지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 제어로봇시스템학회 International Journal of Control, Automation, and Systems International Journal of Control, Automation, and Systems 제6권 제5호
- 발행연도
- 2008.10
- 수록면
- 639 - 650 (12page)
이용수
초록· 키워드
오류제보하기
Electricity price forecasting has become an integral part of power system operation and control. In this paper, a wavelet transform (WT) based neural network (NN) model to forecast price profile in a deregulated electricity market has been presented. The historical price data has been decomposed into wavelet domain constitutive sub series using WT and then combined with the other time domain variables to form the set of input variables for the proposed forecasting model. The behavior of the wavelet domain constitutive series has been studied based on statistical analysis. It has been observed that forecasting accuracy can be improved by the use of WT in a forecasting model. Multi-scale analysis from one to seven levels of decomposition has been performed and the empirical evidence suggests that accuracy improvement is highest at third level of decomposition. Forecasting performance of the proposed model has been compared with (ⅰ) a heuristic technique, (ⅱ) a simulation model used by Ontario’s Independent Electricity System Operator (IESO), (ⅲ) a Multiple Linear Regression (MLR) model, (ⅳ) NN model, (ⅴ) Auto Regressive Integrated Moving Average (ARIMA) model, (ⅵ) Dynamic Regression (DR) model, and (ⅶ) Transfer Function (TF) model. Forecasting results show that the performance of the proposed WT based NN model is satisfactory and it can be used by the participants to respond properly as it predicts price before closing of window for submission of initial bids.
목차
Abstract
1. INTRODUCTION
2. PROBLEM FORMULATION
3. WAVELET TRANSFORM (WT)
4. ONTARIO ELECTRICITY MARKET AND PRICE INFLUENCING VARIABLES
5. EFFECT OF WT ON HOEP
6. MODELS AND METHODOLOGY FOR HOEP FORECASTING
7. FORECASTING RESULT ANALYSIS AND DISCUSSION
8. CONCLUSION
REFERENCES
참고문헌 (31)
참고문헌 신청
1. [단행본] - M. Shahidepour / 2002 / Market Operations in Electric Power Systems Forecast-ing, Scheduling and Risk Management / Willey-Interscience
2. [학술지(정기간행물)] - A. J. Conejo / 2005 / Forecasting electricity prices for a day-ahead pool-based electric energy market / International Journal of Forecasting 21 (3) : 435 ~ 462
3. [학술지(정기간행물)] - J. Bastian / 1999 / Forecasting energy prices in a com-petitive market / IEEE Computer Applications in Power Magazine 12 (3) : 40 ~ 45
4. [학술지(정기간행물)] - H. Y. Yamin / 2004 / Adaptive short-term electricity price forecast-ing using artificial neural networks in the restructured power markets / Electrical Power and Energy Systems 26 : 571 ~ 581
5. [학술지(정기간행물)] - R. Gareta / 2006 / Forecast-ing of electricity prices with neural networks / Energy Conversion and Management 47 : 1770 ~ 1778
2. [학술지(정기간행물)] - A. J. Conejo / 2005 / Forecasting electricity prices for a day-ahead pool-based electric energy market / International Journal of Forecasting 21 (3) : 435 ~ 462
3. [학술지(정기간행물)] - J. Bastian / 1999 / Forecasting energy prices in a com-petitive market / IEEE Computer Applications in Power Magazine 12 (3) : 40 ~ 45
4. [학술지(정기간행물)] - H. Y. Yamin / 2004 / Adaptive short-term electricity price forecast-ing using artificial neural networks in the restructured power markets / Electrical Power and Energy Systems 26 : 571 ~ 581
5. [학술지(정기간행물)] - R. Gareta / 2006 / Forecast-ing of electricity prices with neural networks / Energy Conversion and Management 47 : 1770 ~ 1778
함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
Electricity Price Forecasting in Ontario Electricity Market Using Wavelet Transform in Artificial Neural Network Based Model
International Journal of Control Automation and Systems
2008 .10
-
Forecasting Short-term Electricity Prices in South Korean Electricity Market
대한전기학회 학술대회 논문집
2008 .11
-
Further Advances in Forecasting Day-Ahead Electricity Prices Using Time Series Models
KIEE International Transactions on Power Engineering
2004 .09
-
Support Vector Regression에 기반한 전력 수요 예측
산업공학 (IE interfaces)
2011 .12
-
Forecasting Day-ahead Electricity Price Using a Hybrid Improved Approach
Journal of Electrical Engineering & Technology
2017 .11
-
전력시장가격 예측을 위한 구조적 모델링
대한전기학회 학술대회 논문집
2004 .07
-
신경망 이론에 의한 링크 통행시간 예측모형의 개발
대한교통학회지
1995 .03
-
Adaptive Wavelet Neural Network Based Wind Speed Forecasting Studies
Journal of Electrical Engineering & Technology
2014 .11
-
ARIMA 모형을 이용한 계통한계가격 예측방법론 개발
전기학회논문지 A
2006 .02
-
Forecasting Using Interval Neural Networks : Application to Demand Forecasting
대한산업공학회지
1994 .12
-
전력수급기본계획 수립위한 장기 전력수요 예측절차
전기학회논문지
2010 .09
-
Intermittent Demand Forecasting in the Case of Medical Apparatus By Improving Forecasting Accuracy
대한산업공학회 추계학술대회 논문집
2015 .11
-
기온 데이터를 이용한 하계 단기전력수요예측
전기학회논문지
2015 .08
-
빅데이터를 이용한 인공신경망 기반 시간별 전력수요 예측
전기학회논문지
2020 .06
-
Use of High-performance Graphics Processing Units for Power System Demand Forecasting
Journal of Electrical Engineering & Technology
2010 .09
-
Wavelet 변환과 신경망을 이용한 시계열 데이터 예측 정확도의 향상 ( Enhancement of Forecasting Accuracy in Time-Series Data, Based on Wavelet Transformation and Neural Network )
한국지능정보시스템학회 학술대회논문집
1998 .05
-
웨이블릿패킷분해 및 신경망을 이용한 하천수위예측
대한토목학회 학술대회
2015 .10
-
Wavelet Thresholding Techniques to Support Multi - Scale Decomposition for Financial Forecasting Systems
한국지능정보시스템학회 학술대회논문집
1999 .06
-
기상변수를 이용한 도서지역 전력수요 예측모형의 적합성에 관한 연구
신·재생에너지
2017 .06
-
태양광발전모형 예측력 제고를 위한 지역별 기상요소 적용방안 연구
전기학회논문지
2019 .11
이 논문의 저자 정보
최근 본 자료
댓글(0)
0
UCI(KEPA) : I410-ECN-0101-2013-569-003244216