Optimal planning and operation of microgrids for the enhancing of the resilience in distribution systems

• Grant number: 19/23755-3
• Support type: Scholarships abroad - Research Internship - Post-doctor
• Effective date (Start): October 01, 2020
• Effective date (End): September 30, 2021
• Field of knowledge: Engineering - Electrical Engineering - Power Systems
• Principal researcher: José Roberto Sanches Mantovani
• Grantee: Juan Manuel Home Ortiz
• Supervisor abroad: Joao Paulo da Silva Catalao
• Home Institution: Faculdade de Engenharia (FEIS). Universidade Estadual Paulista (UNESP). Campus de Ilha Solteira. Ilha Solteira , SP, Brazil
• Research place: Instituto de Engenharia de Sistemas e Computadores - Tecnologia e Ciência (INESC TEC), Portugal
• Associated to the scholarship: 19/01841-5 - Planning of Resilient Electric Power Distribution Systems, BP.PD

Abstract

The propose for this research project is to develop an optimization mathematical model to solve the planning electric distribution system problem with the microgrid formation in order to enhance the resilience of the system and the load restoration capability in the case of major permanent faults in the system. The active distribution system planning considers dispatchable and renewable distributed generation (DG) operation, the charge/discharge process of the energy storage devices (ESD), uncertainty in the renewable sources behaviors, and demand response. For the mathematical representation of the problem, it is proposed an optimization model based on stochastic mixed-integer conic programming (SMICP) which can be solved by commercial optimization solvers. The planning of the network focuses on the allocation of renewable and dispatchable DG and ESD in the system to increase post-fault load restoration capacity, in addition to the reinforcement of circuits through the exchange of conductors. The complexity of the problem requires specialized optimization techniques, so it is intended to develop a hybrid solver-metaheuristic (matheuristic) technique based on the VNS algorithm, or another efficient metaheuristic, to solve the problem. Tests will be carried out using real and test systems available in the specialized literature