• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.432-434
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• 2001

This paper proposes a special-day load forecasting method with the characteristics of temperature based on fuzzy linear regression. We can obtain a linear regression model from the relation between daily peak load and daily maximum or minimum temperature. Simulation results show that the proposed method can improve an accuracy of a special-day load forecasting.

• Journal of Korean Society on Water Environment
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• v.21 no.3
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• pp.277-283
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• 2005

This paper aimed to compare the daily water quality as well as the hydrological data gathered for the past two years (2000 to 2001) between the two influent rivers of Paldang reservoir. The analysis also has been carried out to draw out the factors that affect the water quality at the dam site, where the main drinking water drawing point is located. The relationship between total amount of monthly rainfall and monthly inflow showed $r^2=0.74$ (p<0.05). The highest peak of inflow of influent rivers recorded in August and September (in the year of 2000) and July and August (2001). Average inflows of influent rivers in 2000 and 2001 are calculated at 209.0, 161.5 CMS (Bughangang), 268.6, 148.2 CMS(Namhangang), and 7.8, 5.0 CMS (Gyeongancheon). The formula which was driven from the relationship between inflow and COD load of influent rivers, explained that COD concentration in general increased with the inflow. But during the rainy seasons (July, August, and September), COD concentration decreased according to the increase of inflow. The daily rainfall and COD concentration(or load) during the rainy season (August and September in the year of 2000, July and August in 2001) indicated that the peak of COD load correspond with the rainfall, which decreased sharply after 3 or 4 days. The reason was thought that the high COD load was diluted rapidly by the rain flow. Water temperature, pH and conductivity measured at dam site decreased obviously when the inflow sharply increased. Peak period of total phosphorus concentration coincided with that of inflow. In rainy season, chlorophyll-a concentration decreased obviously as the inflow increased. The reason can be ascribed to the flushing effect caused by the operation of floodgate.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.783-790
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• 2012

Electric Vehicles(EVs) and Plug-in Hybrid Electric Vehicles(PHEVs) which have the grid connection capability, represent an important power system issue of charging demands. Analyzing impacts EVs charging demands of the power system such as increased peak demands, developed by means of modeling a stochastic distribution of charging and a demand dispatch calculation. Optimization processes proposed to determine optimal demand distribution portions so that charging costs and demand can possibly be managed. In order to solve the problems due to increasing charging demand at the peak time, alternative electricity rate such as Time-of-Use(TOU) rate has been in effect since last year. The TOU rate would in practice change the tendencies of charging time at the peak time. Nevertheless, since it focus only minimizing costs of charging from owners of the EVs, loads would be concentrated at times which have a lowest charging rate and would form a new peak load. The purpose of this paper is that to suggest a scenario of load leveling for a power system operator side. In case study results, the vehicles as regular load with time constraints, battery charging patterns and changed daily demand in the charging areas are investigated and optimization results are analyzed regarding cost and operation aspects by determining optimal demand distribution portions.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.6
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• pp.749-757
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• 2005

The present study analyzed actual cases of designed flow estimation method and designed flow rate of sewage pipe lines. In order to examine the effects of peak-hour demand factor estimation with given daily highest peak loading, we analyzed its effects on designed flow rate with changing the peak-hour demand factor from 2.0 to 10.0. The results of this study are as follows. When reviewing the recent designs, we found that 59.4% of pipe line with 250mm and 300mm diameter, which fall under minimum allowable pipeline did not meet the minimum velocity which is specified as 0.6m/sec in design standards. The pipe line that have minimal access population or have very low slope did not satisfy the minimum velocity. In estimating the designed sewage flow, the applied daily highest peak loading and hourly highest peaking loading were the load factor for the entire population of the planned area, and for the peak loading of the initial pipes connected to a very small population, we applied the same factor as that applied to the entire area and, as a result, the hourly highest flow was underestimated. Because, in case of the initial pipes, the method of applying the same peak loading to all subject areas is highly possible to produce underestimated design flow, when estimating the designed flow of the initial pipes connected to a small population need to adopt a rational flow factor according to the size of population. For this, it is considered to investigate and analyze raw data on daily and hourly variation of sewage flow.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.9
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• pp.1516-1521
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• 2008

Recently, distribution load analysis using AMR (Automatic Meter Reading) data is researched in electric utilities. Load analysis method based on AMR system generates the typical load profile using load data of AMR customers, estimates the load profile of non-AMR customers, and analyzes the peak load and load profile of the distribution circuits and sectors per every 15 minutes/hour/day/week/month. Typical load profile is generated by the algorithm calculating the average amount of power consumption of each groups having similar load patterns. Traditional customer clustering mechanism uses only contract type code as a key. This mechanism has low accuracy because many customers having same contract code have different load patterns. In this research, We propose a customer clustring mechanism using k-means algorithm with contract type code and AMR data.

