Optimal planning of self-healing multi-carriers energy systems considering integration of smart buildings and parking lots energy resources

• Type: Article in International Scientific Journal
• Date: 2024

Authors

Nazar, MS (Author) Other; Jafarpour, P (Author) Other; Shafie-khah, M (Author) Other; Catalao, JPS (Author) FEUP

Journal

Title: Energy

Vol. 286

ISSN: 0360-5442

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 2 Citations

Other information

Authenticus ID: P-00Y-X92

DOI: 10.1016/j.energy.2023.128674

Abstract (EN): This paper presents a new framework for optimal planning of electrical, heating, and cooling distributed energy resources and networks considering smart buildings' contribution scenarios in normal and external shock conditions. The main contribution of this paper is that the impacts of smart buildings' commitment scenarios on the planning of electrical, heating, and cooling systems are explored. The proposed iterative four-stage optimization framework is another contribution of this paper, which utilizes a self-healing performance index to assess the level of resiliency of the multi-carrier energy system. In the first stage, the optimal decision variables of planning are determined. Then, in the second stage, the smart buildings and parking lots contribution scenarios are explored. In the third stage, the optimal hourly scheduling of the energy system for the normal condition is performed considering the self-healing performance index. Finally, in the fourth stage, the optimization process determines the optimal scheduling of system resources and the switching status of electrical switches, heating, and cooling pipelines' control valves. The proposed method was successfully assessed for the 123-bus IEEE test system. The proposed framework reduced the expected values of aggregated system costs and energy not supplied costs by about 49.92% and 93.64%, respectively, concerning the custom planning exercise.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 31