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[Display omitted] • Carbon neutrality feasibility of buildings was reviewed. • Carbon neutrality of buildings is feasible, but complexity varies. • Multi-building carbon neutrality case studies are limited. • Climate type affects neutrality; high-rise research is deficient. • Long-term lifecycle impacts of carbon measures remain unclear. Achieving carbon–neutral building stock by 2050 contributes to coping with the detrimental impacts of global warming since buildings account for almost 37% of final energy-related CO 2 emissions. This paper reviews the publications on carbon neutrality (CN) feasibility at both single and multi-building complex scales. Publications are retrieved from the Scopus database, and the snowball method is used to find the most relevant studies. The paper addresses the primary question: "Is it possible to reach the life cycle carbon neutrality of buildings?". Various information such as building life cycle carbon assessment, building characteristics (usage type and number of stories), climate type, mitigation measures, and simulation results are extracted, classified, and analyzed. Technically, reaching CN is feasible, but it is challenging given the need to implement multiple mitigation measures simultaneously, especially in the regions with low emissions intensity of the electricity grid, and may not always be economically feasible. A lack of successful case studies for large multi-building complexes, such as cities, is evident in the literature. It can be attributed to the limited availability of input data for carbon assessments as well as the complexity of simulations. Knowledge gaps in the literature and suggestions for future works are also discussed in detail. Due to the small number of studies on the topic, conclusive paths to reach the CN of buildings, specific to different climates and types of buildings, remain unclear, and thus, further research is necessary. [ABSTRACT FROM AUTHOR]

Increasing use of volatile renewable energy sources causes challenges in balancing supply and demand. Therefore, demand-side flexibility has rising importance for system operators and balancing authorities. Flexibility management methods are needed to integrate loads like ventilation systems of different buildings (e.g., residential and commercial) into flexibility service. However, the available methods described in research papers require further development for implementation in practice. Heating and cooling systems have received much attention from researchers, but the potential of ventilation systems has been left out of focus. Therefore, this paper provides a complete set of novel flexibility management methods for ventilation systems created from an aggregator's viewpoint. The flexibility is quantified through capacity (e.i. the amount of power consumption that can be altered), forced ventilation rate duration, and the tendered price for the service. The proposed methods were tested on a building model constructed and simulated in IDA ICE. The data processing and flexibility management methods were applied in MATLAB. Two types of ventilation systems with different sensor configurations were considered: constant and variable air volume. Forced ventilation rate duration is calculated using energy and mass balance analysis where the root means squared error was 10 to 33 min, depending on the system type, measured parameter, and sensor location. The flexibility service pricing model was tested on the 2022 years' manual frequency restoration reserve (mFRR) activation and balance energy market data. [ABSTRACT FROM AUTHOR]

Resilience is becoming increasingly important in power systems, microgrids (MG) and buildings. It evaluates their performance against disruptive events. The approaches mainly correspond to high-impact, low-probability events such as natural disasters and intentional attacks affecting the electrical systems infrastructure. However, resilience can encompass medium and low-impact events such as minor civil structural accidents, light faults and supply disturbances. Some resilience assessment advances are in buildings at the low-voltage (LV) level. They include vulnerability to natural disasters, reliability of supply, and service quality. These works usually use approaches independent of each other, leaving a gap between their relationship and interpretation. Therefore, there is a need to consolidate a resilience assessment strategy to guide the analysis of vulnerabilities and strengths in the same direction. This paper proposes a comprehensive approach to evaluate electrical resilience for buildings. It compiles quantitative strategies for studying electrical resilience, focusing on LV systems. It proposes a methodology for integrating the electrical system infrastructure's vulnerability, the supply's continuity and the voltage service's quality. Implementing this approach in a university building equipped with smart metering demonstrates the effectiveness of the proposed methodology for assessing electrical resilience. The results show a comprehensive resilience analysis and the possibility of extending the methodology to MG and LV distribution networks. • A categorisation of building electrical system disturbances by impact level and frequency. • A methodology to assess electrical resilience for each category of disturbance. • A Comprehensive assessment of electrical resilience, covering structural robustness, service continuity, and supply quality. • A case study application integrating critical loads, a backup system, and smart metering. [ABSTRACT FROM AUTHOR]

This paper presents and discusses results from a field test that uses model predictive control (MPC) to optimise the operation of a multi-source heat pump-based energy system for space heating and hot water provision in a building. The objective of the optimisation is to minimise the electricity consumption of the heat pump using flexibility from the heat sources, the space heating and domestic hot water tanks while ensuring end-user comfort and system constraints. The field test was performed in the context of the RES4BUILD project. The integrated system consists of photovoltaic-thermal (PVT) collectors, an advanced vapour-compression multi-source heat pump and water buffer tanks for space heating and hot water needs. The heat pump utilises a solar buffer, a borehole thermal energy storage (BTES) and air as heat sources. The solar buffer is supplied with heat from the PVT collectors. The optimal operation of the system is obtained by monitoring and controlling the interactions between the different system components using MPC, taking into account the weather and heat load forecasts. Results have shown that MPC has a potential and added value for the optimal operation of multi-source heat pumps in real-life while considering system constraints and user behaviour to ensure thermal comfort. However, significant effort and expert knowledge are needed to develop the sufficiently accurate system models required by this control approach. The outcomes and conclusions of this work are therefore a basis for further development of such control approaches to improve their replicability and feasibility on a large scale, considering the diverse nature of energy system components in buildings. [ABSTRACT FROM AUTHOR]

