應用鯨魚最佳化演算法於綠建築空調系統成本最佳化設計-以辦公廳為例

Abstract

空調系統節能是綠建築節能中不容小覷的一部分，為達到理想的綠建築等級，空調設備配置的設計與選擇十分重要。然而，空調系統節能不易，以過往的人工設計及計算方式並無法精準的選擇各項設備的種類及數量，僅憑經驗或為了達到理想等級常導致成本過高，而形成不必要的浪費。 為解決此問題，達到同時考量節能與最低成本之目標，本研究運用鯨魚最佳化演算法，建立出空調節能成本最佳化系統，協助使用者在設備及節能技術的選擇及設計上更加精準並省時。此系統採用世界通用的美國綠建築標章LEED以及台灣綠建築標章EEWH作為理想分數之基準，在達到理想分數的前提下，以演算法搜尋出成本最低的空調設備配置，並以計算用電成本方式將能耗納入考量， 此外，本研究對鯨魚最佳化演算法以及能耗計算方式進行驗證，結果顯示鯨魚最佳化演算法與窮舉法相比，誤差僅1 %，然運算時間卻較窮舉法快66961倍。由此可知，鯨魚最佳化演算法於空調系統設計成本最佳化求解之效率佳且品質好。能耗計算方面，以EnergyPlus進行驗證，結果顯示本系統計算耗電量之方式與軟體模擬出之能耗差距為6~12%，效果尚可。 本研究亦開發清楚簡單的使用者介面以及輸出模式，使用者僅需輸入建築物基本資訊、空調需求及理想分數，即可於短時間之內輸出符合理想分數之最低成本空調系統配置，以作為設計參考之用。

The electric power consumption of air-conditioning system occupies a large proportion of total consumption of a building. Therefore, a good design for the configuration of air-conditioning system takes an important part of saving energy. However, the budget is often the main consideration for most owners. In order to take account of the energy saving and the cost of green buildings simultaneously, this research aims to develop a model for cost minimization design. In the model, EEWH, Taiwanese green building standards, and LEED, U.S. green building standards, are considered and The Whale Optimization Algorithm is applied to search the optimal solution. The model will find the configuration with the lowest cost in the premise of achieving the optimal score of EEWH or LEED. This research verifies The Whale Optimization Algorithm and the calculation of energy consumption. The result shows that comparing The Whale Optimization Algorithm with The Exhaustive Method, the error is only 1%, and the speed is 66961 times that of The Exhaustive Method. It can be seen that the efficiency and accuracy of The Whale Optimization Algorithm is good enough. In the other part, the calculation of energy consumption is verified by EnergyPlus. The result shows that the error of the energy consumption calculation of the system is 6~12 %. In addition, this research develops clear and simple user interface. Through this system, users can easily input basic building information, and get the output of the air-conditioning configuration with the lowest cost and achieving optimal score in a short time.