研究生: |
柯智涵 Chih-Han Ko |
---|---|
論文名稱: |
基於調頻輔助服務策略之儲能系統老化分析 Evaluating and Analyzing the Degradation of Battery Energy Storage System Based on AFC Control Strategies |
指導教授: |
郭政謙
Cheng-Chien Kuo |
口試委員: |
張宏展
Hong-Chan Chang 陳鴻誠 Hung-Cheng Chen 黃維澤 Wei-Tzer Huang 楊念哲 Nien-Che Yang 郭政謙 Cheng-Chien Kuo |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 電機工程系 Department of Electrical Engineering |
論文出版年: | 2022 |
畢業學年度: | 110 |
語文別: | 中文 |
論文頁數: | 84 |
中文關鍵詞: | 電池儲能系統 、調頻輔助服務 、電池老化 、自動頻率控制 |
外文關鍵詞: | battery energy storage system, frequency regulation service, battery degradation, automatic frequency control |
相關次數: | 點閱:377 下載:5 |
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電池儲能系統(battery energy storage system, BESS)之快速反應特性非常適合調頻輔助服務或即時備轉之應用。儲能系統之調頻輔助服務又能大致分為兩個大類別:動態調頻備轉(dynamic regulation, dReg)、靜態調頻備轉(static regulation, sReg),其中目前又包含三種不同的控制模式:dReg0.5、dReg0.25及sReg,由於響應曲線的不同,每一種控制模式對於相同的頻率,會有不同的輸出需求,相對的也會有不同的電池充電狀態(state of charge, SOC)曲線。
電池儲能系統的主要組成元件為電池,而鋰離子電池在長期的使用下,老化現象難以避免,其中老化表現又與電池使用情形與當前老化狀態有著極大的關聯。因此不同的調頻備轉模式、不同的充放電率(C-rate)與策略中不同的SOC目標準位,都會有不同的電池老化速度。本研究將基於相同的頻率,模擬不同的調頻備轉模式在不同C-rate與不同的電池SOC目標準位下相應的SOC曲線。其後將建置一個基於鋰鐵電池(LiFePO4 battery, LFP battery)老化公式與雨流計數演算法之電池老化模型,藉此分析不同使用情境下的SOC曲線,進一步探討各種不同情境下儲能系統之容量老化情形。
本研究主要的貢獻為:比較與分析不同調頻備轉模式下,C-rate與SOC目標準位對電池壽命的影響,並以台灣電力股份有限公司提供之輔助服務計費公式估算各情境截至電池EOL時的總利潤,扣除儲能系統建置成本,以電池壽命的觀點進行各種情境之淨收益比較,期能夠在規劃儲能案場設備規格及控制策略研製時,給予一些參考依據。
The fast response characteristics of a battery energy storage system (BESS) are very suitable for frequency regulation services or spinning reserve applications. Frequency regulation services can be classified into two main categories: dynamic regulation (dReg) and static regulation (sReg), which currently include three different control modes: dReg0.5, dReg0.25, and sReg. Based on the response curves, each control mode will have its output requirements for the same frequency and correspondingly will have different battery state of charge (SOC) curves.
The main component of BESS is batteries, and the degradation of lithium-ion batteries is inevitable under long-term use. The aging performance is closely related to the usage and current aging state; therefore, with different control modes, C-rates, and SOC targets in the strategy, the batteries will age with totally different speeds. This study will simulate the SOC curves of control modes under different C-rates and different battery SOC targets based on the same frequency series. Afterward, a battery aging model based on LFP battery aging formula and rainflow counting algorithm will be built to estimate the corresponding battery life by analyzing the SOC curve under different usage scenarios.
The main contributions of this study are comparison and analysis of the effects of C-rate and SOC target on battery lifetime under different control modes. Finally, this study will use the billing formula provided by Taipower to estimate the total profit of each scenario until the battery EOL, deduct the construction cost of the energy storage system, and compare the net income of various scenarios from the perspective of battery lifetime.
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