Ensuring Comfort in Office Buildings: Designing a KNX Monitoring and Control System

The prediction of thermal comfort in smart buildings is addressed in this article to support the energy manager in the management of the heating, ventilation, and air conditioning systems. An efficient control is fundamental to meet the user satisfaction as well as the energy cost reduction. The proposed method based on a customized support vector regression technique predicts and suggests to the energy managers the indoor target temperature required to obtain the desired comfort throughout the building. A network of low‐cost wireless sensors has been deployed to measure the indoor conditions of a real indoor scenario. The prediction performance has been experimentally validated and the obtained results have pointed out a temperature prediction error lower than 1°C and the achievement of the thermal comfort requirements.

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“…The PMV is computed starting from the available parameters

{\underset{false¯}{p}}_{n}, n = 1, \dots, N

, measured by the WSN nodes and according to the guidelines of the ISO 7730 standard given in ref. .…”

Section: Mathematical Formulationmentioning

confidence: 99%

A forecasting strategy based on wireless sensing for thermal comfort optimization in smart buildings

Viani

Polo

2017

Micro & Optical Tech Letters

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“…and how each of them could be analyzed. This system have discussed thermal comfort [2].Pellegrino, A. et al, This system have focused on some results that are aimed at being developing an event-driven user-centric middleware. This system have monitored and managed the energy consumption in already existing public building.…”

Section: Related Workmentioning

confidence: 99%

Design and Implementation of Smart Office Automation System

Bhuyar¹,

Ansari²

2016

IJCA

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Automation plays very important role in our lives. It makes the work easier and simpler so for simplified and easy living, Smart office automation system is designed in this system. This system is based on subsystems like lighting, heating. Security and alarming systems are also present. The sensors are used to extract the real time data from environment. Sensors are connected to the ARM 11 Controller. It processes the data and gives the output. Fan, bulb, buzzer are output devices connected to the controller which will work when the system crosses the threshold value. The sensor's data is continuously recorded. Fingerprint Identification module is used for security purpose. Fire alarm and emergency call is given to the service room. This data is stored in PC. This data can be viewed on other PC's through Network switch. The data can be seen on the webpage and on GUI. KeywordsOffice automation system, Security and alarming systems, emergency call.

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“…Moreover, the BEMS has to calculate the power (for ) necessary to obtain the requested temperature (for ). It is noted that the temperature is the set point chosen by the building manager on the basis of the standard thermal comfort indices, according to the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) standard thermal sensation scale [34], [35]. Moreover, can be greater than in order to compensate the time slots in which the power is insufficient to satisfy the condition , by exploiting the thermal gradient.…”

Section: B Bems Optimization Problem Formulationmentioning

confidence: 99%

“…In particular, the PMV predicts the thermal sensation for the human body on the basis of indoor temperature, mean radiant temperature, air velocity, and air humidity, while the PPD provides information on the thermal discomfort or dissatisfaction [35]. Typical values of PMV and PPD are PMV and PPD 10 [36], respectively.…”

Section: B Bems Optimization Problem Formulationmentioning

confidence: 99%

A District Energy Management Based on Thermal Comfort Satisfaction and Real-Time Power Balancing

Fanti

Mangini

Roccotelli

et al. 2015

IEEE Trans. Automat. Sci. Eng.

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This paper presents a district energy management strategy devoted to monitor and control the district power consumption in a twofold human-centered perspective: the respect of user’s comfort preferences and the minimization of the power consumption and costs. The presented district energy management system forwards the power profile determined the day ahead to each building energy management system that, in turn, minimizes its real-time power consumption and costs (based on rewards and penalties), respecting the comfort preferences. Successively, the power is redistributed among the district buildings in order to minimize the penalties by applying two approaches: a centralized approach for public buildings and a distributed methodology for private buildings. Such optimization problems are formalized by defining some linear programming problems: two case studies are solved to show the applicability of the proposed management strategies

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Ensuring Comfort in Office Buildings: Designing a KNX Monitoring and Control System

Cited by 30 publications

References 4 publications

A forecasting strategy based on wireless sensing for thermal comfort optimization in smart buildings

A forecasting strategy based on wireless sensing for thermal comfort optimization in smart buildings

Design and Implementation of Smart Office Automation System

A District Energy Management Based on Thermal Comfort Satisfaction and Real-Time Power Balancing

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