Demand For Energy Services Research Articles

A corridors and power-oriented perspective on energy-service demand and needs satisfaction

In this article, we explore the concept of consumption corridors as it might apply to energy use, with specific attention to both wellbeing and power relations. We employ the distinction between energy provisioning and human-need satisfaction to explore different configurations of energy use, as well as their possible dynamics. Specifically, we draw on past research documenting the benefits of decoupling our thinking about energy services and needs satisfaction and use it as a basis to identify scenarios characterized by different degrees of access to energy services and levels of resource demand. We then translate this perspective to the logic of sustainable consumption corridors. We delineate how minimum and maximum consumption standards would relate to combinations of energy-service demand and needs-satisfier access. Finally, we explore how power dynamics, specifically exercises of discursive power, might move societal trajectories toward sustainable combinations of energy provisioning and needs satisfaction or away from them.

Integrating energy access, efficiency and renewable energy policies in sub-Saharan Africa: a model-based analysis

The role of energy in social and economic development is recognised by sustainable development goal 7 that targets three aspects of energy access: ensure universal access to affordable, reliable and modern energy services, substantially increase the share of renewable energy, and double the global rate of improvement in energy efficiency. With the projected increase in population, income and energy access in sub-Saharan Africa, demand for energy services is expected to increase. This increase can be met through increasing the supply while at the same time improving households’ energy efficiency. In this paper, we explore the interactions between the three SDG7 targets by applying two integrated assessment models, IMAGE and MESSAGE, that incorporate socio-economic heterogeneity of the end-user. The results of the study depict the synergistic relationships between the three SDG7 objectives. Relative to pursuing only the universal access target, integration of all three targets could (a) reduce residential final energy consumption by up to 25%, enabling the use of mini-grid and stand-alone systems to provide better energy services, (b) cut annual energy-use-related residential emissions by a third, and (c) lower energy related investments by up to 30% to save scarce finance.

Assessing Private Investment in African Renewable Energy Infrastructure: A Multi-Criteria Decision Analysis Approach

Energy poverty remains prevalent in many African countries, hindering economic development and exacerbating social inequalities. Simultaneously, population growth throughout the continent is expected to perpetuate the already high demand for basic energy services into the coming decades. Private sector finance is increasingly regarded as a necessary ingredient to remedy Africa’s energy challenges and to stimulate the adoption of renewable energy. However, investments remain insufficient for the burgeoning infrastructure requirements of the African economies. This paper seeks to delineate the financial and non-financial drivers of investment decisions to understand better the barriers to private participation in African renewable energy projects. Using a fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach, we evaluate country-level characteristics and their influence on investor decisions. Investor confidence in regulatory effectiveness is identified as the primary concern for investors. Local capacity building and policy instruments, designed to overcome institutional rigidities, are among the preferred solutions. The findings indicate that non-financial drivers contribute to understanding Africa’s private energy investment challenges.

Development of China TIMES-30P model and its application to model China's provincial low carbon transformation

Abstract To explore the provincial energy system transformation till 2050 under the carbon emission constraints from a bottom-up perspective, this research develops the China TIMES-30P model with detailed characterization of China's provincial energy system and applies it to low carbon scenarios analysis. A set of methodology is developed to project the key provincial socio-economic parameters and the provincial energy service demand, which is the major driving force of the China TIMES-30P model. Results show that compared with the value in 2015, the provincial intensity of final energy consumption will decrease by 65%–90% under different scenarios in 2050. The intensities of primary energy consumption in most of the provinces will be lower than 0.2 tce/1000 dollars under different scenarios in 2050. In the WBD2 scenario, the national CO2 emission can reach the peak value of 9.3 billion tons in 2020 and the provincial CO2 emission intensity in 2050 will decrease by 85%–100%, compared with the value in 2015.

