Energy Demand In Residential Buildings Research Articles

Multi-aspect analysis of measures to reduce the building's energy demand.

Issues related to reducing the energy demand of residential buildings are still relevant in the light of the energy transition and ongoing climate change. A single-family house from the early 1990s with a heated area of approximately 177 m2, located in the north-eastern part of Poland, was used as a case study. The article contains the results of nine years of measurements that included energy consumption for heating and domestic hot water preparation. It was estimated that the annual final energy consumption was 128.2 kWh/m2 [462 MJ/m2]. After insulating the building envelope and replacing the windows with triple-glazed ones, this value reduced to 68.2 kWh/m2 [246 MJ/m2]. The measurement results were used to build a statistical model, based on multiple regression, to calculate the energy demand of a similar building to the one analysed in this article in any given location. The article presents the second, more advanced, energy simulations model made in the DesignBuilder environment, which enabled additional analysis of the operation of the heating and ventilation system. The scope of this study also included a multi-variant economic analysis of the building energy renovation, in which the Life Cycle Cost (LCC), Net Present Value (NPV) and Internal Rate of Return (IRR) values were determined.

The influence of demographic structure on residential buildings' carbon emissions in China

In the process of advancing China’s carbon peak strategy, the residential building is a crucial sector for carbon mitigation. The energy demand for residential buildings, which is dominated by household consumption, is rapidly rising; coping with aging crisis and reducing carbon dioxide (CO2) emissions are two major challenges facing China. This study explores the complex relation between demographic structure and residential buildings' CO2 emissions, and then simulates the future carbon peaking trajectory based on scenario prediction model. The relevant results are fourfold. 1) The overall coupling coordination degree of demographic structure and residential buildings' CO2 emissions in China has entered the optimal state (i.e. high-quality coordination level) until 2020. 2) The increased household size and proportion of children population from 2010 to 2020 had an inhibitory effect on residential buildings' CO2 emissions, whereas increased population size and proportion of elderly population had a promotional effect. 3) Under the influence of demographic structure change, peak residential buildings' CO2 emissions are predicted to be delayed from 2030 to 2032 in China, and the peak value will increase by 3.56%, reaching 1.527 billion tons. 4) At the provincial degree, under the baseline scenario, Beijing will be the first to achieve peak CO2 emissions in 2026; under the aging scenario, Yunnan and Beijing will be the first to reach peak CO2 emissions in 2028. This study provides a reference for Chinese policymakers and other countries to incorporate demographic structure into future projections to advance carbon reduction targets' achievement in the building sector.

Improving daylight performance of residential light wells in dry-cold climate: Optimization and sensitivity analysis

The decrease in non-renewable energy resources of the world and subsequent air pollution regarding the utilization of fossil fuels has led to various actions and solutions to reduce these adverse effects. A sustainable design approach, especially in the first phases of the design, is one of these solutions to preserve the environment and reduce energy demand in residential buildings. Amongst renewable energy resources, daylight plays a vital role in providing energy demands in buildings. The use of daylight for lighting purposes leads to numerous economic and environmental advantages. The light well is one of these solutions that provide natural light into the buildings as well as natural ventilation. This study aims to increase the lighting function in a residential building in dry-cold climates. To achieve this goal, this paper, through a sensitivity analysis, investigates various parameters that could increase the daylight inside the buildings. Also, selected parameters will be optimized by using the genetic algorithm. The study results show a 40% increase in daylight penetration into the building compared with the current light well.

Analysis of the Energy Performance of a Retrofitted Low-Rise Residential Building after an Energy Audit

The main reason for this research is to support the Korean government building retrofitting program initiated to evaluate energy usage trends, propose energy-saving technologies, and focus on reducing the energy demand in residential buildings through energy efficiency improvement. This is achieved by assessing the energy saved after introducing a simple retrofitting measure to an existing residential building. The energy savings in the building were realized after collecting relevant data from the house occupants, analyzing electricity bills, and introducing energy conservation measures (ECMS), leading to an improvement in the energy performance of the building. The building envelope saved 2098 kWh and 6307 kWh of energy via the heating and cooling equipment with an initial incremental cost of USD 500, fuel cost savings of USD 306, and a simple payback of 1.6 years. The analysis takes the occupants 2.6 years to recoup the initial cost of USD 2400 invested with an electricity savings of 2144 kWh. Also, 3.3 tons of CO2 emissions per year were reduced, equivalent to 3.3 people reducing energy use by 20%. Finally, the actual and simulated data are almost the same for the consumption period, with only a slight difference in October and December, given 0.92 as the Pearson Correlation coefficients.

