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題名 | 以粒子群優法作解制環境下機組含有禁止運轉區之經濟調度=Particle Swarm Optimization for Deregulated Economic Dispatch with Probhibited Operating Constraints |
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作者姓名(中文) | 梁瑞勳; 劉建宏; | 書刊名 | 科技學刊. 科技類 |
卷期 | 13:1 2004.01[民93.01] |
頁次 | 頁13-23 |
分類號 | 448.115 |
關鍵詞 | 經濟調度; 代輸成本; 廢氣排放量; 禁止運轉區; 粒子群優法; Economic dispatch; Wheeling cost; Emission; Prohibited operating zone; Particle swarm optimization; |
語文 | 中文(Chinese) |
中文摘要 | 隨著電力自由化,原本一體的發、輸、配電業將分離為各個獨立電業公司,此種新型電力型態,將得經濟調度所慮的問題不單單只是燃料成本,亦須把因輸電業獨立所引出的代輸成本併入進來,且因環保意識的日漸抬頭,所以亦須把廢氣排放量問題併入考量。另機組之限制條件包含機組的電力輸出上限、下限及禁示運輸區;系統之限制條件包含供需平衡、備轉容量,且將系統線路之傳輸限制皆一併考慮進來,使得更能符合實際發電情況。 本文提出一套模擬生物群體的人工智慧法,即粒子群優法,作解制環境下包含燃料成本、廢氣排放量和代輸成本之多目標經濟調度問題。此演算法具有架構簡單、平行運算、收斂快速及容易跳脫最佳化的特性。最後並以二個電力系統例子來驗證粒子群優法的有效性,且以進化規劃法來作相同問題,比較其結果。由結果顯示粒子群優法確實可得到相當好的結果。 |
英文摘要 | With the deregulation of power industry, the generation, transmission, and distribution will therefore gradually divided into independent business entities. The new type of power entities that is an optimized objective function including the generation cost, the wheeling cost and emission cost. Moreover, the constraints that include the limitations of the system and units must be met. In this paper, we present an artificial intelligence algorithm that is particle swarm optimization (PSO) based on simulations of bird flocking to economic dispatch in the deregulated environment. The algorithm has some characteristics, like rapid convergence, simple frame and the ability of going over local solutions toward global optimal solution. Finally, two power systems are used to verify the advantage of the PSO. We also present evolutionary programming, the other artificial intelligence algorithm compared with the PSO. It is concluded form the results that the proposed approach is very effective in reaching economic dispatch. |
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