Demand For Energy Services Research Articles

City energy planning: Modeling long-term strategies under system uncertainties

Cities are facing the dilemma of fulfilling energy service demands for their rapidly growing population while also working towards climate mitigation efforts. City energy planning is essential to deal with this dilemma. Thus, this study explores the role of city energy plans on future cost-efficient energy systems. A technology-rich cost-optimization model was developed using TIMES with intra-sectoral and inter-sectoral interactions and applied to the Gothenburg energy system. The model outcomes are investigated with the application of policy-driven scenarios and further tested under system uncertainties and price sensitivities identified using a participatory approach. Heating sector developments include DH production based on biomass CHP and heat pumps combined with improved building energy efficiency. Cost-efficient transport sector developments show a rapid deployment of biofuel vehicles, followed by increasing electrification later in the time horizon. With the applied uncertainties, different cost-optimal district heat production mixes and heating supply solutions are observed, providing alternative planning strategies. The model results also signify competition of biomass and electricity among sectors in their development pathways. The modeling outcomes enable decision-makers to assess various energy systems transition strategies from a long-term perspective.

EPL-based medium- and long-term end-use energy service demand forecasting model for parks

EPL-based medium- and long-term end-use energy service demand forecasting model for parks

Effects of Removing Energy Subsidies and Implementing Carbon Taxes on Urban, Rural and Gender Welfare: Evidence from Mexico

The demand for different energy goods and services is a fundamental component in a country’s economic structure for development. Understanding it is vital in designing economic policies, such as taxes, that can improve the welfare of the population. A comprehension of the distributional effects of elasticities and the application of them to simulate household responses to price changes, as well as a calculation of the welfare impacts on poor and rich households in Mexico, should inform policy design. This paper uses the Household Income and Expenditure Survey (ENIGH) from 1996 to 2018 to estimate the demand of Mexican households for fuels, specifically electricity, liquefied petroleum gas, and gasoline. A Quasi Ideal Quadratic Demand System (QUAIDS) is employed to analyse the effects of removing energy subsidies and introducing a carbon tax. The results indicate that welfare losses would be regressive concerning electricity price increases, while changes in gasoline prices would be progressive. Redistributing the tax revenues accrued by removing energy subsidies and imposing the carbon tax would have more progressive effects on the economy of Mexican households, with welfare gains of up to 350% for the poorest households in the case of electricity consumption taxes.

Evaluating Prospective Energy Services Demand for Residential Solar Photovoltaic (RSPV) Generated Electricity in Lagos State, Nigeria

Rapid urbanisation is pulling demand for energy services and emission of greenhouse gases (GHG) resulting in energy deficit, climate change and global warming. The ongoing energy crisis and degenerating climate condition demands urgent transformation of the energy system to renewable based from nonrenewable (fossil) based. To meet the growing demand for energy services and simultaneously mitigate the environmental impact of the energy sector, an accurate estimation of the demand for renewable generated electricity is vital to guide the policy makers in planning adequately for the adoption of renewable fuelled electricity generation technology in urban areas. This study evaluated the electricity demand for residential solar photovoltaic (RSPV) technology by potential household adopters of the technology in the metropolitan area of Lagos state, Nigeria. The study adopted quantitative research design with structured questionnaire to solicit information from the respondents. Three hundred and twenty-six (326) responses from the potential adopters were analysed with model for analysis of demand for energy (MADE II) and Pareto tool. The results show that the energy intensity for refrigeration services is 1.06 kWh/hh/day, entertainment services is 0.84 kWh/hh/day, computing services is 0.97 kWh/hh/day, space cooling services is 7.59 kWh/hh/day, ventilation services is 9.05 kWh/hh/day, lighting services is kWh/hh/day, cooking services 2.77 kWh/hh/day, process heating services is 6.43 kWh/hh/day and water pumping is 1.89 kWh/hh/day. The study concluded that the household energy services demand for electricity is 24.43 kWh/hh/day by the potential RSPV technology adopters and the total demand from the solar module panel of 31.59 kWh/hh/day with prospect for improvement on the energy intensity at the same output of energy services. Furtherance to this, the study recommends government intervention with formulation and implementation of dedicated policies on household appliances efficiency standard and also introduce financial schemes to support the replacement of inefficient household appliances with highly efficient ones. Further studies could include other non-common energy services that were not considered in this study. The study could also be conducted in other regions of Nigeria and also investigate the economic feasibility and behavioural acceptability of RSPV technology for effective planning of the national energy system transformation.

