• Asia-Pacific Journal of Business
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• v.13 no.1
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• pp.263-275
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• 2022

Purpose - This study estimated the non-market value of pumped storage power generation using the contingent valuation method(CVM). Design/methodology/approach - CVM, a non-market value estimation method, was used. The perception of pumped storage power generation and the willingness to pay(WTP) for pumped storage power generation were investigated among 612 randomly selected households. Findings - It was analyzed that the average value per household was 7309.99 won/month, and the sources of these benefits were 1819.37 won due to the improvement of power generation efficiency, 1320.48 won due to the improvement of power system reliability, 2359.24 won due to the stabilization of electricity rates, 2110.89 won due to water resource management It was assumed that a circle occurred. If the average monthly benefit per household is expanded to cover countries across the country, it is estimated that the annual value to our society from pumped storage power generation will be KRW 1.796.6 trillion. Research implications or Originality - It is necessary to consider the operation of pumped-water power generation by reflecting the value of pumped-up power generation that is not evaluated in the market. Since Korea's electricity market is isolated in a state where it is impossible to connect with other countries, it may be vulnerable to a stable electricity operation system. Therefore, there is a need for a facility that can stably secure reserve power and produce power quickly when necessary. If pumped-water power generation is actively used for power operation, a more stable power system can be secured.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.649-651
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• 2003

In the framework of competitive electricity market, the Market Power due to the transmission congestion, lack of demand-side response, various uncertain factors etc. have been significant problem. This paper reviews the market rules of Korea power system and the uplift scheme for constrained on/off generators. Then, this paper points out several problems and the mitigation measures of local market power concerning the compensation for constrained-off generators.

• Environmental and Resource Economics Review
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• v.17 no.4
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• pp.751-774
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• 2008

In this paper, we examine the institutional prices differences in the electricity and natural gas industries using unbalanced panel data from 1999 to 2001. The changing market structures following deregulation in both markets allow us to examine the institutional prices differences by ownership type, market structure and merger activities. Estimating the reduced form, after controlling both intrinsic characteristic (marginal costs) and external factors (demand), allows us to identify the extent to which specific factors are correlated with the price. Furthermore it allows us to identify systematic institutional price differences in both electricity and natural gas markets. Our estimation results suggest that the private firms in electricity markets are associated with higher prices than public firms after controlling for demand and cost. We further find that dual-product firms in the natural gas industry and the electricity industry are associated with lower rates than single product firms. These results provide a weak evidence of economies of scope in the dual-product firms. Our results finally suggest that merger activities in natural gas markets are associated with higher rates.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.4
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• pp.457-466
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• 2013

Wind energy is rapidly becoming significant generating technologies in electricity markets. As probabilistic nature of wind energy creates many uncertainties in the short-term scheduling, additional actions for reliable market operation should be taken. This paper presents a novel approach to evaluate ramping capability requirement for changes in imbalance energy between day-ahead market and real-time market due to uncertainty of wind generation as well as system load. Dynamic ramp rate model has been applied for realistic solution in unit commitment problem, which is implemented in day-ahead market. Probabilistic optimal power flow has been used to verify ramping capability determined by the proposed method is reasonable in economic and reliable aspects. This approach was tested on six-bus system and IEEE 118-bus system with a wind farm. The results show that the proposed approach provides ramping capability information to meet both forecasted variability and desired confidence level of anticipated uncertainty.

• Journal of Energy Engineering
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• v.11 no.4
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• pp.324-331
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• 2002

ln competitive electricity market, useful technique would be required to calculate settlement amount for electric power traded between market participants and KPX since a number of market partici-pants would appear and trade electric power. Especially calculation of constrained on/off compensation amount can be complicated, and needs to be understood clearly by market participants to avoid unnecessary disputes. This paper presents a technique to settle more easily constrained on/off compensation amount using surplus function. In this technique, a surplus is calculated by each dispatched values and then the compen-sation amount is calculated by the difference of each surpluses. By doing this, settlement amount can be cal-culated by summing the trading amount and the compensation amount.

• Journal of Energy Engineering
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• v.15 no.4 s.48
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• pp.256-276
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• 2006

Transmission congestion is one of the key factors to local market power in competitive electricity markets. Financial transmission rights provide the financia] protection to their holders by paying back the congestion rent. A variety researches have shown that the existing trading mechanisms on transmission right can exacerbate market power. This paper proposes an alternative methodology in mitigating the local market power using the Contingent Transmission Rights on the locational marginal pricing scheme. The proposed methodology was demonstrated with the Optimal Power Flow.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1654-1666
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• 2024

The goal of this research is to propose a way to maximize small modular reactor (SMR) utilization to gain better market feasibility in support of carbon neutrality. For that purpose, a comprehensive tool was developed, combining off-design thermohydraulic models, economic objective models (levelized cost of electricity, annual profit), non-economic models (saved CO2), a parameter input sampling method (Latin hypercube sampling, LHS), and a multi-objective evolutionary algorithm (Non-dominated Sorting Algorithm-2, NSGA2 method) for optimizing a SMR-combined heat and power cycle (CHP) system design. Considering multiple objectives, it was shown that NSGA2+LHS method can find better optimal solution sets with similar computational costs compared to a conventional weighted sum (WS) method. Out of multiple multi-objective optimal design configurations for a 105 MWe design generation rating, a chosen reference SMR-CHP system resulted in its levelized cost of electricity (LCOE) below $60/MWh for various heat prices, showing economic competitiveness for energy market conditions similar to South Korea. Examined economic feasibility may vary significantly based on CHP heat prices, and extensive consideration of the regional heat market may be required for SMR-CHP regional optimization. Nonetheless, with reasonable heat market prices (e.g. district heating prices comparable to those in Europe and Korea), SMR can still become highly competitive in the energy market if coupled with a CHP system.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1069-1078
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• 2018

Demand response (DR) programs give opportunity to consumers to manage their electricity bills. Besides, distribution system operator (DSO) is interested in using DR programs to obtain technical and economic benefits for distribution network. Since small consumers have difficulties to individually take part in the electricity market, an entity named demand response provider (DRP) has been recently defined to aggregate the DR of small consumers. However, implementing DR programs face challenges to fairly allocate benefits and payments between DRP and DSO. This paper presents a procedure for modeling the interaction between DRP and DSO based on a bilevel programming model. Both DSO and DRP behave from their own viewpoint with different objective functions. On the one hand, DRP bids the potential of DR programs, which are load shifting and load curtailment, to maximize its expected profit and on the other hand, DSO purchases electric power from either the electricity market or DRP to supply its consumers by minimizing its overall cost. In the proposed bilevel programming approach, the upper level problem represents the DRP decisions, while the lower level problem represents the DSO behavior. The obtained bilevel programming problem (BPP) is converted into a single level optimizing problem using its Karush-Kuhn-Tucker (KKT) optimality conditions. Furthermore, point estimate method (PEM) is employed to model the uncertainties of the power demands and the electricity market prices. The efficiency of the presented model is verified through the case studies and analysis of the obtained results.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.7
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• pp.414-419
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• 2004

In TWBP new uncertainty will be increased. Risk management is risen to a important problem. Vesting contract makes market Players trade at fixed price in TWBP early stages. In the case of advanced country, market players manage risk with a future contract. When a risk management method moves from vesting contract to future contract, it may have to use together two contracts for schedule period. In this paper, risk management strategy that use vesting contract and forward contract at the same time is proposed.

• 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.