Improve Building Energy Efficiency Research Articles

Energy renovation rates in the Netherlands – comparing long and short term prediction methods

Energy renovation rates in the Netherlands – comparing long and short term prediction methods

Energy efficiency state of non-profit housing stock in the Netherlands

Improving energy efficiency of buildings is widely considered as the one of the most promising, fast and cost-effective ways to mitigate climate change and achieve the 2020 and 2050 goals set for the built environment (European Commission 2011; Aedes 2017). Energy efficiency of the building stock is hard to achieve if we only focus on the design of new dwellings. In this chapter, we will analyse the energy efficiency state of the existing Dutch non-profit housing stock using data from 2015. We examine the energy efficiency state of the stock using data from the SHAERE monitoring system. The data from SHAERE include the age, type, useful floor area, thermal resistance (Rc-value) of the envelope (roof, facades and floor), thermal transmittance (U-value) of the windows, heating and domestic hot water (DHW) systems, ventilation system, the predicted heating energy consumption and energy production systems, if present. We also use actual heating energy consumption data from Statistics Netherlands to calculate the mean actual energy consumption of the stock. The chapter aims at setting the current energy performance state of the Dutch non-profit housing stock. A complete and detailed assessment of the current efficiency state of the non-profit housing stock in the Netherlands is necessary in order to examine the energy renovation pace and energy saving measures realised. The following sections present the results and conclusions drawn from this chapter. Section 2.2 presents the development of energy efficiency policies in the built environment. The SHAERE monitoring system is presented in 2.3. Section 2.4 sums up the methods used. Section 2.5 brings attention to the results of the research study. Section 2.6 presents the conclusions of this chapter.

Heat island effect on outdoor meteorological parameters for building energy-saving design in a large city in Northern China

The climate change and urban heat island (UHI) effects on outdoor meteorological parameters were determined by analysing design temperatures for heating and air-conditioning in urban centre, suburban and outer suburban areas in a large city in northern China. The results showed that design temperatures increased apparently over the past 20 years and decreased considerably from the urban centre to suburban and outer suburban areas. The climate change and UHI impacts would lead to 1%–5% changes in design loads, decreasing the heating design load and increasing the cooling design load as the buildings moves from outer suburban, suburban to urban areas and from the past to the present. The decrease in the heating load exceeds the increase in the cooling load, being beneficial to improve building energy efficiency. Climate change and UHI impacts should be fully considered to promote energy-saving of building design.

A Review of Internet of Energy Based Building Energy Management Systems: Issues and Recommendations

A building energy management system (BEMS) is a sophisticated method used for monitoring and controlling a building’s energy requirements. A number of potential studies were conducted in nearly or net zero energy buildings (nZEBs) for the optimization of building energy consumption through efficient and sustainable ways. Moreover, policy makers are approving measures to improve building energy efficiency in order to foster sustainable energy usages. However, the intelligence of existing BEMSs or nZEBs is inadequate, because of the static set points for heating, cooling, and lighting, the complexity of large amounts of BEMS data, data loss, and network problems. To solve these issues, a BEMS or nZEB solution based on the Internet of energy (IoE) provides disruptive opportunities for revolutionizing sustainable building energy management. This paper presents a critical review of the potential of an IoE-based BEMS for enhancing the performance of future generation building energy utilization. The detailed studies of the IoE architecture, typical nZEB configuration, different generations of nZEB, and smart building energy systems for future BEMS are investigated. The operations, advantages, and limitations of the existing BEMSs or nZEBs are illustrated. A comprehensive review of the different types of IoE-based BEMS technologies, such as energy routers, storage systems and materials, renewable sources, and plug-and-play interfaces, is then presented. The rigorous review indicates that existing BEMSs require advanced controllers integrated with IoE-based technologies for sustainable building energy usage. The main objective of this review is to highlight several issues and challenges of the conventional controllers and IoE applications of BEMSs or nZEBs. Accordingly, the review provides several suggestions for the research and development of the advanced optimized controller and IoE of future BEMSs. All the highlighted insights and recommendations of this review will hopefully lead to increasing efforts toward the development of the future BEMS applications.

