Energy Efficiency Measures Research Articles

A novel approach for identifying customer groups for personalized demand-side management services using household socio-demographic data

Demand-side management (DSM) is crucial to smart energy systems. This paper presents a data-driven approach for understanding the relationship between energy consumption patterns and household characteristics to better provide DSM services. The proposed method uses a robust learning fuzzy c-Means clustering algorithm to automatically generate the optimal number of customer groups for DSM, and then uses symmetric uncertainty techniques to identify the identified load patterns and socio-demographic characteristics as the features for training a deep learning model. The model obtained can be used to predict the possibility of DSM group membership for a given household. This approach can be applied even in situations where smart meter data are not available, such as when new customers are added to the system or when residents change, or due to privacy concerns. The proposed model is evaluated comprehensively, including prediction accuracy, comparison with other baselines, and case studies for DSM. The results demonstrate the usefulness of weekly energy consumption data and associated household socio-demographic information for distinguishing between different consumer groups, the effectiveness of the proposed model, and the potential for targeted DSM strategies such as time-of-use pricing, energy efficiency measures, and demand response programs.

Assessing the Cost-Effectiveness of Incentives for Energy Transition Using Marginal Abatement Cost Curves

Incentive policies play a crucial role in encouraging the adoption of renewable energy sources and energy efficiency measures. This study analyzes and compares the incentives for energy transition in the South Tyrol region of Italy using a marginal abatement cost (MAC) curve constructed with an expert-based approach. The incentives for residential energy efficiency, mobility, and boiler replacement are characterized based on assumptions for costs, energy savings, and parameters. The resulting expert-based MAC curve analysis reveals boiler replacement incentives to be the most cost-effective, yielding CO2 reductions at the lowest cost but with limited potential as the incentive is limited to apartment blocks that are not in district heating areas. Mobility incentives enabling electric vehicle adoption have the highest CO2 reduction potential, albeit at higher costs per ton abated. Residential energy efficiency incentives fall between the two for cost-effectiveness and potential. The MAC curve approach provides a useful comparison of cost-effectiveness versus potential, guiding policy prioritization. This techno-economic assessment methodology can be applied to other regions pursuing energy transition. Overall, a balanced policy mix encompassing transport, buildings, and heating is required for comprehensive low-carbon transition.

Solar neighborhoods: the impact of urban layout on a large-scale solar strategies application

The article addresses the challenges of evaluating energy performance in different neighborhood settings under various energy efficiency measures and proposes a methodology for selecting appropriate solar strategies on a neighborhood scale. The study selects five representative neighborhoods from various climatic zones with different building and street layouts. The proposed methodology involves a systematic three-step multi-domain workflow for implementing energy efficiency measures and solar strategies in the existing neighborhoods. The first step involves typical energy performance simulation, the second step involves energy simulation using high performance building envelope, and the third step involves the addition of solar strategies in combination with retrofitting materials to achieve net-zero status. The results of the study show that modifying the building envelope leads to a significant reduction in energy consumption, with up to 60% reduction observed. The study also finds that the optimal mix of solar strategies depends strongly on the type of neighborhood, its street layouts, and the type of buildings. The article highlights the importance of considering these factors when implementing solar strategies on a neighborhood scale to achieve energy efficiency and net-zero status. It provides urban planners with a systematic decision-making approach to evaluate and optimize neighborhoods to achieve net-zero energy status.

Review of Industrial Heating and Potential Low-carbon Fuels in the Context of Nepal.

Process heating is an important step in manufacturing industries such as metal, cement, brick, food, etc., and accounts for a large share of the total energy consumption of those industries. In Nepal, process heating alone accounts for around 64% of the process energy of the manufacturing sector. Around 64% of Nepalese industries’ energy demand for process heating is supplied by high-carbon emitting fossil fuels such as coal, diesel, etc. The industrial sector is responsible for significant global greenhouse gas emissions. Nepalese manufacturing Industries emit around 0.002248 GT of CO2 annually. The movement toward carbon neutrality has prompted many countries around the world to look for clean and sustainable fuel to meet their decarbonization goal. This study overviews Nepalese industries’ different industrial heating processes in terms of energy consumption, emissions, energy efficiency measures and interventions, and renewable options from a literature review and using data from secondary sources. Based on the data collected and the literature review of the industries, the potential low-carbon fuels which can be compatible with heating applications in Nepalese industries are reviewed. This paper concludes with recommendations for the future decarbonization of process heating in Nepalese industries.