[Display omitted] • nZEBs in Eastern Europe lack carbon neutrality metrics and targets. • Performance requirements for nZEBs in Eastern Europe are presented. • Eastern Europe needs strategy and local governance for nZEB market penetration. • EPCs require major reform, and effective monitoring of nZEB performance is needed. • The cost-optimality calculation method must be adopted to ensure cost-effective market uptake. The European Unions' ambition for the construction sector is to be carbon neutral by 2030 for new construction. Since 2021, all new buildings in the EU should have been constructed as nearly zero-energy buildings (nZEB). However, Eastern European countries struggle to implement the 2018 Energy Performance of Building Directive recast requirements. Next to the economic challenges, equally essential factors hinder renovating the existing residential building stock and adding newly constructed high-performance buildings sourced primarily from renewable energy sources. Therefore, this study provides a cross-study to identify the barriers to nZEB implementation in ten Eastern European countries, including Bulgaria, Croatia, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, and Slovakia. The study was conducted between 2019 and 2021 and provides an overview of prospects for nZEB in Eastern Europe. The study examines the challenges of nZEB plans faced in those countries and provides constructive recommendations. The regulations and definitions regarding nZEB energy performance, cooling and heating energy demand, thermal comfort, onsite renewables, and construction quality were analyzed. Results show that most Eastern European countries are unprepared to comply with the EPBD guidelines and cost-optimality approach. The paper ranks each country and recommends specific measures to refine the nZEB definitions. The paper provides a thorough comparative assessment and benchmarking of select EU geography that can help shift the identified gaps into opportunities for the future development of climate-neutral high-performance buildings. [ABSTRACT FROM AUTHOR]

[Display omitted] • Implementation of a Hardware-Based BB-BC Optimized Controller with Fractional-Order for a HVAC System. • An FPGA implementation of a fractional order proportional-integral-derivative controller for an HVAC system. • Adoption of the BB-BC algorithm for optimal tuning of the controller parameters. • Use of a second-order plus time delay model to represent the HVAC system. • Illustration of the effective tracking and rejection of disturbance signals by the FOPID controller based on the BB-BC algorithm. • High-performance pipelined implementation of the BB-BC algorithm and FOPID controller on a Xilinx FPGA device. Industrial and commercial buildings are significant energy consumers, worldwide, emphasizing the need for effective control techniques to reduce power consumption. This paper presents an FPGA implementation of a fractional order proportional-integral-derivative (FOPID) controller for a Heating, Ventilation and Air Conditioning (HVAC) system. The FOPID model enhanced improved dynamic performance and system robustness compared to classical PID controllers. However, tuning the FOPID controller is challenging due to the need to adjust several parameters, i.e., the proportional, integral, and derivative gains of the PID model, as well as the fractional differential and integral orders. To address this, the Big Bang-Big Crunch (BB-BC) evolutionary algorithm is adopted to tune the controller parameters optimally. The BB-BC algorithm is executed to minimize six different performance indices. The HVAC system is represented by a second-order plus time delay (SOPTD) model, yielding six different cases are obtained by combining three delay values and two gain values. A high-performance pipelined implementation of the BB-BC algorithm andthe FOPID controller is designed and realized on a Xilinx FPGA device. The implementation has successfully reduced the oscillations of the HVAC output signal by employing auto-tuning of control parameters based on BB-BC, while improved results have been also achieved in terms of rapid convergence. Additionally, a substantial reduction of 80 % in the output control signal and 73 % in error has been observed when using a window size (L) of L = 256, in comparison to L = 32. The simulation results demonstrate the highly efficient performance of the FOPID-BB-BC control unit after optimal tuning. [ABSTRACT FROM AUTHOR]

[Display omitted] • Real-time identification of occupancy and window opening using AI-powered cameras. • Occupant-centric control strategy for better thermal comfort, energy efficiency and air quality. • The heating energy consumption was reduced by between 0.6 % and 29.0 %. • The level of indoor thermal comfort increased by up to 58.8 %. • Indoor CO 2 concentrations below 1000 ppm for 89.2 % of the time being occupied. Recently, Occupant-Centric Control (OCC) strategies have gained mounting interest. Previous studies made use of OCC strategies for adjusting the operation of heating/cooling systems, improving indoor thermal comfort and governing mechanical ventilation systems. However, a very limited number of studies have applied OCC strategies to natural ventilation systems. Further, the feasibility of establishing OCC strategies for controlling indoor thermal comfort, energy use and specifically air quality has received much less attention and investigation. This paper presented an Occupant-Centric Heating and Natural Ventilation Control (OCHNVC) strategy for enhancing indoor thermal comfort, building energy performance and indoor air quality. Firstly, real-time profiles of occupant behavior and window opening in a case study building were collected using artificial intelligence (AI)-powered cameras and deep vision algorithms. Secondly, shallow artificial-neural-networks predictive models were established for forecasting the responses of the studied building to different levels of occupant behavior and window opening behavior. Thirdly, an OCHNVC strategy tailored to the studied room was proposed and applied to the studied room. The strategy could lower heating energy consumption by between 0.6 % and 29.0 % and improve the level of indoor thermal comfort by between 0 % and 58.8 %, relative to a conventional control strategy. Moreover, the conventional window control strategy only maintained indoor CO 2 concentrations below 1000 ppm for 59.7 % of the period that occupants were within the studied room, while the proposed controller could do so for 89.2 % of the period. Future works shall focus on experimentally deploying the strategy to real buildings and evaluating its performance. [ABSTRACT FROM AUTHOR]

