• The Korean Journal of Applied Statistics
• /
• v.34 no.6
• /
• pp.969-977
• /
• 2021

We cluster the electricity consumption of households in A-apartment in Seoul, Korea using Hierarchical K-means clustering algorithm. The data is recorded from the advanced metering infrastructure (AMI), and we focus on the electricity consumption during evening weekdays in summer. Compare to the conventional clustering algorithms, Hierarchical K-means clustering algorithm is recently applied to the electricity usage data, and it can identify usage patterns while reducing dimension. We apply Hierarchical K-means algorithm to the AMI data, and compare the results based on the various clustering validity indexes. The results show that the electricity usage patterns are well-identified, and it is expected to be utilized as a major basis for future applications in various fields.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.2
• /
• pp.981-987
• /
• 2017

In this paper, we estimate the economic benefits of Energy Storage Systems (ESSs) for peak load shaving in an urban railway substation using the annual cost. The annual investment cost of ESSs is estimated using Net Present Value (NPV) and compared with the cost reduction of electricity by the ESS. The optimal capacities of the battery and Power Converting System (PCS) are determined for peak load shaving. The optimal capacity of the ESS and the peak load shaving is determined to maximize the profit by the ESS. The proposed method was applied to real load data in an urban railway substation, and the results show that electric power costs can be reduced. Other aspects of the ESS, such as the lifetime and unit price of the battery, are also investigated economically.

• Proceedings of the KIEE Conference
• /
• 1992.07a
• /
• pp.495-497
• /
• 1992

Hourly load forecasting has become indispensable for practical simulation of electric power system as the system become larger and more complicated. To forecast the future hourly load the cyclic behavior of electric load which follows seasonal weather, day or week and office hours is to be analyzed so that the trend of the recent behavioral change can be extrapolated for the short term. For the long term, on the other hand, the changes in the infra-structure of each electricity consumer groups should be assessed. In this paper the concept and process of hourly load forecasting for hourly load is introduced.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2004.05a
• /
• pp.434-436
• /
• 2004

Load forecasting is essential in the electricity market for the participants to manage the market efficiently and stably. The percentage errors of 24 hourly load forecasting for holidays is relatively large. In this paper, we propose the maximum and minimum load forecasting method for holidays using a fuzz linear regression algorithm. 24 hourly loads are forecasted from the maximum and minimum loads and the 24 hourly normalized values. The proposed algorithm is tested for 24 hourly load forecasting in 1996. The test results show the proposed algorithm improves the accuracy of the load forecasting.

• Journal of Power Electronics
• /
• v.10 no.4
• /
• pp.444-449
• /
• 2010

The generation of electric power using self excited induction generation (SEIG) is a viable option in remote and rural areas where grid electricity is not available. The generated voltage and frequency of these machines, however, varies with varying loads. This characteristic can be resolved either by adjusting the values of the excitation capacitance or by controlling the prime mover speed. Further, in a single-point constant power application, where the machines deliver a fixed amount of power, the electronic load controller (ELC) can be used to switch-in or switch-out a dump load whenever the consumer load decreases or increases respectively. This paper presents a detailed analysis and the design of a microcontroller based SEIG -ELC system intended for stand-alone pico hydro power generation. The simulated performance of the controller is supplemented by experimental results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.720-722
• /
• 2009

Optimal operation of electric power generating plants is very essential for any power utility organization to reduce input costs and possibly the prices of electricity in general. This paper developed models for load forecasting using neural networks approach. This model is tested using actual load data of the Busan and weather data to predict the load of the Busan for one month in advance. The test results showed that the neural network forecasting approach is more suitable and efficient for a forecasting application.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.9
• /
• pp.1486-1492
• /
• 2016

This study presents the electrical load forecasting and error correction method using a real building load pattern, and the way to manage the energy storage system with forecasting results for economical load operation. To make a unique pattern of target load, we performed the Hierarchical clustering that is one of the data mining techniques, defined load pattern(group) and forecasted the demand load according to the clustering result of electrical load through the previous study. In this paper, we propose the new reference demand for improving a predictive accuracy of load demand forecasting. In addition we study an error correction method for response of load events in demand load forecasting, and verify the effects of proposed correction method through EMS scheduling simulation with load forecasting correction.

