Optimal Planning of Virtual Inertia Installations to Improve the Power System Frequency Response

Abstract

In recent years, the power system has seen a fast transformation from one primarily based on fossil energy to one where renewable energy, especially wind and solar power, takes a more significant proportion in the energy profile. With the shift in energy profile come the changes in the electricity generation units. The solar panels and wind turbines replace the synchronous generators in electricity generation. Most solar and wind generation units are converter-interfaced. In contrast, the synchronous generator is connected to the power grid directly. For this reason, the future power system of a high level of renewable penetration will exhibit dynamic properties different from the traditional power system, which poses many challenges. One of the challenges is related to frequency stability. The frequency stability of a traditional power system is secured with a three-level frequency control scheme. The scheme is composed of three frequency regulation mechanisms at different time scales. The fastest control mechanism, named primary frequency control, needs about 5 s to be fully deployed to arrest the frequency drops or overshoots. After that, the other two frequency secondary and tertiary frequency control mechanisms are then slowly deployed to bring the system frequency back to the nominal value. Under this control scheme, the overall active power generation and consumption in a power system get balanced, and the power frequency variation is limited within a narrow range around a nominal value. However, before the primary frequency control is sufficiently deployed, the system relies on the natural inertia response of the synchronous generators to maintain the active power balance at the sacrifice of changes in the generators' rotational speeds. As the power frequency is decided collectively by the rotational speeds of all synchronous generators in the system, larger system inertia means smaller power frequency variation when subject to the same disturbance. Since there is no lack of system inertia in a synchronous generator-dominant power system, the power frequency variation with the help of the tertiary control scheme is usually contained within a limited range. For a future power system with more and more synchronous generators being displaced by converter-interfaced generation (CIG) units, the system inertia decreases. The tertiary frequency control scheme alone can no longer limit the power frequency variation within an acceptable range. For this reason, techniques were proposed to emulate inertia response on a converter-interfaced generation unit. Apart from the level of total system inertia, studies show that the spatial distribution of system inertia can also influence the frequency response. Under this context, a well-planned virtual inertia installation at selected locations can achieve a satisfactory level of improvement on frequency response at a low investment cost. This thesis work aims at developing a systematic method to search for the most economical plan of virtual inertia installations while ensuring a satisfactory level of frequency response. In order to derive the most economical plan of virtual installation, a mathematical optimization problem is proposed with constraints formulated with the help of a newly proposed metric of inertia response that quantifies the influence of inertia on the system frequency response. The formulation of the optimization problem considers all possible combinations of loading and renewable generation profiles. Two methods are proposed to solve the optimization problem of the mixed-integer type. The first one is based on the classic scheme of dynamic programming. The second method adopts a relaxation technique based on the sparsity promotion or Majorize-Minimization (MM) method. Furthermore, parallel and cloud programming techniques are used to facilitate computation speed. Other minor contributions include a design of a supplementary controller on top of the inertia emulation control to improve the voltage stability of a converter-interfaced generation unit. Finally, case studies were conducted on a modified Southeast Australian power system against different types of faults to validate the performance and investment cost of the virtual inertia installation plan givens by the proposed method in comparison with two other methods. The result shows that the virtual inertia installation plan given by the proposed method produces better performance while at lower investment costs

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