本文利用臺電公司近幾年於二次變電所量得之資料，採監錄量測法求得負載模型參數，利用系統發生擾動時所記錄的資料，以基因演算法尋找最佳參數值，再利用模糊基因演算法建立整年度之歸屬函數，進而求得各月份對應之最佳參數來表示負載功率與電壓之關係，經由模擬結果顯示，若單以一組參數模擬整年度之負載特性，在某些月份中，其模擬之誤差值明顯較大，若改採模糊基因模型則其誤差值較為平均，顯示使用模糊基因演算法於負載模型參數確認之可行性。

This paper adopts the data of recent years of Taipower substation to estimate the parameters of load model by using Measured-based Approach. Using the genetic algorithm finds the optimal parameters. And using fuzzy-genetic algorithm constructs the membership function of all year. Then it can get the optimal parameters of each month for representation the relationship between power and voltage. The results show that using a set of parameters to simulate load's characteristics at each month will get larger mismatch at some month. And simulating by using the parameters of fuzzy-genetic model would get the generally mismatch. It shows the workable of load modeling by using fuzzy-genetic algorithm.