Heat island effect on outdoor meteorological parameters for building energy-saving design in a large city in Northern China

The climate change and urban heat island (UHI) effects on outdoor meteorological parameters were determined by analysing design temperatures for heating and air-conditioning in urban centre, suburban and outer suburban areas in a large city in northern China. The results showed that design temperatures increased apparently over the past 20 years and decreased considerably from the urban centre to suburban and outer suburban areas. The climate change and UHI impacts would lead to 1%–5% changes in design loads, decreasing the heating design load and increasing the cooling design load as the buildings moves from outer suburban, suburban to urban areas and from the past to the present. The decrease in the heating load exceeds the increase in the cooling load, being beneficial to improve building energy efficiency. Climate change and UHI impacts should be fully considered to promote energy-saving of building design.

Cost-benefit analysis for Energy Efficiency Retrofit of existing buildings: A case study in China

Abstracts Energy Efficiency Retrofit (EER) of existing buildings is a key program for improving building energy efficiency in northern regions of China. This paper presents a methodological framework to conduct an economic cost-benefit analysis for EER projects, based on the calculation of costs and benefits over life cycle. By conducting a case study of a retrofit project located in Huixin Western Street Residential Area, Beijing, China, this research empirically examines its economic sustainability. The research found that in China, retrofit of existing buildings generally lack of attractiveness to investors from an economic perspective. The retrofit of heat source and outdoor heating pipe networks is cost effective, whilst buildings envelopes retrofit is not economically beneficial. For building envelopes retrofit, if replacing windows using appropriate material, retrofit of external windows represents higher cost effectiveness than that of external walls. By applying sensitivity analysis, the research further discussed the effects of relevant factors on the economic viability of retrofit projects, and found that energy price is the most sensitive factor, followed by initial costs and energy conservation rate. The selection of retrofit materials also greatly influences the economic outcomes. This research offers directions for policy makers and managers to develop incentive mechanisms and management interventions to promote the implementation of the retrofit program.

Modeling urban building energy use: A review of modeling approaches and procedures

Abstract With rapid urbanization and economic development, the world has been experiencing an unprecedented increase in energy consumption and greenhouse gas (GHG) emissions. While reducing energy consumption and GHG emissions is a common interest shared by major developed and developing countries, actions to enable these global reductions are generally implemented at the city scale. This is because baseline information from individual cities plays an important role in identifying economical options for improving building energy efficiency and reducing GHG emissions. Numerous approaches have been proposed for modeling urban building energy use in the past decades. This paper aims to provide an up-to-date review of the broad categories of energy models for urban buildings and describes the basic workflow of physics-based, bottom-up models and their applications in simulating urban-scale building energy use. Because there are significant differences across models with varied potential for application, strengths and weaknesses of the reviewed models are also presented. This is followed by a discussion of challenging issues associated with model preparation and calibration.

Primary energy benefits of cost-effective energy renovation of a district heated multi-family building under different energy supply systems

The European Union's Directive on energy performance of buildings emphasizes the need to take cost-effectiveness into account when measures are implemented for improved building energy efficiency. In this study, we investigate cost-effective energy renovation measures for a district heated building under different contexts, including varied locations, energy supply systems and economic scenarios. We determine the final and primary energy savings of cost-effective energy renovation packages for the building in the different contexts. The measures analysed include: improved insulation for attic floor, basement walls, and exterior walls; improved windows and doors; resource-efficient taps; heat recovery of exhaust ventilation air; energy-efficient household appliances and lighting. We consider three existing Swedish energy supply systems of varying district heat production scale and tariffs, and also plausible renewable-based energy supply systems. Our analysis calculates the final energy savings of the measures including the cost-effective renovation packages on hourly basis and links these to the different energy supply systems. The cost-effectiveness analysis is based on a double-stage optimization method, considering total and marginal investment costs of renovation measures as well as associated net present values of total and marginal cost savings. The results show that significant final and primary energy savings can be achieved when energy renovation measures are implemented for the building in the different contexts. This study shows that heat demand in existing Swedish building could be about halved while electricity use may be reduced considerably with cost-effective energy renovation measures. The economic viability of the renovation measures is sensitive to the economic regimes especially discount rates and energy price increase.