Towards healthy and energy-efficient buildings in the context of Egypt: Modelling demand-controlled ventilation to improve the indoor air quality in a generic office space in Cairo

Cairo is characterised by high concentrations of ambient air pollutants, especially air particulate matter of diameter less than 2.5 micrometre (PM2.5). Many studies have emphasized the impact of PM2.5 on people’s health and wellbeing including a World Bank report that has attributed 12% of the total annual deaths in Cairo to the exposure to ambient PM2.5. On one hand. improving the energy efficiency of buildings may involve implementing energy efficiency measures that aim to achieve indoor thermal comfort by maximizing the use of natural ventilation and minimizing mechanical air-conditioning. However, while natural ventilation can help reduce CO2 levels, it can also potentially lead to an increase in indoor PM2.5 levels. This study aims to investigate the impact of multiple air filtration scenarios on the energy consumption and the indoor air quality for a shoebox model that aims to represent generic offices Cairo. The study uses EnergyPlus simulations that leverage an Energy Management System script to model the demand-controlled ventilation, apply air filters when required, and simulate the increase in energy use due to the relevant pressure drops in the air system. The results for the scenarios investigated in the study highlighted that air filters can reduce the average indoor PM2.5 levels by nearly 40% during occupancy hours while causing an estimated increase of around 2-7% in the total operational energy. Given data and assumptions relevant to the study context, it was found that filtering the recirculated air while minimizing the introduction outdoor fresh air can be sufficient to minimize indoor PM2.5 levels.

Exploring assumptions for air infiltration rate estimates using indoor radon in UK homes

Radon, a known carcinogen, is one of the most commonly monitored indoor contaminants. This paper utilises findings from a previous study on indoor radon measurements in United Kingdom (UK) homes to explore the UK Government’s Standard Assessment Procedure (SAP) assumptions for air infiltration rates. These assumptions are important as they are used to assess the energy performance of dwellings and compliance with building regulations. Indoor radon data is aggregated by 16 combinations of home energy efficiency measures (loft and wall insulation, glazing upgrades and draught proofing) and fitted using a simple analytic radon model. We find indoor radon to be inversely proportional to air change rate and proportional to a fit coefficient, k, of 42.2 ± 3.1 (95% Confidence Interval (CI)). We also show that the assumptions within SAP used to estimate home infiltration rates can be modified to include the impact of home energy efficiency which improves the fit (R 2 from 0.38 to 0.51) to the radon data. This work provides evidence to help improve assumptions regarding the effects of home energy efficiency on infiltration rates.

The future demand of renewable fuels in Germany: Understanding the impact of electrification levels and socio-economic developments

The Climate Change Act recently enacted in Germany highlights the urgency of understanding the future demand for renewable fuels. In this study, we combine technological progress and socio-economic pathways in an energy system analysis to assess future renewable fuel demands in Germany. We apply the whole-system optimisation model, TIMES, to investigate transition pathways with varying electrification levels and socio-economic developments. The results show that renewable fuels demand varies between 388 PJ and 1310 PJ depending on the electrification rates. Furthermore, our findings demonstrate that considering socio-economic aspects and behavioural change, as represented by different Shared-Socio-economic Pathways, can significantly alter the demand for renewable fuels within a narrower yet still noteworthy range compared to the electrification scenarios. This provides country-level evidence highlighting the often-overlooked influence of social developments on demand projections. Consequently, it becomes crucial to prioritize the consideration of the climate mitigation potential arising from socioeconomic-induced changes in demand patterns within the broader framework of energy efficiency measures.

