Advanced Control and Optimization for Future Grid with Energy Storage Devices

Abstract

In the future grid environment, more sustainable resources will be increasing steadily. Their inherent unpredictable and intermittent characteristics will inevitably cause adverse impacts on the system static, dynamic and economic performance simultaneously. In this context, energy storage (ES) devices have been receiving growing attention because of their significant falling prices. Therefore, how to utilize these ES to help alleviate the problem of renewable energy (RE) sources integration has become more and more attractive. In my thesis, I will try to resolve some of the related problems from several perspectives. First of all, a comprehensive Future Australian transmission network simulation platform is constructed in the software DIgSILENT. Then in-depth research has been done on the aspect of frequency controller design. Based on mathematical reasoning, an advanced robust H∞ Load Frequency Controller (LFC) is developed, which can be used to assist the power system to maintain a stable frequency when accommodating more renewables. Afterwards, I develop a power system sensitivity analysis based-Enhanced Optimal Distributed Consensus Algorithm (EODCA). In the following study, a Modified Consensus Alternating Direction Method of Multipliers (MC-ADMM) is proposed, with this approach it can be verified that the convergence speed is notably accelerated even for complex large dimensional systems. Overall, in the Master thesis, I successfully provide several novel and practical solutions, algorithms and methodologies in regards to tackling both the frequency, voltage and the power flow issues in a future grid with the assistance of energy storage devices. The scientific control and optimal dispatch of these facilities could provide us with a promising approach to mitigate the potential threats that the intermittent renewables posed on the power system in the following decades.