Grant: Discovery Grants Program - Individual

High penetration of renewable energy sources in distribution power systems is causing challenges to the voltage regulation of grids. Voltage instability may trigger serious damages in power networks. Current trend in control of power systems is moving toward the use of distributed, flexible, and robust structures. Applying an intelligent agent-based control system is an effective way for solving complex problems in parallel. The Alternating Direction Method of Multipliers (ADMM) can be used as a theoretical framework to design distributed computational systems. ADMM-based algorithm is an iterative optimization method able to solve complex problems by decomposing them into multiple sub-problems in a fully distributed way. Real-time simulation is an efficient way that allows researchers to test complex designed controllers in a secure environment. However, the computational time in the real-time (RT) simulators increase with the complexity of the models. In recent years, despite the identified advantages of the application of multi-agent control technique in power systems, only a few works have been done to modify the ADMM algorithm to fully utilize the parallelized hardware structure of the Field Programmable Gate Arrays (FPGAs) in real-time. FPGA-based platforms are used for Hardware-in-the-Loop (HIL) testing as a solution for running more realistic models in less time. FPGAs offer high-performance simulations in parallel with less time step and higher flexibility. This program is an innovative application in real-time simulation of grid-connected PV systems integrated to an optimal voltage control based on multi-agent systems. Coordination between different agents will be implemented using FPGA. The main objective of the program is to design an innovative, simple, and robust application of FPGA in real-time control of PV systems connected to Hydro- Québec's networks to ensure optimal management of local energy as well as the safe injection of clean energy. The short-term objectives of the program are to: 1.Design and simulate an intelligent agent-based control algorithm based on ADMM. 2.Analyze the operation of proposed technique under high penetrations of PVs. 3.Develop the distributed optimization-based voltage control algorithm to accelerate the convergence of the algorithm. 4.Validate the method by implement it on real networks in large-scale. 5.Design a parallel simulation approach using real-time FPGAs ensuring minimum latency in the whole system division. The long-term objectives of the project are to: 1. Implement a low-cost and effective solution for voltage stability of the system under uncertainties during distribution and transmission level.  2.Develop an intelligent method for training the agents using neural networks aims to reduce the running time of distributed ADMM algorithms. 3.Develop a unique expertise in the management and control of local micro-networks.