Building Energy Use Research Articles

Sustainable residential building energy consumption forecasting for smart cities using optimal weighted voting ensemble learning

In recent times, smart-built environments have gone through an incessant transformation, becoming more independent and sensitive ecosystems which can balance energy consumption and user comfort, whilst also achieving higher order of safety for users. The consumption of a high volume of energy in buildings has resulted in numerous environmental issues which have adverse effects on human survival. The estimation of building energy use becomes necessary to conserve energy and enhance decision-making in reducing energy usage. In addition, constructing energy-efficient buildings will help to reduce the total energy utilized in newly constructed buildings. The machine Learning (ML) technique was regarded as the most suitable method to produce favourable results in forecasting tasks. Therefore, in numerous studies, ML was implemented in the domain of energy utilization in operational buildings. This article introduces an Improved Moth Flame Optimization with Weighted Voting Ensemble Learning (IMFO-WVEL) model for Energy Consumption Forecasting in Residential Buildings. The presented IMFO-WVEL model majorly aims to forecast energy utilization in residential buildings. To accomplish this, the presented IMFO-WVEL model follows the initial stage of data preprocessing to make it compatible with further processing. To forecast the energy consumption in residential buildings, the WVEL technique comprises three DL models namely stacked autoencoder (SAE), deep neural network (DNN), and bidirectional long short-term memory (BiLSTM) is used. Finally, the IMFO algorithm is derived by the integration of MFO with the Levy flight (LF) strategy and is applied for the hyperparameter tuning process. The experimental validation of the IMFO-WVEL technique is performed under distinct aspects. The comparison study exhibited the promising performance of the IMFO-WVEL technique over recent approaches in terms of several performance measures.

From data to strata? How design professionals “see” energy use in buildings

Improving design for efficient energy use in the built environment is a critical area for decarbonisation policy and practice. To date, this research emphasises improving tools and technology for predicting and managing energy use in buildings. No studies to date have explored how energy use is conceptualised by building design professionals. As such, this paper asks - how do architects and engineers ‘see’ and perceive energy use in UK Higher Education (HE) building design? Addressing this question is key to advancing how design professionals and building stakeholders can work together more effectively when designing for decarbonisation. We present visual narratives from 14 UK-based design professionals that include over 100 participant-produced photographs taken to represent their ways of ‘seeing’ energy use when designing HE buildings. The photo-elicitation interviews and images are analysed using Grounded Visual Pattern Analysis. The contributions of this research are twofold; first, they show how energy use is ‘seen’ and understood as both dehumanised graphs as well as emotion, personal values, family, and the natural world. This duality and contradiction sheds new light on the underlying tensions and competing professional/personal demands associated with the work of professionals designing for decarbonisation. Second, the paper provides new directions for the study of energy using visual research methods. Participant-led photography generates a different set of data that provides a deeper understanding of designers' conceptualisations and moves us beyond the dominant technological focus that is currently emphasised in research, policy, and practice.

Scaling in urban building energy use and its influencing factors

AbstractSeveral studies have reported scaling relationships for energy consumption with respect to city size and other indicators. However, such scaling relationships have rarely been reported at the suburban level. This study explored the scaling relationships between energy use (EU) and building size (gross floor area [GFA]) at the building level in 16 urban regions in the United States from 2011 to 2019. We found that the scaling exponents of most of the examined regions changed from either super‐linear or sub‐linear to linear (β = 1) over the years. The scaling exponents of some cities (e.g., New York City) fluctuated around 1. These scaling exponents are negatively correlated with regional climate. This study reports that the scaling relationships between energy consumption and GFA at the building level in heterogeneous cities are evolving toward linear scaling. This study also found that different building types and building energy structures significantly impact building energy consumption. Hotels in New York City had the highest scaling exponent (β = 1.02), and strong correlations were observed between the scaling exponents and the share of electricity in building EU. These insights reveal the common nature of the relationships between building EU and GFA and the intersections between scaling exponents and building attributes. Our study highlights the importance of energy efficiency management in hotels and electricity‐dominated buildings.

