Transforming Smart Homes Via P2P Energy Trading Using Robust Forecasting and Scheduling Framework DOI Creative Commons
Ali Raza, Jingzhao Li,

Muhammad Adnan

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 23, P. 102766 - 102766

Published: Aug. 24, 2024

With the advent of smart grids, advanced information infrastructures, metering facilities, bidirectional exchange information, and battery storage home area networks have all transformed electricity consumption energy efficiency. There is a significant shift in management structure from traditional centralized infrastructure to flexible demand side driven cyber-physical power systems with clean system. These changes significantly evolved (HEM) space. Consequently, stakeholders must define their responsibilities, create efficient regulatory frameworks, test out novel commercial strategies. P2P trading appears be feasible solution these circumstances, allowing users trade one another before becoming completely reliant on utility. offers more stable platform for by facilitating between prosumers consumers. This research proposes generation prediction techniques HEMS optimal using Multi-Objective Optimization model. An enhanced Wild Horse technique was first used summarize historical records' qualities. Then, Bi-LSTM predict values. Furthermore, Grasshopper optimization (GHO) approach employed fine-tune model's hyperparameters. The framework offered probabilistic fault evaluation that upholds load flow balance need supply continuous operations. It results an intelligent community transforming cities into ones, opening new avenues scientific terms technological developments.

Language: Английский

A Comprehensive Survey on Load Forecasting Hybrid Models: Navigating the Futuristic Demand Response Patterns through Experts and Intelligent Systems DOI Creative Commons

Kinza Fida,

Usman Abbasi,

Muhammad Adnan

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 23, P. 102773 - 102773

Published: Aug. 24, 2024

Language: Английский

Citations

9
Transforming Smart Homes Via P2P Energy Trading Using Robust Forecasting and Scheduling Framework DOI Creative Commons
Ali Raza, Jingzhao Li,

Muhammad Adnan

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 23, P. 102766 - 102766

Published: Aug. 24, 2024

With the advent of smart grids, advanced information infrastructures, metering facilities, bidirectional exchange information, and battery storage home area networks have all transformed electricity consumption energy efficiency. There is a significant shift in management structure from traditional centralized infrastructure to flexible demand side driven cyber-physical power systems with clean system. These changes significantly evolved (HEM) space. Consequently, stakeholders must define their responsibilities, create efficient regulatory frameworks, test out novel commercial strategies. P2P trading appears be feasible solution these circumstances, allowing users trade one another before becoming completely reliant on utility. offers more stable platform for by facilitating between prosumers consumers. This research proposes generation prediction techniques HEMS optimal using Multi-Objective Optimization model. An enhanced Wild Horse technique was first used summarize historical records' qualities. Then, Bi-LSTM predict values. Furthermore, Grasshopper optimization (GHO) approach employed fine-tune model's hyperparameters. The framework offered probabilistic fault evaluation that upholds load flow balance need supply continuous operations. It results an intelligent community transforming cities into ones, opening new avenues scientific terms technological developments.

Language: Английский

Citations

5