應用群體均值方差映射優化於低慣性電網具虛擬慣性儲能設備之最佳配置

Abstract

在集中式發電中，電力主要由同步發電機產生。在具有巨大同步發電機的電力系統中，頻率由轉子頻率決定，轉子頻率本身取決於原動機功率。在發生故障或干擾的情況下，保留在大型轉子和相關設備中的動能注入電力系統以維持能量平衡。而且，轉子質量的慣性可以防止頻率的突然變化並提高電力系統的穩定性。 現代電力系統從經典的同步發電演變為更加分佈式電力電子非同步發電，大規模滲透可再生能源，如風能和光伏發電。然而，這種新一代模式沒有自然慣性和阻尼特性，這是同步電機的經典特徵。在這樣的電力系統中，系統慣性的缺乏導致對頻率穩定性的負面的影響，導致電網的弱化。 許多研究人員展示如何將儲能器和逆變器與虛擬慣性控制演算法一起使用，從而使它們被視為電網的等效同步發電機，維護並提高了系統穩定性。 本文强调使用虚擬化的惯性控制的能量存储的最优位置，並研究使用基于群的均值方差映射优化算法於低惯性电网中的频率稳定性的重要性。

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).