Smart grid ready BEMS adopting model-based HVAC control for energy saving

Murayama, Dai; Mitsumoto, Kenji; Takagi, Yasuo; Iino, Yutaka; Yamamori, S.

doi:10.1109/tdc.2012.6281521

Cited by 7 publications

(4 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…30 (B) BILMS. The purpose of this system is the management of the LED system for intelligent energy management using motion and illumination sensors installed in LED lighting system in smart space.…”

Section: Service Factor Contents Of Servicementioning

confidence: 99%

See 1 more Smart Citation

Design of a mass-customization-based cost-effective Internet of Things sensor system in smart building spaces

Park

Byun

Park

2016

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

In the coming Internet of Things era, billions of users and devices will be connected to the Internet; this will lead beyond the era of super-connection to the era of super-fusion. In this era, it is more important than ever to design a highly scalable Internet of Things infrastructure by mass customization for cost-effective production of exponentially increasing numbers of Internet of Things systems to provide more intelligent service in smart spaces. The purpose of this article is the design of mass-customization-based Internet of Things system through three-level analysis of the building; it proposes a new concept of a systematic design for providing economical Internet of Things systems for intelligent service in smart building spaces through three-level analysis comprising environmental-, service-, and functional-level analyses.

show abstract

Section: Service Factor Contents Of Servicementioning

confidence: 99%

“…The HVAC system in BEMS is a representative IoT-based energy management system that adjusts temperature and humidity within a specified range after measuring the temperature and humidity using sensors. 30…”

Section: Implementationsmentioning

confidence: 99%

Design of a mass-customization-based cost-effective Internet of Things sensor system in smart building spaces

Park

Byun

Park

2016

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

show abstract

“…In recent years, numerous studies have been conducted on devising RTP-based DR approaches oriented for either residential [10,11], commercial [12,13] or industrial consumers [14,15]. Among those existing approaches, game theory (GT) has attracted great attention for modeling complex interactions between various entities under a DR framework [10,11,16], since GT has been proven to be an effective tool for solving many challenging real-world problems and handling complex decision-making processes [17].…”

Section: Introductionmentioning

confidence: 99%

Assessing the Feasibility of Game-Theory-Based Demand Response Management by Practical Implementation

Zhang

Jiang

et al. 2021

IEEE Access

View full text Add to dashboard Cite

Demand response (DR) has been widely recognized as an effective solution to help mitigate the stresses imposed on power grids. As new concepts evolve, DR induces various interactions among multiple emerging entities, which further complicates the decision-making processes in grid operations. Recently, game theory (GT) has received great attention in DR management, due to its ability to handle complex decision-making problems. Numerous theoretical GT-based approaches have been proposed for addressing various DR issues, but the feasibility of these theoretical approaches in practical implementation remains in doubt. To bridge the gap between theoretical studies and practical implementations, we first provide specific guidelines regarding how to construct a DR-oriented facility, and then investigate the effectiveness of deploying a Stackelberg game theory-based DR algorithm to manage the energy consumption of the facility, wherein the energy management center (EMC) serves as the leader and multiple devices act as the followers. The experimental evaluation results show that the GT-based DR algorithm achieved great performance in practical DR management, including optimal load control in responding to real-time price (RTP), and peak load reduction with a peak-to-average ratio (PAR) of 1.59.

show abstract

“…For instance, a model for load shifting has been developed from the SG's perspective with a DR solution while the building thermal capacity is simplified [2]. On the contrary, a model for the smart operation of Heat, Ventilation and Air Conditioning (HVAC) system is presented to optimize the system's energy efficiency with an abstraction of the power grid [3]. Thus, there is a clear need to have a comprehensive integration framework to fully address a wide range of variables in different physical environments, on all time scales of the interoperation of the SG-BEMS [4].…”

Section: Introductionmentioning

confidence: 99%

Smart grid and smart building inter-operation using agent-based particle swarm optimization

Hurtado

Nguyen

Kling

2015

Sustainable Energy, Grids and Networks

View full text Add to dashboard Cite

Smart grid ready BEMS adopting model-based HVAC control for energy saving

Cited by 7 publications

References 2 publications

Design of a mass-customization-based cost-effective Internet of Things sensor system in smart building spaces

Design of a mass-customization-based cost-effective Internet of Things sensor system in smart building spaces

Assessing the Feasibility of Game-Theory-Based Demand Response Management by Practical Implementation

Smart grid and smart building inter-operation using agent-based particle swarm optimization

Contact Info

Product

Resources

About