Two-stage low-carbon optimal dispatch of the power system considering demand response to defend large uncertainties and risks DOI Creative Commons

Linjun Cai,

Dongliang Xie,

Feng Xue

et al.

Frontiers in Energy Research, Journal Year: 2024, Volume and Issue: 12

Published: Feb. 20, 2024

Introduction: In order to promote the consumption of renewable energy, reduce carbon emissions, and take into account uncertainty energy output load fluctuations in new power system that can affect normal operation market mechanism, a two-stage low-carbon optimization scheduling method for considers demand response under multiple uncertainties is proposed this paper. Methods: Uncertain scene sets are generated through Latin hypercube sampling heuristic synchronous backpropagation used scenes obtain typical their probabilities. Then, one-stage model established with goal maximizing efficiency corresponding strategies obtained. Green certificate trading joint mechanism consisting tiered green time-sharing established, units optimized minimizing comprehensive operating costs. Result: The simulation results show emissions decreased by 251.57 tons, rate increased 8.64%, total costs 124.0612 million yuan. Discussion: From this, it be seen dual layer strategy considering effectively system, while balancing economic environmental aspects operation.

Language: Английский

Dynamic pricing for load shifting: Reducing electric vehicle charging impacts on the grid through machine learning-based demand response DOI

P. Balakumar,

Senthil Kumar R,

Vinopraba Thirumavalavan

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 103, P. 105256 - 105256

Published: Feb. 7, 2024

Language: Английский

Citations

17
Optimizing electric vehicle charging in distribution networks: A dynamic pricing approach using internet of things and Bi-directional LSTM model DOI

P. Balakumar,

Senthil Kumar R,

Vinopraba Thirumavalavan

et al.

Energy, Journal Year: 2024, Volume and Issue: 294, P. 130815 - 130815

Published: Feb. 29, 2024

Language: Английский

Citations

6
Hilbert-Huang Transform and machine learning based electromechanical analysis of induction machine under power quality disturbances DOI Creative Commons

V. Indragandhi,

R. Senthil Kumar,

R. Saranya

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 24, P. 103075 - 103075

Published: Oct. 9, 2024

Language: Английский

Citations

6
Optimized LSTM-Based Electric Power Consumption Forecasting for Dynamic Electricity Pricing in Demand Response Scheme of Smart Grid DOI Creative Commons

P. Balakumar,

Senthil Kumar R

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104356 - 104356

Published: Feb. 1, 2025

Language: Английский

Citations

0
IoT implementation for energy system sustainability: The role of actors and related challenges DOI Creative Commons
Christopher Ball, Daniel Degischer

Utilities Policy, Journal Year: 2024, Volume and Issue: 90, P. 101769 - 101769

Published: June 8, 2024

Language: Английский

Citations

3
Two-stage low-carbon optimal dispatch of the power system considering demand response to defend large uncertainties and risks DOI Creative Commons

Linjun Cai,

Dongliang Xie,

Feng Xue

et al.

Frontiers in Energy Research, Journal Year: 2024, Volume and Issue: 12

Published: Feb. 20, 2024

Introduction: In order to promote the consumption of renewable energy, reduce carbon emissions, and take into account uncertainty energy output load fluctuations in new power system that can affect normal operation market mechanism, a two-stage low-carbon optimization scheduling method for considers demand response under multiple uncertainties is proposed this paper. Methods: Uncertain scene sets are generated through Latin hypercube sampling heuristic synchronous backpropagation used scenes obtain typical their probabilities. Then, one-stage model established with goal maximizing efficiency corresponding strategies obtained. Green certificate trading joint mechanism consisting tiered green time-sharing established, units optimized minimizing comprehensive operating costs. Result: The simulation results show emissions decreased by 251.57 tons, rate increased 8.64%, total costs 124.0612 million yuan. Discussion: From this, it be seen dual layer strategy considering effectively system, while balancing economic environmental aspects operation.

Language: Английский

Citations

0