Opportunities to improve indoor temperatures and electricity use in remote Australian buildings

Abstract: Adaptation to climate change and mitigation of the rising costs of electricity are key incentives for improving building energy efficiency. The need is particularly acute in remote communities in Far North Queensland and Central Australia. Electricity is expensive, incomes are relatively low and maintenance services are difficult to access. At the same time buildings have to provide an environment that is safe and productive while coping with extremely challenging climates. We report eight case studies that investigated community buildings and their associated electricity consumption, temperatures and relative humidities over a nine month period. The study focused on two building construction types: i) concrete block and ii) steel frame, in the hot arid and hot humid climate zones of northern Australia. Key findings are described relating to i) improving building thermal efficiency, ii) reducing the electricity consumption by appliances, particularly standby consumption, iii) the potential for adapting the energy efficiency rating tool AccuRate for use in remote communities in arid and tropical northern Australia.

Improving building energy efficiency in India: State-level analysis of building energy efficiency policies

India is expected to add 40 billion m2 of new buildings till 2050. Buildings are responsible for one third of India's total energy consumption today and building energy use is expected to continue growing driven by rapid income and population growth. The implementation of the Energy Conservation Building Code (ECBC) is one of the measures to improve building energy efficiency. Using the Global Change Assessment Model, this study assesses growth in the buildings sector and impacts of building energy policies in Gujarat, which would help the state adopt ECBC and expand building energy efficiency programs. Without building energy policies, building energy use in Gujarat would grow by 15 times in commercial buildings and 4 times in urban residential buildings between 2010 and 2050. ECBC improves energy efficiency in commercial buildings and could reduce building electricity use in Gujarat by 20% in 2050, compared to the no policy scenario. Having energy codes for both commercial and residential buildings could result in additional 10% savings in electricity use. To achieve these intended savings, it is critical to build capacity and institution for robust code implementation.

Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis

Buildings in cities consume 30–70% of total primary energy, and improving building energy efficiency is one of the key strategies towards sustainable urbanization. Urban building energy models (UBEM) can support city managers to evaluate and prioritize energy conservation measures (ECMs) for investment and the design of incentive and rebate programs. This paper presents the retrofit analysis feature of City Building Energy Saver (CityBES) to automatically generate and simulate UBEM using EnergyPlus based on cities’ building datasets and user-selected ECMs. CityBES is a new open web-based tool to support city-scale building energy efficiency strategic plans and programs. The technical details of using CityBES for UBEM generation and simulation are introduced, including the workflow, key assumptions, and major databases. Also presented is a case study that analyzes the potential retrofit energy use and energy cost savings of five individual ECMs and two measure packages for 940 office and retail buildings in six city districts in northeast San Francisco, United States. The results show that: (1) all five measures together can save 23–38% of site energy per building; (2) replacing lighting with light-emitting diode lamps and adding air economizers to existing heating, ventilation and air-conditioning (HVAC) systems are most cost-effective with an average payback of 2.0 and 4.3years, respectively; and (3) it is not economical to upgrade HVAC systems or replace windows in San Francisco due to the city’s mild climate and minimal cooling and heating loads. The CityBES retrofit analysis feature does not require users to have deep knowledge of building systems or technologies for the generation and simulation of building energy models, which helps overcome major technical barriers for city managers and their consultants to adopt UBEM.

Numerical study of thermal characteristics of double skin facade system with middle shade

Architectural shade is an effective method for improving building energy efficiency. A new shade combined with the double skin facade (DSF) system, called middle shade (MS), was introduced and developed for buildings. In this paper, a 3D dynamic simulation was conducted to analyze the influence of MS combined with DSF on the indoor thermal characteristics. The research on MS for DSF involves the temperature, the ventilation rate, the velocity distribution of the air flow duct, and the indoor temperature. The results show that the angle and position of the shade in the three seasons are different, and different conditions effectively enhance the indoor thermal characteristics. In summer, the appearance of MS in DSF makes the indoor temperature significantly lower. The indoor temperature is obviously lower than that of the air flow duct, and the temperature of the air flow duct is less affected by MS. The influence of the position of blinds on indoor temperature and ventilation rate is greater than the influence of the angle of blinds. According to the climate characteristics of winter and transition season, in winter, early spring, and late autumn, the indoor temperature decreases with the increase of the position of blinds at daytime, but the opposite is true at night. The results found in this paper can provide reference for the design and use of MS combined with DSF in hot summer and cold winter zone.

