傳統大型發電系統對台灣整體電力系統扮演重要地位，但也排出過量影響環境及人體健康物質(二氧化碳、二氧化硫與氟化物..等)，因此為了達成兼顧成本及符合二氧化碳減量之雙重目標，可將區域能源之汽電共生系統視為最佳選擇。汽電共生系統(Cogeneration System)可同時產生蒸汽與電力，在工業廠區內如需要大量蒸汽及電力時，可由決策者依自身要求興建符合之汽電共生廠，並可就近供應蒸汽與電力於製程廠，以免除能源輸送之損失。本文探討考量各種二氧化碳效應因素下與電力最佳調度間策略關係，利用引進多項指標方式，如成本對二氧化碳排放抵換曲線(Trade-off Curve)與二氧化碳減量之增量發電成本曲線(Incremental Cost for CO2 Reduction Curve, ICCR Curve)藉以評估二氧化碳對經濟調度之影響。綜合上述指標，更進一步利用單、雙目標規劃之方式，並滿足決策者需求下，建立二氧化碳影響下之電力調度規劃，使決策者能兼具環保與經濟因素之議題。並利用改良式粒子群演算法配合編碼方式來助於避免提早收斂及快速求得高品質之最佳電力規劃解。總結來說，以南部某煉油之汽電共生系統進行模擬測試，並針對背壓式蒸汽渦輪機及抽汽冷凝式渦輪機混合系統之高壓、中壓製程蒸汽和電力需求考量，且由尖峰、半尖峰、離峰三種情境下之研究結果得知，其調度結果確實能夠有效考量二氧化碳減量及碳價交易對於能源成本之影響，並達到兼顧環保與經濟之目的。

Conventional large-scale power generation systems are crucial in the overall power system in Taiwan. However, these systems emit excessive amounts of substances that negatively influence the environment and human health, e.g. carbon dioxide (CO2), sulfur dioxide (SO2), and fluoride (F). Thus, to achieve both cost and carbon reductions, cogeneration systems are deemed the optimal choice for generating regional energy. Cogeneration systems can simultaneously generate steam and electrical power, and customized cogeneration power plants can be established according to the specific requirements of policy makers for industrial complexes that require large amounts of steam or electrical power. These cogeneration plants can then provide steam or electrical power to nearby processing plants, thereby preventing power transmission loss. Considering the various effects of CO2 emissions and their strategic relationship with optimal power dispatch, this study used numerous indicators, e.g. CO2 emission trade-off curve and an incremental cost for CO2 reduction curve to evaluate the influence that CO2 has on economic dispatch. In addition, by integrating the indicators and adopting single/dual objective planning methods, this study developed a CO2-influenced power dispatch plan that satisfies the demands of policy makers, accounting for both environmental and economic considerations. The improved particle swarm optimization (IPSO) method combined with coding proposed in this study further prevents premature convergence and facilitates the rapid calculation of a high-quality optimal power planning solution.
In this study, simulation tests were performed on a cogeneration system of an oil refinery in Southern Taiwan. These tests focused on the steam and electrical power requirements for the high- and medium-pressure processing of a hybrid steam turbine system (back pressure and extraction condensing). Three conditions were subsequently tested, namely, peak, semi-peak, and off-peak conditions. The findings of this study suggest that the dispatch outcomes effectively accounted for the influences that CO2 reduction and changes in carbon prices have on the overall power generation costs, thereby achieving both environmental protection and economic efficiency.

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