Global trends in biodiversity with tree plantation age

Tree plantations are expanding globally to satisfy demands for wood, food, energy, oil and other ecosystem services, often replacing primary vegetation. Plantations are generally less biodiverse than primary vegetation, yet the effects of plantation age on biodiversity are not well understood. More accurate estimations of biodiversity within plantations over time could improve predictions of the ecological effects of tree planting, guiding more sustainable land use and management decisions. Here, we assess the effects of plantation age on the abundance and number of species of invertebrates, birds, plants, mammals, amphibians, reptiles and lichens, and on compositional similarity to minimally-used primary vegetation. We find that plantations usually support fewer species than both minimally-used primary vegetation and mature secondary vegetation, fewer individuals, and some novel species (i.e. species not also found in primary vegetation). We also find that, on a global scale, plantation age has positive effects on species richness, the abundance of individuals, and compositional similarity to primary vegetation. However, geographic realm, biome, management intensity and plantation type influence the biodiversity trends. We also include a case study for oil palm, showing that species richness increases with oil palm plantation age. Nevertheless, plantations typically remain less biodiverse than natural vegetation even thirty years after planting, especially in the tropics, where compositional similarity between plantations and minimally-used primary vegetation remains approximately 20% lower than the non-tropics. Our results highlight the negative ecological consequences of establishing new plantations in place of primary vegetation or restoration, yet we also reveal spatio-temporal differences in plantation biodiversity.

Is timing everything? Assessing the evidence on whether energy/electricity demand elasticities are time-varying

In this review we assess both the reasons/hypotheses for why GDP and price elasticities of energy/electricity demand might change over time, and the evidence from papers that have addressed that issue. We consider papers that have used parametric methods (e.g., endogenous or exogenous breaks, rolling window regressions) and semi- or non-parametric approaches (e.g., structural time series models, local linear estimators). The most convincing reasons for GDP and price elasticities varying over time were: (i) results from reactions to the energy price shocks of the 1970s and early-1980s (that would have affected OECD countries directly and non-OECD countries, possibly, via leapfrogging); (ii) saturation of the demand for energy services (typically at high income levels); and (iii) country-specific events such as policy changes and/or economic crises/recoveries/shocks/transitions. Despite those reasons, the weight of evidence points toward income/GDP and price elasticities of energy/electricity demand that are fairly stable over time. In addition to changes caused by reactions to the energy crises and (other) country specific events, the main exception to effectively constant elasticities is the GDP elasticity of economy-wide electricity demand in OECD countries. This elasticity may have declined substantially over time, perhaps, because the share of energy services provided by electricity has saturated. Lastly, it is recommended that modelers consider a combination of (parametric and nonparametric) approaches and search for consensus among the results.

Industry’s role in Japan’s energy transition: soft-linking GCAM and National IO table with extended electricity supply sectors

Japan’s energy transition towards carbon neutrality by 2050 will require a shift from fossil fuel energy on the energy supply side. The introduction of new power generation capacities and infrastructures will then lead to increasing demand for materials and industrial products. To capture such industrial energy service demand, we conducted a soft-linking between an integrated assessment model (GCAM) with an input–output framework (IONGES), considering both inter-model and inter-period iteration. The results show that: i) the industrial final energy under the carbon neutrality scenario would be 0.2-0.7EJ more after linking, which is almost the gap between the carbon neutrality and the reference scenario; ii) to achieve carbon neutrality by 2050, more power generation capacities would be introduced in the near-term periods (2020-2030), bringing additional growth afterward. Our soft-linking approach emphasized the role of industries in the energy transition and explored how industries can benefit from an increasingly low-carbon energy supply.

