Optimal operational planning of distribution systems: A neighborhood search-based matheuristic approach

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

Authors

Yumbla, J (Author) Other; Home Ortiz, J (Author) Other; Pinto, T (Author) Other; Catalao, JPS (Author) FEUP; Mantovani, JRS (Author) Other

Journal

Title: Sustainable Energy, Grids and Networks

Vol. 38

ISSN: 2352-4677

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

Other information

Authenticus ID: P-010-4QS

DOI: 10.1016/j.segan.2024.101330

Abstract (EN): This study proposes a strategy for short-term operational planning of active distribution systems to minimize operating costs and greenhouse gas (GHG) emissions. The strategy incorporates network reconfiguration, switchable capacitor bank operation, dispatch of fossil fuel-based and renewable distributed energy resources, energy storage devices, and a demand response program. Uncertain operational conditions, such as energy costs, power demand, and solar irradiation, are addressed using stochastic scenarios derived from historical data through a k-means technique. The mathematical formulation adopts a stochastic scenario-based mixed-integer second-order conic programming (MISOCP) model. To handle the computational complexity of the model, a neighborhood-based matheuristic approach (NMA) is introduced, employing reduced MISOCP models and a memory strategy to guide the optimization process. Results from 69 and 118-node distribution systems demonstrate reduced operational costs and GHG emissions. Moreover, the proposed NMA outperforms two commercial solvers. This work provides insights into optimizing the operation of distribution systems, yielding economic and environmental benefits.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 14