Urban microclimate and climate change impact on the thermal performance and ventilation of multi-family residential buildings

Urban settings and climate change both impact on energy use and thermal comfort inside buildings. This paper first presents a study of changes in energy demand in residential buildings considering the overlapping effect of climate change and urban heat island intensity in two European locations; Cadiz (Spain) and London (United Kingdom), representing temperate and hot European climates and moderate and dense urban settings. Future-urban weather files were generated and simulations were run considering energy demand and indoor thermal comfort. In hot climate regions such as the one of Cadiz, future climate will increase the cooling demand and the additional impact of the UHI leads to a further increase of up to +28% of total energy demand compared to the current climate without considering urban effects. Future-urban weather conditions will be detrimental also for buildings in London, where the annual energy demand is predicted to increase by up to the 16% if future climate and urban effects are included. This is due to a higher increase in cooling demand compared to the reduction for the heating need. The paper also presents a method to take into account microclimatic conditions in naturally ventilated buildings, especially the effect of wind variations around the building which impacts natural ventilation rates. Air and surface temperature and wind speeds were studied using ENVImet and the resulting microclimatic conditions were used as inputs to the EnergyPlus Airflow Network model for the calculation of the building ventilation rates. It was found that ventilation rates are reduced (in comparison to meteorological weather files) and this reduction impacts negatively on internal operative temperatures. A thermal comfort analysis was carried out indicating that the selection of a suitable weather file and microclimatic conditions is essential for more accurate predictions of internal thermal comfort and will assist in the sizing of passive and active systems to avoid overheating.

Impact of coupled heat and moisture transfer on indoor comfort and energy demand for residential buildings in hot-humid regions

Moisture significantly affects indoor thermal comfort and energy demand. However, the coupled heat and moisture transfer (HAMT) effect inside the wall assemblies is often ignored in building performance calculations. To quantify its impact on building performance under hot and humid climates, the thermal environment and energy demand of an apartment in Guangzhou (China) were evaluated with and without HAMT finite element algorithm, respectively. The HAMT effects are quantified and analyzed in different periods. Different boundary conditions regarding climate uncertainty, wind-driven rain effect, and wall solar absorptance are considered. The results show that under naturally ventilated conditions, ignoring the effect of HAMT in walls can lead to an overestimation of indoor operative temperature by 1.2 °C in summer and an underestimation of 1.7 °C in winter. The deviation in indoor operative temperature calculated by the two models is noticeable from noon to midnight. On the other hand, cooling and dehumidification demand energy demand can be underestimated by 8.4% and 12.4%, respectively, without consideration of HAMT. The HAMT also increases the probability of high hourly energy demand for cooling and dehumidification under the HAMT effect. These findings emphasize the importance of considering the HAMT effect when evaluating building performance in hot and humid regions.

The effects of climate change on the energy demand of residential buildings: A case study of a coastal city

The effects of climate change on the energy demand of residential buildings: A case study of a coastal city

An agile heating and cooling energy demand model for residential buildings. Case study in a mediterranean city residential sector

