Energy Savings In Residential Buildings Research Articles

Performance optimization of phase change energy storage combined cooling, heating and power system based on GA + BP neural network algorithm

Combined cooling, heating, and power systems present a promising solution for enhancing energy efficiency, reducing costs, and lowering emissions. This study focuses on improving operational stability by optimizing system design using the GA + BP neural network algorithm. By integrating phase change energy storage, specifically a box-type heat bank, the system effectively addresses load imbalance issues by aligning building thermoelectric demand with system output. This approach increases energy storage density, improves space utilization efficiency, and streamlines maintenance. The study evaluates the system's implementation in residential buildings across five climate zones, leveraging the GA + BP neural network algorithm to optimize energy, economic, and environmental aspects. The proposed full-load operation strategy, rather than the traditional hybrid operation strategy, reduces the need for frequent system adjustments, enhancing stability and efficiency. Results show a significant reduction in primary energy consumption, ranging from 7.74 × 103 to 2.08 × 106 kWh across the five cities studied. Energy optimization indexes improve by 0.27 %–3.78 % compared to electricity load operation and 1.94 %–8.58 % compared to thermal load operation. Comprehensive optimization indexes also demonstrate enhancements ranging from 5.78 % to 27.68 % and 2.67 % to 28.22 %, respectively. The full-load operation strategy proves highly effective for energy savings in residential buildings, offering innovative contributions to optimizing combined cooling, heating, and power systems, developing distributed energy systems, and promoting sustainable building development.

Optimising building envelope and insulation materials for energy efficiency and life-cycle cost in Cypriot residences

ABSTRACT Residential buildings consume approximately 36% of total electricity consumption in Cyprus and this is expected to continue increasing in the coming years. This study explores the potential for energy savings in residential buildings in Cyprus through optimising building envelopes and insulation materials. Using building information modelling and energy modelling software, the study analyses 120 combinations of building envelopes and eight insulation materials, identifying an optimal combination of wall, roof, and flooring materials that could result in 32% energy load reductions and 27% lower life-cycle costs compared to the median scenario. High-density rock wool insulation on roofs and double-glazed windows were also found to offer both monetary and energy performance benefits. A sensitivity analysis revealed that the current high energy prices could provide greater economic incentives to adopt these optimisation strategies. Optimising building materials in Cyprus could play a critical role in climate strategy while also offering significant economic benefits.

The Influencing Factors of Energy Saving in Residential Buildings Based on Energy Consumption and Emission Reduction

The Influencing Factors of Energy Saving in Residential Buildings Based on Energy Consumption and Emission Reduction

A Review of Thermal Comfort in Residential Buildings: Comfort Threads and Energy Saving Potential

Residential buildings instigate a vital role in creating a safe and comfortable indoor living environment. The phenomenon of overheating, an impact of climate change, can cause a negative effect on residents’ productiveness and heat-related illnesses and can even force high pressure on electricity generation by increasing the risk of power outages due to excessive peak cooling and heating requirements. Various issues on building thermal comfort are being evolved and discussed in review articles. However, there are few articles that review the current condition of adaptive thermal comfort studies and the potential for energy savings in residential buildings. Therefore, the aims for this paper are to: identify comfort temperature ranges in residential buildings, investigate the correlation of comfort temperature with indoor and outdoor temperatures with the aid of ‘comfort threads’, and clarify the effect of adaptive measures on residential energy saving potential. This study obtained a large variation of residential comfort temperatures, which mostly depend on the climate and operation modes of the building. ‘Comfort threads’ explains that people are adapting to a large variation of indoor and outdoor temperatures and the wide range of comfort temperature could provide significant energy savings in residential buildings. This review provides insight on and an overview of thermal comfort field studies in residential buildings.

