A novel strategy for real-time optimal scheduling of grid-tied microgrid considering load management and uncertainties

E.G. Hassaballah, H.E. Keshta, K.M. Abdel-Latif and A.A. Ali

Energy, 2024, vol. 299, issue C

Abstract: This paper proposes an efficient bi-level energy management strategy (EMS) to optimize the operation cost of a grid-connected microgrid, considering the system operational constraints and uncertainties for renewable energy sources and load demand. The first level is optimal day-ahead scheduling based on two stages: the first stage is finding the optimal operating points of sources during the next day while the second one is controllable loads management. The second level of the proposed EMS is rescheduling and updating the set-points of sources in real-time according to the actual solar irradiance, wind speed, load, and grid tariff. In this paper, a novel real-time strategy is proposed to keep the economic operation during real-time under uncertainties. Also, a recent meta-heuristic algorithm called Honey Badger Algorithm (HBA) is used to solve the problem of day-ahead scheduling of batteries, which is a complex constrained non-linear optimization problem. Results obtained demonstrate that the HBA based bi-level EMS provides the real-time optimal economic operation of a grid tied microgrid under uncertainties in weather, utility tariff and load forecasts.

Keywords: Energy management system; Microgrids; Demand side management; Day-ahead scheduling; Meta-heuristic techniques (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544224011927
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:299:y:2024:i:c:s0360544224011927

DOI: 10.1016/j.energy.2024.131419

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().