Energy Efficiency最新文献

This paper examines the problem of attribution in the evaluation of energy efficiency program impact. The methodological problem concerns the observability of consumer behavior under the baseline condition of no program intervention. The statistical solution to the problem, which entails randomized exposure of targeted individuals to program influence, is not a viable alternative in most applications. Randomized opt-in and randomized encouragement designs do not conform to this requirement because all targeted individuals are encouraged to participate in the program, resulting in negative exposure bias. Quasi-experimental methods which utilize non-targeted individuals or targeted nonparticipants as baseline surrogates are further subject to selection bias of unknown magnitude and direction. Valid attribution in the general case of unrestricted eligibility depends on prior knowledge of the determinants of measure adoption and program participation. In default of such knowledge, evaluators must rely upon structural assumptions that have no foundation in empirical science. On the other hand, established measurement and verification methods which exploit scientific knowledge of the determinants of end-use energy consumption should be utilized to obtain unbiased estimates of individual measure and gross program energy savings.

Decarbonising the energy system requires high shares of variable renewable generation and sector coupling like power to heat. In addition to heat supply, heat pumps can be used in future energy systems to provide flexibility to the electricity system by using the thermal storage potential of the building stock and buffer tanks to shift electricity demand to hours of high renewable electricity production. Bridging the gap between two methodological approaches, we coupled a detailed building technology operation model and the open-source energy system model Balmorel to evaluate the flexibility potential that decentral heat pumps can provide to the electricity system. Austria in the year 2030 serves as an example of a 100% renewable-based electricity system (at an annual national balance). Results show that system benefits from heat pump flexibility are relatively limited in extent and concentrated on short-term flexibility. Flexible heat pumps reduce system cost, CO₂ emissions, and photovoltaics and wind curtailment in all scenarios. The amount of electricity shifted in the assessed standard flexibility scenario is 194 GWh_el and accounts for about 20% of the available flexible heat pump electricity demand. A comparison of different modelling approaches and a deterministic sensitivity analysis of key input parameters complement the modelling. The most important input parameters impacting heat pump flexibility are the flexible capacity (determined by installed capacity and share of control), shifting time limitations, and cost assumptions for the flexibility provided. Heat pump flexibility contributes more to increasing low residual loads (up to 22% in the assessed scenarios) than decreasing residual load peaks. Wind power integration benefits more from heat pump flexibility than photovoltaics because of the temporal correlation between heat demand and wind generation.

The electrical energy expenditure of households in Turkey has been increasing over the years, and households account for one-fifth of the overall electrical energy consumption. For this reason, it is of vital importance to determine the factors that affect household electricity expenditure, reveal consumption patterns for different consumer groups, and propose suggestions for the efficient use of electrical energy. In the present study, determinants of household electricity expenditure were analyzed with the quantile regression approach using the Household Budget Survey published by the Turkish Statistical Institute. In conclusion, it was determined that demographic, economic, and residential factors had significant effects on the electricity expenditures of households. The present study will serve as a guide for policymakers and decision-makers in developing strategies and conducting studies toward reducing the electricity expenditures of households, which is an important factor for energy usage.

The use of solid fuel (dirty fuel) that includes firewood, coal, charcoal, crop residue, kerosene, and dung cake is hazardous to human health and the environment. Therefore, it is crucial to understand the factors influencing the household-level transition to clean fuel. Against this backdrop, the present study analyzes the clean fuel choice and consumption intensity using the latest HIES 2018–2019 data. Findings revealed that 76 and 14% of households in Pakistan use dirty cooking fuel in rural and urban areas, respectively. In addition, choices of fuel for cooking, heating, and lighting fuel vary across provinces. Probit and Tobit model shows that income, wealth, urban location, small family size, and fewer women and children influence households’ transition towards clean fuel. The study underscores the importance of tailored policies, including tariff structures, pricing mechanisms, and financial incentives, to accelerate the adoption of energy-efficient and clean technologies. These recommendations aim to drive sustainable energy access, economic growth, and environmental sustainability in Pakistan.

Energy efficiency opportunities in the industrial sector can reduce air emissions and benefit human health. One national-level energy efficiency program, the Department of Energy (DOE)-funded Industrial Assessment Center (IAC), provides US manufacturing facilities with cost-effective energy efficiency recommendations. However, the effect of the IAC on air quality and human health has not been explored. While several studies have evaluated the health impacts of air emissions reduction associated with energy efficiency, most of them did not consider regional differences in electricity grid profiles. These differences can change both emissions and health outcomes. This study focuses on air quality and health impacts of electricity and natural gas-related recommendations from the IAC program in 2022. It estimates 248 GWh of electricity, and 1.1E6 MMBtu of natural gas savings will result from the recommendations. Using the Environmental Protection Agency (EPA)’s Avoided Emissions and GeneRation Tool (AVERT) to estimate regional electricity emissions, published natural gas emission rates, and EPA’s co-benefit risk assessment (COBRA) tool, the total annual health outcomes associated with these savings range from 4.85 to 16.9 million USD (2023). This range includes different NO_x emission rates and high and low COBRA estimates. Additionally, we introduce an energy savings health estimator (ESHE) tool that calculates air emissions and associated health outcomes of energy savings measures. We also apply it to the 2022 IAC recommendations and compare the health outcomes to those calculated using AVERT and COBRA separately. This tool can quickly estimate the health impacts of various energy efficiency projects or programs.