A model developed for predicting thermal comfort during sleep in response to appropriate air velocity in warm environments

Using air movement to improve sleeping environments is widely practiced in summer; while research into how to evaluate thermal comfort and sleep quality under such non-uniform environments is lacking, due to the greatly reduced ability of occupants to adjust to the immediate environments during sleep. This study conducted climate chamber sleeping experiments under a combination of conditions of temperature (28 / 30 / 32 °C), relative humidity (50% / 80%), and air velocity (0.39 / 0.69 / 1.17 m / s). The results showed that the appropriate air velocities alleviated the thermal discomfort caused by higher temperature and humidity; however, when the temperature was higher than 32 °C and coupled with high humidity, the cooling efficiency of air velocity was reduced significantly. The subjective evaluations of sleep quality were consistent with the measured sleep indicators - Total Sleep Time (TST), Sleep Onset Latency (SOL), and Slow Wave Sleep (SWS) - indicating that recall-based sleeping evaluations after waking up could reflect the actual sleep quality to some degree. A developed PMVs model was proposed considering three aspects of the body heat exchanges: the parts in contact with the mattress (e.g. back, buttocks), the parts covered by the quilts or clothes (e.g. abdomen, chest), and the parts directly exposed to the air (e.g. head, arms, legs). The upper temperature and humidity limits, appropriate air velocity zones, and different bedding thermal insulation levels were thus obtained. The work can guide the application of local ventilation devices in sleeping environments in summer and contribute to reducing the use of air conditioners and achieving energy savings in residential buildings. • Explore sleep thermal comfort in warm-humid environments with air movement. • Increased airflows improve the sleeping thermal comfort except for hot-humid condition. • Subjective evaluations are consistent with measured sleep indicators such as Total Sleep Time (TST). • Develop a PMVs model including three heat exchange aspects with/without body coverings. • Appropriate temperature, humidity and air velocity designs are obtained by PMVs model.

Analysis of the Gamification Applications to Improve the Energy Savings in Residential Buildings

This paper proposes a set of metrics to evaluate and compare applications in a new but quickly developing field – energy management software (EMS) in residential buildings. The goal of the paper is to highlight tendencies and to detect drawbacks of present applications to develop a new one taking into account the results of previous analysis. It shows a shortlist of applications examined. Provides the conclusion drawing to the metrics and proposes main issues to be considered in the development of a new application.

Numerical investigation of a cooling system with phase change material thermal storage for the energy savings in residential buildings

Energy consumption for cooling is the fastest-growing use of energy in buildings, and the space cooling systems have become one of the major end-users in building service systems. In recent years, phase change materials (PCM) have been increasingly adopted to reduce cooling energy consumption. This paper presents the simulations of an integrated latent heat thermal energy storage (ILHTES) system for residential buildings, which includes the PCM-to-air heat exchanger (PAHX) and air conditioner (AC). In this study, the Modelica language is adopted to develop the numerical model of the ILHTES system. A numerical heat transfer model has been used to simulate the performance of PCM-to-air heat exchanger, and it has been validated against data from the literature. Using the Modelica library AixLib, a simulation of the dynamic behavior and energy consumption of the building is performed. With the help of the ILHTES model, the optimal design of the system can be obtained using the results of the simulations throughout the cooling season. This study evaluates the energy savings potential of the ILHTES system over the conventional air conditioning system under realistic climate conditions in Budapest. The results show that an energy saving ratio of 32.4% can be achieved. The effect of PCM type on energy consumption of the ILHTES system is investigated, the results show that for three commercially available PCMs, RT25, RT20, and RT18, the ILHTES system using RT25 can utilize less energy and obtain a higher energy saving ratio.

Multifamily building energy retrofit comparison between the United States and Finland

Due to the high heating demand, energy savings in residential buildings in cold climates has played an important role in reducing carbon emissions. This study aims to investigate differences between the United States and Finland regarding characteristics and energy retrofit practices of current multifamily buildings (MFBs). The study focuses on net zero energy or nearly zero energy performance in cold and very cold climatic conditions. First an overview is presented of the status of multifamily housing stocks in the two countries, followed by an explanation of energy use patterns of residential buildings in both countries. Then, building codes related to energy efficiency in Finland and the United States are examined as well as major differences between the codes. Lastly, to further understand the different strategies and techniques used in energy retrofit projects, a dataset of 57 MFBs from both countries, both net zero energy buildings (ZEB) and nearly zero energy buildings (nZEB), were collected and analyzed. The preliminary results indicate three differences: (1) For the existing national MFB stock, the United States has a higher average energy use (EUI), at 266 kWh/m2 per year (cold and very cold regions), compared to that of Finland, at 235 kWh/m2 per year, (2) Finland has more stringent energy code requirements that contribute to lower energy use in studied case projects with a mean EUI of 80 kWh/m2 per year compared to 148 kWh/m2 per year in the U.S. sample,(3) In the Finnish studied cases, the heating and ventilation systems play a more critical role in explaining the building energy use differences in the sample, while in the U.S. cases, building envelope thermal properties explained the energy use intensity variations in the sample. Overall, the comparison of the Finnish and American cases showed that good technical practices from Finland can be learned to reduce the heating demand in cold and very cold climate regions of the United States.