A reference architecture for orbiting solar reflectors to enhance terrestrial solar power plant output

Orbiting reflectors offer the possibility of illuminating large terrestrial solar power plants to enhance their output, particularly at dawn and dusk when their output is low but energy spot prices can be high. While the concept of orbiting solar reflectors has been considered in various forms in the past, there is now a timely overlap of rapidly growing global demand for clean energy services, falling launch costs through reusability and the emergence of in-orbit manufacturing technologies to enable the fabrication of large, ultra-lightweight space structures. This paper provides an end-to-end analysis of a possible minimum initial architecture to deliver such global clean energy services. The analysis will cover orbit selection, attitude control requirements, structural analysis and economical viability, followed by a discussion on regulatory issues, future improvements and further applications.

Performance of Equity Investments in Sustainable Environmental Markets

Despite a significant increase in global clean energy investments, as part of the decarbonization process, it remains insufficient to meet the demand for energy services in a sustainable manner. This study investigates the performance of sustainable energy equity investments, with focus on environmental markets, using monthly equity index data from 31 August 2009 to 30 December 2022. The main contributions of our study are (i) assessment of the performance of trading strategies based on the trend, momentum, and volatility of Environmental Opportunities (EO) and Environmental Technologies (ET) equity indices; and (ii) comparison of the performance of sustainable equity index investments to fossil fuel-based and major global equity indices. Market performance evaluation based on technical analysis tools such as the Relative Strength Index (RSI), Moving Averages, and Average True Range (ATR) is captured through the Sharpe and the Sharpe per trade. The analysis is divided according to regional, sector, and global EO indices, fossil fuel-based indices, and the key global stock market indices. Our findings reveal that a momentum-based strategy performed best for the MSCI Global Alternative Energy index with the highest excess return per unit of risk, followed by the fossil fuel-based indices. A trend-based strategy worked best for the MSCI Global Alternative Energy and EO 100 indices. The use of volatility-based information yielded the highest Sharpe ratio for EO Europe, followed by the Oil and Gas Exploration and Production industry, and MSCI Global Alternative Energy. We further find that a trader relying on a system which simultaneously provides momentum, trend, or volatility information would yield positive returns only for the MSCI Global Alternative Energy, the S&P Oil and Exploration and Production industry, NYSE Arca Oil, and FTSE 100 indices. Overall, despite the superior performance of the MSCI Global Alternative Energy index when using momentum and trend strategies, most region and sector EOs performed poorly compared to fossil fuel-based indices. The results suggest that the existing crude oil prices continue to allow fossil fuel-based equity investments to outperform most environmentally sustainable equity investments. These findings support that sustainable investments, on average, have yet to demonstrate consistent superior performance over non-renewable energy investments which demonstrates the need for continued, rigorous, and accommodating regulatory policy actions from government bodies in order to reorient significant capital flows towards sustainable equity investments.

Household responses to winter heating costs: Implications for energy pricing policies and demand-side alternatives

I conduct a survey that presents research subjects with hypothetical costs to adjust their thermostats. I estimate responses to the cost of heating and analyze the causes for heterogeneity in household demand for energy services using the survey results as a complete-information baseline. I find that even at the highest price level ($8 per 5 °F or 2.8 °C), half of the participants exhibit zero response to price. On average, a 100 percent increase in the marginal cost of heating the home induces a 0.31 to 0.97 degree Fahrenheit (0.17 to 0.51 °C) reduction in the winter heating level, corresponding to a −0.005 to −0.014 elasticity. Further, I find that participants’ survey behavior with complete information can explain observed real-world temperature settings, suggesting a limited role for informational barriers or salience issues in energy-service demand heterogeneity. Inelastic demand suggests that energy efficiency policies may have high returns and that centralized demand–response policies may be required to address winter energy emergencies.

