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1. ENENGY MANAGEMENT OF SMART COMMUNITY WITH EV CHARGING USING DISTRIBUTED MODEL PREDICTIVE CONTROL

   Fenglin Zhou, Yaoyu Li (October 2018, Proceedings of ASME 2018 Dynamic Systems and Control Conference)

   Human activities in buildings are connected by various transportation measures. For the emerging Smart and Connected Communities (S&CC), it is possible to synergize the energy management of smart buildings with the vehicle operation/travel information available from transportation infrastructure, e.g. the intelligent transportation systems (ITS). Such information enables the prediction of upcoming building occupancy and upcoming charging load of electrified vehicles. This paper presents a predictive energy management strategy for smart community with a distributed model predictive control framework, in which the upcoming building occupancy and charging load are assumed to be predictable to certain extent based on the ITS information. An illustrative example of smart community is used for simulation study based on a Modelica simulation model, in which a chilled-water plant sustains the ventilation and air conditioning of three buildings, and each building is assumed to host a number of charging stations. Simulation study is performed to validate the proposed strategy. 

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2. A Global Building Occupant Behavior Database

   https://doi.org/10.1038/s41597-022-01475-3  

   Dong, Bing; Liu, Yapan; Mu, Wei; Jiang, Zixin; Pandey, Pratik; Hong, Tianzhen; Olesen, Bjarne; Lawrence, Thomas; O’Neil, Zheng; Andrews, Clinton; et al (December 2022, Scientific Data)

   Abstract This paper introduces a database of 34 field-measured building occupant behavior datasets collected from 15 countries and 39 institutions across 10 climatic zones covering various building types in both commercial and residential sectors. This is a comprehensive global database about building occupant behavior. The database includes occupancy patterns (i.e., presence and people count) and occupant behaviors (i.e., interactions with devices, equipment, and technical systems in buildings). Brick schema models were developed to represent sensor and room metadata information. The database is publicly available, and a website was created for the public to access, query, and download specific datasets or the whole database interactively. The database can help to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems (e.g., light switching, set-point changes on thermostats, fans on/off, etc.) and envelopes (e.g., window opening/closing). With these more realistic inputs of occupants’ schedules and their interactions with buildings and systems, building designers, energy modelers, and consultants can improve the accuracy of building energy simulation and building load forecasting. 

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3. Demand response through ventilation and latent load adjustment for commercial buildings in humid climate zones

   https://doi.org/10.1016/j.apenergy.2024.123940  

   Ma, Zhihao; Cui, Shuang; Chen, Jianli (November 2024, Applied Energy)

   Space cooling constitutes >10% of worldwide electricity consumption and is anticipated to rise swiftly due to intensified heatwaves under emerging climate change. The escalating electricity demand for cooling services will challenge already stressed power grids, especially during peak times of demand. To address this, the adoption of demand response to adjust building energy use on the end-user side becomes increasingly important to adapt future smart buildings with rapidly growing renewable energy sources. However, existing demand response strategies predominantly explore sensible cooling energy as flexible building load while neglecting latent cooling energy, which constitutes significant portions of total energy use of buildings in humid climates. Hence, this paper aims to evaluate the demand response potential by adjusting latent cooling energy through ventilation control for typical medium commercial office buildings in four representative cities across different humid climate zones, i.e., Miami, Huston, Atlanta, and New York in the United States (US). As the first step, the sensible heat ratio, defined as sensible cooling load to total building load (involving both sensible and latent load), in different humid climates are calculated. Subsequently, the strategy to adjust building latent load through ventilation control (LLVC) is explored and implemented for demand response considering the balance of energy shifting, indoor air quality, and energy cost. Results reveal that adjusting building ventilation is capable of achieving 30%–40% Heating, Ventilation, and Air-conditioning (HVAC) cooling demand flexibility during HVAC operation while among this, the latent cooling energy contributes 56% ~ 66.4% to the overall demand flexibility. This work provides a feasible way to improve electricity grid flexibility in humid climates, emphasizing the significant role of adjusting latent cooling energy in building demand response. 

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4. Modelling, Simulation and Control of Smart and Connected Communities

   Li, Zhaoxuan; Pipri, Ankur; Dong, Bing; Gatsis, Nikolaos; Taha, Ahmad; Yu, Nanpeng (August 2017, Building Simulation 2017)

   This study attempts to establish the need for a framework to assess the impact of connected buildings in a smart community. The contribution is a software framework designed to optimize buildings and grids at a district level. The following research products are developed: (1) An innovative method to model a cluster of buildings—with people’s behavior embedded in the cluster’s dynamics—and their controls so that they can be integrated with grid operation and services; (2) a novel optimization framework to solve complex, centralized control problems for large-scale systems, leveraging convex programming approaches; and (3) a methodology to assess the impacts of connected buildings in terms of (a) the grid’s operational stability and safety and (b) buildings’ optimized energy consumption. To test the proposed framework, a large-scale simulation of a subtransmission network with three power generating stations and serving over 300 artificial buildings is conducted. 

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5. Doppler Radar Occupancy Sensing and Monitoring for Smart Buildings

   https://doi.org/10.1109/TELSIKS57806.2023.10316022  

   Boric-Lubecke, Olga; Lubecke, Victor M; Setthapittayakul, Wannasa; Wen, Jin; Hoque, Simi; Girotto, Sara (October 2023, IEEE)

   Smart buildings promise to adapt environmental conditions to the needs of occupants based on statistical analytics applied to various monitored data. While sensors for accurate monitoring of building parameters such as temperature, lighting, and air-quality abound, currently available occupancy sensors are limited to sensing of presence only, with limited accuracy. Doppler radar sensors have shown great promise for unobtrusive recognition and monitoring of occupant presence, count, activity, and cardiopulmonary vital signs. With such measures, a smart building can optimize operations not only for the most efficient use of energy and space, but also to create healthy and sustainable environments that support occupant wellness, comfort, and productivity. This paper presents an overview of Doppler radar occupancy sensors for smart building applications. 

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