Bioenergy technologies in long-run climate change mitigation: results from the EMF-33 study

Bioenergy is expected to play an important role in long-run climate change mitigation strategies as highlighted by many integrated assessment model (IAM) scenarios. These scenarios, however, also show a very wide range of results, with uncertainty about bioenergy conversion technology deployment and biomass feedstock supply. To date, the underlying differences in model assumptions and parameters for the range of results have not been conveyed. Here we explore the models and results of the 33rd study of the Stanford Energy Modeling Forum to elucidate and explore bioenergy technology specifications and constraints that underlie projected bioenergy outcomes. We first develop and report consistent bioenergy technology characterizations and modeling details. We evaluate the bioenergy technology specifications through a series of analyses—comparison with the literature, model intercomparison, and an assessment of bioenergy technology projected deployments. We find that bioenergy technology coverage and characterization varies substantially across models, spanning different conversion routes, carbon capture and storage opportunities, and technology deployment constraints. Still, the range of technology specification assumptions is largely in line with bottom-up engineering estimates. We then find that variation in bioenergy deployment across models cannot be understood from technology costs alone. Important additional determinants include biomass feedstock costs, the availability and costs of alternative mitigation options in and across end-uses, the availability of carbon dioxide removal possibilities, the speed with which large scale changes in the makeup of energy conversion facilities and integration can take place, and the relative demand for different energy services.

The climate change mitigation potential of sugarcane based technologies for automobiles; CO2 negative emissions in sight

Continuous effort to mitigate climate change relies onnew technologies able to satisfy human demand for energy services with high energy efficiency andreasonable costs. We show that blending a well-known technology with recently introduced and proven technical advances can mitigate climate change in the road transport sector. Furthermore, the achievement of a reasonable cost target is proved to be true when internal combustion engines (ICE) light duty vehicles (LDVs), powered by gasoline fuel, are replaced by plug-in hybrid LDVs (PHEV), powered by ethanol and electricity produced from sugarcane, using well established technology. The only improvements in such ethanol producing technology are the addition of woody biomass to extend the operation of sugar mills and the capture of carbon dioxide (CO2) generated during sugar fermentation into ethanol. Both actions are already adopted and well developed. The study quantifies greenhouse gas (GHG) emissions, expressed as carbon dioxide equivalent (CO2e) emissions and the present value cost for operation of a global fleet of 1 billion LDV over a 60-year period. The PHEV powered by sugar cane products reduces GHGs emissions partly through negative emissions, at a lower cost than gasoline fueled ICE vehicles or electric vehicles. Total potential GHG emission reduction is significant but lower than what is required for the transport sector to fulfill international commitments. Nevertheless, if 1 billion sugarcane-based PHEV hit the streets by the year 2060, 6.18 Gt CO2e/year can be avoided while the necessity of land for biomass plantation is kept at a reasonable value (86 Mha).

Long-term impacts of urbanization through population migration on China’s energy demand and CO2 emissions

Better modeling of urbanization trends helps improve our understanding of the potential range of future energy demands and carbon dioxide emissions in developing countries and make informed response strategies. This paper extends the current analytical structure by integrating the population migration process from rural to urban areas with the energy system into a systematic framework, within which a link between urbanization and energy service demands through direct and indirect effects is built. Taking China as a study case, the results show that approximately 333 million people from rural areas are expected to migrate to urban areas toward 2050, resulting in the expansion of large-sized cities and the rapid growth of future energy service demands. Without significant technological improvements, urbanization will lead to more than double and triple the current energy consumption levels by 2050 in the building and transport sectors, respectively, while energy consumption growth in the industry sector will be the largest due to the rising demand for materials through the indirect effect. As a result, urbanization in China will cause more than double the total primary energy demand and an 82% increase in the carbon dioxide emissions by 2050, compared with 2013. In response, major mitigation measures and the role of each sector in the low carbon urbanization transition have been identified. Non-fossil fuel power generation is the top mitigation strategy, which can contribute 40% to the total mitigation potential, while power sector and industrial sector play a key role in realizing an earlier peak for the whole country. The total capital investment needed in each period will cost less than 2.5% of the total gross domestic product (GDP). Therefore, this work highlights the importance of understanding urbanization impact on energy system through applying an integrated population-energy-environment analytical framework and synthesizing the urbanization and long-term low carbon strategies in developing countries which are under rapid urbanization process.

