Advanced controls on energy reliability, flexibility and occupant-centric control for smart and energy-efficient buildings

Liu, Zhengxuan; Zhang, Xiang; Sun, Ying; Zhou, Yuekuan

doi:10.1016/j.enbuild.2023.113436

Cited by 42 publications

(6 citation statements)

References 176 publications

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“…Although the technologies require high upfront costs, they offer long-term energy conservation potential and require minimal ongoing consumer effort. Nonetheless, widespread adoption in household use has proven challenging due to higher upfront costs, privacy/autonomy concerns, and technical barriers commonly associated with the efficiency of smart technology [33].…”

Section: Human-technology Interaction At the Household Level And Its ...mentioning

confidence: 99%

Sustainable Smart City Technologies and Their Impact on Users’ Energy Consumption Behaviour

Ramli,

Azizi,

Thurairajah

2024

Energies

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Sustainable smart cities (SSCs) target decarbonisation by optimising energy consumption through the emerging capabilities of technology. Nevertheless, the energy consumption behaviour of end users has the potential to compromise the effectiveness of technological interventions, reflecting the importance of active social engagement in realising decarbonisation goals. Although extensive research exists on energy consumption behaviour, little is known about how technology engagement affects it, the nature of these technologies, and their role in SSC. The paper aims to identify, categorise, and investigate the smart technologies that impact household energy consumption behaviours and their integration into the larger SSC system. Following a systematic review of 60 articles from the Scopus database (2013–2023), the study found 45 smart technologies cited, with 49% affecting efficiency behaviour and 51% affecting curtailment behaviour. While these technologies inform the city administration level in the SSC framework, the role of end users remains unclear, suggesting a technocratic approach. The study proposes the Sustainable Smart City Network to facilitate a grassroots approach, identifying five key domains: government policies, smart technology adoption, smart technology engagement, smart city infrastructure, and urban sustainability. The study provides an original contribution to knowledge by unveiling the key technologies affecting energy consumption behaviour and outlining the pragmatic requirements for achieving decarbonisation through a grassroots approach.

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Section: Human-technology Interaction At the Household Level And Its ...mentioning

confidence: 99%

Sustainable Smart City Technologies and Their Impact on Users’ Energy Consumption Behaviour

Ramli,

Azizi,

Thurairajah

2024

Energies

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“…The pursuit of nZEBs, ZEBs, and PEBs is a complex and multi-faceted endeavor, requiring the resolution of a multitude of technical, financial, behavioral challenges, consistent implementation, monitoring and verification, and interdisciplinary challenges as presented, for example, in [64,89,[130][131][132]. The realization of nZEBs, ZEBs, and PEBs necessitate a comprehensive understanding of these challenges and the development of effective strategies to overcome them.…”

Section: Boundary 3: Individual Buildingsmentioning

confidence: 99%

Challenges and Strategies for Achieving High Energy Efficiency in Building Districts

Chen,

Vand,

Baldi

2024

Buildings

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Achieving climate neutrality requires reducing energy consumption and CO2 emissions in the building sector, which has prompted increasing attention towards nearly zero energy, zero energy, and positive energy communities of buildings; there is a need to determine how individual buildings up to communities of buildings can become more energy efficient. This study addresses the scientific problem of optimizing energy efficiency strategies in building areas and identifies gaps in existing theories related to passive design strategies, active energy systems, and renewable energy integration. This study delineates boundaries at the building and community scales to examine the challenges of attaining energy efficiency goals and to emphasize the intricate processes of selecting, integrating, and optimizing energy systems in buildings. The four boundaries describe: (B1) energy flows through the building envelope; (B2) energy flows through heating, ventilation, air conditioning and energy systems; (B3) energy flows through individual buildings; (B4) energy flows through a community of buildings. Current theories often treat these elements in isolation, and significant gaps exist in interdisciplinary integration, scalable frameworks, and the consideration of behavioral and socioeconomic factors. Achieving nearly zero energy, zero energy, and positive energy communities requires seamless integration of renewable energy sources, energy storage systems, and energy management systems. The proposed boundaries B1–B4 can help not only in analyzing the various challenges for achieving high energy efficiency in building communities but also in defining and evaluating these communities and establishing fair methods for energy distribution within them. The results demonstrate that these boundaries provide a comprehensive framework for energy-efficient designs, constructions, and operational practices across multiple buildings, ensuring equitable energy distribution and optimized performance. In addition, the definition of boundaries as B1-B4 contributes to providing an interface for energy-efficient designs, constructions and operational practices across multiple buildings.

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“…These instruments and methods are crucial in conducting a thorough analysis and accurately predicting a building's energy performance. This involves understanding how a building consumes energy under different conditions and identifying opportunities for energy conservation and efficiency improvements [4,5]. The imperative to reduce energy consumption within the building sector intensifies as the global community shifts toward a sustainable, low-carbon energy framework [6].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Advanced Energy Performance Modelling: Case Study of an Engineering and Technology Precinct

Tahmasebinia,

Lin,

et al. 2024

Buildings

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The global demand for energy is significantly impacted by the consumption patterns within the building sector. As such, the importance of energy simulation and prediction is growing exponentially. This research leverages Building Information Modelling (BIM) methodologies, creating a synergy between traditional software methods and algorithm-driven approaches for comprehensive energy analysis. The study also proposes a method for monitoring select energy management factors, a step that could potentially pave the way for the integration of digital twins in energy management systems. The research is grounded in a case study of a newly constructed educational building in New South Wales, Australia. The digital physical model of the building was created using Autodesk Revit, a conventional software for BIM methodology. EnergyPlus, facilitated by OpenStudio, was employed for the traditional software-based energy analysis. The energy analysis output was then used to develop preliminary algorithm models using regression strategies in Python. In this regression analysis, the temperature and relative humidity of each energy unit were used as independent variables, with their energy consumption being the dependent variable. The sigmoid algorithm model, known for its accuracy and interpretability, was employed for advanced energy simulation. This was combined with sensor data for real-time energy prediction. A basic digital twin (DT) example was created to simulate the dynamic control of air conditioning and lighting, showcasing the adaptability and effectiveness of the system. The study also explores the potential of machine learning, specifically reinforcement learning, in optimizing energy management in response to environmental changes and usage conditions. Despite the current limitations, the study identifies potential future research directions. These include enhancing model accuracy and developing complex algorithms to boost energy efficiency and reduce costs.

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Advanced controls on energy reliability, flexibility and occupant-centric control for smart and energy-efficient buildings

Cited by 42 publications

References 176 publications

Sustainable Smart City Technologies and Their Impact on Users’ Energy Consumption Behaviour

Sustainable Smart City Technologies and Their Impact on Users’ Energy Consumption Behaviour

Challenges and Strategies for Achieving High Energy Efficiency in Building Districts

Advanced Energy Performance Modelling: Case Study of an Engineering and Technology Precinct

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