考慮成本最小化及可靠度之分散式電源規劃

Distributed Generation Planning Considering Cost Minimization and Reliability

梁若晨(Ruo-Chen Liang)

指導教授 ： 洪穎怡

中原大學/工學院/電機工程研究所/碩士(2010年)

https://doi.org/10.6840/cycu201000896

摘要

近年來石油價錢飆漲，溫室效應及二氧化碳排放量議題逐漸被重視，使得分散式電源的研究與發展更加熱絡。
本論文應用Fuzzy-c-Mean(FCM)、馬可夫模型及基因演算法求解小型獨立電力系統電源規畫問題。首先應用FCM分類法將風力機出力、太陽能電池出力及負載分類，以提高馬可夫模型分析之準確度。再運用馬可夫模型計算其機率、頻率及持續時間，可加快基因演算法算運算速度。最後考慮可靠度指標LOLP及LOLE，並結合應用基因演算法求出符合可靠度指標之系統新增電源最低成本。因分散式電源成本較高，故裝設柴油機並考慮二氧化碳排放量，可有效提高系統可靠度並降低成本。
本論文應用馬可夫模型可使基因演算法模擬時間較時間依序法減少近百倍且最小成本之誤差皆於5%以內。

關鍵字

分散式電源 ； 風力機 ； 太陽能電池 ； 可靠度 ； 模糊分類 ； 基因演算法 ； 馬可夫模型

並列摘要

Due to the increase in fossil fuel prices , concerns about greenhouse effect and CO2 emissions, the use of renewable energy sources as an alternative for existing fossil-fueled power plants has been widely studied.
The thesis uses Fuzzy-c-Mean (FCM), Markov model and Genetic Algorithm(GA) to study the generation expansion in a small isolated power system . The first step of the thesis, use FCM to classify wind turbine, photovoltaic and load. This step can make more accuracy in the next step, Markov model. Markov model, which makes Genetic Algorithms more efficient, is used to calculate probability, frequency and duration. Finally the reliability indices Lose Of Load Probability (LOLP) and Lose of load Expectation (LOLE), are considered. The cost of distributed generation is too high. This paper considers the diesel generator in the power system and uses Co2 constraint to limit the number of diesel generators, This help improve the reliability and reduce cost.
The difference between the results of Markov Model and Time Sequence Genetic Algorithm is less than 5%. The CPU time used by the proposed method can be reduced greatly.

並列關鍵字

Distributed Generation ； Wind Turbine ； Photovoltaic ； Fuzzy Clustering ； Markov Model ； Genetic Algorithm ； Reliability Index

參考文獻

[1] C. Marnay and G. Venkataramanan, “Optimal Technology Selection and Operation of Commercial-Building Microgrids”, IEEE Transactions on Power Systems, Vol. 23, No. 3, pp.975-982, August 2008.

[2] F. Katiraei, M. R. Iravani and P. W. Lehn,“Micro-Grid Autonomous Operation During and Subsequent to Islanding Process”, IEEE Transactions on Power System Delivery, Vol. 20, No. 1, pp.248-257, January 2005.

[3] A.G. Tsikalakis and N.D. Hatziargyriou, “Centralized Control for Optimizing Microgrids Operation”, IEEE Transactions on Energy Conversion, Vol 23, No. 1, pp. 241-248, March 2008.

[4] C. Marnay, G. Venkataramanan, M. Stadler, A.S. Siddiqui, R. Firestone, and B. Chandran, “Optimal Technology Selection and Operation of Commercial-Building Microgrids ”, IEEE Transactions on Power Systems, Vol. 23 , No. 3, pp. 975-982, August 2008.

[5] J. K. Kaldellis, “Optimum Autonomous Wind–Power System Sizing For Remote Consumers, Using Long-Term Wind Speed Data”, Applied Energy, Vol. 71, No. 3, 2, pp. 215-233, March 2002.