建立颱洪時期抽水站智慧型最佳化操作規則

Abstract

都市快速的開發導致地面透水性降低、逕流量增大、集流時間減少等問題，如何能有效地將都市內水排至河川，抽水站成為都市防洪系統重要環節之一。目前現有抽水站操作規則僅根據前池水位決定抽水機組開啟數量，而臨場即時操作仍須依賴有經驗操作人員，無法真正根據操作規則進行操作；依抽水站實際操作時，需考量儘速將內水排至河川、抽水機組開啟數量、起抽水位(前池水位)、抽水機抽水效能(揚程)等因素。亦應避免抽水機組在短時間內啟閉操作頻繁。本研究同時考慮颱洪時期前池水位與揚程等因素對抽水量之影響，提出以非優勢排序遺傳演算法(NSGA-II)搜尋抽水站最佳化多目標操作規則。 本研究以臺北市之玉成抽水站為研究區域，建立玉成抽水站多目標之最佳化操作模式，應用NSGA-II特有之非優勢排序及擁擠距離比較進行多目標最佳化操作規則搜尋，並應用多目標函數值評定該染色體之優劣，以挑選柏拉圖峰之最佳解。本研究共建立兩種多目標最佳化模式，以探討不同目標函數設定所得之最佳操作規則的模擬結果表現。Model A之三目標函數為前池水位標準差總和最小、前池最高水位總和最小與抽水機操作次數總和最小；Model B則將Model A的第一個目標函數改為前池前後時刻水位差總和最小。以14場颱洪事件搜尋兩種模式之最佳操作規則，3場颱洪事件依兩種模式所得之最佳操作規則進行操作歷程模擬，並比較現有規則操作與歷史人為操作之成效。 結果顯示，Model A僅在第一個目標較現有操作規則差，其他兩個目標值皆優於現有操作規則；Model B則在三個目標值皆較現有操作規則優異，其改善率分別可達43.14%、2.79%及71.27%。Model A在操作次數較Model B頻繁，操作次數歷程明顯比Model B震盪，但此二模式皆比抽水站現有操作規則平穩，且可有效降低抽水機之操作次數。 整體而言，本研究所提出兩種抽水站多目標操作規則模式皆可避免抽水機在短時間內頻繁開啟，且模擬操作歷程與具豐富經驗之人員實際操作歷程近似，故本研究之最佳化多目標操作規則可應用於發展玉成抽水站自動化操作系統。

The rapid urbanization in metropolitan areas causes less water infiltration, flashy floods and shorter rainfall concentration time. To effectively manage urban inundation problems, pumping stations play an important role for flood mitigation in urban areas. The operation rules for pumping stations have been designed to determine the number of duty pumps based only on the water levels of the front storage pool (FSP). Nevertheless, current pump operation depends mainly on experienced operators rather than on pump operation rules. In practice, pump operation needs to not only consider the discharge amount to rivers, the number of duty pumps, FSP water levels, as well as the water head difference of the surrounding river and the FSP but also avoid switching a pump on or off too frequently within a short time. Therefore, this study aims to propose an approach to deriving multi-objective optimal pump operation rules through the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) in consideration of the water head difference of the surrounding river and the FSP as an objective during typhoon periods for urban flood control. The Yu-Cheng pumping station of Taipei City in Taiwan is the study area. The optimization search of the multi-objective pump operation rules is conducted by the non-dominated sorting and crowding-distance calculation of the NSGA-II, in which the objective functions identify good chromosomes in order to select the optimal pump operation rules from the Pareto-front. Two NSGA-II models with different objective functions are established to investigate the impacts of various objective functions on pump operation rules in this study. The objective functions of Model A include: (A1) minimize the standard deviation of FSP water levels at t+i and t+i+1; (A2) minimize the accumulated peak FSP water levels; and (A3) minimize the accumulated absolute differences on the numbers of duty pumps at t+i and t+i+1. Model B has the same objective functions as Model A except for the first objective function, which is modified to minimize the absolute differences of FSP water levels at t+i and t+i+1 in Model B. This study first adopts 14 typhoon and storm events to search the optimal pump operation rules for the two models and further applies 3 additional events to simulating the optimal pump operations of the two constructed models, for which the two optimization models are compared with current pump operation rules and historical operation. Results indicate that Model A performs better than current pump operation rules, except for the first objective function (A1). Model B performs better than current pump operation rules in terms of all three objective functions, for which the improvement rates can achieve 43.14%, 2.79% and 71.27% for objective functions B1, B2 and B3, respectively. In addition, Model A produces more fluctuations than Model B, which means pumps are switched on and off more frequently by Model A. However Model A and Model B perform more stable than current pump operation rules and thus can effectively reduce the number of duty pumps for the whole operational period. As a consequence, the derived multi-objective optimal pump operation rules can avoid switching a pump on or off too frequently within a short time, and it makes little difference in pump operations based on the optimal pump operation rules suggested by the proposed model and the experiences of operators. The multi-objective optimal pump operation rules of the propose models are considered superior to current pump operation rules, and therefore can provide useful information to operators at pumping stations for real-time urban flood control.