人類依賴化石能源將會排放大量的溫室氣體，導致全球暖化逐年加劇，因此各國紛紛開始尋找替代能源，而再生能源就是很好的選擇。由於再生能源取自於自然資源，不會被耗盡，生產能源的過程也不會排放溫室氣體。但是若想利用再生能源替代化石能源，首先，需要克服再生能源的間歇性，所以有效的再生能源規劃對地球永續發展至關重要。 隨著科技發展，電器普及化，導致用電量連年增加，加上化石燃料逐年減少，缺電問題將愈來愈嚴重，如此將對人類生活帶來不便。為了解決缺電問題，及緩解全球暖化現象，本研究預利用光電埤塘發電，滿足區域民生用電之需求，此發電系統由浮力式太陽能及儲能電池所組成，為了確保系統可靠度，當電力供不應求時，將以台電與儲能系統作為輔助；電力供過於求時，電力可以儲存或供應給附近區域。 本研究建立的數學模型，屬於多目標混合整數規劃，加入裝置容量、滿足需求等多項限制，為了不影響水面景觀與水中生態，本研究將對浮力式太陽能設置面積加以限制。為了確定模型之效果，將以桃園市復興區作為研究案例，由於此區域擁有豐富埤塘資源，並且屬於高山地形，經常因為強風豪雨導致當地停電，對於人民生活帶來不便。若能對再生能源供給進行規劃，有助於再生能源滿足區域民生用電需求，以及減少溫室氣體排放量。為了了解不同季節太陽能發電量之差異，本研究將以一年的數據進行實驗。 接著蒐集桃園市復興區之用電量，與歷年日射量數據，將數據代入模型，並利用Gurobi軟體進行規劃求解。本研究在不同預算下，以最小化二氧化碳排放成本以及輸電成本為目標，目的為增加再生能源的使用量，進而減少溫室氣體的排放量。同時以最小化輸電成本，進行區域能源分配。藉此獲得光電埤塘滿足民生用電之最佳規劃，達到能 源管理之目的。 ;Global warming mainly results from human activities such as burning fossil fuels and deforestation. The use of renewable energy (RE) serves as an alternative way to reduce greenhouse gas (GHG) emissions. RE is available all across the globe and they are considered environmentally friendly. RE is a source of energy that occurs and replenishes in a natural manner without human intervention. However, if we wish to replace fossil energy with RE, overcoming their intermittent supply is a great challenge. Energy management is critical for the sustainable development of our environment. Nowadays, with the advance of science and technology, the popularity of electrical appliances has led to an increase in electricity consumption. Fossil fuels have been in great demand, and power shortage has become a serious issue bringing inconvenience to our daily lives. In order to prevent power shortage and global warming, this research attempts to meet residential electricity demand with floating photovoltaic power. This power generation system consists of floating photovoltaic panels and a storage unit. This research adopts multiple-objective mixed integer programming to minimize CO2 emission costs and the costs to transport energy. Our focus to minimizeCO2 emission costs is to increase the use of RE, thereby resulting in a reduction of GHG emissions. Moreover, regional energy allocation is accomplished with the minimization of transmission costs. This will achieve optimal planning to meet residential electricity demand.