Climate change will affect people's health, especially in cities. Hence, energy planning will play a key role in the development of sustainable and resilient cities. Urban building energy models facilitate energy planning as heating and cooling demand becomes known, and the consequences of different planning actions can be modelled. This research presents an agile heating and cooling demand model. It combines a European standard's methodology, geometric information of buildings collected from cadastral and altimetric datasets using GIS-based technologies, solar irradiation analysis and the degree-days method. The model is validated with various case studies and then applied to several buildings in different environments.The model shows the strong influence of the building's age (design and materials), the building surface-to-volume ratio on the energy demand and the importance of the solar irradiation analysis. Furthermore, the model can predict the effects of the temperature rise on energy demand and prioritise the buildings to be retrofitted. Indeed, one of the conclusions obtained from the model is that advanced retrofitting of 17% of the most energy demanding buildings would obtain a 50% decrease in thermal demand; if the percentage was 50%, an 85% reduction could be reached. In conclusion, the energy planning tool hereby presented is a useful tool to viably foresee the energy demand of residential buildings and districts and the effects of climate change on their energy demand, as well as the consequences of countermeasures like retrofitting.

Artificial Intelligence and Machine Learning for Energy Consumption and Production in Emerging Markets: A Review

An increase in consumption and inefficiency, fluctuating trends in demand and supply, and a lack of critical analytics for successful management are just some of the problems that the energy business throughout the world is currently facing. This study set out to assess the potential contributions that AI and ML technologies could make to the expansion of energy production in developing countries, where these issues are more pronounced because of the prevalence of numerous unauthorized connections to the electricity grid, where a large amount of energy is not being measured or paid for. This study primarily aims to address issues that arise due to frequent power outages and widespread lack of access to energy in a wide range of developing countries. Findings suggest that AI and ML have the potential to make major contributions to the fields of predictive turbine maintenance, energy consumption optimization, grid management, energy price prediction, and residential building energy demand and efficiency assessment. A discussion of what has to be done so that developing nations may reap the benefits of artificial intelligence and machine learning in the energy sector concluded the paper.

Analysis of the rule of window-to-wall ratio on energy demand of residential buildings in different locations in China

Building energy demands are influenced by the window-to-wall ratio (WWR). The impact of the WWR on the energy demand in the same area has been researched by software. However, the impact of the WWR on the energy demand of buildings in different locations of China has not been investigated using the energy balance equation. The equation for the indoor temperature variation under various internal and external disturbances was provided in this study. The relationship between parameters A and B and the change in indoor temperature was proven. China's Harbin, Beijing, and Chengdu air-conditioning and heating loads, as well as the impact of changing WWR on the rate of energy savings for air-conditioning and heating energy demand, were studied. After investigating the changes in the cooling and heating loads in various cities under various WWRs, the suitable relationship between the cooling and heating loads and the WWR of three urban units was discovered. The findings indicated that despite the three cities' various climates and the diverse energy demands for air conditioning and heating in each city, with the same change in the WWR of urban buildings, the change rate of the air conditioning and heating loads in each city was near. Meanwhile, the heating and cooling loads were linear with WWR.

Assessment of building energy performance integrated with solar PV: Towards a net zero energy residential campus in India

Building Applied Photovoltaics (BAPV) such as Roof-top Solar PV has gained significant attention in recent years for harnessing the untapped potential of renewable energy sources. However, rooftop PV poses hurdles of space restriction and shadowing in densely packed urban residential neighborhoods. This study aims to design and assess the feasibility of an integrated grid-connected Rooftop and Façade Building Integrated Photovoltaic (BIPV) for meeting the energy demand of residential buildings on an academic campus. Three distinctive groups of residential typologies have been investigated in this study, categorized based on built area and occupants’ past energy usage. Additionally, the variation in the measured Energy Performance index of the three different residential groups is illustrated to pave the path for the development of a typology-based residential energy benchmarking and labelling system. The Solar PV system has been designed for the maximum household energy demand recorded in CoVID-affected years due to high residential electricity usage in this period. The study showcases that integration of façade BIPV for low-rise residential buildings increases the system energy production to up to 62.5 % based on the utilized surface area for active PV. Furthermore, the Net Zero Energy Building (ZEB) potential for each typology has been achieved by integration of the proposed Solar PV, evaluated as a function of the Energy Performance Index (EPI) and Energy Generation Index (EGI). The designed nominal PV power of the proposed grid-connected plant is 5.6 MW, producing 7182 MWh annually, meeting the maximum residential energy demand in the studied academic campus in CoVID affected year.