Scrutinizing the direct rebound effect for French households using quantile regression and data from an original survey

This article develops a quantile regression model to measure the magnitude of the direct rebound effect for residential electricity demand based on micro-level data from an original survey of a representative sample of 2356 French households. We explore the rebound effect for different groups of residents. Traditionally, debate has focused on decreased prices for energy services due to efficiency improvements and their effects on energy demand. The methodological innovation provided by this paper is that it implements two theoretical estimation strategies: (i) energy efficiency elasticity of the demand for energy services, and (ii) price elasticity of the demand for energy services. Our findings reject the hypothesis of a backfire effect in the context of residential electricity use. Specifically, based on energy efficiency elasticity, we provide evidence of a rebound effect of between 72% and 86% but with substantial heterogeneity among consumption quantiles. Our results show that the direct rebound effect has critical relevance for energy efficiency policy in the face of energy invisibility in France.

Reducing inequality resulting from UK low-carbon policy

ABSTRACT In the UK, the cost of low-carbon policies, such as renewable energy subsidies, household retrofit and installation of smart meters, adds an additional 13% to household energy bills. Given that the lowest income households spend 10% of their income on heating and powering their homes, whereas the highest spend less than 1.5%., any increase in prices hits the poor disproportionately. Using an energy-extended multiregional input-output model combined with household expenditure survey data, we calculate the full supply-chain energy embodied in goods and services consumed by different households. First, we demonstrate that low-carbon policy costs are placed on a small percentage of household energy demand – perversely on items representing a higher proportion of expenditure for low income households. The lifestyles of higher income households require nearly five times more energy than the lowest, but because levies are only raised on energy bills, those with high incomes pay only 1.9 times more towards policy costs. Second, we evaluate alternative approaches to funding low-carbon policy: a household energy footprint approach, taking account of households’ full energy service demands; and funding the costs from general taxation payments. We explore the demographic characteristics of the households who would pay less towards funding policy costs and those who would take on a larger burden under these new proposals. While none of the approaches offer a ‘perfect solution’ in terms of distributional impacts, raising the funds through general taxation offers a fairer and practical solution. Key policy insights Low income households currently pay disproportionately more towards low-carbon policy costs in the UK. Funding low-carbon policy through general taxation would better align energy demand with policy costs, and would reduce costs for 65% of UK households. Households comprising women of retirement age living alone; single parent families; and households who have never worked or are long-term unemployed could see reductions in bills by recovering climate policy costs through general taxation. A general taxation approach requires leadership and long-term commitment to avoid leaving the policy vulnerable to short-term budgetary changes.

Assessment of the bioenergy policy for the sustainable development of rural-based bioenergy systems in Zambia

Traditional biomass remains the primary energy source in rural Zambia – providing 98% of the energy needs. Its use is unsustainable, inefficient, and leads to harmful emissions with serious health implications, and deforestation. Modern bioenergy systems offer viable energy supply alternatives - but only if sustainably developed. Among other causes, the limited provision of modern bioenergy in rural areas is attributed to an ineffective public policy for promoting these systems in Zambia. Accordingly, this study evaluates the policy in place that seeks to promote sustainable bioenergy systems for rural areas in Zambia through the analysis of related strategies. It is observed that one of the significant weaknesses of the bioenergy policy framework is its lack of consideration of the bioenergy supply chains. These are influenced by four main elements – i.e., feedstock availability, conversion technology, intermediate energy carriers, and energy service demands - that considerably differ across rural localities within districts. Thus, the bioenergy policy-making process should be considered at such subnational levels (district). A suggestion that is well-aligned with the country’s decentralized governance agenda that is being implemented. Considering that there are numerous rural communities within a district and that information regarding the different elements of the bioenergy supply chain is required for the local government policy-making process, a framework to guide the generation of such information has been proposed.

