Banca de DEFESA: DAVIDSON DA COSTA MARQUES

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
STUDENT : DAVIDSON DA COSTA MARQUES
DATE: 31/05/2023
TIME: 14:00
LOCAL: Sala de Seminários - LDSP/CTG (4º andar do prédio administrativo)
TITLE:

FREQUENCY CONTROL IN MICROGRIDS USING BATTERIES BASED ON EMOTIONAL BRAIN LEARNING .

KEY WORDS:

Distributed generation. Microgrids. MR hierarchical control. Battery Energy Storage Systems. BELBIC. PSO.  

PAGES: 209
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUMMARY:

The current development of electrical energy sources is primarily driven using Distributed Energy Resources (DERs), which include Distributed Generation (DG) and Distributed Generation (DG) and Energy Storage Systems (ESS). Microgrids (MR) emerge as a new emerging concept in electrical engineering, presenting itself as an attractive alternative to overcome the challenges in the integration of grids to the traditional electrical system, thus ensuring reliability and significant use of energy resources. In MR it is necessary to have a manager system to coordinate the operation of its components, being it connected or disconnected from the main grid. In the isolated mode, the MR manager must establish the setpoints for the operation of the EDRs so as not to violate the operation restrictions, such as economic dispatch, use of renewable sources and prioritization of loads. Besides the numerous benefits, there are many problems and challenges in integrating this concept into power systems - such as stability control. One of the most important requirements of MR operation is to keep the frequency within the allowed values in an eventual unbalance - in the case of Brazil 60Hz - which is directly related to the balance of load and generation. Thus, it is proposed the use of battery energy storage systems (BESS), which have fast response time and can inject or absorb power to ensure the stability of the frequency in the MR. However, the control action has a fundamental task for the best use of resources. As a complement to droop control, the concept of MR controlled by secondary control has been widely studied to restore voltage and frequency. However, several alternatives for improving the implementation of conventional droop have been discussed in the literature. The overall objective of this thesis is to propose an intelligent controller based on the brain's emotional learning process (BELBIC) that can minimize, within allowable values, the frequency deviations in MR. Biologically inspired controllers show great success in various applications, especially in situations that present disturbances and uncertainties in system dynamics when compared to other controllers. Furthermore, the parameters of this controller are optimized using particle swarm-based technique (PSO), thus resulting the optimal controller parameters. Finally, from the simulation results, it is intended to demonstrate an expressive gain also when using BELBIC, because storage systems have limitations in their capacities and thus ensure the preservation of battery life. The proposed control strategies are simulated in a RM through the Simulink tool, of the MATLAB computing platform and the results will be compared to the droop and PI controllers, whether they act as primary and/or secondary controls. 

COMMITTEE MEMBERS:
Presidente - 1171041 - RONALDO RIBEIRO BARBOSA DE AQUINO
Interno - 1543575 - PEDRO ANDRE CARVALHO ROSAS
Interno - 1237647 - JOSE FILHO DA COSTA CASTRO
Interno - 2889145 - GUSTAVO MEDEIROS DE SOUZA AZEVEDO
Externo à Instituição - MANOEL AFONSO DE CARVALHO JUNIOR
Externo à Instituição - BENEMAR ALENCAR DE SOUZA - UFCG