• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.531-537
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• 1999

This paper presents the evaluaton procedures and the estimation model for DSM potential on commercial sector in Korea. In general, the evaluation process of the potential savings for DSM measures or programs consists of baseline electricity consumption forecast and potential evaluation such as technical potential(TP), economic potnetial(EP), and achievable potential(AP). A library of energy conservation measures applicable to each end-use or apparatus is developed, and energy savings and other factors are applied to the baseline demand estimates of consumption to produce potential savings estimates. The purpose of this paper is to establish the evaluation process of those DSM potential for commercial sector. In case study, we applied it to commercial sector for horizon years by end-use.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.842-843
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• 2007

In this paper, the proper rebate level can be decided in programs of energy savings by solving an optimization problem with an objective function, which satisfies a maximum value of total energy savings. And then, each prevalence amount is estimated by using virtual Bass model which is a function of rebate level, instead of the conventional Bass model. Finally, by cost/benefit analysis of the estimated prevalence amounts, the priority order is obtained for the investment of each program. The priority order obtained in this way may result the improvement of investment efficiency for DSM(Demand-Side Management) programs and the reasonable plan decision for supply and demand in power system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.312-321
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• 2018

The Korean DR market proposes suppression of peak demand under reliability crisis caused a natural disaster or unexpected power plant accidents as well as saving power plant construction costs and expanding amount of reserve as utility's perspective. End-user is notified a DR event signal DR execution before one hour, and executes DR based on requested amount of load reduction. This paper proposes a DR energy management algorithm that can be scheduled the optimal operations of chiller system and ESS in the next day considering the TOU tariff and DR scheme. In this DR algorithm is divided into two scheduling's; day-ahead operation scheduling with temperature forecasting error and operation rescheduling on DR operation. In day-ahead operation scheduling, the operations of DR resources are scheduled based on the finite number of ambient temperature scenarios, which have been generated based on the historical ambient temperature data. As well as, the uncertainties in DR event including requested amount of load reduction and specified DR duration are also considered as scenarios. Also, operation rescheduling on DR operation day is proposed to ensure thermal comfort and the benefit of a COB owner. The proposed method minimizes the expected energy cost by a mixed integer linear programming (MILP).

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1998.05a
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• pp.179-184
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• 1998

'90년대 이후 전기에너지의 효율적 이용에 따른 절약과 전력사용패턴의 개선을 목적으로 하는 수요관리 즉 DSM(Demand Side Management)의 중요성이 증대되고 있다. 하지만 전기소비량의 약 60%를 차지하는 산업용에 대해서는 전동기 보급율 조사, 냉방수요 행태 조사 및 조명기기 보급실태 조사와 같이 단일기기나 온도에 대한 조사 및 분석만이 이루어져 왔으며, 산업용 전체를 대상으로 업종별 End-Use별 사용실태 조사, 분석, 예측 등 체계적 분석이 이루어지지 않았다. (중략)

• Proceedings of the Korea Technology Innovation Society Conference
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• 2000.11a
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• pp.177-193
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• 2000

In foreign countries, high-efficiency electric machineries have been developed in view of cost reduction, environmental issues, energy conservation etc. Especially they focus on developing energy conservation measures and demand-side management. Thus, patent application and secure of patent claims are on the rise as important issues in this field. In this paper, we analyzed patent application trends about inverters, ac/dc converters, reactive power control equipments, high-efficiency transformers and electric ballasts among high-efficiency electric machineries. First, we analyzed general technology trends, and constructed patent technology data. Second, we graphed patent application trends in terms of application years, assignees and nations.

• Journal of Energy Engineering
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• v.25 no.3
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• pp.136-148
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• 2016

We analyze economic effects of GHG reduction measures of the generation industry to meet 2030 GHG reduction target using the scenario based approach. We estimate the GHG emission of the Korean power industry in 2030 based on both the $7^{th}$ Electricity Supply & Demand Plan and the GHG emission coefficients issued by IAEA. We set up three scenarios for reduction measures by replacing the coal fired plants with nuclear power, renewable energy and carbon capture and storage. Once and for all, the nuclear power scenario dominates the other energy technologies in terms of GHG reduction quantities and economic effects.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.455-460
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• 2014

South Korea's power consumption is increasing every year. For stable electric power supply, more generation facilities are needed. But it is not easy to build nuclear power generation facilities, so provision of renewable energy is thought of as the solution. For the system's stable management, practical use of energy storing system is needed. Currently, pumping up electric power station is considered most useful. In this study, we have calculated the least amount of energy storing device by considering the renewable energy, HVDC, and change in power for the appliance of ESS in Jeju system, according to The 6th Basic Plan for Long-term Electricity Supply and Demand. Also we have calculated the amount of the battery and about the load equalizing effect to use battery as power storing device. Finally, we have calculated the reduction of electricity generation and the reduction of $CO_2$ emission with this study.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.10
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• pp.381-386
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• 2016

An optimization algorithm is developed based on a simulation case of a single family house model equipped with PV arrays. To increase the nationwide use of PV power generation facilities, a market-competitive electricity price needs to be introduced, which is determined based on the time of use. In this study, quadratic programming optimization was applied to minimize the electricity bill while maintaining the indoor temperature within allowable error bounds. For optimization, it is assumed that the weather and electricity demand are predicted. An EnergyPlus-based house model was approximated by using an equivalent RC circuit model for application as a linear constraint to the optimization. Based on the RC model, model predictive control was applied to the management of the cooling load and electricity for the first week of August. The result shows that more than 25% of electricity consumed for cooling can be saved by allowing excursions of temperature error within an affordable range. In addition, profit can be made by reselling electricity to the main grid energy supplier during peak hours.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2668-2670
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• 2004

This paper presents an advanced load control method in Direct Load Control(DLC) system. It is important to aggregate a various demand side resource which is surely controllable at the peak power time for a successful DLC system. Because the DLC system use simple On/Off control that may cause a harmful effect on a plant to reduce a peak power load, there are some restriction on deriving a voluntary participation of demand side resource. So it needs a new approach to direct load control method, and this paper describes an advanced load control method using control logic which is based on load properties. This method is easy to take account of a various characteristic of load, it can be use as a dynamic control logic which is good for adaptive control. The suggested control logic method is verified by modeling a control logic for a turbo refrigerator which affects on peak power in summer season.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.68-77
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• 2018

Regarding demand response (DR) by residential users (R-users), the users try to reduce electricity costs by adjusting their power consumption in response to the time-varying price. However, their power consumption may be affected not only by the price, but also by user convenience for using appliances. This paper proposes a methodology for appliance scheduling (AS) that considers the user convenience based on historical data. The usage pattern for appliances is first modeled applying the copula function or clustering method to evaluate user convenience. As the modeling results, the comfort distribution or representative scenarios are obtained, and then used to formulate a discomfort index (DI) to assess the degree of the user convenience. An AS optimization problem is formulated in terms of cost and DI. In the case study, various AS tasks are performed depending on the weights for cost and DI. The results show that user convenience has significant impacts on AS. The proposed methodology can contribute to induce more DR participation from R-users by reflecting properly user convenience to AS problem.