Distributed Secondary Frequency Control Algorithm Considering Storage Efficiency

作     者：Megel, Olivier Liu, Tao Hill, David J. Andersson, Goran 

作者机构：Swiss Fed Inst Technol Power Syst Lab CH-8092 Zurich Switzerland Univ Hong Kong Dept Elect & Elect Engn Hong Kong Hong Kong Peoples R China Univ Sydney Sch Elect & Informat Engn Sydney NSW 2006 Australia 

出 版 物：《IEEE TRANSACTIONS ON SMART GRID》 (IEEE智能电网汇刊)

年 卷 期：2018年第9卷第6期

页      面：6214-6228页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

主　　题：Frequency control storage distributed algorithm storage efficiency 

摘      要：Storage technologies, such as batteries, have higher ramping capability than conventional generators, and so they could lead to better dynamic tracking performance when following a frequency control signal. However, storage units are energy constrained, so the energy content of the signal they follow should preferably be low. Our first contribution is a method for decomposing the target signal into a different signal for each generator and each storage unit, depending on their characteristics and on the storage energy levels. Faster units receive signals with higher ramping rates. Storage units with low energy-to-power ratios (tau(i)) receive signals which are energy-neutral (efficiency-corrected) in shorter time frames than the signals for storage units with larger tau(i). Our method is particularly suitable when the tau(i) vary by orders of magnitude over the storage population. It dispatches the units by solving a modified economic dispatch problem. The energy content of the storage unit signals is managed through a term penalizing energy level deviation in the cost function. The second contribution is a distributed implementation of our method, which approaches the dispatch of its centralized counterpart. Our distributed implementation innovates compared to other distributed algorithms in that it considers non-unity storage efficiency. Using a population of 1000 units we show that the distributed implementation is: 1) up to 700 times faster than the centralized implementation, therefore allowing for real-time implementation with a large number of units;and 2) robust to loss of communication links.