Exploring the Differential Effects of Urban Heat Islands on Energy Use and Carbon Emissions in Warm and Cold Climates: a Case Study of North Africa and North Europe

The urban heat island (UHI) phenomenon has differential impacts on energy use and carbon emissions in buildings depending on the climate of the region and the urban planning strategies in place. This study explores the differential effects of UHI on energy use and carbon emissions in warm and cold climates, using North Africa and North Europe as case studies. We address the following research questions: 1) How does the UHI phenomenon impact energy use and carbon emissions in buildings in these regions? 2) What urban planning strategies are currently in place to mitigate the negative impacts of UHI on energy demand and emissions in these regions? 3) How effective are these strategies in mitigating the negative impacts of UHI on energy demand and emissions in both warm and cold climates? 4) What additional urban planning strategies could be implemented to reduce further the negative impacts of UHI on energy demand and emissions in both warm and cold climates? The UHI increases energy bills and emissions due to the higher demand for cooling energy in warm climates, while in cold climates, UHI reduces energy demand and emissions by decreasing the need for heating energy. Urban planning strategies, such as incorporating green space, using reflective materials, choice of colors, and designing for natural ventilation, can effectively mitigate the negative impacts of UHI on energy demand and emissions in both warm and cold climates. However, the effectiveness of these strategies varies depending on the climate of the region and the specific urban context. In this study, we will provide a recommendation for urban planning strategies that can be implemented to further reduce the negative impacts of UHI on energy demand and emissions in both warm and cold climates. Our study contributes to the understanding of the UHI phenomenon. It provides insights for urban planners and policymakers in developing effective strategies to reduce energy use and carbon emissions in buildings and cities.

Analyzing the impact of COVID-19 on the electricity demand in Austin, TX using an ensemble-model based counterfactual and 400,000 smart meters

The COVID-19 pandemic caused lifestyle changes and has led to the new electricity demand patterns in the presence of non-pharmaceutical interventions such as work-from-home policy and lockdown. Quantifying the effect on electricity demand is critical for future electricity market planning yet challenging in the context of limited smart metered buildings, which leads to limited understanding of the temporal and spatial variations in building energy use. This study uses a large scale private smart meter electricity demand data from the City of Austin, combined with publicly available environmental data, and develops an ensemble regression model for long term daily electricity demand prediction. Using 15-min resolution data from over 400,000 smart meters from 2018 to 2020 aggregated by building type and zip code, our proposed model precisely formalizes the counterfactual universe in the without COVID-19 scenario. The model is used to understand building electricity demand changes during the pandemic and to identify relationships between such changes and socioeconomic patterns. Results indicate the increase in residential usage , demonstrating the spatial redistribution of energy consumption during the work-from-home period. Our experiments demonstrate the effectiveness of our proposed framework by assessing multiple socioeconomic impacts with the comparison between the counterfactual universe and observations.

A co-creative method for mapping and improving energy use and management in non-residential buildings

The built environment has a significant role to play to support a transition towards sustainability. A critical point is the energy use and management of non-residential buildings, where the operational phase has been identified as the largest contributor to energy use over a building’s lifecycle. To achieve performance in line with ambitions, there is a strong need to address interactions between architecture, technology and the people who use and maintain non-residential buildings, and to foster collaboration between different stakeholders. This article introduces a co-creative method that offers the opportunity to gather insights on how energy management and use happen on a day-to-day basis in the building, as experienced by the different stakeholder groups. The main goals of the presented method are to gather insights into the perspectives of different stakeholder groups on a systemic level and to offer innovative ways to search for opportunities to improve the energy performance of the building. Stakeholders include users or tenants, building operators, facility managers, and building owners. The article presents the method, examples from user-testing in Norwegian school and office buildings and reflects on how co-creation principles can add value to improving energy use and management in non-residential buildings.

