Virtual energy storage capacity estimation using ANN‐based kWh modelling of refrigerators

Kandasamy, Nandha Kumar; Vijayakumar, K.; Chaudhari, Kalpesh

doi:10.1049/iet-stg.2018.0001

Cited by 21 publications

(3 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Meanwhile, convergence is achieved when the error in every training iteration decreases continuously to the point where the weight value for each neuron reaches the best for the data provided. Conversely, divergence is attained when the error does not tend to decrease to a certain point [6,17,18].…”

Section: Methodsmentioning

confidence: 99%

The Estimate of Fault Location based on Transmission Tower Coordinates

2022

View full text Add to dashboard Cite

This study was conducted to predict the fault location based on tower coordinates using the Artificial Neural Network (ANN). The electrical power system modeled made use of an actual system including 150 kV transmission line with KP bus to the GS bus and 64 km length while ANN technique was used to coordinate the points for the fault location on the electric power transmission line due to its ability to predict what will happen in the future based on the pattern of past events. The ANN was tested and trained at certain iterations with different data which were simulated for short circuit fault type at several locations to achieve the best value. The results obtained with fault location coordinates were in the form of latitude and longitude while the simulation results for the AG fault were at 0.0381 km distance starting from the KP bus to the GS bus at 8,246 kA. Moreover, the estimated error values were found in the 2-phase fault to the ground at 4.01×10- 3 % while the ANN structure performance showed the MSE value to be 2.08 - 4 % with a very small error value of 0.57 % and this means it is included in the existing standard tolerance category. The data validation of this system modeling was conducted on the short circuit current value between simulation and theoretical estimation.

show abstract

Section: Methodsmentioning

confidence: 99%

The Estimate of Fault Location based on Transmission Tower Coordinates

2022

View full text Add to dashboard Cite

show abstract

“…In this respect, the authors of References [177][178][179][180][181][182][183] have thoroughly reviewed the role of storage systems in modern smart grids in terms of applications, costs, characteristics, optimal operation, sizing, and hybridization of storage technologies. For instance, the applications may include, but not limited to, energy arbitrage [184][185][186][187][188][189], peak shaving [190][191][192], frequency regulation [193][194][195][196] and [197], spinning reserves [198], voltage support [199][200][201], black start capabilities [202], intermittency smoothing [203], congestion mitigation [204], system expansion deferrals [205], multi-agent grid services [206][207][208][209], and load-following applications [210]; Tables 7 and 8 highlight the most recent characteristics of storage technologies.…”

Section: Energy Storage Technologiesmentioning

confidence: 99%

A Comprehensive Review of Recent Advances in Smart Grids: A Sustainable Future with Renewable Energy Resources

et al. 2020

View full text Add to dashboard Cite

The smart grid is an unprecedented opportunity to shift the current energy industry into a new era of a modernized network where the power generation, transmission, and distribution are intelligently, responsively, and cooperatively managed through a bi-directional automation system. Although the domains of smart grid applications and technologies vary in functions and forms, they generally share common potentials such as intelligent energy curtailment, efficient integration of Demand Response, Distributed Renewable Generation, and Energy Storage. This paper presents a comprehensive review categorically on the recent advances and previous research developments of the smart grid paradigm over the last two decades. The main intent of the study is to provide an application-focused survey where every category and sub-category herein are thoroughly and independently investigated. The preamble of the paper highlights the concept and the structure of the smart grids. The work presented intensively and extensively reviews the recent advances on the energy data management in smart grids, pricing modalities in a modernized power grid, and the predominant components of the smart grid. The paper thoroughly enumerates the recent advances in the area of network reliability. On the other hand, the reliance on smart cities on advanced communication infrastructure promotes more concerns regarding data integrity. Therefore, the paper dedicates a sub-section to highlight the challenges and the state-of-the-art of cybersecurity. Furthermore, highlighting the emerging developments in the pricing mechanisms concludes the review.

show abstract

“…Here, the authors use an online recursive identification algorithm that captures the predominant dynamics and disturbance patterns of the refrigerator based on that proposed in [21]. The model (1) is widely used in the refrigerator control literature, including [8][9][10][11]18,[22][23][24]:…”

Section: Real-time Identification Of Refrigerator Dynamicsmentioning

confidence: 99%

Model Predictive Control with Binary Quadratic Programming for the Scheduled Operation of Domestic Refrigerators

Sabegh

Bingham

2019

Energies

View full text Add to dashboard Cite

The rapid proliferation of the ‘Internet of Things’ (IoT) now affords the opportunity to schedule the operation of widely distributed domestic refrigerator and freezers to collectively improve energy efficiency and reduce peak power consumption on the electrical grid. To accomplish this, the paper proposes the real-time estimation of the thermal mass of each refrigerator in a network using on-line parameter identification, and the co-ordinated (ON-OFF) scheduling of the refrigerator compressors to maintain their respective temperatures within specified hysteresis bands commensurate with accommodating food safety standards. A custom model predictive control (MPC) scheme is devised using binary quadratic programming to realize the scheduling methodology which is implemented through IoT hardware (based on a NodeMCU). Benefits afforded by the proposed scheme are investigated through experimental trials which show that the co-ordinated operation of domestic refrigerators can i) reduce the peak power consumption as seen from the perspective of the electrical power grid (i.e., peak load levelling), ii) can adaptively control the temperature hysteresis band of individual refrigerators to increase operational efficiency, and iii) contribute to a widely distributed aggregated load shed for demand side response purposes in order to aid grid stability. Importantly, the number of compressor starts per hour for each refrigerator is also bounded as an inherent design feature of the algorithm so as not to operationally overstress the compressors and reduce their lifetime. Experimental trials show that such co-ordinated operation of refrigerators can reduce energy consumption by ~30% whilst also providing peak load levelling, thereby affording benefits to both individual consumers as well as electrical network suppliers.

show abstract

Virtual energy storage capacity estimation using ANN‐based kWh modelling of refrigerators

Cited by 21 publications

References 57 publications

The Estimate of Fault Location based on Transmission Tower Coordinates

The Estimate of Fault Location based on Transmission Tower Coordinates

A Comprehensive Review of Recent Advances in Smart Grids: A Sustainable Future with Renewable Energy Resources

Model Predictive Control with Binary Quadratic Programming for the Scheduled Operation of Domestic Refrigerators

Contact Info

Product

Resources

About