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The distributed energy system (DES) represents an innovative approach to energy generation and distribution that promotes decentralization and diversification of energy sources. DESs can offer numerous benefits, including increased resiliency, reduced transmission losses, improved efficiency, and lower carbon emissions. The optimal design of a DES requires careful consideration of various factors such as geographical location, climate conditions, and energy demand patterns. This paper utilizes a multi-objective genetic algorithm to optimize the combination of technologies and their corresponding sizes in a distributed energy system for three types of commercial buildings—hospitals, large offices, and large hotels across eight different climate zones in the U.S. A range of technologies are considered for integration into the DES. These technologies include photovoltaic systems, wind turbines, combined heat and power systems, solar thermal collectors, and electrical and thermal energy storage. The two objectives considered are maximizing the reduction in carbon dioxide emissions and minimizing the life cycle costs for the DES. The purpose of this study is to optimize and evaluate the multi-objective design of distributed energy systems aimed at decentralizing and diversifying energy sources. The analysis of optimized DES designs across all 24 case scenarios shows that a balance between cost saving and emission reduction has been achieved. Although this study primarily focuses on specific buildings and climate zones, the methods and findings can be adapted for a wider variety of building types across different geographical locations, thus paving the way for more widespread adoption of optimized distributed energy systems. [ABSTRACT FROM AUTHOR]

Buildings use up to 40% of the global primary energy and 30% of global greenhouse gas emissions, which may significantly impact climate change. Heating, ventilation, and air-conditioning (HVAC) systems are among the most significant contributors to global primary energy consumption and carbon gas emissions. Furthermore, HVAC energy demand is expected to rise in the future. Therefore, advancements in HVAC systems' performance and design would be critical for mitigating worldwide energy and environmental concerns. To make such advancements, energy modeling and model predictive control (MPC) play an imperative role in designing and operating HVAC systems effectively. Building energy simulations and analysis techniques effectively implement HVAC control schemes in the building system design and operation phases, and thus provide quantitative insights into the behaviors of the HVAC energy flow for architects and engineers. Extensive research and advanced HVAC modeling/control techniques have emerged to provide better solutions in response to the issues. This study reviews building energy modeling techniques and state-of-the-art updates of MPC in HVAC applications based on the most recent research articles (e.g., from MDPI's and Elsevier's databases). For the review process, the investigation of relevant keywords and context-based collected data is first carried out to overview their frequency and distribution comprehensively. Then, this review study narrows the topic selection and search scopes to focus on relevant research papers and extract relevant information and outcomes. Finally, a systematic review approach is adopted based on the collected review and research papers to overview the advancements in building system modeling and MPC technologies. This study reveals that advanced building energy modeling is crucial in implementing the MPC-based control and operation design to reduce building energy consumption and cost. This paper presents the details of major modeling techniques, including white-box, grey-box, and black-box modeling approaches. This paper also provides future insights into the advanced HVAC control and operation design for researchers in relevant research and practical fields. [ABSTRACT FROM AUTHOR]

The building sector is one of the largest contributors to the world's total energy use and greenhouse gas emissions. Advancements in building energy technologies have played a critical role in enhancing the energy sustainability of the built environment. Extensive research and new techniques in energy and environmental systems for buildings have recently emerged to address the global challenges. This study reviews existing articles in the literature, mostly since 2000, to explore technological advancement in building energy and environmental systems that can be applied to smart homes and buildings. This review study focuses on an overview of the design and implementation of energy-related smart building technologies, including energy management systems, renewable energy applications, and current advanced smart technologies for optimal function and energy-efficient performance. To review the advancement in building energy-related technologies, a systematic review process is adopted based on available published reviews and research types of articles. Review-type articles are first assessed to explore the current literature on the relevant keywords and to capture major research scopes. Research-type papers are then examined to investigate associated keywords and work scopes, including objectives, focuses, limitations, and future needs. Throughout the comprehensive literature review, this study identifies various techniques of smart home/building applications that have provided detailed solutions or guidelines in different applications to enhance the quality of people's daily activities and the sustainability of the built environmental system. This paper shows trends in human activities and technology advancements in digital solutions with energy management systems and practical designs. Understanding the overall energy flow between a building and its environmentally connected systems is also important for future buildings and community levels. This paper assists in understanding the pathway toward future smart homes/buildings and their technologies for researchers in related research fields. [ABSTRACT FROM AUTHOR]

In this paper, we present a performance-based approach to building configuration design to improve the urban ventilation potential at the conceptual design stage, and we demonstrate its application through a case study. The target performance optimized was the ventilation potential of a district, including a region of interest at a spatial scale of hundreds of meters. To estimate this performance, we used computational fluid dynamics (CFD), coupled with an evolutionary algorithm, to optimize the design alternatives to produce the building configuration most suitable for a given set of site conditions. Three calculation components must be assembled for a CFD-based design optimization: an optimizer, a geometry/mesh generator, and a CFD solver. To provide links between the calculation components, we utilized an in-house parametric design program. A case study was conducted to test the applicability of the proposed design method to identify the optimal solutions that minimize adverse effects on the ventilation potential of the surrounding area. For a configuration of buildings in a dense urban area, the proposed design method successfully improved the design alternatives. The results show that the urban ventilation potential in the case of the optimized building configuration is 16% greater than that of the initial building configuration. [ABSTRACT FROM AUTHOR]