CAJ | 학술논문

提出了针对容量较小、负荷波动较大的地区级电力系统适用的短期负荷预测方法，共分为四个步骤：①原始数据的预处理，②用模糊系统预测预测日的峰谷值，③用人工神经网络预测预测日的24h负荷值，④根据第②③步的结果用专家系统决定最终的负荷预测值。利用本文提出的方法对福建永安电力系统1999年1月至2000年6月的数据进行预测，结果证明了方法的快速性和准确性。
제출료침대용량교소、부하파동교대적지구급전력계통괄용적단기부하예측방법，공분위사개보취：①원시수거적예처리，②용모호계통예측예측일적봉곡치，③용인공신경망락예측예측일적24h부하치，④근거제②③보적결과용전가계통결정최종적부하예측치。이용본문제출적방법대복건영안전력계통1999년1월지2000년6월적수거진행예측，결과증명료방법적쾌속성화준학성。
This paper presents a kind of short-term load forecasting algorithm for some systems which have small capacity and big load fluctuation.The algorithm consists of four steps: ① original data processed; ② forecasted the peak and valley load of the next day; ③ obtained the next day's hourly load through ANN learning; ④ achieved the terminal load forecasting based on step 2 and 3 by ES. Some evaluations and conclusions are acquired from experiments on historical data in the system of Yongan, Fujian China. The result shows the algorithm's accuracy and rapidity.