• Journal of Energy Engineering
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• v.28 no.4
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• pp.82-93
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• 2019

In this study, a new model is proposed to improve the problem of the decline of predict rate of heat demand on a particular date, such as a public holiday for the conventional heat demand forecasting system. The proposed model was the Four Season Mixed Heat Demand Prediction Neural Network Model, which showed an increase in the forecast rate of heat demand, especially for each type of forecast date (weekday/weekend/holiday). The proposed model was selected through the following process. A model with an even error for each type of forecast date in a particular season is selected to form the entire forecast model. To avoid shortening learning time and excessive learning, after each of the four different models that were structurally simplified were learning and a model that showed optimal prediction error was selected through various combinations. The output of the model is the hourly 24-hour heat demand at the forecast date and the total is the daily total heat demand. These forecasts enable efficient heat supply planning and allow the selection and utilization of output values according to their purpose. For daily heat demand forecasts for the proposed model, the overall MAPE improved from 5.3~6.1% for individual models to 5.2% and the forecast for holiday heat demand greatly improved from 4.9~7.9% to 2.9%. The data in this study utilized 34 months of heat demand data from a specific apartment complex provided by the Korea District Heating Corp. (January 2015 to October 2017).

• Journal of Energy Engineering
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• v.18 no.4
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• pp.221-229
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• 2009

This study develops the optimized operation program which enables effective and economic operation between individual and connected branch offices by analyzing the current status and influential indicators of district heating companies' capital branch offices. Accordingly, the study examines the efficiency of optimized operation program. In doing so, this study has diagnosed and analyzed various factors, such as boilers, pumps, and relevant tags (temperature, pressure, fuel amount) through investigation of individual branch offices, and finally succeeded in developing wide-ranging data base by factor covering one-year time period. Additionally, after running the optimized operation program, different branch offices, optimum preference has turned out "incinerator receiving heat from KEPCO>CHP >PLBs>PLBw." Meantime, except the connected offices, there has been no big difference between actual and optimum operation program in branch offices. Meanwhile, the integrated optimum operation program has made it possible the most optimal result only via the connecting supply and demand heat without changing received Heat from KEPCO which is the same as total productive heat. The result has showed that the reduction percentage per day is 2.45~6.80%, and the reduction cost per day is 22,727~60,077 thousand won given the randomly selected sample days. In particular, winter time shows the highest demand with the largest reduction cost whereas summer time illustrates the lowest demand with the smallest reduction cost. Given this result, reduction cost per year compared to actual heat production cost for one year theoretically would be 84 hundred million won. Also, the economic effect showed that the reduction cost percentage per year is more than 2.74% on heat production cost per year for all capital branch offices.

• Journal of Energy Engineering
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• v.28 no.2
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• pp.18-35
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• 2019

The Korea District Heating Corporation operates a gas engine generator with a capacity of $4500m^3 /day$ of biogas generated from the sewage treatment plant of the Nanji Water Recycling Center and 1,500 kW. However, the actual operation experience of the biogas power plant is insufficient, and due to lack of accumulated technology and know-how, frequent breakdown and stoppage of the gas engine causes a lot of economic loss. Therefore, it is necessary to prepare technical fundamental measures for stable operation of the power plant In this study, a series of process problems of the gas engine plant using the biogas generated in the sewage treatment plant of the Nanji Water Recovery Center were identified and the optimization of the actual operation was made by minimizing the problems in each step. In order to purify the gas, which is the main cause of the failure stop, the conditions for establishing the quality standard of the adsorption capacity of the activated carbon were established through the analysis of the components and the adsorption test for the active carbon being used at present. In addition, the system was applied to actual operation by applying standards for replacement cycle of activated carbon to minimize impurities, strengthening measurement period of hydrogen sulfide, localization of activated carbon, and strengthening and improving the operation standards of the plant. As a result, the operating performance of gas engine # 1 was increased by 530% and the operation of the second engine was increased by 250%. In addition, improvement of vent line equipment has reduced work process and increased normal operation time and operation rate. In terms of economic efficiency, it also showed a sales increase of KRW 77,000 / year. By applying the strengthening and improvement measures of operating standards, it is possible to reduce the stoppage of the biogas plant, increase the utilization rate, It is judged to be an operational plan.