Evaluating the capabilities of a simplification algorithm for Urban Building Energy Modeling in performing building-level Multi-Objective Optimizations at district scale

Since Urban Building Energy Modeling and Multi-Objective Optimization require large computational resources, both could benefit of simplification techniques able also to make them more affordable to professionals. In this work, the capabilities of a simplification algorithm for urban scale application are assessed in the context of the optimization of energy efficiency measures for buildings. A group of buildings from different districts were selected along with a set of energy efficiency measures and four objectives, such as heating and cooling needs, thermal comfort, and costs. The performance of the simplification was assessed by using precision, recall and F1-score as metrics to check whether the simplified models could obtain the same optimal solutions as the detailed ones. Overall, the simplification produced adequate results with an F1-score greater than 0.8 for 85 % of the cases considered in all climates, allowing the simulation time to be reduced up to 15.7 times.

Investment preference for either technical or operational energy efficiency measures to achieve sustainable maritime shipping

AbstractThe reduction in energy consumption in shipping is a crucial issue to achieve a more sustainable sector. Nevertheless, investments in energy efficiency are inhibited by barriers. Consequently, under a Principal-Agent approach, this study aims to analyze the factors affecting the investment preference for either technical or operational measures. To date, the research problem has barely been addressed from a similar approach. This work further integrates agency theory with the identification of barriers and drivers, as well as the cost–benefit ratio from both an environmental and a financial perspective. This makes it possible to consider shipping management from a more comprehensive perspective. The study sample is current and representative (658 individual bulk carriers). The research was carried out utilizing two binominal logistic models that provide similar results when testing the proposed hypotheses. The outcomes show that regulatory factors, such as the distance of a vessel’s technical emissions from EEDI requirements (standardized coefficients: −2.8352 and −2.5069), and Principal-Agent problems, such as split incentives (standardized coefficients: −1.0059 and −0.9828), have the greatest influence on investment preferences. As a consequence of Principal-Agent problems, vessels operating under Time Charter contracts are less likely to invest in technical measures than in operational ones. Verified information and activity promote technical measures. Maritime regulation promotes technical measures in younger vessels, especially those meeting only the minimum requirements. Better knowledge can help achieve a more environmentally responsible shipping sector. The role of shipowners and charterers should be highlighted, and transparency should be promoted to enable well-informed decisions to be made.

The Conceptual Model of the BIM4NZEB-DS System for Selecting Technological Variants of Rational Passive Energy Efficiency Measures for a Sustainable Building


 
 
 
 Implementing sustainable solutions in building design is one of the significant elements in achieving the transition to sustainability. The diversity of structural elements, construction materials, and the various preferences of interested parties complicate the decision-making process. Building Information Modeling (BIM) provides a wide range of available technological solutions and methods for automated decision support and can make decision-making more efficient. This study presents the conceptual model for BIM4NZEB-DS system for the automated selection of rational variants of passive energy efficiency measures. The algorithm of this system will integrate the solutions for data transfer from the BIM model and multi-criteria methods for the analysis of variants. The assessment of variants is based on economic and environmental criteria. The purpose of the system is to increase the reliability of the assessment, optimise the technological and human resources required, and minimise the time of decision-making. The developed system will be validated using the BIM model of real-case building
 
 
 

Why don’t we consume energy more efficiently? a Lisbon Parish council case study

Introduction: Almost 50% of the European Union’s final energy consumption is used for heating and cooling, 80% of which in buildings. The European Commission recently issued the “Efficiency Energy First Principle,” a formal recommendation to EU countries prioritizing energy efficiency measures over other energy-related investments. Decarbonizing the aging housing stock represents a significant challenge to Southern Europe and the remaining Member States. This exploratory research aims to understand why Portuguese people fail to increase their energy efficiency; it then proposes potential interventions. Several studies have looked into the effect of technology-based and behavior-based strategies (individual, socioeconomic and demographic, as well as contextual factors) regarding residential energy consumption. Few, however, have brought all these factors together in one project as in this case.Methods: We used the integrative COM-B model to investigate three core influences of behavior, namely, capability, opportunity, and motivation in a qualitative analysis of a sample of citizens of one specific Lisbon, Portugal community. The Behavior Change Wheel model was then used to propose interventions that might promote energy-responsible behavior.Results: Our finding suggests that investments in structural strategies, and, above all, in behavioral strategies are needed to achieve efficient residential electricity consumption. Specifically, we found a lack of capability (i.e., people’s physical skills and strength, knowledge, and regulation skills) represented the greatest barrier to energy consumption efficiency. A lack of motivation (involving habits and self-conscious intentions or beliefs) was the least decisive factor in the adoption of efficient energy consumption behaviors.Discussion: We therefore recommend the following interventions: 1) training and enablement addressing residents’ physical capability (primarily the replacement of high consumption equipment); 2) training, restriction, environmental restructuring, and enablement would increase residents’ physical opportunity (arising from poor home insulation and citizens’ lack of financial resources to invest in energy solutions); and 3) education, training, and enablement to change psychological capability (regarding insufficient or confusing energy use information).