Study on the Coupling System of Building Flexible Energy and Energy Storage on Power Grid Operation Performance

The flexible building energy storage coupling dispatching framework and optimal dispatching model have been established in this paper by using the multi-levels network dispatching analysis method of the grid system. It would include solving the optimization model with the objective function having the minimum standard deviation and the constraint conditions of charging and discharging power and capacity. Second, a simulation analysis who used an example is implemented based on the typical daily load of a Tianjin district. The findings indicate that: energy storage, construction, and flexible energy use The joint optimization’s respective standard deviations are 1.40, 1.59, and 1.24. The system’s power storage, peak-clipping, valley-filling, and other features have a greater impact than the flexible energy use of a standard structure. The building’s flexible energy use has a good peak shaving effect, which can compensate for the problems caused by the general battery energy storage system’s power and capacity limitations during the generation capacity period. In addition, the battery energy storage system can use the valley time to charge, resolving issues with valley filling optimization and the lack of flexible energy use in buildings. From this, it can be seen that the power storage system and the building’s flexible energy use jointly regulate the overall energy use performance of the structure, which not only achieves good peak load cutting and valley filling effect but also controls other issues such as frequent load fluctuations, large load peak valley difference, and other issues, ultimately leading to high energy utilization in China.

Experimental and numerical investigation of the thermal inertia of sugar-beet-pulp/starch based bricks enhanced with phase change materials

Due to environmental concerns, bio-based materials are being increasingly investigated and used in buildings. In general, the density of these materials, and thus their thermal inertia, is low. Thermal inertia can be beneficial for reducing the energy use of buildings by damping indoor temperature fluctuations or by reducing and delaying incoming (solar) heat through the façade.This study explores the thermal inertia of regular-sized bricks made of a sugar-beet-pulp/starch mixture (BP/S), and with 17 circular holes inside. The holes were filled either with the BP/S mixture, with air, with a stabilised phase change material (PCM) gel or with a salt-hydrate based PCM. The brick was insulated on all sides but one. Two series of experimental measurements were performed: 1.) a heating film placed at the back (insulated) side of the brick heated the brick until steady-state conditions were reached; 2.) the heated brick was then passively cooled down to ambient temperature by cutting the power to the heating film. Numerical simulations of these experimental measurements were also modelled using the COMSOL Multiphysics® software. In addition, simulations were run to study the thermal inertia of a full brick wall made out of 1 layer and of 4 layers of the BP/S brick with and without PCM, exposed to a combination of a sinusoidal outdoor air temperature fluctuation with an imposed radiation flux on the outdoor surface, representing summer conditions.The results show that the brick in which the holes were filled with phase change material had a slower temperature response and thus higher thermal inertia than the bricks in which the holes were filled with BP/S or with air. The salt-hydrate based PCM with the higher latent heat of fusion led to the slowest temperature response and highest thermal inertia. Furthermore, the calculated simulations could accurately reproduce the experimental measurements. Applying PCM in thick walls (40 cm) made of BP/S bricks however hardly affects the temperature amplitude damping and time delay of the complete wall. The addition of PCM therefore is only effective for thinner walls (10 cm).

Analyzing and Managing Various Energy-Related Environmental Factors for Providing Personalized IoT Services for Smart Buildings in Smart Environment

More energy is consumed by domestic appliances all over the world. By reducing energy consumption, sustainability can be improved in domestic contexts. Several earlier approaches to this problem have provided a conceptual overview of green and smart buildings. This paper aims to provide a better solution for reducing energy consumption by identifying the fields of abnormal energy consumption. It creates a better environment-friendly smart building to adopt the various lifestyles of people. This paper’s main objective is to monitor and control the energy efficiency of smart buildings by integrating IoT sensors. This paper mainly analyzes various prime factors that can help to improve energy efficiency in smart buildings. Factors impacting energy consumption are analyzed, and outliers of energy consumption are predicted and optimized to save energy. Various parameters are derived from IoT devices to improve energy efficiency in lighting and HVAC controls, energy monitoring, building envelope and automation systems, and renewable energy. The parameters used in water, network convergence, and electrical and environmental monitoring are also used for improving energy efficiency. This paper uses various IoT devices for monitoring and generating data in and around a smart building and analyzes it by implementing an intelligent Information Communication Technology (ICT) model called the Dynamic Semantic Behavior Data Analysis (DSBDA) Model to analyze data concerning dynamic changes in the environment and user behavior to improve energy efficiency and provide better sustainable lifestyle-based smart buildings. From the analyzed output, the outliers of the power consumption and other abnormalities are identified and controlled manually or automatically to improve sustainability regarding energy use in smart buildings.

