考慮太陽光電系統之晶圓級封裝廠電力品質與可靠度分析

Power Quality and Reliability Analysis in Wafer Level Packaging Factory Considering Photovoltaic Arrays

賴必健(Pi-Chien Lai)

指導教授 ： 洪穎怡

中原大學/工學院/電機工程研究所/碩士(2013年)

https://doi.org/10.6840/cycu201300931

摘要

隨著時代進步與科技發展，人類耗損能源的速度越來越快，全球性異常的氣候變遷現象日益明顯，同時也加速對於地球環境的破壞，為了降低能源使用對地球環境的衝擊，近年來政府提倡節能減碳、推行再生能源(綠能)政策。政府並鼓勵業主自行投資太陽能與風力發電。台電會依據「再生能源發展條例」與政府規定，收購民間電力。在能源價格不斷攀升下，若能將綠色電力引入企業用戶用電系統，一則可以減少電費成本，二則可以提升廠內供電系統之穩定性。

其本文的主旨是探討分析綠色能源併入晶圓封裝廠的電力系統對電力品質的影響與可行性，尤其是電壓驟降事故。並模擬某公司電力系統在於有無太陽能的情況下之可靠度分析。讓公司對於未來，有一個方向是明確的，就是綠色環保的觀念與科技的發展是並重的。

關鍵字

綠色能源 ； 電力品質 ； 電壓驟降

並列摘要

With the progress of technology development nowadays and human consumption of energy, global climate changes very dramatically. This accelerates the destruction of environment. In order to reduce impacts of energy use on the global environment in recent years, the government promotes energy conservation and carbon reduction and promotes renewable energy (green energy) policy. Government encourages
enterprises to invest solar and wind power. TPC follows "Renewable Energy Development Act" and government regulations to acquire the renewable power. If a company introduces renewable power in its factory system, then the cost of electricity can be reduced and the reliability of
the power system can be enhanced.

Purpose of this thesis is to explore the impacts of green energy embedded into the power system of a wafer packaging plant and applicability of power quality, especially voltage sags accidents. The reliability analysis considering the solar PV system is also studied. The company, in the future, has a clear vision that the environmental protection and technological development are equally.

並列關鍵字

Voltage Sag ； Power Quality ； Green Energy

參考文獻

[8] 蔡明杰，「考慮可靠度的面板廠諧波分析與改善」，碩士論文，中原大學，民國九十八年。

[9] R. Billinton, “Distribution System Reliability Indices,” IEEE Transactions

on Power Delivery, Vol. 4, No. 1, pp. 561-568, Jan. (1989)

in Distribution System Planning,” IEEE Transactions on Power Delivery,

[11] Y. Ou and L. Goel, “Using Monte Carlo Simulation for Overall Distribution