Integrating Passive Energy Efficient Measures to the Building Envelope of a Multi-Apartment Building in Sweden: Analysis of Final Energy Savings and Cost Effectiveness

A major challenge in building energy renovation is to cost effectively achieve notable energy savings. This paper investigates cost-effective passive energy-efficiency measures for thermal envelope retrofit of a typical Swedish multi-apartment building from the 1970s. Here, the use of different types of insulation materials for the retrofits of roof, exterior walls, and ground floor are analyzed along with changing windows and doors with varying thermal transmittance values. The cost-effectiveness analysis is based on the net present value of the investment costs of the energy-efficiently measures and the achieved energy cost saving. Different economic scenarios and renovation cases are considered in techno-economic analyses to determine the cost-effective energy-efficiency retrofit measures. The results indicate that improved windows reduce energy demand for space heating by up to 23% and yield the highest final energy savings. However, additional mineral wool roof insulation is the most cost-effective measure under all economic scenarios. This measure gave the lowest ratio of cost effectiveness of about 0.1, which was obtained under the stable scenario. The final energy savings that can be achieved in a cost-effective manner vary between 28% and 61%, depending on the economic scenario and renovation case. This analysis emphasizes the influence of different renovation cases and economic parameters on the cost effectiveness of passive energy-efficiency measures.

Formulating sustainable development policy for a developed nation: exploring the role of renewable energy, natural gas efficiency and oil efficiency towards decarbonization

ABSTRACT Limiting CO2 emissions is crucial for sustainable development, environmental protection, and climate change mitigation, ensuring a more resilient and cleaner future. Prioritizing sustainable urbanization renewable energy, and energy efficiency is vital for achieving this prosperous and sustainable future. As a result, we adopt the Fourier testing approach for stationary, cointegration, estimator, and causality, to scrutinize the role of renewable energy, energy efficiency, and urbanization on CO2 emissions in Finland over the period between 1990 and 2020, controlling economic growth and trade openness. The empirical analysis of the Fourier ARDL estimator establishes that energy efficiency measures such as gas and oil efficiency exhibit an adverse effect on CO2 emissions, so energy efficiency mitigates CO2 emissions. Similarly, the study also found that urbanization and renewable energy reduce CO2 emissions. Conversely, economic growth and trade openness induce CO2 emissions. Additionally, the Fourier-Toda-Yamamoto method provides robust evidence regarding the long-term implications of the examined factors. Based on this result, the study emphasizes that implementing a regulatory framework to enhance energy efficiency, promote renewable energy adoption, and support sustainable urban development will be an essential strategy in the global effort to attain the net-zero emissions target, which offers valuable insights to other countries seeking to transition towards cleaner and more sustainable energy sources.

