再生能源以風力發電及太陽能發電最具環保及分散式等優點,所以發展風力發電及太陽能發電對於環境之保護及再生能源之開發有重大意義。然而風力發電併入電力系統後會延伸與許多問題,例如發電效益評估、併聯技術及調度排程等。 本論文將以風力發電系統、太陽能發電系統、柴油發電機組及充電電池組所組成一獨立發電系統,考慮風力及太陽光之氣候不確定因素進行上述之獨立發電系統短期排程,使柴油機組之成本最小,並滿足所有運轉限制式。本論文將風力及太陽光為模糊參數之拉格朗日式子表示之,並以基因演算法配合處罰函數求解最佳化問題。 本文以一獨立發電系統進行發電排程之測試,分別以基因演算法模擬未考慮風力及太陽能模糊化時與考慮風力及太陽能模糊化時之發電排程。由測試結果顯示,本研究所提出之方法對發電排程問題之最佳解具有相當之可行性。
Renewable energy including wind power and solar power has advantages, e.g., environmental protection. Developing the wind power generation and solar power generation has great significance to the protection of the environment and development of the renewable energy. However, the wind and solar power generation will cause a lot of problems after being incorporated into the power system, for example, estimating benefit of generating, commitment technique, and scheduling of power generation, etc. This thesis deals with independent generation system that includes wind power, solar power, diesel unit and rechargeable battery group. This thesis considers the uncertain factors of climate (e.g., wind and sunlight) and investigates the short-term generation scheduling of the above-mentioned independent generation system. The cost of diesel units is minimized and all operation constrains are satisfied. The wind power and solar power modeled by fuzzy theory are expressed with the Lagrange multiplier as well as membership function for reducing the computational complexity using the genetic algorithm cooperated with penalty function. The simulations of the non-fuzzy and fuzzy generation scheduling were performed individually. An independent generation system was used as a test system for showing the applicability of the proposed method.