Advancing and demonstrating the Impact Indices method to screen the sensitivity of building energy use to occupant behaviour

A critical gap between the occupant behaviour research field and the building engineering practice limits the integration of occupant-centric strategies into simulation-aided building design and operation. Closing this gap would contribute to the implementation of strategies that improve the occupants’ well-being while reducing the buildings’ environmental footprint. In this view, it is urgent to develop guidelines, standardised methods, and supporting tools that facilitate the integration of advanced occupant behaviour models into the simulation studies. One important step that needs to be fully integrated into the simulation workflow is the identification of influential and non-influential occupant behaviour aspects for a given simulation problem. Accordingly, this article advances and demonstrates the application of the Impact Indices method, a fast and efficient method for screening the potential impact of occupant behaviour on the heating and cooling demand. Specifically, the method now allows the calculation of Impact Indices quantifying the sensitivity of building energy use to occupancy, lighting use, plug-load appliances use, and blind operation at any spatial and temporal resolution. Hence, users can apply it in more detailed heating and cooling scenarios without losing information. Furthermore, they can identify which components in building design and operation require more sophisticated occupant behaviour models. An office building is used as a real case study to illustrate the application of the method and asses its performance against a one-factor-at-a-time sensitivity analysis. The Impact Indices method indicates that occupancy, lighting use and plug-load appliances have the greatest impact on the annual cooling demand of the studied office building; blind operation is influential only in the west and south façades of the building. Finally, potential applications of the method in building design and operation practice are discussed.

Energy, Thermal, and Economic Benefits of Aerogel Glazing Systems for Educational Buildings in Hot Arid Climates

The high cost of air conditioning during the summer makes it crucial to develop strategies to reduce energy use in buildings, especially in hot arid climates. Nanomaterial-based external window insulation is considered an effective method for achieving this goal. This research examines the effectiveness of using aerogel-based glazing systems combined with passive design techniques to improve energy efficiency in buildings in hot arid regions. This study presents various scenarios, including building orientation and aspect ratio, utilizing field measurements and energy simulations with aerogel-filled windows. This study is two-phased. The first phase compares two rooms with aerogel and conventional glazing in Aswan. The new glazing system made the room 0.3–1.9 °C cooler. The second phase simulated the Egyptian Japanese School in Aswan to assess the effects of aerogel glazing systems and altering the enclosed semi-open courtyard’s building orientation and aspect ratio. Results show that using aerogel glazing systems and altering the building orientation and aspect ratio can significantly reduce energy consumption and improve indoor thermal comfort. The results reveal that Scenario 1, which represents using aerogel glazing in the northern façade, could reduce the average air temperature between 0.30 and 1.49 °C below the base case (BC). Scenario 3, which used aerogel glazing on the southern facade, reduced annual energy consumption by 26.3% compared to the BC. Meanwhile, Scenario 5, a semi-open courtyard with an aerogel glazing system and an aspect ratio of 2.40, could save 25.7% more energy than Scenario 1. The economic viability of the scenarios was also analyzed using a simple payback period analysis, with Scenario 3 having the second-shortest payback period of 4.13 years. By insulating the exterior panes of windows, this study proposes that adopting aerogel glazing systems can make windows more cost-effective and ecologically sustainable.