The energy rebound effect of residential buildings: Evidence from urban and rural areas in China

Technological progress in energy efficiency is generally considered as an effective measure to address climate change issues. However, the expected results of such progress might be impacted by the rebound effect. Employing the linear approximation of the Almost Ideal Demand System (LA-AIDS) model, this paper aims to measure the direct rebound effect of residential buildings, considering the differences in the rebound effect for residential buildings between urban and rural China over the period 1994–2016. The empirical results reveal the magnitudes of direct rebound effect for residential energy consumption. The anticipated energy savings in residential buildings cannot be fully achieved in either urban or rural areas, and even significant “back-fire” effect exists in rural China. More specifically, the magnitudes of the rebound effect for residential buildings in urban areas fluctuate between 79.43% and 110.00%, while that in rural areas increase from 115.28% to 120.40%. The main reason of rebound effect is that the energy demand for residential buildings would increase when energy efficiency improves. This study provides a significant reference for the formulation of more targeted policies to achieve the anticipated energy savings, such as development of energy efficiency education program for urban residents and clean energy project for rural residents.

Performance analysis of light shelves in providing visual and thermal comfort and energy savings in residential buildings

Using light shelves (LSs) is one of the passive-enhancement methods for energy saving and providing better thermal comfort conditions of the building users. The goal of this research is to create a consistent daylight environment that improves the visual and thermal comfort of users in buildings. Comfort effects on the four fronts of a building (in the Pars residential complex of Mashhad city in Iran as a case study) are investigated. Five types of LSs are suggested for improving the building’s thermal and visual conditions. Then, the illuminance analysis is performed for the building with and without the LSs. Horizontal and vertical LSs are considered in building to enhance visual quality and uniformity of daylight in the building space. According to the highest and lowest light intensity in the investigated spaces, the LS that provides optimal visual conditions for space is selected. Then, the role of optimum LS in thermal comfort and energy indicators (heating, cooling, and electricity) has been investigated and compared with the base situation. Analyzing the results reveals that using the optimal LS causes an annual average improvement of 18%, 11%, and 7% in the demand for heating, cooling, and electricity, respectively, of the building throughout the year.

Probabilistic reliability assessment and case studies for predicted energy savings in residential buildings

This study aims to (1) investigate the key influential parameters (KIPs) in estimating the uncertainty of energy savings using a residential building energy simulation model and (2) perform uncertainty quantification for energy savings for several different scenarios. The proposed methodology was successfully applied to the calculation of uncertainties associated with residential energy retrofits using two test houses designed for pre- and post-retrofit cases. Uncertainties were determined using basic parameters that might be supplied to an energy model and then reevaluated based on an audit of the KIPs identified, resulting in substantially reduced uncertainty. Of four different scenarios, the most uncertain scenario estimated the annual energy savings from the retrofit would be between 18% and 51% at a 95% confidence level, and the least uncertain scenario estimated the annual savings would be between 26% and 40% at a 95% confidence level. The actual measured annual savings from the two test houses was 28%, which shows an agreement with the uncertainty analysis.

Effect of insulation on indoor thermal comfort in a detached house with a floor heating system

Appropriate insulation materials, with unique physical properties and of moderate thickness, are essential for energy savings in residential buildings. However, the impact of thermal insulation on indoor thermal comfort with floor heating systems has not been studied extensively. In this study, simulations of a typical Japanese detached house were conducted with four different thicknesses of insulation material in the walls, ceiling, and floor to estimate the mean air temperature (MAT), mean radiant temperature (MRT), floor temperature, predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD). The results showed that increasing the thickness of thermal insulation increased the MAT and MRT by 1.4 – 4.0 ℃ and 1.3 – 4.4 ℃, respectively. Moreover, as the thickness of the thermal insulation increased, the floor temperature rose and exhibited smaller fluctuations. Finally, it was found that increasing the thickness of thermal insulation improved the indoor thermal comfort environment, as evidenced by an increase in the PMV from –1.0 to 0.3, and a decrease in the PPD from 25.1% to 9.5%.

