Autonomous Perception and Decision Making in Building Automation

Velik, Rosemarie; Zucker, Gerhard

doi:10.1109/tie.2009.2038985

Cited by 28 publications

(10 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This prevailing situation needs to be addressed appropriately for the cost-effective energy supply in remote areas. The significance of renewable energy augmentation with the existing power supply has already been highlighted in previous studies [3][4][5][6][7][8][9] to meet the energy demand. However, the involvement of the huge capacity storage battery with these schemes limits its utility concerning the energy cost and environmental issues with reference to the dumping of huge battery waste.…”

Section: Introductionmentioning

confidence: 89%

“…Initially, the DFIG was operating at a supersynchronous speed of 1.1 pu while delivering the power to the DC link through both stator and rotor circuits. Therefore, the reference q-axis rotor current changes accordingly as shown in Figure 5C with reference to Figure 3 and Equation (8). The load that is connected with DC link was drawing rated power as shown in Figure 5A.…”

Section: Response Of the Proposed Controller To The Load Variationsmentioning

confidence: 99%

“…As the load fixed at DC link varies continuously, the DFIG stator current changes in synchronous with load variations. Therefore, the reference q-axis rotor current changes accordingly as shown in Figure 5C with reference to Figure 3 and Equation (8). Under such a situation, the rotor power will be adjusted through q-axis DFIG rotor current loop, which maintains DC link voltage at its rated value as shown in Figure 5D.…”

Section: Response Of the Proposed Controller To The Load Variationsmentioning

confidence: 99%

See 2 more Smart Citations

Remote area power supply through suitable solar PV augmented micro‐hydro generation: A case study

Parida

Chatterjee

2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary Electrification in remote villages using locally available hybrid renewable energy sources is a viable option to eradicate energy poverty. At the same time, energy supply to the unprivileged population at the affordable cost is a major issue. Moreover, appropriate technology is the key factor for the sustainable operation of small‐scale generation system in remote places. Therefore, in this paper, a simple controller‐based standalone solar photovoltaic (PV) augmented micro‐hydro generation system suitable for remote area has been proposed. Because of its robustness for wide speed range applications, doubly fed induction generator (DFIG) has been used for micro‐hydro power generation in the proposed scheme. The developed controller effectively stabilizes the load voltage with load, micro‐hydro generation, and solar PV generation variations. In order to provide cost‐effective renewable power supply to the rural population, a generation capacity trade‐off criterion has been developed considering solar PV and micro‐hydro generations as the two operators. In the proposed trade‐off process, cost analysis has been performed considering the salvage dumping cost (SDC) for solar PV. The proposed hybrid generation scheme has been simulated through HOMER Pro‐3.2 for cost‐benefit analysis. Also, a prototype hardware set‐up for the proposed scheme has been developed and tested successfully. In this paper, Section 1 describes literature review; Section 2 discusses power generation strategy; Section 3 discusses energy cost analysis; and Section 4 describes experimental results.

show abstract

Section: Introductionmentioning

confidence: 89%

Section: Response Of the Proposed Controller To The Load Variationsmentioning

confidence: 99%

Section: Response Of the Proposed Controller To The Load Variationsmentioning

confidence: 99%

See 1 more Smart Citation

Remote area power supply through suitable solar PV augmented micro‐hydro generation: A case study

Parida

Chatterjee

2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“…Thus, in order to maintain and improve both energy efficiency and occupant comfort, close monitoring of the building environment is necessary [2], [3], [14]. To achieve this, modern buildings rely on thousands of sensors strategically placed throughout the building [15].…”

Section: Introductionmentioning

confidence: 99%

Neural Network based downscaling of Building Energy Management System data

Amarasinghe

Wijayasekara

Manic

2014

2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE)

View full text Add to dashboard Cite

Building Energy Management Systems (BEMSs) are responsible for maintaining indoor environment by controlling Heating Ventilation and Air Conditioning (HVAC) and lighting systems in buildings. Buildings worldwide account for a significant portion of world energy consumption. Thus, increasing building energy efficiency through BEMSs can result in substantial financial savings. In addition, BEMSs can significantly impact the productivity of occupants by maintaining a comfortable environment. To increase efficiency and maintain comfort, modern BEMSs rely on a large array of sensors inside the building that provide detailed data about the building state. However, due to various reasons, buildings frequently lack sufficient number of sensors, resulting in a suboptimal state awareness. In such cases, a cost effective method for increasing state awareness is needed. Therefore, this paper presents a novel method for increasing state awareness through increasing spatial resolution of data by means of data downscaling. The presented method estimates the state of occupant zones using state data gathered at floor level using Artificial Neural Networks (ANN). The presented method was tested on a real-world CO 2 dataset, and compared to a time based estimation of CO 2 concentration. The downscaling method was shown to be capable of consistently producing accurate estimates while being more accurate than time based estimations.

show abstract

“…However, this research field is still quite recent and existing approaches are challenged by this abundance of data and the ways in which it should be analyzed and responded to [4], [5]. There is thus a need for new concepts to handle future demands [6]. One solution introduced recently to process and interpret such a flood of sensory information is the neuro-symbolic information processing principle [7].…”

Section: Introductionmentioning

confidence: 99%

Neurosymbolic Alerting Rules

Velik

Boley

2010

IEEE Trans. Ind. Electron.

Self Cite

View full text Add to dashboard Cite

Abstract-Future building automation will require complex (human-like) perception and decision-making processes not being feasible with classical approaches. In this paper, we address both the perception and the decision-making process and present an alerting model that reacts to perceived situations in a building with decisions about possible alerts. Perception is based on the neuro-symbolic information processing model, which detects candidate alerts. Integrated with perception, decision-making is based on the rule model of RuleML, which computes alerts to relevant building occupants about current opportunities and risks. A general model of neuro-symbolic alerting rules is developed and exemplified with a use case of building alerts.

show abstract

Autonomous Perception and Decision Making in Building Automation

Cited by 28 publications

References 22 publications

Remote area power supply through suitable solar PV augmented micro‐hydro generation: A case study

Remote area power supply through suitable solar PV augmented micro‐hydro generation: A case study

Neural Network based downscaling of Building Energy Management System data

Neurosymbolic Alerting Rules

Contact Info

Product

Resources

About