The effects of climate change on heating energy consumption of office buildings in different climate zones in China

Climate plays an important role in heating energy consumption owing to the direct relationship between space heating and changes in meteorological conditions. To quantify the impact, the Transient System Simulation Program software was used to simulate the heating loads of office buildings in Harbin, Tianjin, and Shanghai, representing three major climate zones (i.e., severe cold, cold, and hot summer and cold winter climate zones) in China during 1961–2010. Stepwise multiple linear regression was performed to determine the key climatic parameters influencing heating energy consumption. The results showed that dry bulb temperature (DBT) is the dominant climatic parameter affecting building heating loads in all three climate zones across China during the heating period at daily, monthly, and yearly scales (R 2 ≥ 0.86). With the continuous warming climate in winter over the past 50 years, heating loads decreased by 14.2, 7.2, and 7.1 W/m2 in Harbin, Tianjin, and Shanghai, respectively, indicating that the decreasing rate is more apparent in severe cold climate zone. When the DBT increases by 1 °C, the heating loads decrease by 253.1 W/m2 in Harbin, 177.2 W/m2 in Tianjin, and 126.4 W/m2 in Shanghai. These results suggest that the heating energy consumption can be well predicted by the regression models at different temporal scales in different climate conditions owing to the high determination coefficients. In addition, a greater decrease in heating energy consumption in northern severe cold and cold climate zones may efficiently promote the energy saving in these areas with high energy consumption for heating. Particularly, the likely future increase in temperatures should be considered in improving building energy efficiency.

Mining big building operational data for improving building energy efficiency: A case study

Massive amounts of building operational data are collected and stored in modern buildings, which provide rich information for in-depth investigation and assessment of actual building operational performance. However, the current utilization of big building operational data is far from being effective due to the gaps between building engineering and advanced big data analytics. Data mining is a promising technology for extracting previously unknown yet potentially useful insights from big data. This paper aims to explore the potential application of advanced data mining techniques for effective utilization of big building operational data. A case study of mining the operational data of an educational building for performance improvement is presented. Decision tree, clustering analysis, and association rule mining are adopted to analyze the operational data. The results show that useful knowledge can be extracted for identifying typical building operation patterns, detecting operation deficiencies, and spotting energy conservation opportunities. Practical application:The current utilization of big building operational data in the building industry is rather limited due to the lack in experience of using advanced big data analytics. This study presents a data mining-based method for analyzing massive building operational data. The case study results validate the efficiency and effectiveness of the method proposed. It can help building professionals to discover valuable insights into building operation patterns and thereby developing strategies for improving building energy efficiency. The method can be fully realized using the open-source software R, which provides great flexibilities in its integration with building automation systems.

Guidelines for developing efficient thermal conduction and storage models within building energy simulations

Improving building energy efficiency is of paramount importance due to the large proportion of energy consumed by thermal operations. Consequently, simulating a building's environment has gained popularity for assessing thermal comfort and design. The extended timeframes and large physical scales involved necessitate compact modelling approaches. The accuracy of such simulations is of chief concern, yet there is little guidance offered on achieving accurate solutions whilst mitigating prohibitive computational costs. Therefore, the present study addresses this deficit by providing clear guidance on discretisation levels required for achieving accurate but computationally inexpensive models. This is achieved by comparing numerical models of varying discretisation levels to benchmark analytical solutions with prediction accuracy assessed and reported in terms of governing dimensionless parameters, Biot and Fourier numbers, to ensure generality of findings. Furthermore, spatial and temporal discretisation errors are separated and assessed independently. Contour plots are presented to intuitively determine the optimal discretisation levels and time-steps required to achieve accurate thermal response predictions. Simulations derived from these contour plots were tested against various building conditions with excellent agreement observed throughout. Additionally, various scenarios are highlighted where the classical single lumped capacitance model can be applied for Biot numbers much greater than 0.1 without reducing accuracy.

Optimal coordination of air conditioning system and personal fans for building energy efficiency improvement

Air temperature and speed play a critical role in the thermal sensation of comfort felt by occupants, especially in the tropics. It is of great practical interest to coordinate air conditioning and mechanical ventilation (ACMV) system and personal fans so as to enhance building demand response (DR) capability while minimizing energy cost in response to a specific electricity price signal and maintaining a thermal comfort level. In this paper, an optimization problem of coordinating ACMV and personal fans is addressed, which captures the coupling between ACMV and fans. A Lagrangian relaxation-based algorithm is developed to solve the problem by individually solving the subproblems of ACMV and personal fans with Lagrangian multipliers as the coordinated signals. This algorithm can separate the calculation of the cooling effect from the optimization procedure, so we do not have to solve the problem using a non-analytical model for evaluating the cooling effect provided by the fans. The performance of the proposed method is evaluated and validated using experimental and simulation results. Both the results show that coordinating ACMV and fans can substantially enhance building DR capability, save energy cost, and also improve customized thermal comfort microenvironment.

