CNN-LSTM for Secure Distributed Demand Response in Smart Grid DOI
Aschalew Tirulo, Siddhartha Chauhan

Published: Nov. 22, 2023

Integrating cyber and physical elements in smart grids amplifies susceptibility to false data injection attacks (FDIAs), jeopardizing home automation energy infrastructure. Traditional security strategies often underperform FDIA detection due varied origins. We propose an advanced anomaly framework using CNN-LSTM, tailored detect FDIAs the grid's demand response. Our model employs supervised learning for improved precision when enriched with label information. Empirical tests genuine from Austin, Texas, demonstrate our model's superiority over existing methods, metrics like accuracy, precision, recall, F1 score, positive rate consistently affirming its robustness real-world applicability.

Language: Английский

Demand Response and HVAC Controls in Smart Grid Integration DOI Open Access
V.V. Mistry

Journal of Engineering and Applied Sciences Technology, Journal Year: 2023, Volume and Issue: unknown, P. 1 - 5

Published: Dec. 31, 2023

This extensive research paper meticulously investigates the intricate synergies between demand response strategies and Heating, Ventilation, Air Conditioning (HVAC) controls within dynamic realm of smart grid integration. As global energy landscape undergoes transformative changes driven by technological advancements sustainability imperatives, study critically examines symbiotic relationship consumers, HVAC systems, grid. The paramount importance this interaction is underscored, emphasizing its pivotal role in achieving elevated levels efficiency, reliability, sustainability. explores multifaceted potential inherent programs advanced controls, unraveling their collective capacity to reshape ecosystem. It goes beyond theoretical framework delving into real-world applications, case studies, cutting-edge advancements. By doing so, seeks provide not only a understanding but also practical insights evolving demand-side management. investigation poised contribute significantly existing body knowledge illustrating how harmonious coordination consumer behaviors systems can be strategically harnessed. strategic collaboration aims optimize consumption, mitigate peak loads, substantively establishment more sustainable, adaptive, responsive infrastructure. community grapples with imperative transition towards cleaner efficient positions itself as valuable resource for policymakers, researchers, industry stakeholders seeking innovative solutions resilient sustainable future.

Language: Английский

Citations

0
CNN-LSTM for Secure Distributed Demand Response in Smart Grid DOI
Aschalew Tirulo, Siddhartha Chauhan

Published: Nov. 22, 2023

Integrating cyber and physical elements in smart grids amplifies susceptibility to false data injection attacks (FDIAs), jeopardizing home automation energy infrastructure. Traditional security strategies often underperform FDIA detection due varied origins. We propose an advanced anomaly framework using CNN-LSTM, tailored detect FDIAs the grid's demand response. Our model employs supervised learning for improved precision when enriched with label information. Empirical tests genuine from Austin, Texas, demonstrate our model's superiority over existing methods, metrics like accuracy, precision, recall, F1 score, positive rate consistently affirming its robustness real-world applicability.

Language: Английский

Citations

0