長久以來，電力消費與尖峰負載預測之方法不外乎使用迴歸模式及時間序列模式。其選用之自變數往往很多，如國民生產毛額(GNP)、價格、冷氣機台數、冷氣度(Cooling Degree Days)、冷氣時…等，因而使得整個預測模式相當複雜。吾人嘗試簡單以「溫度」單一變數來解釋電力消費與尖峰負載，作迴歸模式與時間序列模式並比較各模式的優劣，尋最適模式適配於『電力消費與溫度』、『尖峰負載與溫度』，並且以台灣地區為例，作實證分析研究，研究結果顯示溫度因素在電力消費上確實佔重要地位。文中溫度因素之單位，選用最具代表性之冷氣度(CDD)來表示，方便吾人探討。

Thesis deals with weather derivatives and their position within other financial instruments. It is divided into five main parts. The aim of the first part is to describe the basic mechanism and hallmarks of derivatives as a part of financial market. Also a brief history of weather derivatives is charted. The second chapter is focused on risk and fundamental risk factors and approaches. The weather risk management is presented. The third part discuses weather risk as special kind of risk. This part analyzes the impact of weather on the economy. The differences between weather derivatives and insurance are highlighted. The fourth chapter presents the weather derivatives from the users' points of view; it describes weather derivatives' structure and usage, main underlying indices and also looks on the pricing issues. In the final part the current situation and the possible future evolution of weather derivatives is presented. This part also includes information about the main organizations dealing with either weather management or derivatives.

This study has focused on exploring how climate change, specifically increasing temperatures, impact the cooling demand in buildings on the island of Gotland. Cooling is a necessity for the wellbeing of people, where extreme heat, as a consequence of climate change, can lead to increased mortality. Increased cooling can also cause stress on the electricity grid and its technical components. While there are some previous studies regarding cooling, overall research and data is relatively lacking. Explorative scenarios were used as methods. Four scenarios based on different cooling assumptions on Gotland were explored for the years 2050 and 2090, as well as comparing them to a base year of 2020. The cooling demand for the different scenarios was based on two different projections of increased temperatures, using the climate scenarios RCP 4.5 and RCP 8.5; a generalised energy consumption of space cooling in different residential and nonresidential buildings; and the current floor area of Gotland. The result showed an increasing demand of cooling on Gotland, although the demand varied greatly depending on scenario. The result also briefly analyses the last heatwave in 2018, as well as the impact of two other climate variables of increased temperatures, namely Tropical days and length of heatwaves (Heatwave days). Observed climate variables from 2018 also deviate more much more than the projection of climate variables in the future. Only RCP 8.5 Tropical days for 2090 shows a greater number than the observed data of 2018, showing that deviating warmer years can happen and impact already now. The study concludes that further research is needed on the topic, but that clear trends of increased cooling demand can be seen.