A deep learning architecture for energy service demand estimation in transport sector for Shared Socioeconomic Pathways

Meeting current global passenger and freight transport energy service demands accounts for 20% of annual anthropogenic CO2 emissions, and mitigating these emissions remains a considerable challenge for climate policy. Pursuant to this, energy service demands play a critical role in the energy systems and integrated assessment models but fail to get the attention they warrant. This study introduces a novel custom deep learning neural network architecture (called TrebuNet) that mimics the physical process of firing a trebuchet to model the nuanced dynamics inherent in energy service demand estimation. Here we show, how TrebuNet is designed, trained, and used to estimate transport energy service demand. We find that the TrebuNet architecture shows superior performance compared with traditional multivariate linear regression and state of the art methods like densely connected neural network, Recurrent Neural Network, and Gradient Boosted machine learning algorithms when evaluated for regional demand projection for all modes of transport demands at short, decadal, and medium-term time horizons. Finally, TrebuNet introduces a framework to project energy service demand for regions having multiple countries spanning different socio-economic development pathways which can be replicated for wider regression-based task for timeseries having non-uniform variance.

The causal effect of income on household energy transition: Evidence from old age pension eligibility in South Africa

Rising household income may affect energy technology choice and total fuel consumption, with significant implications for the environment and health. Yet the causal connection between income and fuel choice is difficult to pin down, given the endogeneity bias that may arise from reverse causality and omitted (unobserved) confounding variables. We exploit exogenous variation in household income resulting from the discontinuous age-based eligibility for the Old Age Pension (OAP) benefit in South Africa, to identify the causal effect of income on fuel choice and expenditures. We find that the eligibility for pension income within a household increases primary reliance on electricity, while reducing dependence on biomass and other polluting fuels. Results are consistent across three major household energy services – lighting, heating and cooking – that can be obtained using substitute fuels. Expenditures on electricity and other commercial fuels also increase, indicating that household demand for energy services increases with income. Moreover, the effect on electricity demand is twice as large as that on demand for other fuels. Our study sheds light on an understudied benefit of cash assistance programs to the poor in an important and populous middle-income country, and more generally provides important new causal evidence on the role that income plays in facilitating household energy transitions.

Energy Sufficiency in the Household Sector of Lithuania and Hungary: The Case of Heated Floor Area

Economic development and rising welfare lead to higher demand for energy services, which can limit or even negate the results of costly energy efficiency (EE) upgrades. At present, some consumption patterns in Central and Eastern European countries are more sustainable compared to the European Union (EU) average but are rapidly approaching it. Energy sufficiency (ES) leading to an absolute reduction in energy demand will be essential for achieving net zero climate goals, as it will contribute to reducing energy use and the significant investment needs associated with the electrification of the energy system. Various regulatory solutions can be deployed in pursuit of ES targets, but little information is available on the possible impacts on energy use and greenhouse gas (GHG) emissions, especially at the national level. This paper focuses on the residential building sector of two Central and Eastern European countries: Lithuania and Hungary. It attempts to quantify the potential energy demand reduction, associated GHG savings and the resulting change in the energy mix from limiting the per capita heated floor area using scenario analysis with the MESSAGE and HU-TIMES energy system models. The findings suggest that final energy demand could be reduced by 3.6% in Lithuania and 0.9% in Hungary. This would lead to a change in the energy production mix resulting in lower GHG emissions and savings on new energy generation capacity. The results of the research are indicative, as no costs were assigned to ES measures and the calculations were based on assumed levels of ES indicators. However, they suggest that it is worth identifying the consumption segments with ES potential, as a combination of the relevant measures can largely contribute to the achievement of net zero emissions.

Socio-technical modelling of UK energy transition under three global SSPs, with implications for IAM scenarios

