Development and implementation of control techniques for optimal management of microgrids

Author(s)

Jéssica Alice Alves da Silva

• Document type: Doctoral Thesis
• Press: Campinas, SP.
• Institution: Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação
• Defense date: 2023-11-30

Examining board members

Luiz Carlos Pereira da Silva; Marcos Julio Rider Flores; Daniel Dotta; Enes Gonçalves Marra; Osvaldo Ronald Saavedra Mendez

• Advisor: Luiz Carlos Pereira da Silva; Maria Nataly Banol Arias; Juan Camilo López Amézquita

Abstract

In an increasingly energy-dependent world, where efficiency and reliability are crucial, optimizing energy management systems in microgrids emerges as a fundamental necessity to shape the sustainable future of energy distribution. In this context, this work develops and investigates optimization methodologies for the problem of optimal management of microgrids. A centralized stochastic model of mixed-integer linear programming is formulated for unbalanced three-phase alternating current microgrids, considering contingency constraints, stochastic scenarios of local demand, and renewable generation. The mathematical model serves as the basis for developing the Economic Dispatch Optimizer (EDO), which is responsible for defining the dispatch of distributed energy resources in the microgrid while respecting network constraints, such as voltage, current, and power limits. The EDO is part of an Internet of Things (IoT)-based Energy Management System (EMS) for the optimal operation of unbalanced three-phase AC microgrids. The EMS includes a database, a web-based Graphical User Interface (GUI), and an Application Programming Interface (API). Its effectiveness is validated through testing in a real-time simulator in a software-in-the-loop (SIL) experimental setup with Typhoon HIL and in an actual microgrid at the Laboratory of Smart Grids (LabREI). The results demonstrate that the proposed model and tool are suitable for real-world applications, providing resilient, cost-effective, and robust solutions for contingencies while maximizing the utilization of local renewable energy sources. This work also develops a simplified distributed optimization approach for microgrids, opening new horizons for efficient microgrid control in support of a more sustainable and resilient energy future (AU)

• FAPESP's process: 19/17306-1 - Centralized and distributed control techniques for the energy management of microgrids: development and implementation
• Grantee: Jéssica Alice Alves da Silva
• Support Opportunities: Scholarships in Brazil - Doctorate