近年來隨著環境永續理念與國際能源議題快速興起，使得再生能源占比大幅提高，其發電間歇性導致電網穩定度受到考驗，為了使太陽能發電功率變動符合國際規範之限制，裝設儲能系統以進行太陽能輸出平滑化被視為最有效的解決方法之一，然而儲能系統之高成本問題將導致太陽能業者效益受損，且既有方法中較少可適用於多種場域並確保有效性。
本文提出配合太陽能發電場域發電特性之最佳太陽能發電平滑化系集控制方法，其整合經驗模態分解、指數移動平均及斜坡率控制三種既有平滑化方法，並最佳化三者之權重分配以進一步提升儲能系統運用效能，此外亦根據案場發電特性進行最佳儲能建置容量規劃，過程中假設違反太陽能發電輸出變動率須繳納罰金，本文納入考慮不同程度之違反變動率罰金，並於控制法中導入棄光策略，以協助太陽能業主藉承擔部分罰金及棄光損失換取儲能容量需求降低之可能性，進而減低裝設儲能之高額成本，以達到太陽能發電場域售電利潤最大之目標。
本文以沙崙科學城C區智駕實驗室及龍井太陽能案場之發電數據為基礎，探討不同平滑化控制方法對案場總售電收益、儲能建置容量需求與成本、平滑化違約罰金及投資淨現值之影響，結果顯示本文提出之系集控制方法可綜合各方法優點，在各種模擬情境下皆可獲得最佳投資淨現值，並有效平滑再生能源注入電網之功率，未來可用於太陽能相關業者執行輸出平滑化控制與儲能容量需求評估，並可供政府有關單位制訂管制標準之參考。

In recent years, the penetration rate of renewable energy (RE) has gradually increased. The intermittency of energy generation would lead to the instability of power grid. To deal with this, using energy storage system (ESS) to smooth its intermittent power has become one of the mainstream solutions. However, due to the high investment cost, the capacity of ESS should be appropriately plan. Besides, although there are lots of PV smoothing methods, seldom of them can guarantee that they are suitable for a variety of PV generation fields and obtain the best results.
Therefore, this thesis proposes a photovoltaic (PV) generation smoothing ensemble control scheme. It integrates three existing smoothing methods, empirical mode decomposition, exponential moving average, and ramp rate control, then optimizes the ensemble weights based on the real PV generation data and meanwhile optimizes the capacity of ESS within planning period. It is assumed that there will be different levels of penalty for violating the PV fluctuation rule, and also considers the active power curtailment (APC) strategy. This method can improve the stability of the power grid, reduce the construction cost of ESS, and achieve the goal of maximizing the profit of the PV generation field.
Based on the PV generation data from Shalun and Longjing, this thesis will explore the effect of different smoothing control methods on the total revenue of the field, the demand and cost of ESS, the violation penalty, and the net present value (NPV) of investment. From the simulation results, the ensemble control scheme can integrate the advantages of each substructure, obtain the best NPV of investment, and smooth the power output at the point of common coupling (PCC). In the future, the proposed method can be used for solar energy related companies to implement PV smoothing control and ESS capacity planning, and can be taken as a reference for government agencies to formulate the standards.

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