Intelligent control system for efficient energy management in commercial buildings

Smitha, S D; Savier, J S; Chacko, Fossy Mary

doi:10.1109/aicera-icmicr.2013.6575942

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…The Commercial Buildings Energy Consumption Survey (CBECS) classifies buildings based on the principal activity, which includes the primary business, commerce, or function carried out within each building [19]. The break-down of energy end-use in buildings for the commercial sector is shown in Fig.…”

Section: Energy Consumption Distributionmentioning

confidence: 99%

See 1 more Smart Citation

Energy efficiency index as an indicator for measuring building energy performance: A review

Bakar

Hassan

Abdullah

et al. 2015

Renewable and Sustainable Energy Reviews

194

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Section: Energy Consumption Distributionmentioning

confidence: 99%

“…The more comfort level is being provided to the occupants of a building, the more the energy consumption [24]. Energy can be saved to a great extent by properly managing the energy while ensuring reliability of the critical loads [19], which also minimizes the total energy consumption [25].…”

Section: Energy Consumption Distributionmentioning

confidence: 99%

Energy efficiency index as an indicator for measuring building energy performance: A review

Bakar

Hassan

Abdullah

et al. 2015

Renewable and Sustainable Energy Reviews

194

View full text Add to dashboard Cite

“…The most important unit of SB systems is Building Energy Management System (BEMS), which is applied to manage energy effectively [8,9]. This technology manages and controls energy flow in building through different types of information to ensure operational safety, reliability, and economy by automating DR approaches [4].…”

Section: Introductionmentioning

confidence: 99%

Demand-Side Energy Management in Smart Buildings: A Case Study

HASANOVA¹,

Neşe²

2021

European Journal of Technic

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Electrical energy is indispensable in our daily life with the developing technology. The most important feature is reliable and sustainable transmission of electrical energy to consumers is to provide the supply-demand balance in real-time. The ever-increasing demand for electrical energy, gradual depletion of traditional resources used to meet demand, and increasing dependence on foreign sources resulted in diverse electricity generation plants. As a result of this diversity, with the increase in the importance of electricity storage systems and awareness of energy-saving, Demand Side Management (DSM) gains great importance in ensuring supply-demand balance. DSM reduces costs by scheduling consumption instead of increasing generation to balance supply and demand. Residences constitute a large part of energy consumption worldwide, so DSM applications in buildings increase efficient usage of energy. Various management strategies can be used to save energy depending on the building type. In this article, an overview of Energy Management System (EMS) strategies to increase energy efficiency is presented. Then a case study is carried out in a residential model in Matlab/Simulink environment. The electrical devices were controlled with a Fuzzy Logic Controller (FLC), taking into account comfort, cost, and Demand Response (DR). In addition, Renewable Energy Resources (RES) to demonstrate their contribution were modelled and integrated into the system. Finally, case studies were conducted, and a comparative analysis of obtained results was carried out.

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“…One of the most widespread is to use the very general framework of multi-agent systems as it has been done at the microgrid level in [1] with a market-based control, or in [2] with an artificial neural network as learning module, or in [3] with a system of auctions. Multi-agents systems were also used at the building level [4], [5]. Although the exact logic of a multi-agent control scheme varies widely from one author to the other, it may be stated that these schemes generally suffer from the lack of mathematical convergence proofs, that translates into lack of guarantees concerning the solution quality as well as the convergence speed.…”

Section: Introductionmentioning

confidence: 99%