Energy Efficiency Measures Research Articles

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.

Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort

Nowadays, in contemporary building and energy management systems (BEMSs), the predominant approach involves rule-based methodologies, typically employing supervised or unsupervised learning, to deliver energy-saving recommendations to building occupants. However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. This inherent lack of adaptability to occupants significantly hampers the effectiveness of energy-saving solutions. Moreover, the prevalent cloud-based nature of these systems introduces elevated cybersecurity risks and substantial data transmission overheads. In response to these challenges, this article introduces a cutting-edge edge computing architecture grounded in virtual organizations, federated learning, and deep reinforcement learning algorithms, tailored to optimize energy consumption within buildings/homes and facilitate demand response. By integrating energy efficiency measures within virtual organizations, which dynamically learn from real-time inhabitant data while prioritizing comfort, our approach effectively optimizes inhabitant consumption patterns, ushering in a new era of energy efficiency in the built environment.

Carbon insetting as a measure to raise supply chain energy efficiency potentials: Opportunities and challenges

There is great potential for companies to reduce greenhouse gas emissions (GHGE) by implementing and financing decarbonisation measures in their own value chain. A company's active contribution to reducing GHGE at a stakeholder in its value chain is considered as carbon insetting e.g. financing of energy efficiency measures along the supply chain as one possibility. The implementation of insetting measures by industrial companies is currently only rudimentarily established. Moreover, there are no precise rules on how insetting should be accounted for. However, the resulting GHGE reductions can affect the corporate carbon footprints of several companies. This leads to the question on how insetting could be transparently reported, while still setting incentives for emission reductions along the supply chain. A comparison of literature based carbon insetting concepts are distinguished from each other in regard to local references and accounting approaches. Based on these a case study of the implementation of supply chain energy efficiency measures in the automotive industry to illustrate accounting issues is developed. The case study exemplifies, that a company that finances an energy efficiency measure at a supplier can only report 10% of the reduced GHGE in its carbon footprint. In light of this background, the pillar model for GHGE accounting is adapted to incorporate carbon insetting. In addition to the carbon footprint (pillar A), two other pillars are introduced. In pillar B, the GHGE reductions outside the scopes of the reporting company can be accounted for. Greenhouse gases removed from the atmosphere can be accounted for in pillar C. The novelty of this study is applying the concept of insetting to an industrial case study and the use of the pillar model to enable transparent accounting of insetting measures. It can thereby serve as a basis for industrial reporting of carbon insetting. By addressing methodological challenges the study provides a basis for further discussion on the concept of carbon insetting.

Energy efficiency improvement in multi-family houses in Kosovo

Energy efficiency analysis for space heating is based on MESP Regulation no. 04/18 for Minimum Requirements for Energy Performance of Buildings according to the reference model M-Type R. The M-Type R model represents the building reference model for buildings built from 1960 to 2017, M-Type A: E. The study is conducted on the comparison of UA: E [W/m2K] heat transfer coefficients for the envelope surfaces of multi-family houses (walls, exterior doors, and windows, basement, and roof) according to years of construction with UR [W/m2K] based on heat transfer coefficient as well as the ratio of specific heat coefficients UA: E/UR [-]. For these buildings are presented depending on the construction periods: the number of buildings, the number, and area of housing units as well as the types of materials used to build their enclosure. The analysis of energy savings for heating is done considering only the heat losses in the building envelope (transmission losses). By the obtained results it can be concluded that the consumption of energy for heating is too high and with the measures for energy efficiency for heating there will be savings of energy for heating as well as reductions in CO2 emissions per stock of multi-family houses which is 2,125,776 m2, the number of buildings is 2,939 with 40,886 residential units.

Does economic growth spark efficiency? Unveiling the Electricity Kuznets Curve (ELKC) in ASEAN-5 nations

We contribute to the conventional Environmental Kuznets Curve literature by modeling the relationship between income and electric power consumption among five Asian economies (ASEAN-5): Indonesia, Malaysia, the Philippines, Singapore, and Thailand. Economic growth together with rapid urbanization contributes to increases in electricity use. Still, it is not clearly understood whether and to what extent improvements in technology could ultimately allow a more efficient use of power. We test whether electricity consumption follows an inverted U-shape curve (Electricity Kuznets Curve, ELKC) using the unrestricted error correction model fitted on historical data for each country. The long-run results indicate that the ELKC hypothesis is detected in Indonesia, the Philippines, and Singapore. Our results suggest that if these countries continue to follow the ELKC trajectory, further increases in income could facilitate energy-efficiency innovations to prevent a monotonic relationship between growth and electric power use. The finding implies that there is room for policies to incentivize energy efficiency measures in multiple sectors.