Development of a realistic scenario for the thermal energy demand of residential buildings in Bavaria till 2050

To achieve the climate protection goals, enormous efforts must be undertaken in all sectors: households, industry, commerce, and transport. Following a straightforward approach, the political objectives foresee, that in the building sector a massive reduction of energy use for the heat supply is accomplished. However, previous investigations have shown that this reduction of energy consumption is not feasible. Older buildings exhibit especially high energy demand and emissions. Yet, due to the low refurbishment rate, no substantial change of the heat demand can be expected within the next decades. By fully renovating the entire residential building stock, approximately 70 % of the final energy demand and related CO2 emissions could be saved, still not enough to reach the political goals. Therefore, renovation or renewal of buildings and of the use of renewable energy sources have to be implemented jointly for achieving the desired savings.The methods used to estimate the characteristics of Bavaria’s residential building stock as well as its heating energy demand and related CO2 emissions for the year 2050 are presented. Alternative goals are given which base upon the achievable final energy saving for a realistic renovation scenario accompanied by further reduction of CO2 emissions by using renewable energies.

Building a Sustainable Energy Community: Design and Integrate Variable Renewable Energy Systems for Rural Communities

This study proposes a decentralized hybrid energy system consisting of solar photovoltaics (PV) and wind turbines (WT) connected with the local power grid for a small Najran, Saudi Arabia community. The goal is to provide the selected community with sustainable energy to cover a partial load of the residential buildings and the power requirements for irrigation. For this, a dynamic model was constructed to estimate the hourly energy demand for residential buildings consisting of 20 apartments with a total floor area of 4640 m2, and the energy requirements for irrigation to supply a farm of 10,000 m2 with water. Subsequently, HOMER software was used to optimize the proposed hybrid energy system. Even considering the hourly fluctuations of renewable energies, the artificial neural network (ANN) successfully estimated PV and wind energy. Based on the mathematical calculations, the final R-square values were 0.928 and 0.993 for PV and wind energy, respectively. According to the findings, the cost of energy (COE) for the optimized hybrid energy system is $0.1053/kWh with a renewable energy penetration of 65%. In addition, the proposed system will save 233 tons of greenhouse gases annually.

Impact of urban heat island on cooling energy demand for residential building in Montreal using meteorological simulations and weather station observations

Urban heat island (UHI) and the increased frequency of heatwaves due to climate change reduce thermal comfort inside buildings leading to increased use of air conditioning systems. In this research, the impact of the actual local climate on the cooling energy demand of residential buildings in Montreal is studied. Building energy simulations (BES) are conducted for microclimates at eight locations in the Montreal area and compared with a reference weather data. The climate data for four locations are provided by weather stations. The other climate data are simulated with a detailed weather research and forecasting (WRF) model at 250 m resolution with detailed land-use data over a period of four months during the summer of 2020. The air temperatures from meteorological mesoscale simulations are validated with available weather station observations. The BES results show an increase in the cooling energy demand due to higher air temperatures at urban locations compared to the rural periphery. The cooling energy demand varies significantly over the eight locations although being within a radius of 20 km. The mean variation in cooling energy demand between the locations amounts to 14 % compared to the average cooling demand. Using the reference climate data provided in BES, the cooling energy demand is significantly underestimated by 25 % to 34 % on average. Increasing the thermostat cooling setpoint with 1 °C results in a reduction in mean cooling energy demand of 4.5 kWh/m2, or 11.7 %. A linear trend is found between the cooling energy demand from BES and cooling degree hours (CDH) indicating CDH can be used as a first indication for building energy demand.