Thermal Analysis of Integrating Roof with Phase Change Materials for Energy Saving in Residential Buildings

The sector of air-conditioning in the residential building consumes most of the total ‎electricity supplied for heating or cooling. Thus it has a major impact on the greenhouse gases and climate. Phase change ‎materials (PCMs) are regarded as a possible solution for reducing the energy consumption of ‎buildings by storing the heat and releasing it in certain times. The present study assists for the ‎utilization of PCMs in the roof of residential building to absorb the heat comes from solar ‎radiation during the daytime and releasing it to the inside nightly. Building considerations ‎as well as thermo-physical properties of PCMs have been taken and measured experimentally. ‎Results have shown that these materials have a good potential for reducing energy demand ‎and satisfy comfortable thermal conditions. The obtained readings, from a rig model built for that purpose, ‎showed that the indoor temperature could increase by 5-9oC in the winter compared to that ‎measured in a traditional one. Furthermore, a simulation program depended on degree-days ‎method explained that the energy consumption could be saved up to 75%. Thus PCMs could ‎submit encouraging suggestions toward the sustainability.‎

Energy Saving in Residential Buildings for a Sustainable City: the Characteristics of Energy Consumption and Analysis based on the Theory of Planned Behavior

Energy Saving in Residential Buildings for a Sustainable City: the Characteristics of Energy Consumption and Analysis based on the Theory of Planned Behavior

Renovation strategies for the Italian public housing stock: Applying building energy simulation and occupant behaviour modelling to support decision-making process

The central role of occupants for achieving energy savings in residential buildings is increasingly recognised. Simulation programmes able to take into account occupant behaviour are considered to be powerful tools for bridging the gap between the predicted and the actual energy consumption for new buildings. Nevertheless, the majority of residential buildings that will constitute the housing stock in 2050 have already been built today, therefore occupant behaviour and building simulation tools need to be fully exploited for supporting the renovation of existing housing stock. The aim of this paper is to explore the role of occupant behaviour modelling in supporting decision-makers dealing with the design of renovation strategies for residential buildings. An Italian multi-family public housing building is assumed as case study to estimate the influence of three dimensions linked with occupant behaviour – management of the thermostat, management of the heating system, variation of building characteristics – on energy heating consumption. The results show that, while the occupant behaviour influences the heating loads up to 1/3 in case of high level of building retrofit, the less the building is renovated, the higher is the behavioural impact in absolute terms of energy reduction. Therefore, in order to be effective, renovation strategies are required to design appropriate informative instruments at an early stage to support behaviour changes towards responsible energy consumption.

A new unified approach to evaluate economic acceptance towards main green technologies using the meta-analysis

The aim of this paper is to analyze the main determinants of the economic acceptability of four Green Technologies (GTs): alternative fuel vehicles, energy savings in residential buildings, smart meters and renewable electricity, using a meta-analysis on a sample of 35 selected papers, which provided 245 primary data. This approach allows detecting relationships across heterogeneous studies, avoiding the subjectivity of qualitative surveys. We implement a new two-step procedure. First, we compute a measure of the implicit price for a kilogram of CO2 avoided (PCO2), homogenizing the usable information for the GTs considered. Second, we conduct a meta-regression using the computed PCO2 values to estimate the socio-economic determinants' impact. In general, our results show a wide degree of acceptability for GTs which is stronger among European citizens. In particular, it emerges that, on average, the estimated PCO2 is positive for the GTs considered, and additional positive effects exist when respondents are confronted with an explicit reference to quantitative targets in terms of CO2 abatement, a clear proposal for payment timing, and a specific renewable electricity mix. These results indicate that information and transparency are crucial to spur GTs deployment. Therefore, to support GTs’ market penetration, public and private institutional stakeholders, have to provide “ad hoc” information to the end users, setting a clear and suitable system of prices to increase the economic value end users place on GTs.

