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최신 기상예측을 활용한 익일 24시간 전력수요예측 알고리즘
조세원(Se-Won Jo),권보성(Bo-Sung Kwon),송경빈(Kyung-Bin Song) 대한전기학회 2019 전기학회논문지 Vol.68 No.3
Along with the spread of renewable energy, hourly load is further affected by the hourly weather. In the past, the Korea Meteorological Administration provided only weather forecasts for daily maximum and minimum temperatures and daily average amount of cloud. Currently, Dong-Nae forecasts for weather provided by Korea Meteorological Administration are provided for hourly temperature, amount of cloud, precipitation, precipitation probability, direction of the wind and wind speed by region at 3-hour intervals 8 times per day. Accordingly 24-hours load forecasting algorithm using Dong-Nae forecast is proposed to improve the performance. In the proposed algorithm, the effect of temperature to load is reflected using the weekly load sensitivity to temperature per 3-hours, while day ahead load forecasting is performed using the exponential smoothing model. In addition the effect of small solar photovoltaic generation is considered in the proposed algorithm using daytime load sensitivity to amount of cloud per 3-hours. In the case study, the load forecast is performed for the day ahead except special days in 2017. The accuracy of the proposed algorithm was improved by 27.88%, 9.25%, and 9.29% for the overall average percentage error, on Monday, weekday, and weekend, respectively, in 2017 over the overall average percentage error of the algorithm of the exponential smoothing model that reflects the effects of maximum and minimum temperatures.
기상에 대한 동네예보를 활용한 제주도의 특수일 전력수요예측 알고리즘
조세원(Se-Won Jo),박래준(Rae-Jun Park),송경빈(Kyung-Bin Song) 한국조명·전기설비학회 2019 조명·전기설비학회논문지 Vol.33 No.6
It is necessary to increase the accuracy of the load forecast by reflecting the characteristics of the load in Jeju and the effect of temperature on load when performing load forecast for Jeju special day. In order to the accuracy of load forecast, Jeju special day load forecasting algorithm that reflects the effect of temperature on load by using the Dong-Nae forecast provided by Korea Meteorological Administration is proposed. The proposed algorithm uses a fuzzy linear regression model to perform 24-hour special day load forecasting. Then, the load sensitivity for temperature per 3-hour for the special day is calculated using the load on the special day normalized by the basic load and temperature. Using load sensitivity for temperature, the effect of temperature on load is adjusted by the difference between the four days of weekday before special day and special day of the past three years and by the difference between the four days of weekday before the forecast day and forecast day. Case studies were performed for the proposed algorithm from 2014 to 2016. The accuracy of the proposed algorithm is improved by 41.51% from 5.42% to 3.17% on MAPE.
조세원(Se-Won Jo),박래준(Rae-Jun Park),김경환(Kyeong-Hwan Kim),권보성(Bo-Sung Kwon),송경빈(Kyung-Bin Song),박정도(Jeong-Do Park),박해수(Hae-Su Park) 대한전기학회 2018 전기학회논문지 Vol.67 No.8
In this paper sensitivity analysis of temperature on special day electricity demand of land and Jeju Island is performed. The basic electricity demand per 3 hours is defined as electricity demand that reflects the GDP effect without the temperature influence. The temperature sensitivity per 3 hours is calculated through the relationship between special day electricity demand normalized to basic electricity demand and temperature. In the future, forecast error will be improved if the temperature sensitivity per 3 hours is applied to the special day load forecasting.