OPTIMAL PLACEMENT OF ENERGY STORAGE WITH VIRTUAL INERTIA CONTROL ON A LOW INERTIA POWER GRID USING SWARM-BASED MEAN-VARIANCE MAPPING OPTIMIZATION

• Main Author: Israjuddin
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/46201
• Institution: Institut Teknologi Bandung

In centralized electric power generation, electric power mainly generated by Synchronous Generators (SGs). In a power system dominated by SGs, the frequency is determined by the rotation frequency, which depends on the prime mover power. In the event of a fault or disturbance, kinetic energy is stored in a massive rotor, and related equipment is injected into the power system to maintain energy balance. Besides, the inertia of the rotating mass prevents sudden changes in frequency and increases the stability of the power system. Modern power systems evolved from classical synchronous generation to more distributed power electronic-based non-synchronous generation, with large-scale penetration of renewable energy sources (RESs) such as photovoltaic and wind turbines. However, this new generation mode does not have natural inertia and damping properties, which is a classic feature of synchronous machines. In such a power system, the lack of system inertia causes undesirable influence to frequency stability, leading to weakening of the grid. Many researchers have shown how to use energy storages and inverters with virtual inertia control algorithms so that they are recognized as synchronous generators to power grids, maintain and improve system stability. This thesis emphasizes the importance of the optimal placement of energy storage with virtual inertia control for frequency stability in a low inertia power grid using Swarm-Based Mean-Variance Mapping Optimization (MVMOS).