Split-degree day method: A novel degree day method for improving building energy performance estimation

Degree days have been widely used in different applications in buildings, such as estimating building energy use and climate classification for building energy standards. However, there are limitations with the use of conventional degree days that result in inaccuracies in estimating building energy consumption using degree day-based methods. This paper proposes a new method, the split-degree day method, that shows substantially improved results in the accuracy of the building energy use estimation compared to the conventional degree day methods. The analysis in 801 locations in the U.S. using regression models showed that the new, proposed split-degree day method in this paper, compared to the conventional degree day method, better accounts for the weather parameters and more accurately estimates end-uses. The split-degree days showed an improvement of over 5% in the accuracy of the total annual energy use prediction, 8% for predicting the heating energy use, 0.3% for predicting the cooling energy use, and 33% for predicting the fan energy use. Additionally, the analysis showed improved results for the model with higher thermal mass and the model with a 24-hour operating schedule. These improvements were due to the fact that the split-degree day method includes more information related to the weather characteristics of a location, which is missing in a conventional degree day calculation procedure that relies on aggregated data at daily intervals. Furthermore, as opposed to the conventional degree days, the accuracy of the estimations using the split-degree days are shown to maintain their high accuracy when the base temperature deviates from the optimal base temperature. The proposed method can be used as a more accurate alternative to the conventional degree days in different applications, including but not limited to building climate classification, building energy estimation, and weather normalization for building energy savings calculation.

Performance evaluation of a ventilated roof desiccant bed by direct use of solar energy for zero-energy buildings

Indoor dehumidification is usually achieved by mechanical cooling resulting in significant consumption of high-grade energy resources such as electricity. Conventional rotary dehumidification systems also require the use of high-grade energy to heat the desiccant and regenerate it. Utilization of renewable energy for indoor dehumidification is highly of concern. Ventilated roof desiccant bed system is a novel dehumidification method which can regenerate itself automatically with low-grade energy usage by taking advantage of solar energy and natural ventilation directly. Using renewable energy as an alternative, it can reduce the building energy consumption, which is beneficial to achieve nearly zero energy building (nZEB) target. This study establishes the heat and moisture transfer model of the ventilated roof desiccant bed while the moisture transfer model is validated by using the reference data. The flow-field characteristics in the airflow channels are numerically analyzed, and the regeneration process of the desiccant bed in a typical day is also simulated. Results show that both the temperature and air velocity in the channel are increasing from the inlet to the outlet. The air velocity increment can reach 0.5 m/s, and the temperature can rise about 6 °C under the same boundaries. On a typical day, the regeneration process of the ventilated roof desiccant bed lasts for approximately 3 h, and 80 g of water is desorped per unit. It means that about 18 units are sufficient to remove the moisture produced in 8 h by a man. The research results can provide data reference for the design of the system, and thus facilitates the realization of engineering application.

Occupant's health and energy use in an office building: A sensor-enabled life cycle assessment

Indoor air quality (IAQ) has an important impact on human health and productivity. For this reason, its integration into the life cycle assessment (LCA) framework contributes to sustainably manage the operation of a building and improve the living and working conditions in homes and offices. In this study, the damages on human health caused by IAQ are quantified starting from the air pollutants’ concentrations recorded by dedicated sensors placed in an office building located in Luxembourg. Data on concentrations of total volatile organic compounds, particulate matter and radon are combined with estimated occupancy and intake fractions to calculate the total human health impact expressed in Disability Adjusted Life Years (DALYs). The impacts of indoor air quality on human health prove to be relevant, representing one tenth of the score obtained in a conventional LCA on the operational phase of the building. It can be highlighted that radon, a substance usually overlooked in IAQ studies, had the highest impact, contributing to 46% of the impact caused by exposure to indoor pollutants. The heating loads and the influence of different air exchange rates are analyzed starting from a simplified energy model of the building fed with real energy use data. LCA has proven a useful tool to analyze this trade-off in the operation of the building, where it is found that doubling the ventilation rate would reduce the impact of indoor pollutants on human health by 34% while resulting in less than 1% increase in the total energy demand over the studied period.

