太陽能光伏發電系統多點設置之最佳併網容量規劃

Optimal Grid-connected Capacity Planning of Solar Photovoltaic Generation Systems at Multiple Buses

黃俊銘(Chun-Ming Huang)

指導教授 ： 謝世傑

義守大學/電機資訊學院/電機工程學系/碩士(2016年)

摘要

由於環保意識盛行，世界各國正積極發展太陽能發電。根據Solar Power Europe (原EPIA)調查，西元2014年日本、中國及美國在太陽能系統的安裝量上有顯著的成長；日本太陽能光電協會(JPEA)也將日本至西元2020年及西元2030年預期的總裝置容量分別提高至65.7GW及100GW，而在中國大陸的年度裝置容量已躍升全球第一，預計至西元2020年的總裝置容量將達150GW。
本文以台電饋線為例，考量饋線併接多台太陽光伏發電系統，探討其最大併網容量。同時依循台電陽光屋頂百萬座計畫相關之並聯技術與規定，在配電系統中，再生能源併接容量不得超過5000kWp，電壓變動率不得超過2.5%的情況下，進行配電系統多台太陽光伏發電系統併入饋線之規劃探討。
　　本文先利用Matlab結合OpenDSS模擬軟體，執行Power Flow、計算七種情況之太陽光伏發電系統實功率最大允許注入量，以及在不同的七種太陽光伏發電系統裝置容量下之實際注入饋線的實功率；然後，本文亦將以淨現值(Net Present Value, NPV)最大化為目標，運用粒子群優(PSO)法結合OpenDSS與Matlab軟體探討多台太陽光伏發電發電系統之最佳併網容量；最後再針對相關參數做靈敏度分析。

關鍵字

太陽能 ； 電壓變動率 ； 淨現值法 ； 粒子群優法 ； 靈敏度分析 ； 最佳化

並列摘要

Owing to the prevailing environmental awareness, countries around the world are actively developing solar power generation systems. According to Solar Power Europe (original EPIA) investigation, in 2014, Japan, China and the United States have great growth in solar system installation; Japan Photovoltaic Association (JPEA) will increase the total installed capacity to 65.7 GWp and 100 GWp. On the other hand, the annual installed capacity in Mainland China has advanced and ranked the first in the world, and in 2020 the total installed capacity will reach 150 GWp.
This paper takes Taipower feeder No.22 as an example, and consider connecting multiple solar photovoltaic generation systems to investigate the largest connected capacity. Meanwhile, according to the connecting technology and regulations for the Project of Million Roof-Top PVs, the connecting capacity of renewable energy must not exceed 5,000 kWp and the voltage variation percentage must not exceed 2.5% in distribution systems. The thesis will conduct the optimal grid-connected capacity planning of solar photovoltaic generation systems at multiple buses.
　　This thesis utilizes Matlab and OpenDSS simulation software to execute power flow analysis, calculate the maximum allowed real power injection for seven different situations. Furthermore, this thesis takes Net Present Value (NPV) as the objective function, and utilize the particle swarm optimization method, OpenDSS, and Matlab to study the optimal grid-connected capacity of multiple solar photovoltaic generation systems. Final, sensitivity analysis about related parameters is also presented.

並列關鍵字

solar energy ； percentage of voltage variation ； Net Present Value (NPV) method ； particle swarm optimization method (PSO) ； sensitivity analysis ； optimization

參考文獻

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