Laboratory study of subjective perceptions to low temperature heating systems with exhaust ventilation in Nordic countries

Given the global trends of rising energy demand and the increasing utilization of low-grade renewable energy, low-temperature heating systems can play key roles in improving building energy efficiency while providing a comfortable indoor environment. To meet the need to retrofit existing buildings in Nordic countries for greater energy efficiency, this study focused on human subjects' thermal sensation, thermal comfort, thermal acceptability, draft acceptability, and perceived air quality when three low-temperature heating systems were used: conventional radiator, ventilation radiator, or floor heating with exhaust ventilation. Human subject tests were carried out in the climate chamber at the Technical University of Denmark. In total, 24 human subjects, 12 females and 12 males, participated in the tests during the winter season. The results show that no significant differences in thermal sensation and thermal comfort between the three heating systems. Ventilation radiator promised a comfortable indoor environment with a decreased water supply temperature and floor heating with exhaust ventilation can provide a basic thermal comfort level. Thermal acceptability and draft acceptability show variations in different heating systems. Gender has significant influences on thermal sensation, draft acceptability, and preference of clo values. Personal thermal preference is observed between males and females. The males prefer to dress lighter than the females, but both can get the same thermal comfort level. It is concluded that low-temperature heating systems using exhaust air ventilation are a potentially solution when buildings are being retrofitted for improved energy efficiency and comfort of the occupants.

Numerical Simulation Study on Concentration Distribution of Indoor pollutions by Different Natural Ventilation Strategies in Shenyang

Reasonably use of natural ventilation is conducive to improving building energy efficiency and indoor air quality, In order to explore the reasonable natural ventilation modes of residential buildings in Shenyang. In summer, through investigation and analysis of residential buildings in Shenyang, Analyzes the situation of Shenyang residents to use natural ventilation to eliminate indoor pollutants. Using CFD software Airpak 3.0 for numerical simulation analysis. Taking the benzene as the indoor pollution source. Four different natural ventilation strategies are used to simulate the velocity field, concentration field and mean age of air in the room. Finally, through the comparative analysis, the conclusion is that the natural ventilation mode case 4 is the best, followed by the case 2, case 3 and case 1. Finding reasonable natural ventilation strategies in Shenyang and providing the theoretical basis for the indoor air quality assurance and energy saving in Shenyang.

A Study on Comparing and Analyzing Building Energy Efficiency Improvement Certification System of Public Law Perspective

A Study on Comparing and Analyzing Building Energy Efficiency Improvement Certification System of Public Law Perspective

A global analysis of residential heating and cooling service demand and cost-effective energy consumption under different climate change scenarios up to 2050

Climate change and energy service demand exert influence on each other through temperature change and greenhouse gas emissions. We have consistently evaluated global residential thermal demand and energy consumption up to the year 2050 under different climate change scenarios. We first constructed energy service demand intensity (energy service demand per household) functions for each of three services (space heating, space cooling, and water heating). The space heating and cooling demand in 2050 in the world as a whole become 2.1–2.3 and 3.8–4.5 times higher than the figures for 2010, whose ranges are originated from different global warming scenarios. Cost-effective residential energy consumption to satisfy service demand until 2050 was analyzed keeping consistency among different socio-economic conditions, ambient temperature, and carbon dioxide (CO2) emission pathways using a global energy assessment model. Building shell improvement and fuel fuel-type transition reduce global final energy consumption for residential thermal heating by 30% in 2050 for a 2 °C target scenario. This study demonstrates that climate change affects residential space heating and cooling demand by regions, and their desirable strategies for cost-effective energy consumption depend on the global perspectives on CO2 emission reduction. Building shell improvement and energy efficiency improvement and fuel fuel-type transition of end-use technologies are considered to be robust measures for residential thermal demand under uncertain future CO2 emission pathways.