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Mohammad Bayat

Mohammad Bayat

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0003-1465-0015
Education: PhD.
ScopusId: 56681445600
Faculty: Engineering
Address: Arak University
Phone:

Research

Title
A multi-objective bi-level optimization framework for dynamic maintenance planning of active distribution networks in the presence of energy storage systems
Type
JournalPaper
Keywords
Maintenance planning, Reliability, Microgrids, Distribution feeder reconfiguration, Demand response program, Epsilon-constraint approach
Year
2022
Journal Journal of Energy Storage
DOI
Researchers seyed alireza alavi matin ، Seyed Amir Mansouri ، Mohammad Bayat ، Ahmad Rezaee Jordehi ، Pouria Radmehr

Abstract

Improving the reliability of microgrids as well as satisfying technical and economic constraints are very important challenges for distribution system operators (DSOs), which should be considered in both the long-term and short-term horizons. Therefore, this paper presents a dynamic model for multi-microgrids maintenance planning over a 10-year period, taking into account daily operating conditions. The proposed model is designed as a bi-level problem, in the first level of which the microgrids perform their maintenance planning and report its result to the DSO. Then, in the second level, DSO performs day-ahead scheduling of the entire network with the goals of adhering to microgrids schedule and minimizing system average interruption frequency index (SAIFI). Note that the objective functions of both levels are formulated in the form of two-objective problems through the Epsilon-constraint method. Finally, the proposed model is implemented on a 69-bus distribution network and results demonstrate that maintenance services, despite the increase in planning costs, will lead to a significant reduction in operating costs and will be cost-effective in the long-term horizon. The results also indicate that distribution feeder reconfiguration (DFR), despite a 19.62% increase in maintenance costs, leads to a 15.23% reduction in operating costs. Finally, the results illustrate that coordinated operation of storage systems and demand response (DR) programs reduces operating costs by 5.67%.