Energy Supply Chains and Change

The energy sector's critical importance to the economy and national security on the one hand and its association with potential environmental impacts on the other subject it to competing and sometimes oscillating forces in policymaking and corporate decision‐making that can affect both supply and demand. As such, energy supply chains need to be resilient in order to meet the economy's dynamic demand for energy services, adapt to policy actions, respond effectively to natural and manmade disasters, foster transitions to emergent technologies, and serve long‐lived infrastructure. This paper presents a framework that guides systematic analysis of energy supply chains subject to ongoing change. While the framework is qualitative, it is strengthened by quantitative data. A case study of the utility‐scale gas turbine supply chain illustrates the framework.

Spatially-resolved urban energy systems model to study decarbonisation pathways for energy services in cities

This work presents the COMET (Cities Optimisation Model for Energy Technologies) model, a spatially-resolved urban energy systems model that takes into account energy service demands for heating, cooling, electricity, and transport, and finds cost-effective pathways for supplying these demands under carbon constraints, trading-off energy supply, network infrastructure, and end-use technologies. Spatially-resolved energy service demands were obtained for the city of Sao Paulo, and six scenarios were modelled. Results show that district cooling is cost-effective in the highest linear cooling density zones, with full penetration in zones with over 1100 kWh/m by 2050. This threshold diminishes with tighter carbon constraints. Heating is electrified in all scenarios, with electric boilers and air-source heat pumps being the main supply technologies for the domestic and commercial sectors respectively by 2050. In the most carbon constrained scenario with a medium decarbonised electricity grid, ground source heat pumps and hydrogen boilers appear as transition technologies between 2030 and 2045 for the commercial and domestic sectors respectively, reaching 95% and 40% of each sector’s heat installed capacity in 2030. In the transport sector, ethanol cars replace gasoline, diesel, and compressed natural gas cars; compressed natural gas buses replace diesel and electric buses; and lorries continue using diesel. In carbon constrained scenarios, higher penetrations of electric cars and buses are obtained, while no change is observed for lorries. Finally, the most expensive scenario was only 6% more expensive than the reference scenario, meaning that achieving decarbonisation targets is not much costlier when comparing scenarios from a system-wide perspective.

On the Way to a Sustainable European Energy System: Setting Up an Integrated Assessment Toolbox with TIMES PanEU as the Key Component

The required decarbonization of the energy system is a complex task, with ambitious targets under the Paris Agreement, and related policy analysis should consider possible impacts on the economy and society. By coupling the energy system model TIMES PanEU with the impact assessment model EcoSense and the computable general equilibrium model NEWAGE, we present an integrated assessment toolbox for the European energy system capable of internalizing health damage costs of air pollution while simultaneously accounting for demand changes in energy services caused by economic feedback loops. The effects of each coupling step are investigated in a scenario analysis. Additionally, CO2 decomposition analysis is applied to identify the main drivers to decarbonize the energy system. Our results show that integrating externalities forces the system to take early action, which provides benefits on the societal level. Including macro-economic variables has a negative effect on energy service demands and generally reduces the need for structural change, which are still the main drivers of decarbonization. The tighter the models are coupled, the fewer the iterations needed and the lower the CO2 prices resulting from the carbon cap and trade system. In this aspect, an integrated view can provide valuable insights to determine efficient and effective decarbonization paths.

