Adaptive Robust Optimal Scheduling of Combined Heat and Power Microgrids Based on Photovoltaic Mechanism/Data Fusion-Driven Power Prediction DOI Creative Commons

Yueyang Xu,

Yibo Wang, Chuang Liu

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(3), P. 732 - 732

Published: Feb. 5, 2025

In order to effectively deal with the adverse effects of randomness photovoltaic output on operation combined heat and power (CHP) microgrids, this paper proposes an adaptive robust optimal scheduling strategy for CHP microgrids based mechanism/data fusion-driven prediction. Firstly, mechanism clear sky radiation model is used calculate limit random output, latter reorganized in different periods by using idea similar days. Then, data-driven prediction results are superimposed established, framework provided. Secondly, boundary information uncertain factors deeply explored, uncertainty set considering confidence interval predictive error statistical constructed. On basis, a optimization lowest operating cost proposed, solved column constraint generation algorithm. Finally, rationality effectiveness proposed verified through simulation examples analytical calculations.

Language: Английский

Energy Optimisation in Aquaponics—Integrating Renewable Source and Water as Energy Buffer for Sustainable Food Production DOI Creative Commons
Abdul Aziz Channa, Kamran Munir, Mark Hansen

et al.

Energy Science & Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 5, 2025

ABSTRACT Aquaponics, a symbiotic integration of aquaculture and hydroponics, has emerged as promising solution for sustainable food production, offering efficient water land utilisation. However, the high energy costs associated with maintaining optimal conditions remain critical factor in ensuring its long‐term viability. While renewable sources like solar wind power can offset costs, their intermittent nature limits effectiveness. Batteries, often used buffers during these intermittencies, but introduce additional environmental concerns. This study presents novel optimisation approach aquaponic systems. We employed dynamic control algorithm to intelligently adjust temperature based on forecasts. By leveraging system thermal buffer, method reduces reliance grid thereby enhancing integration. Simulations reveal that this achieve up 26.9% annual reduction consumption systems compared conventional methods. strategy not only decreases usage also highlights potential aquaponics evolve into more cost‐effective production.

Language: Английский

Citations

0
Energy-efficient greenhouse climate control using Gaussian process-based stochastic model predictive control DOI
Jin‐Sung Kim, Fengqi You

Applied Energy, Journal Year: 2025, Volume and Issue: 391, P. 125841 - 125841

Published: April 14, 2025

Language: Английский

Citations

0
Adaptive Robust Optimal Scheduling of Combined Heat and Power Microgrids Based on Photovoltaic Mechanism/Data Fusion-Driven Power Prediction DOI Creative Commons

Yueyang Xu,

Yibo Wang, Chuang Liu

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(3), P. 732 - 732

Published: Feb. 5, 2025

In order to effectively deal with the adverse effects of randomness photovoltaic output on operation combined heat and power (CHP) microgrids, this paper proposes an adaptive robust optimal scheduling strategy for CHP microgrids based mechanism/data fusion-driven prediction. Firstly, mechanism clear sky radiation model is used calculate limit random output, latter reorganized in different periods by using idea similar days. Then, data-driven prediction results are superimposed established, framework provided. Secondly, boundary information uncertain factors deeply explored, uncertainty set considering confidence interval predictive error statistical constructed. On basis, a optimization lowest operating cost proposed, solved column constraint generation algorithm. Finally, rationality effectiveness proposed verified through simulation examples analytical calculations.

Language: Английский

Citations

0