The potential for using findings from socio-technical energy transition (STET) models in integrated assessment models (IAMs) has been proposed by several authors. A STET simulation model called TEMPEST, which includes the influence of societal and political factors in the UK’s energy transition, is used to model three of the global shared socioeconomic pathways (SSPs) at the national level. The SSP narratives are interpreted as inputs to TEMPEST, which drive scenario simulations to reflect varying societal preferences for mitigation measures, the level of political support for energy transition, and future economic and population trends. SSP1 and SSP2 come close to meeting UK net zero targets in 2050 but SSP5 does not reach net zero before 2080. An estimate of the total societal, political, and economic cost of scenarios indicates that while SSP1 achieves the best emissions reductions it also has the highest total cost, and SSP2 achieves the best ratio between rate of emissions reductions and total cost. Feasibility appears to be highest for SSP2 since it is the least different to historical precedent. Current UK government energy strategy is closer to the narrative in SSP5, however, which has the highest total cost and exceeds an estimated carbon budget by 32%. Three key TEMPEST findings are recommended for use in IAMs: (i) the uncertainty in emissions savings due to variability in political and societal support for energy transition, (ii) the influence of negative societal pushback to policies in achievement of expected policy outcomes, and (iii) the combined influence on energy service demand of disposable income, public willingness to participate, and user impacts from measures.

Controller Development and Experimental Validation for a Vertical Axis Wind Turbine

This paper reports experimental results, in a wind tunnel, of controllers for a vertical axis wind turbine (VAWT). Models and controllers from previous works were validated and improved through the acquisition of new data sets. The control methods used are PID, LQR and CRONE (a type of fractional order control, i.e., a controller using fractional derivatives). The simulation results led to the choice of the CRONE controller for implementation. Hardware and software were developed to perform tests in a wind tunnel, that proved the correct behavior of the controller whilst validation results exceeded those from simulation. These results are expected to contribute for the viability of VAWTs in urban environments since they can aid in the increasing demand of energy services in urban areas without increasing the carbon emission levels of the area.

A critical review on global CO2 emission: where do industries stand?

Global CO2 emissions from different industries have been increasing at an alarming rate. This growth is outpacing the efforts, nations are putting in place to reduce their carbon footprints. In this topical review, we critically analyze the level of CO2 emissions on a global scale andacross various industries and activities within them and the dominant anthropogenic forcing instability. The global CO2 emission from various economic sectors such as industries, transportation and variety of waste sources were traced globally and regionally. To contextualize our review, the sector wise CO2 emission trends data for a period more than a decade is reviewed which highlighted the main sources of emissions. The data shows the overall reduction of carbon footprints and its progress across various sectors is very limited. The governing factors for this continued global pattern can be ascribed to two main factors: high consumer demands, and poor efforts towards shifting low and zero carbon services across all sectors. Some efforts have been witnessed to shift towards clean fuels and renewables, particularly in Europe and North America. However, rapid growth in industrialization limits the shifting of fossil-based energy systems towards less harmful systems. In Asia, particularly in eastern, southern, and south-eastern regions, the carbon footprints were found to increased owing to a huge demand for materials production, travelling and energy services. Therefore, it is of utmost importance to identify, understand and tackle the most persistent and climate-harmful factors across all industries and drive such policies to substitute the fossil fuels with renewables.

Pandemic, War, and Global Energy Transitions

The COVID-19 pandemic and Russia’s war on Ukraine have impacted the global economy, including the energy sector. The pandemic caused drastic fluctuations in energy demand, oil price shocks, disruptions in energy supply chains, and hampered energy investments, while the war left the world with energy price hikes and energy security challenges. The long-term impacts of these crises on low-carbon energy transitions and mitigation of climate change are still uncertain but are slowly emerging. This paper analyzes the impacts throughout the energy system, including upstream fuel supply, renewable energy investments, demand for energy services, and implications for energy equity, by reviewing recent studies and consulting experts in the field. We find that both crises initially appeared as opportunities for low-carbon energy transitions: the pandemic by showing the extent of lifestyle and behavioral change in a short period and the role of science-based policy advice, and the war by highlighting the need for greater energy diversification and reliance on local, renewable energy sources. However, the early evidence suggests that policymaking worldwide is focused on short-term, seemingly quicker solutions, such as supporting the incumbent energy industry in the post-pandemic era to save the economy and looking for new fossil fuel supply routes for enhancing energy security following the war. As such, the fossil fuel industry may emerge even stronger after these energy crises creating new lock-ins. This implies that the public sentiment against dependency on fossil fuels may end as a lost opportunity to translate into actions toward climate-friendly energy transitions, without ambitious plans for phasing out such fuels altogether. We propose policy recommendations to overcome these challenges toward achieving resilient and sustainable energy systems, mostly driven by energy services.

