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Optimizing power system efficiency and costs in smart buildings with renewable resources
- Source :
- Ain Shams Engineering Journal, Vol 15, Iss 11, Pp 103014- (2024)
- Publication Year :
- 2024
- Publisher :
- Elsevier, 2024.
-
Abstract
- The increasing industrial development and energy demand have necessitated the maximization of available energy use and the deployment of renewable resources. Effective energy management, optimal modeling, and efficient planning are essential to transform the power system into a high-efficiency, optimal model. This study focuses on the initial step of modeling smart buildings (SBs) equipped with non-responsive devices and renewable photovoltaic sources. A comprehensive energy management (EM) plan is formulated for these buildings, incorporating the KNX protocol for solar energy system management. Batteries are integrated into the building model to store energy during periods of low consumption and serve as generators during peak load conditions, with the primary goal of minimizing power system losses and related costs. To address the complexity of this model, whale optimization algorithm (WOA) is employed for optimization. Optimal candidate buses are selected for interconnected building management based on a suggested sensitivity analysis to minimize losses. Cost performance is then assessed, considering energy production and sales. The findings indicate that substantial control of operating costs can be achieved through strategic management of battery charging and discharging, as well as the utilization of photovoltaic units. The proposed model is evaluated across various scenarios using a test system comprising 30 modified system, demonstrating its effectiveness in enhancing energy efficiency and management.
Details
- Language :
- English
- ISSN :
- 20904479
- Volume :
- 15
- Issue :
- 11
- Database :
- Directory of Open Access Journals
- Journal :
- Ain Shams Engineering Journal
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.00a19f5a05e8469fb602f97dbdf793ae
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.asej.2024.103014