Analysis of Algerian energy efficiency measures in buildings for achieving sustainable development goals

The building sector is among the most energy consumer with 42 %, it absorbs 44% of the total final energy consumption, the major part of housing, which currently exceeds eight (8) million homes, are "obsolete" in terms of energy efficiency, As a result, energy demand for residential buildings are of a very high level, Unfortunately Algeria faces to major energy challenges, his dependence of fossil resources oil and gas price drop, and the increases of the consumption. The needs of the building sector will be multiplied by 2.7 while the tertiary sector will increase its power consumption by 3.2 ,an increase of 40% relative to current consumption, The policy of energy efficiency in Algeria was concretized by adoption of the new renewable energy program and energy efficiency by 2030, program Eco-bat, the aim is reducing the high consumption in this sector, a new version of thermal regulation for buildings 2016 to introduce a minimum requirement for new buildings, to optimize their heating and cooling needs while improving the high quality of comfort, launching a labelling certificate for equipment’s, the building sector represents an energy saving potential of 38%,there are a lot of options to improve efficiency in building , focus to use of renewable energy in heating, cooling and electricity, improvement to the building envelope ,including materials ,natural ventilations and delighting, As a result, this indicates the urgent need to adopt a policy and strategy to reduce the excessive use of energy in buildings. In the light of the current global challenge of energy which calls for the development of sustainable economies, this paper analyses the approach efficiency policy in the Algerian building, and suggest improvement to reduce the gap between the policy of government and the real situation.

HYBRID TEG SYSTEM FOR INDUSTRIAL AND AIR CONDITIONING APPLICATIONS

A new system to generate electric energy using thermoelectric generators (TEG’s) based on Peltier cells has been conceived, designed and built. The system consists of a Peltier cell assembly installed in a replica of an air conditioning circuit to benefit from hot and cold air flow to generate the appropriate temperature gradient. The new system has been characterized using a group of Peltier cells mounted on a dual thermostatic chamber where cold air from air conditioning equip and hot air coming from an industrial heater are flowing through independent half-chambers. The two half-chambers are separated by an insulation wall where Peltier cells have been inserted. Temperature difference between hot and cold air flow is used by the Peltier cells to generate a voltage and current using the Seebeck effect. Peltier cells are connected in series and parallel to increase voltage and current to obtain appropriate values compatibles with external applications. Experimental tests have been developed to characterize the new design obtaining electric current and voltage, thus power, from the Peltier cell assembly. The amount of power is proportional to the temperature difference between hot and cold side of the chamber through an exponential evolution with maximum performance for specific temperature difference. Power density of the TEG has been found of 2.5x10 4 W/m 2 for a temperature difference of 160º C. TEG assembly generates a current of 8 A and 5 VDC voltage at the peak power point. The system has been tested at temperature differences compatible with those created in air conditioning ducts to recreate a real situation. Power generation for set up conditions of 50º C at the hot side and 5º C at the cold one, like in conventional air conditioning ducts, has been found of very low value because of the low temperature difference. However, when using industrial conditions with hot temperature in the range 100º C to 130º C and cold temperature between -30º C and 0º C, the power generation has increased significantly, showing the critical influence of the temperature difference. The simulation analysis indicates that the new design is capable of generating enough power to cover energy demand in residential buildings.

Predicting energy demand of residential buildings: A linear regression-based approach for a small sample size

Abstract The key design strategies that reduce the energy demand of buildings are not present in most thermal codes in many countries. Therefore, modeling techniques offer an alternative to combine the architects' modus operandi with the energy efficiency in the early stages of architectural design and with higher speed and precision. However, a review of the scientific literature using modeling techniques shows that most researchers use a relatively large sample of thermal simulations. This paper proposes a simplified method based on the linear regression modeling technique and considers a relatively smaller sample of thermal simulations. A total of 6 key building design strategies were identified, related to the urban context, building envelope, and shape factor. A simulation protocol containing 60 possible combinations was designed by random selection. In the present study, the Pleiades software was used to estimate the annual energy demand for heating and cooling for a typical dwelling in a humid climate zone. A parametric study and sensitivity analysis to identify the most efficient parameters was performed in SPSS 21. The resulting model predicts the annual energy demand with an accuracy of 93.7%, a root mean square error (RMSE) of 5.88, and a scatter index (SI) of 8.59%. The models performed could efficiently and quickly assist architects while designing the buildings in the architectural practice.