The aim of this work is to exploit the influence of using ozonized air to achieve stable and efficient combustion of lean mixtures in a gasoline-fuelled Spark-Ignition (SI) engine. The influence of ozone on the combustion of near-stoichiometric mixtures, which are typical of SI engines, has also been assessed. A Computational Fluid Dynamics (CFD) model has been employed to simulate compression, combustion, and expansion of a spark ignition, axisymmetric engine fuelled with iso-octane/air/ozone mixtures. The aim is to assess how ozone improves the engine performance under different engine speeds, ignition timings and equivalence ratios. The model has been validated against experimental data available in the literature. Parametric analyses have been carried out by considering three values of engine speeds (800, 1000 and 1200 rpm), three different ozone concentrations at Intake Valve Closure (IVC) (0, 100 and 200 ppm) and two equivalence ratios (0.9 and 0.7). The results show that ozone enables reactions in the Low Temperature Combustion (LTC) regime, modifies the mixture chemical composition and the auto-ignition tendency. Specifically, for all the cases under examination, the addition of ozone to the air/fuel mixture reduces the combustion duration, leading to an increase in terms of work output and a reduction of the specific fuel consumption. Moreover, the advantage of using ozone is greater for lean mixtures than for near-stoichiometric mixtures. Finally, for the near-stoichiometric cases, when the residence time of the mixture is high enough, auto-ignition occurs in the end gases.

Fuel poverty is a pressing global issue for households, particularly low-income ones. This study employs a subjective approach to examine fuel poverty in Jordan. Analyzing data from a survey of 490 participants in Zarqa Governorate, it evaluates the main determinants of subjective fuel poverty. The survey was conducted over 1 month, from March 10 to April 10, 2022. Findings reveal that the sample households experience challenges related to fuel poverty. The modeling of subjective indicators indicates an association between income level and the probability of being in arrears with utility bills. Moreover, the results highlight issues such as an inability to maintain adequate summer and winter temperatures and the presence of leaks, damp, and rot. In light of these findings, policy interventions should focus on enhancing energy efficiency and supporting vulnerable low-income households, particularly those in rural areas.

The residential sector has a large potential to reduce its energy use. Improving the energy performance of buildings is one way to realise this potential. For single-family buildings, improving the energy efficiency by energy renovations can produce a net financial gain. However, there are unaccounted barriers that act as impediments for house-owners to undertake energy efficiency measures. This study postulates that transaction costs are such a barrier. Transaction costs are defined as the cost of making an economic exchange on a market in addition to the market price. The purpose is to empirically estimate the magnitude of the transactions costs and its determinants for energy efficiency measures in the residential sector. Specifically, the transaction costs for heat insulation and energy-saving windows in Swedish single-family buildings are assessed. The analysis is based on a unique dataset, constructed from a web-based survey. The results indicate that transaction costs for energy efficiency measures are considerable. The average transaction cost to make additional heat insulation is SEK 18,046 (EUR 1,510) and SEK 21,106 (EUR 1,766) to install energy-saving windows. The determinants of the transaction costs are cognitive limitations, social connectedness, asset specificity and previous experiences. Therefore, to reduce the transaction costs, the complexity of energy efficiency measures must be addressed, potential opportunistic behaviour must be reduced, and financial options expanded.

This work projects the long-term energy demand and assesses the effects of using renewable-energy technologies on greenhouse gas (GHG) emissions in the Marun Basin, Iran. Energy projections are made with the Low Emissions Analysis Platform (LEAP) model. Demographic and macro-economic data, per capita energy use in the urban and agricultural sectors in the Marun Basin, were gathered and input to the LEAP model to simulate the energy system in the period 2016–2040. This work’s results show that under the Business As Usual (BAU) scenario the electricity demand trend in the domestic sector would increase from 1783 MWh in 2016 to 2341 MWh by 2040. The fossil fuels consumed by the urban sector would increase from 738 million barrel of oil equivalents (BOE) in 2016 to 968 million BOE in 2040. The CO₂ emissions under the BAU scenario would increase from 27.33 million tons in 2016 to 35.87 million tons in 2040. A scenario was created to provide electricity service by means of residential solar panels (RSPs) to rural areas currently not connected to the national power grid. The LEAP model’s results show CO₂ emissions would be reduced by 17%, and 20% of the domestic diesel use would be replaced by electricity generated with solar panels.

The primary objective of the current study is to examine the social issue of energy poverty from a multi-dimensional perspective in Pakistan’s national, sub-national, and urban-rural regions. The universally attributed Alkire and Foster indexing approach and globally organized PSLM (Pakistan Social and Living Standard Measurement) data from 2010–2011 to 2019–2020 were used to calculate numerical results. The study’s empirical findings emphasize that multiple-attribute energy poverty is primarily a rural phenomenon in Pakistan and its provinces. Furthermore, the time-variant situation reveals that with a shorter (longer) period, energy poverty exhibits a hybrid (declining) trend for Pakistan as a whole, its four provinces, and its regions. Finally, decomposability analyses of population subgroups and key dimensions show that households in two provinces (Sindh and KPK) and three attributes (cooking, home appliances, and entertainment) are the primary contributors to multi-dimensional energy poverty. Hence, to achieve the UN’s Millennium Development Goals, i.e., SDG7, by 2030, several measures must be implemented rapidly, particularly in rural areas and the provinces, especially Sindh and KPK, such as providing easy access to modern energy services, reducing load shedding and energy shortfalls through advanced technology adoption, and improving households’ living standards by reducing financial poverty. All of these solutions will assist in rapidly reducing energy poverty at all levels, paving the way for achieving the zero energy poverty goal (SDG7) by 2030.