기온변화에 의한 수요변동을 고려한 단기 전력수요예측 전문가시스템의 연구

• 영문명: A study on the short-term load forecasting expert system considering the load variations due to the change in temperature
• 발행기관: 강원대학교 산업기술연구소
• 저자명: 김광호(Kwang Ho Kim) 이철희(Chul Heui Lee)
• 간행물 정보: 『산업기술연구』vol.15, 187~193쪽, 전체 7쪽
• 주제분류: 공학 > 공학일반
• 파일형태: PDF
• 발행일자: 1995.09.30

영문 초록

In this paper, a short-term load forecasting expert system considering the load variation due to the change in temperature is presented. The change in temperature is an important load variation factor that varies the normal load pattern. The conventional load forecasting methods by artificial neural networks have used the technique where the temperature variables were included in the input neurons of artificial neural networks. However, simply adding the input units of temperature data may make the forecasting accuracy worse, since the accuracy of the load forecasting in this method depends on the accuracy of weather forecasting. In this paper, the fuzzy expert system that modifies the forecasted load using fuzzy rules representing the relations of load and temperature is presented and compared with a conventional load forecasting technique. In the test case of 1991, the proposed model provided a more accurate forecast than the conventional technique.

목차

ABSTRACT

1. 서론

2. 1차 전력수요 예측

3. 온도변화을 고려한 2차 전력수요 예측

4. 사례연구

5. 결론

참고문헌