近年來再生能源的興起，雖有效地緩解對於化石燃料的依賴，但其間歇性及不可調度性仍為一大問題。儲能系統的導入除了有助於再生能源的整合，確保能源供應的穩定性，亦可提高電網的效率及可靠性以拓展應用性。然而，隨著再生能源需求的提升，雖帶動儲能產業的發展，但目前仍屬於新興市場階段，除了深受政策及環境的影響，成本的高低亦為取得成功的重要因素之一。

本研究除了考慮技術的成熟性，並考量我國現有儲能案場所選用的電池類型，以鋰離子電池及釩液流電池作為研究對象，建立單因子及雙因子的學習曲線模型以評估儲能技術未來的成本趨勢。此外，藉由敏感度分析，設定不同情境，進一步地探討各類參數對未來儲能技術發展競爭力之影響。

分析結果顯示，單因子模型對鋰離子電池(電動車)、鋰離子電池(大型儲能)及釩液流電池(大型儲能)所估算的學習率分別為19.15%、16.24%及12.82%；若加入創新因子的雙因子模型，鋰離子(大型儲能)之學習率提高至21.70%，突顯出研發資源的投入能夠有效地促進技術成本的下降。相較之下，釩液流電池的學習率微幅成長至13.84%，成本進一步下降的幅度並不明顯。總和上述，儘管鋰離子之初始成本相較於釩液流電池較為高昂，但近年來隨著技術創新及材料的研發，鋰離子成本降幅大，應用範圍廣泛，被視為未來具有發展潛力的儲能技術之一。除此之外，透過不同情境的假設可知，除了材料改良及技術的精進，政府政策為未來推廣儲能系統不可缺少的因子，有助於刺激產業發展及市場潛力。

In spite of the fact that renewable energy has effectively alleviated the dependence on fossil fuel resources in recent years, its intermittency and lack of dispatchability are recognized as the main shortcomings. Thus, the energy storage system has introduced not only the capability of integrating renewable energy to stabilize the output in energy supply, but also the improved efficiency and reliability for grid network to extend the applications. However, renewable energy is still viewed as an emerging market despite the fact that its increased demand has resulted in the development of energy storage industry. Therefore, besides its dependence on policies and environment, the cost is also a factor we must take into account.

In this study, we considered the maturity of technology and adopted the lithium-ion battery and Vandium Redox Flow Battery (VRB) as the research subjects by taking the existing pilot plant of energy storage systems in Taiwan into consideration. We constructed models of one-factor and two-factor learning curves to estimate the cost trend of energy storage technologies in the future. In addition, we arranged scenario settings to further discuss the relationship between those parameters and the competitiveness of developing energy storage technologies.

The results showed the learning rates of lithium-ion battery (EV), lithium-ion (Utility) and VRB (Utility) were 19.15%, 16.24% and 12.82%, respectively in the one-factor model. After introducing the two-factor model with innovative indicator, the learning rate of lithium-ion battery (Utility) increased to 21.70%, which revealed that the investment of R&D resources can effectively reduce the cost. In comparison, the learning rate of VRB only increased to 13.84%, and the cost reduction was not obvious. To sum up, although the initial cost of lithium-ion battery is higher than VRB, the cost for lithium-ion battery has dropped recently with the technical innovation and R&D. Widely used in various fields, lithium-ion battery is recognized as one of the promising energy storage technologies in the future. Also, according to scenario settings, if we want to promote the energy storage system for the development of relevant industry as well as its market potential, not only the improvement of material and engineering, but also government policies are needed.

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