Parametrized passive house standard compliance energy analysis of three exemplary carbon neutral hybrid timber technology-based building renovations in the Republic of Korea

So-called Passive House (PH) and near net Zero Energy Building (nZEB) concepts have become standards for energy-efficient building renovations with low greenhouse gas (GHG) emissions. Minimizing building service energy demand related GHG emissions requires detailed specification and assessment of energy-efficient renovation measures and user behavior prediction. This study examines the compliance with the PH-standard of three exemplary carbon neutral hybrid-timber technology-based building renovations in the Republic of Korea. The simulation of assessment indicators employed a parametric design system to automate exporting data from building models to the PH Planning Package. Calculations were compared with threshold values for the PH-standard to evaluate compliance. The results showed that thermal bridge compensation contributed to the reduction of heating- and cooling-associated primary energy demand. The residential buildings (apartment and multi-unit) achieve the passive house standard, while the renovated mixed-use building does not achieve the standard due to high user and process loads. The parametric design facilitates the evaluation of multiple design options with variable user behavior. Integration of heating, cooling, mechanical ventilation, hot water production, and user behavior related to passive ventilation and the shading of transparent components were found to be critical factors in achieving passive house standard thresholds.

Ranking model to measure energy efficiency for warehouse operations sustainability

Implementing sustainable or green strategies in warehouse management has become increasingly important. The environmental impact can be assessed by evaluating resource usage and productivity. A proper method for assessing the sustainability of internal processes can provide a valuable tool for companies to understand what is being done correctly and what needs to be improved to comply with new guidelines. For this paper, a case study at Arvato warehousing provider for end consumer products was conducted, and a rating mechanism model for warehouses was developed. Data on energy consumption and productivity were collected from output of 13 warehouse units (modules). From the collected data, a set of KPIs, an index system, an automation categorization system, and a ranking system were created to help with decision making, problem identification, and solving. As result, this paper demonstrates the impact of different material handling systems on energy consumption and found that a higher level of automation does not always translate into operating more efficiently in terms of sustainability. Instead of reporting absolute numbers, this study created an index that displays relative values, making it much easier to identify the most efficient modules. Additionally, this study takes the automation index a step further by creating three categories of automation levels in addition to the percentage that indicates how advanced the technology in a warehouse is, allowing for the creation of groups of warehouses and the comparison of their performance.

Challenges in benchmarking whole-life GHG emissions from renovation cases: Evidence from 23 real-life cases

While political initiatives focus on energy efficiency to reduce greenhouse gas emissions (GHGe), there is currently a lack of knowledge about GHGe from energy-efficiency measures versus other renovation measures. Recognizing the multitude of purposes and functions in play within real-life renovations is central to the ongoing development in benchmarking and regulating the life-cycle GHGe of building projects, to ultimately limit emissions from the growing number of renovation projects. This study therefore investigates lifecycle-based GHGe from the multitude of changed functions in 23 real-life cases of renovation and considers how the results contribute to discussions on benchmarking renovation projects. The results show that, from a lifecycle perspective, energy efficiency actions in renovation produced operational savings of around 50 % from 13.5 kg CO2-eq/m2/year to 7.0 kg CO2-eq/m2/year on average, indicating the significance of reducing the energy demand of buildings. The material-related, embodied GHGe contributed to an average of 2.8 kg CO2-eq/m2/year in the 23 renovation cases. A remarkable 54 % of these lifecycle-embodied impacts from the renovation cases are associated with other functions than energy efficiency, such as spatial adjustments, changes in interior layout, or the construction of balconies. The results contribute to discussions of three benchmarking approaches suggested in literature. First, single benchmarks for the whole building. This approach does not encompass the large variation in impacts and functions that are showcased in the renovation cases. Second, benchmarks on a smaller scale, such as building elements. This approach can be explored further, and the study provides pointers to the significance of different elements. Finally, benchmarks based on GHGe “savings” from energy reductions. The approach only considers one function and not the significance of the multitude of other functions added in renovation projects.

Decarbonisation strategies for manufacturing: A technical and economic comparison

Decarbonisation strategies for eight German manufacturing companies of different industries (electrical, chemical, beverage, mechanical engineering, automotive, polymer processing) are developed and analysed. The abatement potential and economic feasibility of strategies depend to a large extent on individual preconditions e.g., the area available for renewable energy systems, and dynamic effects, for example the changing emission intensity of local electricity generation. The strategies lead to a reduction of between 41 % and 88 % for seven of the eight companies.The in-depth case studies show that energy efficiency measures and expanding the company's own renewable energy plants, except for solar heat, are particularly cost-effective, while shutting-down existing combined heat and power plants has the highest abatement costs between 169 and 1686 EUR/tCO2e. Decarbonising electricity procurement and switching from natural gas to biomethane have the highest greenhouse gas abatement potential in Scope 1 and 2.The novelty of this work is the linking of economic and ecological considerations of measures in the context of company-specific decarbonisation strategies. Using marginal abatement cost curves, different options for emission reductions are discussed and general conclusions for the development of decarbonisation strategies in the manufacturing sector are drawn.