Implications of digitalization in facilitating socio-technical energy transitions in Europe

The energy sector is digitalizing - we see a lot of smart energy services providing higher value to customers through data processing, which also increases the importance of transparency and security of data access and processing. Nevertheless, the widespread use of these services is lagging behind for enabling fundamental transitions of energy systems. This interdisciplinary article operationalises the MLP of sustainability transitions and draws together previous research on the application and implications of energy data and consumer motivation for analysing the imbalance between the supply and demand of smart energy services in the current energy transition. Besides drawing together the opportunities and challenges with energy data of 85 international smart energy services, the empirical findings present some new energy data use cases aimed especially for consumers and provide an extensive overview of additional data types with reasoning needed by service providers. These findings are complemented with the more in-depth Estonian electricity sector digitalization case study. Furthermore, we propose a list of characteristics essential for Pan-European energy data access with the main aim to open up data, activate consumers and increase the demand of smart energy services for speeding up the green energy transition.

China’s Energy Transition Pathway in a Carbon Neutral Vision

China’s energy system requires a thorough transformation to achieve carbon neutrality. Here, leveraging the highly acclaimed the Integrated MARKAL-EFOM System model of China (China TIMES) that takes energy, the environment, and the economy into consideration, four carbon-neutral scenarios are proposed and compared for different emission peak times and carbon emissions in 2050. The results show that China’s carbon emissions will peak at 10.3–10.4 Gt between 2025 and 2030. In 2050, renewables will account for 60% of total energy consumption (calorific value calculation) and 90% of total electricity generation, and the electrification rate will be close to 60%. The energy transition will bring sustained air quality improvement, with an 85% reduction in local air pollutants in 2050 compared with 2020 levels, and an early emission peak will yield more near-term benefits. Early peak attainment requires the extensive deployment of renewables over the next decade and an accelerated phasing out of coal after 2025. However, it will bring benefits such as obtaining better air quality sooner, reducing cumulative CO 2 emissions, and buying more time for other sectors to transition. The pressure for more ambitious emission reductions in 2050 can be transmitted to the near future, affecting renewable energy development, energy service demand, and welfare losses.

TIM: modelling pathways to meet Ireland's long-term energy system challenges with the TIMES-Ireland Model (v1.0)

Abstract. Ireland has significantly increased its climate mitigation ambition, with a recent government commitment to reduce greenhouse gases by an average of 7 % yr−1 in the period to 2030 and a net-zero target for 2050, underpinned by a series of 5-year carbon budgets. Energy systems optimisation modelling (ESOM) is a widely used tool to inform pathways to address long-term energy challenges. This article describes a new ESOM developed to inform Ireland's energy system decarbonisation challenge. The TIMES-Ireland Model (TIM) is an optimisation model of the Irish energy system, which calculates the cost-optimal fuel and technology mix to meet future energy service demands in the transport, buildings, industry, and agriculture sectors, while respecting constraints in greenhouse gas emissions, primary energy resources, and feasible deployment rates. TIM is developed to take into account Ireland's unique energy system context, including a very high potential for offshore wind energy and the challenge of integrating this on a relatively isolated grid, a very ambitious decarbonisation target in the period to 2030, the policy need to inform 5-year carbon budgets to meet policy targets, and the challenge of decarbonising heat in the context of low building stock thermal efficiency and high reliance on fossil fuels. To that end, model features of note include future-proofing with flexible temporal and spatial definitions, with a possible hourly time resolution, unit commitment and capacity expansion features in the power sector, residential and passenger transport underpinned by detailed bottom-up sectoral models, cross-model harmonisation, and soft-linking with demand and macro models. The paper also outlines a priority list of future model developments to better meet the challenge of deeply decarbonising energy supply and demand, taking into account the equity, cost-effectiveness, and technical feasibility. To support transparency and openness in decision-making, TIM is available to download under a Creative Commons licence.