Experimental evaluation of daylighting performance and energy output of building-integrated photovoltaic (BIPV) panel in Bandung, Indonesia

Building energy use contributes up to 40% of total global energy use and increases by 8-10% every five years, encouraging the development of technology-based renewable energy sources. Building-Integrated Photovoltaic (BIPV) is a potentially relevant application of integrated PV in buildings which, it provides electricity cost savings, and increases the architectural attractiveness of a building. In contrast to conventional PV installations on building roofs, vertical PV installations are significantly influenced by the building orientation and the transparency of the PV. Study and analysis were conducted to implement BIPV windows in tropical climates using experimental measurement methods in energy output and indoor daylighting in four cardinal directions. This research was done by modelling a simple 2 × 2 × 1 m3 room with a PV solar window glazing made of Monocrystalline silicon 105Wp, placed on the roof of CADL Building, Institut Teknologi Bandung, Indonesia, for four days. The measurement results indicate that South is the most recommended orientation for installing BIPV windows for tropical areas in Bandung with the performance indicators for energy output = 564 Wh, DA300 = 100%, UDI250-750 = 93%, UDI100-3000 = 100%, and UDI>3000 = 0%. In contrast, West and East orientations are not recommended because of the significant difference in energy output and illuminance in the morning and the afternoon.

A French Residential Retrofit toward Achieving Net-Zero Energy Target in a Mediterranean Climate

Cities are paying more attention to building energy use and carbon footprint for attaining sustainability. Within this building sector, there is a growing attention toward development and adoption of energy efficient retrofit strategies. Plagued by the lack of efforts in achieving comprehensive energy efficient retrofit solution sets (passive, active, and renewable energy systems), the authors acknowledge the concept of NZEB toward achieving energy efficiency by 2050. Toward this end, a numerical energy simulation modeling is carried out to retrofit an existing French “Puccini house” using ‘passive, energy efficient building systems and renewable energy’ strategies toward an NZEB target in the Mediterranean climate of Nice. Using Design builder 7.0, the simulated baseline energy model (Case A) is retrofitted through variations in the proposed energy efficient retrofit measures using two case scenarios (Case B: passive retrofit; Case C: energy-efficient building) to achieve NZEB (Case D). Assessing the performance of energy efficient retrofits using % energy reduction, the implementation of a high-performance building envelope is achieved using a thermally insulated external wall (46.82%), upgraded airtightness (20.39%), thermally insulated pitched roof component (33.03%), and high-performance window type—a glazing system (3.35%) with maximized window-to-wall ratio (5.53%). The maximum energy-saving retrofit solutions provide an ambitious reduction in energy consumption by approximately 90% from the baseline. A deep retrofitting of the French house meets the NZEB targets, as it reduces the baseline energy consumption from 194.37 kWh/m2/year to 23.98 kWh/m2/year using both passive and active strategies. The remaining energy demand is met by the integration of on-site PV panels (EUI= −27.71 kWh/m2/year), which achieve an increase in energy production by 15.5%, while returning energy back to the grid (−3.73 kWh/m2/year). Findings of this study serve as a guideline for retrofitting traditional French single-family residences, while contributing toward the NZEB goal.

Investigating pathways to a net-zero emissions building sector in the European Union: what role for the energy efficiency first principle?

European Union (EU) legislation is increasingly embracing the energy efficiency first (EE1st) principle. This principle seeks to prioritise energy efficiency measures whenever these involve lower costs to society than generators, networks and other energy supply options while achieving the same outcomes. This study contributes to the quantitative evidence on the relevance of EE1st by modelling the impact of moderate to ambitious end-use energy efficiency measures on energy supply and the associated system cost under a net-zero greenhouse gas emissions constraint by 2050. These measures focus on the EU building sector and include both building retrofits (e.g. wall insulation) and efficient products (e.g. lighting). The results indicate that implementing more ambitious energy saving measures reduces the total electricity, heat and hydrogen capacities needed to achieve the net-zero target. Reducing energy use in buildings by at least 21% between 2020 and 2050 is essential to avoid excessive energy supply costs. This requires actions that go well beyond business-as-usual trends. Reductions of around 30% could be justified on the grounds of (i) high fossil fuel prices and (ii) multiple impacts (e.g. health benefits). Overall, the outcomes provide reasonable justification for the EE1st principle. To put the principle into practice, policy actions such as doubling building renovation rates and setting higher energy efficiency targets are key.