Energy efficiency enhancement in wireless sensor network: ant colony optimization

<p><span>Wireless sensor networks (WSNs) have received significant scholarly attentionwithin the scientific community lately. The use of small and energy efficient devices with restricted computing capabilities has gained traction in various fields of application, including environmental monitoring, target tracing, and medical health observation. Node localization is a fundamental system parameter in numerous applications. Categorizing hybrid solutions as either range-based or range-free poses a challenge in general. In this article, we aim to simplify the classification process by examining range-based and range-free schemes. There are two distinct classifications of schemes, namely fully schemes and hybrid schemes. Furthermore, we conduct a comparative analysis of the predominant energy efficiency measures in WSN networks and deliberate on prospective avenues for research in WSNs deploying ant colony algorithm.</span></p>

Regional persistence of the energy efficiency gap: Evidence from England and Wales

The pursuit of reducing imported energy dependence via energy efficiency measures has become crucial to achieving sustainability goals, reducing greenhouse gas emissions, and minimising reliance on imported energy. Despite the significant heterogeneity of energy dependence across regions, heavy reliance on energy imports can expose countries to energy security risks that impact wholesale market energy prices and global energy security, especially in periods of geopolitical conflict. Recent geopolitical conflicts and pent-up demand from post-pandemic recovery have caused global energy prices to rise, leading to high inflation and a severe cost-of-living crisis worldwide. The existence of persistent patterns of energy efficiency gap can quickly exacerbate the associated environmental and economic losses caused by energy price shocks. This paper aims to provide robust empirical evidence of the existence of patterns of persistence of the energy efficiency gap and analyses cross-sectional heterogeneity in such persistence. In a large sample of 18,361,088 domestic dwellings across England and Wales, this study incorporates observable cross-sectional heterogeneous factors, such as socioeconomic conditions, regional characteristics, and structural constraints, to understand the potential barriers preventing residents from adjusting their energy efficiency ratings and their energy efficiency gaps. Notably, the study finds that the energy efficiency gap exhibits an average high degree of persistence of almost 50%, a finding that is statistically and economically significant across all of the LSOAs in England and Wales. The study also finds significant evidence of cross-sectional heterogeneity. This analysis is unique, both in terms of methodology and the subject of investigation, as it is the first empirical analysis that investigates regional patterns of persistence of the energy efficiency gap across England and Wales with such a large degree of granularity. The findings of this study contribute to the scarce academic literature in the field and provide valuable information for designing effective policies that can help achieve energy security and climate change goals while tackling growing socioeconomic inequalities.

Analysis and Implementation of Energy Efficiency Measures in Multi-Apartment Buildings in Latvia

Abstract A simplified life cycle of any product or service consists of three main stages – manufacturing, including obtaining, transformation, combination of raw materials; transportation, as well as packaging; consumption from purchase up to actual use. Energy is not an exception, it is also an item offered by the market in different forms, and everyone in need of it has the right to buy it in case the price is acceptable. Heat power is one of the energy types required by households and important for proper maintenance. Without heating, as well as electricity, modern houses cannot function appropriately, are not attractive to their inhabitants, do not provide comfort and safety. Nevertheless, heat power often is considered as a by-product of electricity production, nowadays a swift price increase for both types of energy is inevitable. Energy efficiency is the level of appropriate usage of energy resources, which can be determined as the relation between final product type, quality, quantity and consumption of energy necessary to create this product [1]. Indirectly energy efficiency impacts health of the society in general and each individual in particular. Renovated energy efficient apartment buildings have a better ventilation system and microclimate. The problem of moisture and mold is at least partly solved, comfort is reached by consuming less energy, especially, heat power [2]. The aim of the paper is to research the impact of different energy efficiency increasing measures on heat consumption in multi-apartment buildings.