are suggested.

Despite an emerging consensus that societal energy consumption and related emissions are not only influenced by technical efficiency but also by lifestyles and socio-cultural factors, few attempts have been made to operationalise these insights in models of energy demand. This paper addresses that gap by presenting a scenario exercise using an integrated suite of sectoral and whole systems models to explore potential energy pathways in the UK transport sector. Techno-economic driven scenarios are contrasted with one in which social change is strongly influenced by concerns about energy use, the environment and well-being. The ‘what if’ Lifestyle scenario reveals a future in which distance travelled by car is reduced by 74% by 2050 and final energy demand from transport is halved compared to the reference case. Despite the more rapid uptake of electric vehicles and the larger share of electricity in final energy demand, it shows a future where electricity decarbonisation could be delayed. The paper illustrates the key trade-off between the more aggressive pursuit of purely technological fixes and demand reduction in the transport sector and concludes there are strong arguments for pursuing both demand and supply side solutions in the pursuit of emissions reduction and energy security.