Targeting Energy Efficiency through Air Conditioning Operational Modes for Residential Buildings in Tropical Climates, Assisted by Solar Energy and Thermal Energy Storage. Case Study Brazil

Economy and parsimony in the consumption of energy resources are becoming a part of common sense in practically all countries, although the effective implementation of energy efficiency policies still has a long way to go. The energy demand for residential buildings is one of the most significant energy sinks. We focus our analysis on one of the most energy-consuming systems of residential buildings located in regions of tropical climate, which are cooling systems. We evaluate to which degree the integration of thermal energy storage (TES) and photovoltaic (PV) systems helps to approach an annual net zero energy building (NZEB) configuration, aiming to find a feasible solution in the direction of energy efficiency in buildings. To conduct the simulations, an Energy Efficiency Analysis Framework (EEAF) is proposed. A literature review unveiled a potential knowledge gap about the optimization of the ASHRAE operational modes (full storage load, load leveled, and demand limiting) for air conditioning/TES sets using PV connected to the grid. A hypothetical building was configured with detailed loads and occupation profiles to simulate different configurations of air conditioning associated with TES and a PV array. Using TRNSYS software, a set of scenarios was simulated, and their outputs are analyzed in a life cycle perspective using life cycle costing (LCC). The modeling and simulation of different scenarios allowed for identifying the most economic configurations from a life cycle perspective, within a safe range of operability considering the energy efficiency and consequently the sustainability aspects of the buildings. The EEAF also supports other profiles, such as those in which the occupancy of residential buildings during the day is increased due to significant changes in people’s habits, when working and studying in home office mode, for example. These changes in habits should bring a growing interest in the adoption of solar energy for real-time use in residential buildings. The results can be used as premises for the initial design or planning retrofits of buildings, aiming at the annual net zero energy balance.

Stochastic RCM-driven cooling and heating energy demand analysis for residential building

Changes associated with global warming are expected to significantly alter existing heating and cooling demands in buildings. In order to develop appropriate adaptation measures in response to these climate changes, policy makers will require reliable and comprehensive assessments of anticipated variations in building energy use. In this study, a stochastic RCM-driven residential energy demand analysis is developed to provide robust support for policy makers to consider various adaptation actions for building energy system. High-resolution climate projections are firstly generated via proposed approach, based on which the heating and cooling energy demand of residential buildings in the province of British Columbia, Canada is analyzed from a comprehensive perspective (i.e., considering optimistic, neutral, and pessimistic levels). The results show that energy-related infrastructure and adaptation policies are likely to face huge challenges in the next 80 years due to a large increase in the energy use demand for space cooling and a relatively slight decrease in that for heating. Under an optimistic level, annual heating energy use is projected to decline 6% while cooling energy use will increase by 23% in 2088–2099. However, under a pessimistic level these changes could surge by 21% and 88%, respectively. The difference in projected energy use between these two levels can be equivalent to 1.30 Mt of CO2e greenhouse gas emissions. The analysis proposed in this study could also be applied in other regions under similar contexts.

Analysis of design improvements for thermal bridges formed by double-brick façades and intermediate slabs for nZEB residential buildings in Spain

The traditional construction systems of façades in Spain give rise to a large number of thermal bridges. Designers do not attach importance to their impact on the energy demand of buildings. This effect is increased with the introduction of greater thicknesses of thermal insulation required by regulations. One of the thermal bridges that has the greatest impact on energy demand in residential buildings is the junction of façades with intermediate slabs (slab fronts), which becomes more significant as the number of floors in the building increases. This paper analyzes this type of thermal bridges and proposes two novel construction improvements that reduce their impact on energy demand, while maintaining traditional façade construction systems. Thermal bridges (traditional construction system and improved systems) have been analyzed through the value of the linear thermal transmittance using THERM software. EnergyPlus was used to carry out an analysis of annual energy efficiency indicators of nZEB dwellings in three Spanish cities: Alicante, Barcelona and Madrid. This study shows that the application of the two proposed novel constructive improvements allows reducing the value of the linear thermal transmittance of the thermal bridge between 20% and 63.4% and the heating demand between 16.1% and 22.6%.