Building Energy Management Systems: The Age of Intelligent and Adaptive Buildings

Manic, Milos; Wijayasekara, Dumidu; Amarasinghe, Kasun; Rodríguez-Andina, Juan J.

doi:10.1109/mie.2015.2513749

Cited by 195 publications

(88 citation statements)

References 55 publications

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“…In [4,5], the authors discussed the necessities of using computational intelligence in the DEMSs and a review of energy management systems based on multi-agent systems, respectively. On the other hand, in [6], the present and future perspectives regarding EVs and their operation modes in smart grids and smart homes have been discussed.…”

Section: Literature Reviewmentioning

confidence: 99%

Energy Flexibility Management Based on Predictive Dispatch Model of Domestic Energy Management System

et al. 2017

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This paper proposes a predictive dispatch model to manage energy flexibility in the domestic energy system. Electric Vehicles (EV), batteries and shiftable loads are devices that provide energy flexibility in the proposed system. The proposed energy management problem consists of two stages: day-ahead and real time. A hybrid method is defined for the first time in this paper to model the uncertainty of the PV power generation based on its power prediction. In the day-ahead stage, the uncertainty is modeled by interval bands. On the other hand, the uncertainty of PV power generation is modeled through a stochastic scenario-based method in the real-time stage. The performance of the proposed hybrid Interval-Stochastic (InterStoch) method is compared with the Modified Stochastic Predicted Band (MSPB) method. Moreover, the impacts of energy flexibility and the demand response program on the expected profit and transacted electrical energy of the system are assessed in the case study presented in this paper.

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Section: Literature Reviewmentioning

confidence: 99%

Energy Flexibility Management Based on Predictive Dispatch Model of Domestic Energy Management System

et al. 2017

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“…Salvadori F [4] uses wireless sensor digital systems to achieve realtime and efficient monitoring of factory power. Erol-Kantarci M [5] combines wireless technology with smart power and applies it to power monitoring system, which improves the effective utilization rate of home power. Wei Chuyuan designed [6] an intelligent building system for energy consumption monitoring and energy saving management by using the Internet of things technology.…”

Section: Literature Reviewmentioning

confidence: 99%

Intelligent Building Control System Based on Mobile Wireless Internet of Things

2017

Int. J. Onl. Eng.

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Abstract-In order to develop an advanced intelligent building control system, the new system based on mobile wireless Internet of things is designed. By analyzing the new technology, it is proved that the application and development of the Internet of things technology provides a new method for the effective control of intelligent buildings. In addition, a series of researches are carried out on the core technology of the construction equipment networking system. The hardware, software and wireless self-organization networks of the intelligent terminal are designed and implemented, and the key indexes of the intelligent terminal are tested. The fixed transmit power test results show that when the fixed emission frequency is 10 dB, the communication distance is inversely proportional to the communication rate, which means that the smart terminal wireless network has strong ability to pass through obstacles. Based on the above finding, it is concluded that the stability of the mobile internet wireless network intelligent terminal can fully meet the performance requirements of intelligent building control, which lay is a good basis for its flexible use of the future. Keywords-Intelligent building; Internet of things; wireless network; intelligent terminal IntroductionWith the increasing degree of economic and social informatization, the Internet of things and electronic information technology are gradually applied to the field of architecture. Therefore, it has become the focus of attention and discussion all over the world, which gave birth to the intelligent control system of intelligent building. According to relevant data, the energy consumption of construction electricity equipment can account for 80% of the total energy consumption of buildings, which has become the key point of restricting the sustainable development of the construction field [1]. As the number and types of electrical equipment in buildings are increasing, the traditional intelligent building control system cannot meet the needs of people's intelligent, diversified and convenient management and control. Therefore, an integrated control and management system for building electric equipment is urgently needed.

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“…Also, Particle Swarm Optimization (PSO) method has been used to maximize welfare and energy efficiency in [17]. In [18], authors has discussed about the necessities of using Computational Intelligence (CI) in REMSs. CI has been applied to three parts of the REMS in [18].…”

Section: Introductionmentioning

confidence: 99%

“…In [18], authors has discussed about the necessities of using Computational Intelligence (CI) in REMSs. CI has been applied to three parts of the REMS in [18]. These parts consist of the prediction of building required power, forecasting the purchasing electrical load from the power grid, and ANN-based controllers.…”

Section: Introductionmentioning

confidence: 99%