At the roots of the energy performance gap: Analysis of monitored indoor air before and after building retrofits

The growing concern about climate change and energy security has fostered energy efficiency measures to reduce building consumption in many European countries. The policies and incentives behind these improvements typically rely on pre-calculated expected energy savings. However, evidence shows that the actual energy performance after such interventions often falls short of the expected targets. People's behavior is one of the causes of the energy performance gap between measured and predicted building energy performance. This study contributes to this discussion by analyzing data on air temperature, relative humidity, and Volatile Organic Compounds monitored in eleven apartments in Milan (Italy) before and after building renovation. These data were then used to simulate two representative flats, thus obtaining their energy demand for space heating. The analysis of the measured data shows that users adapt differently to building retrofits. Under the assumption of constant moisture generation during the periods monitored, some occupants appear to increase air change rates and reduce indoor air temperatures, while others show the opposite behaviour. These trends could be related to the fact that some users prioritize air quality over thermal comfort and vice versa. Energy simulations suggest that the former behaviour leads to a larger energy performance gap.

Envisioning an Energy Performance Certificate for livestock houses: A general methodological development and a specific application to growing-finishing pig houses

Climate control represents a significant energy use in livestock houses. Although energy-efficient solutions aimed at reducing this energy consumption are expanding, their spread in these facilities is hindered by the lack of standardized methodologies for assessing their impacts on the energy performance. An Energy Performance Certificate (EPC) for livestock houses represents a solid solution for assessing and rating the energy performance of these buildings accordingly to a standardized methodology. Unfortunately, specific EPC s for livestock houses are not present in literature. The aim of this work is to propose the first methodological framework for an EPC specifically developed for livestock houses which can be easily adapted to different types of livestock productions. An exemplificative adaptation and a practical application are provided for growing-finishing pig houses with the aim of clarifying the certification procedure, highlighting the potentialities of this approach, and providing and discussing some examples of results. The results show that the certified pig house has a low energy performance, labelled with the class E. By adopting the energy efficiency measures proposed in the framework of the EPC, the energy performance could remarkably improve and achieve a class-B rating. This EPC proposal represents a complete novelty in literature and an innovative and promising approach to the topic of energy efficiency in livestock sector by enhancing the comparison of the energy performance between existing livestock houses or design alternatives equipped with different energy-efficient technologies and solutions.

MEVO: A Metamodel-Based Evolutionary Optimizer for Building Energy Optimization

A deep energy retrofit of building envelopes is a vital strategy to reduce final energy use in existing buildings towards their net-zero emissions performance. Building energy modeling is a reliable technique that provides a pathway to analyze and optimize various energy-efficient building envelope measures. However, conventional optimization analyses are time-consuming and computationally expensive, especially for complex buildings and many optimization parameters. Therefore, this paper proposed a novel optimization algorithm, MEVO (metamodel-based evolutionary optimizer), developed to efficiently identify optimal retrofit solutions for building envelopes while minimizing the need for extensive simulations. The key innovation of MEVO lies in its integration of evolutionary techniques with design-of-computer experiments, machine learning, and metaheuristic optimization. This approach continuously refined a machine learning model through metaheuristic optimization, crossover, and mutation operations. Comparative assessments were conducted against four alternative metaheuristic algorithms and Bayesian optimization, demonstrating MEVO’s effectiveness in reliably finding the best solution within a reduced computation time. A hypothesis test revealed that the proposed algorithm is significantly better than Bayesian optimization in finding the best cost values. Regarding computation time, the proposed algorithm is 4–7 times faster than the particle swarm optimization algorithm and has a similar computational speed as Bayesian Optimization.