Mitigating energy demand sector emissions: The integrated modelling perspective

Limiting climate change below a given temperature will require fundamental changes in the current energy system, both in the energy supply and the energy demand sectors. Previous global model-based analyses, however, have focused mostly on energy supply transformations. Therefore, in this study we respond to this knowledge gap by analysing the future energy demand projections in both baseline and climate policy scenarios of global models in detail. We examine the projections for the industry, transport and buildings sectors across four models and three different reference scenarios from the Shared-Socioeconomic Pathway framework by applying a decomposition analysis. We compare the projected demand side mitigation efforts to a more detailed, sector-specific, technology-oriented assessment of demand-side abatement potential for the year 2030. Without climate policy, model-based projections show that baseline emissions can grow rapidly in industry and transport sectors, but are also highly uncertain across models. The decomposition analysis shows that the key uncertainty across the global scenarios is the projected final energy per capita. For modellers therefore there lies a challenge to better understand drivers of future energy efficiency and service demand, that contribute to the projected energy demand. This model enhancement would moreover allow to evaluate policy measures that can impact this relation. The technology assessment estimates that in particular in the transport and buildings sector there is a higher potential to reduce demand-side emissions through energy efficiency improvements than implemented in the scenarios. Improved insulation, higher electric vehicle penetration rates and modal shift for example could reduce final energy demand to lower levels in the short term than currently projected, reducing the dependency on fuel switching required in current scenarios to meet the stringent climate targets.

Policies and Programs Critical for Greater Energy Efficiency

In 2018 businesses, households and government enterprises throughout the global economy spent an estimated €7.4 trillion to meet the many demands for various energy services. Current projec­tions suggest that the present scale of annual expenditures may increase by more than 60 per­cent to €12.0 trillion by 2050 (with all costs expressed in real 2018 values). Although the global economy derives important benefits from the purchase of many energy services, the inefficient use of energy also creates an array of costs and constraints that burden our social and economic well-being. Among these costs or constraints are increased health costs, air pollution, climate change and a less productive economy—especially over the long term. Yet there is good news within the countless energy markets throughout the global economy. Whether improved lighting in homes and schools, transporting people and goods more efficiently, or powering the many industrial processes within any given nation, there are huge opportunities to improve the productive use of energy in ways that reduce total economic costs. And those same energy efficiency upgrades can also reduce greenhouse gas emissions that drive climate change, as well as lessen other impacts on both people and the global environment. However, as this manuscript suggests, it will take an adequately funded set of smart policies and effective programs, including a skilled work force, to drive the optimal scale of energy efficiency investments.

Integrated energy service demand evaluation based on AHP and entropy weight method

In the context of the energy revolution, integrated energy services have ushered in a period of opportunities for rapid development. To assess the demand of users of integrated energy services, we establish indexes of demand of integrated energy service users. We got the assessment model based on the analytic hierarchy process (AHP) and entropy weight method. The proposed assessment model is tested on 50 users, and K-means clustering algorithm is used to cluster users. The characteristics of the service requirements of each type are analysed.

China's long-term low carbon transition pathway under the urbanization process

This study develops a comprehensive analysis framework and socio-economic energy system model that interlinks demographic change and energy system in order to analyze the urbanization process and its relation with China's long-term CO2 emissions trend as China’ economy enters the “new normal” stage. The results show that, around 300 million people are expected to migrate from rural areas to urban areas by 2050 following a trend, in which people are moving gradually from small and medium city groups to large and super city groups. The migration trend together with the improvement in living standard will promote China's infrastructure construction, industry production, and energy service demand growth. Under the Business as Usual (BAU) scenario, total primary energy consumption in China will reach 8.4 Gtce by 2050, energy-related CO2 emissions will increase to 17.6 Gt, which is 83% higher than the 2013 level. While in the Low Carbon Transition (LCT) scenario with technology innovation, the total primary energy demand for China in 2050 could be controlled at ∼6 Gtce; CO2 emissions would peak during 2020–2025, and be reduced by 78% by 2050 compared to the BAU scenario. In the transition process, non-fossil fuel power generation and energy efficiency technologies have the largest mitigation potentials. Industry and power sectors would peak first before 2020, followed by the building and transport sectors which are projected to peak around 2030. The total additional capital investment required for LCT would account for 1.5% of GDP. Therefore, it is technologically and economically feasible for China to implement new urbanization strategy.

