• 전기학회논문지
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• 제64권8호
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• pp.1137-1144
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• 2015

Accurate and robust load forecasting model is very important in power system operation. In case of short-term electric load forecasting, its result is offered as an standard to decide a price of electricity and also can be used shaving peak. For this reason, various models have been developed to improve forecasting accuracy. In order to achieve accurate forecasting result for summer season, this paper proposes a forecasting model using corrected effective temperature based on Heat Index and CDH data as inputs. To do so, we establish polynomial that expressing relationship among CDH, load, temperature. After that, we estimate parameters that is multiplied to each of the terms using PSO algorithm. The forecasting results are compared to Holt-Winters and Artificial Neural Network. Proposing method shows more accurate by 1.018%, 0.269%, 0.132% than comparison groups, respectively.

• International Journal of Air-Conditioning and Refrigeration
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• 제11권4호
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• pp.170-177
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• 2003

The electric power load during the summer peak time is strongly affected by cooling load, which decreases the preparation ratio of electricity and brings about the failure in the supply of electricity in the electric power system. The ice storage system and heat pump system etc. are used to settle this problem. In this study, the method of estimating temperature and humidity to forecast the cooling load of ice storage system is suggested. The method of forecasting the cooling load using neural network is also suggested. The daily cooling load is mainly dependent on actual temperature and humidity of the day. The simulation is started with forecasting the temperature and humidity of the following day from the past data. The cooling load is then simulated by using the forecasted temperature and humidity data obtained from the simulation. It was observed that the forecasted data were closely approached to the actual data.

• 제어로봇시스템학회논문지
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• 제8권11호
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• pp.948-953
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• 2002

The electric power load during the peak time in summer is strongly affected by cooling load, which decreases the preparation ratio of electricity and brings about the failure in the supply of electricity in the electric power system. The ice-storage system and heat pump system are possible solutions to settle this problem. In this study. the method of estimating temperature and humidity to forecast the cooling load of ice-storage system is suggested, then the method of forecasting the cooling load using fuzzy logic is suggested by simulating that the cooling load is calculated using actual temperature and humidity. The forecast of the temperature, humidity and cooling load are simulated, and it is shown that the forecasted data approach to the actual data. Operating the ice-storage system by the forecast of cooling load with night electric power will improve the ice-storage system efficiency and reduce the peak electric power load during the summer season as a result.

• 설비공학논문집
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• 제14권8호
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• pp.626-633
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• 2002

The electric power load during the peak time in summer is strongly affected by cooling load, which decreases the preparation ratio of electricity and brings about the failure in the supply of electricity in the electric power system. The ice-storage system and heat pump system etc. are used to settle this problem. In this study, the method of estimating temperature and humidity to forecast the cooling load of ice storage system is suggested. And also the method of forecasting the cooling load using neural network is suggested. For the simulation, the cooling load is calculated using actual temperature and humidity, The forecast of the temperature, humidity and cooling load are simulated. As a result of the simulation, the forecasted data is approached to the actual data.

• 에너지공학
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• 제22권2호
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• pp.211-225
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• 2013

본 연구에서는 서로 다른 위도의 도시 유형별로 주택과 건물 구성비를 가진 3지역을 선정하여 대상 지역별로 2008년 1년간(1.1~12.31)의 실제 운전실적을 이용하여 지역난방 사용자의 일일 및 연간 열소비 패턴을 분석하고, 지역별 상호 차이점을 파악하기 위하여 주택과 건물의 열소비 패턴을 비교 분석하였다. 특히 본 연구에서는 실제 주택 및 건물 지역난방 사용자가 사용한 열소비 패턴을 매시간대별로 파악하고, 연결 열부하(난방면적 ${\times}$ 단위열부하 : 시설용량과 지역난방 배관망의 설계기준이 되는 열부하로 난방면적에 용도별 단위열부하를 곱하여 산출[Gcal/h])와의 관계를 분석하여 일일, 연간 및 최대 부하율 결과값을 도출함으로써 주택 및 건물 지역난방 사용자 비율에 따른 최적의 열원시설 용량산정이 가능케 하고 수요개발(해당 시설용량으로 열공급이 가능한 지역난방 사용자의 범위로 각 사용자기계실의 연결열부하 합과 같음.)단계에서의 정확한 방향을 제시할 수 있는 근거를 도출하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.61-64
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• 2001

The electric power load during the peak time in summer is strongly affected by cooling load. which decreases the preparation ratio of electricity and brings about the failure in the supply of electricity in the electric power system. The ice-storage system and heat pump system etc are used to settle this problem. In this study, the method of estimating temperature and humidity to forecast the cooling load of ice-storage system is suggested. And also the method of forecasting the cooling load using neural network is suggested. For the simulation, the cooling load is calculated using actual temperature and humidity. The forecast of the temperature, humidity and cooling load are simulated. As a result of the simulation, the forecasted data approached to the actual data.