• This paper conducts assessment of hybrid renewable systems for urban buildings. • A new demand model for heterogeneous building types is developed. • Time series forecast of electricity market is proposed. • Novel renewable supply and balance scenarios are developed. • Techno-economic assessment of hybrid renewable systems shows feasibility. This research conducts a technical and economic feasibility study of multi-energy hybrid systems (MEHS) combining different renewables for a northern climate city of Finland to address issues of replacing fossil energy by renewable energy sources (RES) to achieve zero carbon emissions. The renewable energy systems MEHS include geothermal, biomass and solar energy. The selected city-study site is the Olympic Training Center occupied by heterogeneous buildings which presents a good representative urban city for the assessment of the energy supply and demand. A generic and integrated modeling framework grounded in a combination of novel forecasting models for the heterogeneous building energy demands, the splitting of space heating and hot water use, the coupled renewable energy generation, and the time series electricity market is developed to investigate optimal MEHS configurations based on the technical and financial analysis. Innovative scenarios of MEHS are developed. The analysis results show that MEHS can flexibly meet the energy demand for the heterogeneous buildings and the optimal configurations can be realised by an innovative integration of geothermal and solar sources as well as electricity as complementary energy. Model uncertainty and its impacts on the analysis are also considered and discussed. [ABSTRACT FROM AUTHOR]

[Display omitted] • The motivations to implement pre-cooling are discussed. • Recent pre-cooling and solar pre-cooling studies are reviewed. • Pre-cooling simulation methods are briefly introduced. • Method, aims, and findings of each study are summarized. • Current gaps in the field are identified and future works are suggested. Ever increasing numbers of air-conditioners and, in many places, more extreme weather and urban overheating are placing additional stresses on electricity networks globally, reflecting not only their high power draw but also highly correlated operation driven by weather conditions. The resulting peak demands can be considerably greater than average network flows requiring additional electricity generation and network capabilities for what might only be infrequent periods. Energy users must of course pay for this additional investment, including potentially via peak demand and time-of-use charges. Pre-cooling of buildings to spread air conditioning demand is one approach to reduce these peaks. Its potential contribution depends on the thermal performance of the building stock, particularly how long it can retain pre-cooled air, and patterns of weather on warm days. The use of solar energy, including particularly rooftop solar photovoltaics presents another possible option. Photovoltaics generates during daylight hours, which is well-matched with higher temperatures. However, photovoltaics generation may often be declining while heat loads in buildings and hence air conditioning are still climbing in the late afternoon. This suggests the potential of solar pre-cooling when solar photovoltaic electricity is used to run air conditioners in the pre-cooling phase. Literature reviews to date have tended to focus on only aspects of pre-cooling and solar pre-cooling, for example, the effect of thermal mass on the energy performance of buildings but not specifically on peak demand shifting and cost reduction. There is a particular gap with review papers that investigate pre-cooling and solar pre-cooling together with detailed characterization of their potential in different circumstances. The review presented here covers a wide range of state-of-the-art studies in the field of pre-cooling and solar pre-cooling covering the period 2014 to 2021. It also presents, for the first time, the necessary steps to design and implement pre-cooling and solar pre-cooling strategies. It is intended to support the growing research studies and practical implementations of pre-cooling and solar pre-cooling within the electricity sector. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) strategies can be applied to the coordination of energy hubs to reduce their energy consumption. Despite the effectiveness of these techniques, their potential for energy savings are potentially underutilized due to the fact that energy demands are often assumed to be fixed quantities rather than controlled dynamic variables. The joint optimization of energy hubs and buildings' energy management systems can result in higher energy savings. This paper investigates how different MPC strategies perform on energy management systems in buildings and energy hubs. We first discuss two MPC approaches; centralized and decentralized. While the centralized control strategy offers optimal performance, its implementation is computationally prohibitive and raises privacy concerns. On the other hand, the decentralized control approach, which offers ease of implementation, displays significantly lower performance. We propose a third strategy, distributed control based on dual decomposition, which has the advantages of both approaches. Numerical case studies and comparisons demonstrate that the performance of distributed control is close to the performance of the centralized case, while maintaining a significantly lower computational burden, especially in large-scale scenarios with many agents. Finally, we validate and verify the reliability of the proposed method through an experiment on a full-scale energy hub system in the NEST demonstrator in Dübendorf, Switzerland. [ABSTRACT FROM AUTHOR]