Effect of Block Morphology on Building Energy Consumption of Office Blocks: A Case of Wuhan, China

Block morphology refers to critical parameters influencing building energy performance on the block scale. However, analysis of the combined effect of block morphological parameters on building energy consumption with real blocks is lacking. In this paper, the aim is to evaluate the combined effect of office block morphology on building energy consumption in the context of the Hot-summer and Cold-winter zone in China. First, a workflow for the energy assessment of office buildings with the coupled block morphology on the block scale was proposed with evaluation tools. Seventy office blocks in Wuhan were taken as examples and then classified based on building layout typology and building height. Afterwards, the morphological parameters and building energy use intensity (EUI) for different blocks were calculated. Then, the combined effect of block morphology on the buildings’ energy consumption was evaluated and the model on predicting the building energy consumption of office blocks was proposed. Finally, based on the results, low-energy design strategies were projected for office blocks. The results illustrated that the effect of block morphology on building cooling, heating, and lighting is EUI 28.83%, 28.56%, and 23.23%, respectively. Building shape factor (BSF), floor area ratio (FAR), average building height of block (BH), and average building depth of block (BD) are effective block morphological parameters. The key morphological parameters which combined affect the building energy consumption of office blocks are BSF and FAR; BSF has 1.24 times the effect on building energy consumption than FAR. The workflow built in this paper can be applied to other cities around the world for promoting sustainable cities.

Improved locust swarm optimization algorithm applied for building retrofitting based on the green policy of buildings

Regarding the high costs associated with retrofitting buildings, finding an optimal retrofit plan considering existing buildings' environmental effects is critical. Each building following the green policy of buildings should gain a particular rate of EPC. In this paper, the most appropriate defined retrofit options are selected by the decision-makers for the building retrofits based on an optimization model. To assist decision-makers in have sensible decisions, the model incorporates economic analysis. A new algorithm called Improved Locust Swarm Optimization is used to retrofit an existing office building as a studied case. By incorporating the envelope components and indoor facilities into the model, optimal retrofit plans are systematically determined for an entire building. Electricity produced from fossil fuels decreased by utilizing a solar PV system on the roof. As a result, the concept of a zero-energy building with the lowest environmental concerns is achievable by reducing the use of nonrenewable energy in buildings. The model breaks down a long-term investment into yearly short-term investments to make investments further appealing to investors. Investments have an extended payback time that is offset by a government tax incentive program. The results indicate that 761.6 MWh of energy can be saved with a 70-month payback period and a rating form of EPC, demonstrating the model's effectiveness. Environmental concerns, such as excessive fossil fuel use and CO2 emissions, have significantly decreased.

Research on Application and International Policy of Renewable Energy in Buildings

It has been proposed in China that the country should reach a “carbon peak” by 2030 and be “carbon neutral” by 2060. In the context of energy conservation and emission reduction, the country’s energy structure needs to be transformed to improve the technology level and more widespread consumption of renewable energy. The global renewable energy utilization situation is first analyzed in this study from the perspective of renewable energy and the buildings using it, highlighting the importance of the application of renewable energy in buildings. Secondly, from the perspective of solar energy utilization technology, ground source heat pump technology, and systems for managing energy use in buildings, the progressiveness of renewable energy applications in buildings is analyzed. The application of these technologies in buildings is demonstrated from various angles. Thirdly, the development prospect of buildings using renewable energy is discussed from the perspective of the promotion of renewable energy-powered buildings and green construction. The development prospects of buildings using renewable energy are discussed from the economic benefits of green finance, the promotion and social support of renewable energy, and the environmental benefits of green buildings. Finally, based on studies in the United States, the United Kingdom, Russia, and China, the international energy policy and development direction, as well as the evaluation criteria of green buildings, are discussed, along with an assessment system for green buildings that is complementary to the strategic agreement.