Improving energy savings from a residential retrofit policy: A new model to inform better retrofit decisions

Retrofitting is one of the most important policy measures for timely decarbonisation of the residential sector due to slow turnover of the housing stock. Ireland is an interesting case study given the high reliance on oil as a fuel, the dispersed pattern of residential housing and the relatively poor energy efficiency performance of the existing housing stock. Decarbonising residential space and water heating has proved challenging in the Irish context. These energy service demands are generally inflexible and resilient to reduction due to a range of considerations including external weather conditions, fuel price and the rebound effect. This paper examines and challenges the suitability of popular retrofit combinations as they apply to nine distinct building archetypes in Ireland's housing stock portfolio. An archetype simulation model is used to evaluate the potential for improved energy efficiency gains within the existing retrofit program. We introduce a new methodology that provides insights into sub-optimal retrofit choices. The five most common retrofit combinations are simulated for each of the nine archetypes. The results show that the alternative retrofit combination differs by archetype and that additional energy efficiency gains of up to 86% can be achieved due to alternative retrofit choices. We believe there is room to improve building energy efficiency standards in Ireland through the implementation of a bespoke building retrofit grant scheme which delivers better informed retrofit choices and more effectively considers the pre-existing condition of a building as part of the initial application process. The implications of this analysis are explored and insights for policy are also provided.

The specific contributions of activities to household electricity demand

In this paper we present new methods to collect and analyse household activity and electricity consumption data. We show how such data can be used to establish relationships between activities and electricity consumption in two different ways. First we create direct associations between activities and the electricity demand at the time. This electricity footprint gives an insight into the typical load intensity of an activity, which can include other activities that are commonly performed in close temporal proximity.Our novel contribution is the concept of marginal electricity demand which can be attributed to specific activities. To disaggregate and approximate the loads for such an activity, we present a new regression approach. The marginal demand of an activity is based on its relative load contribution to any other activity within a collection of over 18,000 activity pairs.Meal types stand out as clearly distinguishable activities. Hot meal related activities show some of the strongest positive contributions to demand, whereas cold meals tend to reduce demand at the time of reporting. Activities such as a hot drink can lead to an overall reduction in demand at the time, despite their direct energy consumption.The potential of this marginal metric will be discussed as a new way to understand energy service demands. Unlike conventional attribution of demand to appliances, it is possible for activities to have a negative marginal demand. This opens up new opportunities to conceptualise the meaning of energy service demand and approaches to encourage demand reduction or shifting through positive actions.

Energy demand transitions and climate mitigation in low-income urban households in India

Growing household energy demand, particularly in developing countries starting from a low base of consumption, is an important driver of current and future greenhouse gas emissions. Yet, our understanding of transitioning residential energy demand in developing country contexts is limited. This paper discusses changing energy service demands in urban low-income households in India, an emerging economy where the largest future growth in energy demand globally is projected to occur, and where 12 million new low-income homes for the urban poor are to be built by the government between 2015 and 2022. Based on mixed quantitative and qualitative methods comprising of surveys, interviews and focus group discussions, we analyze two inter-related questions: how does the demand for energy services change as the ability of low-income households to consume increases; and how do energy related behaviors influence household electricity consumption? We analyze the data collected to rank households according to their ability to consume and to identify the types of, and progression in, energy services acquired. The appliances and associated services pursued are lights, fans, televisions, and refrigerators, with varied energy efficiencies. Analogously, we quantify the influence of behavior in determining electricity consumption, and show that the inclusion of socio-demographic and behavioral factors explain a significant proportion (51%) of the variance in household electricity consumption, along with the role of material factors such as building physical characteristics and appliance stocks. We complement the statistical analysis with qualitative fieldwork and discuss changing energy related behaviors as the ability of households to consume increases. We conclude with recommendations for climate actions that are compatible with development in the growing low-income housing stock.