A novel energy saving system for office lighting control by using RBFNN and PSO

Si, Wa; Ogai, Harutoshi; Li, Tansheng; Hirai, Katsumi

doi:10.1109/tenconspring.2013.6584469

Cited by 9 publications

(3 citation statements)

References 3 publications

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“…The most frequent category is the data-driven models [121,144,[161][162][163][164][165][166][167][168][169][170]148,[171][172][173][174][175][176][177][178][179][180]149,[181][182][183][184][185][186][187][188][189][190]152,[191][192][193][194][155][156][157][158]160], followed by the stochastic OPA modeling methods [153,159,[195][196][197][198][199]…”

Section: Lighting Operationunclassified

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Modeling occupant behavior in buildings

Carlucci

Simone

Firth

et al. 2020

Building and Environment

153

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In the last four decades several methods have been used to model occupants' presence and actions (OPA) in buildings according to different purposes, available computational power, and technical solutions. This study reviews approaches, methods and key findings related to OPA modeling in buildings. An extensive database of related research documents is systematically constructed, and, using bibliometric analysis techniques, the scientific production and landscape are described. The initial literature screening identified more than 750 studies, out of which 278 publications were selected. They provide an overarching view of the development of OPA modeling methods. The research field has evolved from longitudinal collaborative efforts since the late 1970s and, so far, covers diverse building typologies mostly concentrated in a few climate zones. The modeling approaches in the selected literature are grouped into three categories (rule-based models, stochastic OPA modeling, and data-driven methods) for modeling occupancy-related target functions and a set of occupants' actions (window, solar shading, electric lighting, thermostat adjustment, clothing adjustment and appliance use). The explanatory modeling is conventionally based on the model-based paradigm where occupant behavior is assumed to be stochastic, while the Revised Manuscript with No Changes MarkedClick here to view linked References data-driven paradigm has found wide applications for the predictive modeling of OPA, applicable to control systems. The lack of established standard evaluation protocols was identified as a scientifically important yet rarely addressed research question. In addition, machine learning and deep learning are emerging in recent years as promising methods to address OPA modeling in real-world applications.

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Section: Lighting Operationunclassified

“…MSE [155][156][157]161,163,168,193,208]; RMSE [121,152,166,183,184,208,210,211]; statistical parameters such as standard deviation, kurtosis, and skewness [165,167,197,209].…”

Section: Lighting Operationmentioning

confidence: 99%

Modeling occupant behavior in buildings

Carlucci

Simone

Firth

et al. 2020

Building and Environment

153

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“…At the same time, the control commands received from the WSN by the monitoring device for energy saving, transfers to the relevant control units of the energy consumption system or equipment inside the building by RS232 interface. The energy consumption system or equipment should have unified interface used to receive commands, and make relevant control movements on the basis of the control commands [4,5]. Fig.…”

Section: The Construction Of the Interaction And Monitoring System Fo...mentioning

confidence: 99%

The Interaction and Monitoring System for Energy Saving in Building

Zhong

Chen

Wang

et al. 2012

AMM

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The continuous advance of the policy about ‘Energy saving and emission reduction’, along with the continuous development of information technology, control technology, which bring profitable conditions for the monitoring and control over the building (here mainly refers to the large building of government, commercial or industrial user). In particular, a interaction and monitoring system is proposed, which is used to monitor the parameters about energy consumption of energy consumption system or equipment inside the building, in addition the information about the running of the energy consumption system or equipment. At the same time, the relevant units of the energy consumption system or equipment is controlled by the interaction and monitoring system. The interaction and monitoring system for energy saving in building consists of the node for energy saving and monitoring, wireless sensor network (hereinafter referred to as WSN), the platform for energy saving and monitoring, making up the three-layer structure of the interaction and monitoring system inside the building. The node for energy saving and monitoring is a wireless sensor actually, which plays the role as collecting data and controlling. Along with the other nodes for energy saving and monitoring, as well as the nodes acting as repeater, router, coordinator, all nodes inside the building compose the WSN. The node acting as the repeater is of great significance for the transmission of data, especially when some nodes for energy saving and monitoring is located in underground building and some other places where the signal of WSN is blocked, as well as the places far away from the neighbor nodes of WSN. The coordinator is located on the platform for energy saving and monitoring, meanwhile the function of gateway is integrated in the node acting as the coordinator. This node converge the data of the WSN, and transfers the data to the server of the platform for energy saving and monitoring.

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