• Korean System Dynamics Review
• /
• v.2 no.2
• /
• pp.25-40
• /
• 2001

This paper describes the forecast of power plant construction in a competitive korean electricity market. In Korea, KEPCO (Korea Electric Power Corporation, fully controlled by government) was responsible for from the production of the electricity to the sale of electricity to customer. However, the generation part is separated from KEPCO and six generation companies were established for whole sale competition from April 1st, 2001. The generation companies consist of five fossil power companies and one nuclear power company in Korea at present time. Fossil power companies are scheduled to be sold to private companies including foreign investors. Nuclear power company is owned and controlled by government. The competition in generation market will start from 2003. ISO (Independence System Operator will purchase the electricity from the power exchange market. The market price is determined by the SMP(System Marginal Price) which is decided by the balance between demand and supply of electricity in power exchange market. Under this uncertain circumstance, the energy policy planners such as government are interested to the construction of the power plant in the future. These interests are accelerated due to the recent shortage of electricity supply in California. In the competitive market, investors are no longer interested in the investment for the capital intensive, long lead time generating technologies such as nuclear and coal plants. Large unclear and coal plants were no longer the top choices. Instead, investors in the competitive market are interested in smaller, more efficient, cheaper, cleaner technologies such as CCGT(Combined Cycle Gas Turbine). Electricity is treated as commodity in the competitive market. The investors behavior in the commodity market shows that the new investment decision is made when the market price exceeds the sum of capital cost and variable cost of the new facility and the existing facility utilization depends on the marginal cost of the facility. This investors behavior can be applied to the new investments for the power plant. Under these postulations, there is the potential for power plant construction to appear in waves causing alternating periods of over and under supply of electricity like commodity production or real estate production. A computer model was developed to sturdy the possibility that construction will appear in waves of boom and bust in Korean electricity market. This model was constructed using System Dynamics method pioneered by Forrester(MIT, 1961) and explained in recent text by Sternman (Business Dynamics, MIT, 2000) and the recent work by Andrew Ford(Energy Policy, 1999). This model was designed based on the Energy Policy results(Ford, 1999) with parameters for loads and resources in Korea. This Korea Market Model was developed and tested in a small scale project to demonstrate the usefulness of the System Dynamics approach. Korea electricity market is isolated and not allowed to import electricity from outsides. In this model, the base load such as unclear and large coal power plant are assumed to be user specified investment and only CCGT is selected for new investment by investors in the market. This model may be used to learn if government investment in new unclear plants could compensate for the unstable actions of private developers. This model can be used to test the policy focused on the role of unclear investments over time. This model also can be used to test whether the future power plant construction can meet the government targets for the mix of generating resources and to test whether to maintain stable price in the spot market.

• Journal of the Korean Solar Energy Society
• /
• v.26 no.1
• /
• pp.13-19
• /
• 2006

The efficiency of building-integrated photovoltaic(BIPV) system is mainly determined by solar radiation and the temperature of PV modules. The performance of BIPV systems is reported to be different from that of conventional PV systems installed in the open-air. This paper presents the relationship of solar radiation and electricity generation from a 2kWp roof-integrated PV system that is applied as building elements on an experimental house, and the energy saving effect of the BIPV system for a typical house. For the performance evaluation of the BIPV system, it produced a regression equation with measured data for winter days. The regression equation showed that a comparison of the measured electricity generation and the predicted electricity generation of the BIPV system were meaningful. It showed that an annual electricity generation of the system appeared to cover around 52% of an annual electricity consumption of a typical domestic house with the floor area of $96m^2$.

• Proceedings of the KIEE Conference
• /
• 2006.10b
• /
• pp.141-146
• /
• 2006

According as level of industry develops day after day, electricity load system of industry requires high level control, effectiveness and high efficiency. Among supply and control unit of suitable power supply in these load characteristic, inverter systems of constant current regulate is used widely control of lighting and electric heating system. Therefore, in this paper proposed an inverter systems with constant current regulation and power factor correction (PFC) circuit for Lighting and Beaconing of Aerodromes. The effectiveness of the proposed system confirmed through experimental results of CCR.