Intelligent Digital Solutions for High-Performance and Low-Carbon Building Operations
A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".
Deadline for manuscript submissions: closed (11 March 2024) | Viewed by 260
Special Issue Editors
Interests: intelligent algorithms; model predictive control; machine learning; demand-flexible energy management; data-driven approaches and their applications in smart energy systems; building energy systems; renewables; thermal & electric energy storage; electric vehicle for higher energy efficiency and reduced environment impacts
Special Issues, Collections and Topics in MDPI journals
Interests: industrial ecology; low carbon city development; circular economy; life cycle assessment; climate change mitigation
Interests: modeling; ML; algorithm; HW design; HVAC
Interests: fast simulation of the indoor environment; coupled simulation of building systems and indoor environment; simulation-based optimization; model predictive control; learning-based optimal control
Interests: machine learning; building simulation; building energy management; optimal control; smart building
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the evolving realm of building operations, a prominent transition is underway towards high-performance and low-carbon solutions, with digital technologies steering this paradigm shift. This Special Issue seeks to delve into the transformative power of intelligent digital solutions in revolutionizing building operations, emphasizing both efficiency and environmental sustainability. As global climate change and energy conservation concerns mount, harnessing the power of digital intelligence to implement high-performance, low-carbon operational strategies becomes increasingly imperative. Such intelligent operations not only enhance building performance but also transform buildings into demand-side resources and smart infrastructures to advance smart grids, smart cities, electric vehicles, and renewable energy systems. This Special Issue invites studies exploring intelligent digital solutions, including intelligent control, data-driven techniques, machine learning, optimization algorithms, predictive analytics, etc., for pioneering new trajectories in building operations ranging from individual buildings to regional scales. Additionally, we also welcome studies that demonstrate how these digitally augmented buildings can be integrated with smart grids, electric vehicles, and distributed energy resources and create synergistic benefits.
Dr. Shiyu Yang
Prof. Dr. Lu Sun
Dr. Dafang Zhao
Dr. Xu Han
Dr. Sicheng Zhan
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- intelligent building control
- data-driven modelling and control
- predictive building analytics
- digital twin
- design optimization
- low-carbon buildings
- grid-interactive buildings
- building energy management
- regional energy system optimization