• Journal of the Korea Convergence Society
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• v.9 no.5
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• pp.1-6
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• 2018

In smart grid an accurate load forecasting is crucial in planning resources, which aids in improving its operation efficiency and reducing the dynamic uncertainties of energy systems. Research in this area has included the use of shallow neural networks and other machine learning techniques to solve this problem. Recent researches in the field of computer vision and speech recognition, have shown great promise for Deep Neural Networks (DNN). To improve the performance of daily electric peak load forecasting the paper presents a new deep neural network model which has the architecture of two multi-layer neural networks being serially connected. The proposed network model is progressively pre-learned layer by layer ahead of learning the whole network. For both one day and two day ahead peak load forecasting the proposed models are trained and tested using four years of hourly load data obtained from the Korea Power Exchange (KPX).

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.7
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• pp.414-420
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• 2003

The domestic needs for larger capability of power sources are increasing to cope with the expanding power load which results from the industrial developments & the progressed life style. In summer, the peak load is mainly due to the non-industrial reasons such as air-conditioners and other cooling equipments. To cover the concentrated peak load in stable, the power transmission lines should be more constructed and efficiently operated. The ampacity design of the underground cable system is generally following international standards such as IEC287, IEC60853 and JCS168 which regards the shape of 100% daily full power loads. It is not so efficient to neglect the real shapes of load curves generally below 60~70% of full load. The dynamic (real time) rating system tends to be used with the measured thermal parameters which make it possible to calculate the maximum ampacity within required periods. In this paper, the CTM(Conductor Temperature Monitoring) which is the base of dynamic rating systems for tunnel environment is proposed by a design of lumped thermal network ($\pi$-type thermal model) and distribution temperature sensor attached configuration, including the estimation results of its performances by load cycle test on 345kV single phase XLPE cable.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1608-1614
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• 2014

Power demand forecasting is an important factor of the peak management. This paper deals with the 15 minutes ahead load forecasting problem in a DC urban railway system. Since supplied power lines to trains are connected with parallel, the load characteristics are too complex and highly non-linear. The main idea of the proposed method for the 15 minutes ahead prediction is to use the daily load similarity accounting for the load nonlinearity. An Euclidean norm with weighted factors including loads of the neighbor substation is used for the similar load selection. The prediction value is determinated by the sum of the similar load and the correction value. The correction has applied the neural network model. The feasibility of the proposed method is exemplified through some simulations applied to the actual load data of Incheon subway system.

• International Journal of Air-Conditioning and Refrigeration
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• v.11 no.4
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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.

• Journal of Korean Society on Water Environment
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• v.25 no.1
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• pp.58-68
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• 2009

Low impact development (LID) technique is relatively new concept to reduce surface runoff and pollutant loading from land cover by attempting to match predevelopment condition with various integrated management practices (IMPs). In this study, computational model for designing and evaluating LID, named LIDMOD, was developed based on SCS-CN method and applied at Andong bus terminal to evaluate LID applicapability and design retention/detention area for volume or peak flow control. LIDMOD simulated with 21 years simulation period that yearly surface runoff by post-development without LID was significantly higher than that with LID showing about 2.8 times and LID could reduce efficiently yearly surface runoff with 75% reduction of increased runoff by conventional post development. LIDMOD designed detention area for volume/peak flow control with 20.2% of total area by hybrid design. LID can also efficiently reduce pollutant load from land cover. Pollutant loads from post-development without LID was much higher than those from pre-development with showing 37 times for BOD, 2 times for TN, and 9 times for TP. Pollutant loads from post-development with LID represented about 57% of those without LID. Increasing groundwater recharge reducing cooling and heating fee, creating green refuge at building area can be considered as additional benefits of LID. At the point of reducing runoff and pollutant load, LID might be important technique for Korean TMDL and LIDMOD can be useful tool to calculate unit load for the case of LID application.