田口-免疫演算法應用於含風力發電之火力機組調派

Thermal Unit Commitment with Wind Farms Using Taguchi-Immune Algorithm

劉威良(Wei-Liang Liu)

指導教授 ： 陳昭榮

國立臺北科技大學/電資學院/電機工程系研究所/碩士(2012年)

摘要

近年來國際能源價格不斷高漲，許多國家意識到再生能源的重要性，而再生能源技術中以風力發電為最成熟、具有商業化發展前景的新能源技術。機組調派是指一天24小時中規劃發電機組排程及發電量，其中必須滿足發電機及系統上各項限制條件，有效地調度各台發電機，並且需要在足夠的備轉容量下運轉，其中限制式以最小起/停機時間及斜率變動量為本文考慮之重點。將風力與火力機組有效地結合，以減少石化能源的使用，達到全球關注的環保議題。
因為風力具有不確定性之因素，故本論文假設已知隔天最有可能的10種風力發電資料，使火力機組在其風力發電資料下達到近似最佳化的調度與排程，並且加入了輸電線損失，以符合實際系統的運轉情況。演算法則使用田口-免疫演算法應用於風力發電下進行火力機組調派，利用免疫演算法之親合度篩選，可有效避免運算太過相似的解，以減少運算次數，為了增進搜尋近似最佳解，在免疫演算法於交配與突變間，插入田口直交表實驗，此方法能有效搜尋全局最佳解。
本文以IEEE 30-Bus及IEEE 118-Bus之系統來驗證其功效，並與免疫演算法及基因演算法做比較，模擬結果證明該方法是可行的，並比其他演算法在相同時間下更能獲得近似最低成本。在此，期望能給調度人員提供更經濟之參考。

關鍵字

免疫演算法 ； 免疫-田口混合演算法 ； 機組調派 ； 風力發電

並列摘要

Due to the increase of international energy prices in recent years, many countries are aware of the importance of renewable energies. To this day, wind power is the most advantageous renewable energy with a technological prospect for business development. Each unit is committed to aim a schedule power plan for 24 hours a day. It has to meet various constraints on the generators and in the systems, also to schedule each generator effectively, as well as the operation requirement for adequate spinning reserve. We focus on the minimum of the on and off time and constraint the ramp amount in this different way. To achieve this global issue, the acquisition of wind power may reduce fossil fuels efficiently and protect the ecosystem and environment.
Due to the uncertainty factors of wind, we can possible assume that ten possibility wind power data will be known the next day and this will allow to achieve approximately optimization of dispatch and unit commitment in these wind power data. By joined the transmission line losses, in order to comply with the actual functioning of the system the result would be exponential. The Taguchi - immune algorithm is used to deploy thermal units when wind turbines are operating. The immune algorithms’ affinity screening will avoid computing similar solutions effectively in order to reduce the numbers of operations. For enhancing the search result of finding optimal solution, we insert the Taguchi orthogonal array experiment between crossover and mutation of the immune algorithm. This method can search the global optimal solution effectively.
In this thesis, the IEEE 30-Bus and IEEE 118-Bus systems are applied to verify their effectiveness and to compare the immune algorithm and genetic algorithm. Simulation results are approximated by the lowest cost at the same time. This proves that the method is better and more feasible than other algorithms. By this point, we would expect to give the dispatchers a more performing and economical reference.

並列關鍵字

Immune Algorithm ； Hybrid Taguchi-Immune Algorithm ； Unit Commitment ； Wind Power

參考文獻

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