Analysis of Applications to Improve the Energy Savings in Residential Buildings Based on Systemic Quality Model

Creating a definition of the features and the architecture of a new Energy Management Software (EMS) is complex because different professionals will be involved in creating that definition and in using the tool. To simplify this definition and aid in the eventual selection of an existing EMS to fit a specific need, a set of metrics that considers the primary issues and drawbacks of the EMS is decisive. This study proposes a set of metrics to evaluate and compare EMS applications. Using these metrics will allow professionals to highlight the tendencies and detect the drawbacks of current EMS applications and to eventually develop new EMS applications based on the results of the analysis. This study presents a list of the applications to be examined and describes the primary issues to be considered in the development of a new application. This study follows the Systemic Quality Model (SQMO), which has been used as a starting point to develop new EMS, but can also be used to select an existing EMS that fits the goals of a company. Using this type of analysis, we were able to detect the primary features desired in an EMS software. These features are numerically scaled, allowing professionals to select the most appropriate EMS that fits for their purposes. This allows the development of EMS utilizing an iterative and user-centric approach. We can apply this methodology to guide the development of future EMS and to define the priorities that are desired in this type of software.

Assessment of Residential Building Energy-Saving with 2-Tuple Linguistic Information

With the acceleration of the process of our country’s urbanization, the investment of urban infrastructure construction continues to increase and the construction industry has become a pillar industry of the national economy. However, the proportion of building energy consumption in the total energy is increasing at the same time. In order to achieve the sustainable development of the society, the energy-saving target is proposed in the 12th Five-Year Plan of China, which sets for the requirements for building energy-saving in Shaanxi Province. Evaluation of building energy-saving is an effective method to promote the healthy development of the work of building energy efficiency, but there is not a complete, reasonable and practicable the evaluation system. In this paper, we investigate the multiple attribute group decision making (MAGDM) problems for evaluating the residential building energy-saving with 2-tuple linguistic information. Then, a model based on the 2-tuple weighted geometric (TWG) operator to evaluate the residential building energy-saving is presented. In this model, alternative appraisal values are calculated by the aggregation of 2-tuple linguistic information. Thus, the ranking of alternative or selection of the most desirable trip(s) is obtained by the comparison of 2-tuple linguistic information. Finally, an illustrative example for evaluating the residential building energy-saving is given to verify the developed approach and to demonstrate its practicality and effectiveness.

Smart grid data analytics framework for increasing energy savings in residential buildings

Abstract Human energy consumption has gradually increased greenhouse gas concentrations and is considered the main cause of global warming. Currently, the building sector is a major energy consumer, and its share of energy consumption is increasing because of urbanization. This paper presents a framework for smart grid big data analytics and components required for an energy-saving decision-support system. The proposed system has a layered architecture that includes a smart grid, a data collection layer, an analytics bench, and a web-based portal. A smart metering infrastructure was installed in a residential building to conduct an experiment for evaluating the effectiveness of the proposed framework. Furthermore, a novel hybrid nature-inspired metaheuristic forecast system and a dynamic optimization algorithm are designed behind the analytics bench for achieving accurate prediction and optimization of future energy consumption. The main contribution of this study is that an innovative framework for the energy-saving decision process is presented; the framework can serve as a basis for the future development of a full-scale smart decision support system (SDSS). Through the identification of consumer usage patterns, the SDSS is expected to enhance energy use efficiency and improve the accuracy of future energy demand estimates. End users can reduce their electricity costs by implementing the optimal operating schedules for appliances, which are provided by the SDSS.

The socioeconomic impact of energy saving renovation measures in urban buildings

The purpose of the paper is to investigate the role of measures oriented to energy savings in residential buildings in the economic development at the regional level. The aim of the paper is to estimate overall socio-economic impact of energy saving renovation measures in the Croatian urban areas. Impact assessment is based on input–output methodology which is able to quantify direct and indirect effects of investment in the energy saving projects on the economic activity and employment. Gross output, gross value added and employment multipliers for building renovation projects are estimated to be in the range 2.5–2.9.