• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.1
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• pp.30-45
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• 2013

Predicting monthly electricity price has been a significant factor of decision-making for plant resource management, fuel purchase plan, plans to plant, operating plan budget, and so on. In this paper, we propose a sophisticated prediction model in terms of the technique of modeling and the variety of the collected variables. The proposed model hybridizes the semi-supervised learning and the artificial neural network algorithms. The former is the most recent and a spotlighted algorithm in data mining and machine learning fields, and the latter is known as one of the well-established algorithms in the fields. Diverse economic/financial indexes such as the crude oil prices, LNG prices, exchange rates, composite indexes of representative global stock markets, etc. are collected and used for the semi-supervised learning which predicts the up-down movement of the price. Whereas various climatic indexes such as temperature, rainfall, sunlight, air pressure, etc, are used for the artificial neural network which predicts the real-values of the price. The resulting values are hybridized in the proposed model. The excellency of the model was empirically verified with the monthly data of electricity price provided by the Korea Energy Economics Institute.

• Environmental and Resource Economics Review
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• v.15 no.2
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• pp.319-353
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• 2006

This paper shows how weather derivatives can be used to hedge against the price risk and volume risk of purchasing relatively large amounts of electricity. Our specific approach to designing new contracts for electricity is to focus on the return over a summer season rather than on the daily levels of demand and price. It is shown that correct market signals can be preserved in a contract and the associated financial risk can be offset by weather options. The advantage of combining a forward contract with a weather derivative is that the high prices on hot days or when the temperature is high reflect the underlying high cost of producing power when the load is high and that the combined contract with a weather derivative substantially reduces the volatility of the return.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.4
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• pp.172-178
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• 2006

In this paper, an advanced demand clustering algorithm which can explore the planned maintenance outage of generators in changed electricity industry is proposed. The major contribution of this paper can be captured in the development of the long-term estimates for the generation availability considering planned maintenance outage. Two conflicting viewpoints, one of which is reliability-focused and the other is economy-focused, are incorporated in the development of estimates of maintenance outage based on the advanced demand clustering algorithm. Based on the advanced clustering algorithm, in each demand cluster, conventional effective outage of generators which conceptually capture maintenance and forced outage of generators, are newly defined in order to properly address the characteristic of the planned maintenance outage in changed electricity markets. First, initial market demand is classified into multiple demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the initial demand. Then, based on the advanced demand clustering algorithm, the planned maintenance outages and corresponding effective outages of generators are reevaluated. Finally, the conventional demand clusters are newly classified in order to reflect the improved effective outages of generation markets. We have found that the revision of the demand clusters can change the number of the initial demand clusters, which cannot be captured in the conventional demand clustering process. Therefore, it can be seen that electricity market situations, which can also be classified into several groups which show similar patterns, can be more accurately clustered. From this the fundamental characteristics of power systems can be more efficiently analyzed, for this advanced classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.

• KIEE International Transactions on Power Engineering
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• v.5A no.1
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• pp.85-92
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• 2005

In this paper, Nash equilibriums of generation markets are investigated using a game theory application for simplified competitive electricity markets. We analyze the characteristics of equilibrium states in N-company spot markets modeled by uniform pricing auctions and propose a new method for obtaining Nash equilibriums of the auction. We assume that spot markets are operated as uniform pricing auctions and that each generation company submits its bids into the auction in the form of a seal-bid. Depending on the bids of generation companies, market demands are allocated to each company accordingly. The uniform pricing auction in this analysis can be formulated as a non-cooperative and static game in which generation companies correspond to players of the game. The coefficient of the bidding function of company-n is the strategy of player-n (company-n) and the payoff of player-n is defined as its profit from the uniform price auction. The solution of this game can be obtained using the concept of the non-cooperative equilibrium originating from the Nash idea. Based on the so called residual demand curve, we can derive the best response function of each generation company in the uniform pricing auction with N companies, analytically. Finally, we present an efficient means to obtain all the possible equilibrium set pairs and to examine their feasibilities as Nash equilibriums. A simple numerical example with three generation companies is demonstrated to illustrate the basic idea of the proposed methodology. From this, we can see the applicability of the proposed method to the real-world problem, even though further future analysis is required.

• Journal of Electrical Engineering and Technology
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• v.4 no.3
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• pp.346-352
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• 2009

The eventual goal of this paper is to help the generating companies and load-serving entities to choose appropriate relative levels of interconnected system versus bilateral trades while considering risk, and economic performance. In competitive power markets, electricity prices are determined by balance between demand and supply in electric power exchanges or bilateral contracts. The problem formulation is bilateral contract incorporated into Multi-area unit commitment with import/export and tie-line constraints. This proposed method considers maximizing own profit or minimize the operating cost among the generating companies in multi-area system. The feasibility of the proposed algorithm has been demonstrated using IEEE system with four areas and experimental results shows that proposed method is reliable, fast and computationally efficient

• Journal of Energy Engineering
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• v.11 no.2
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• pp.142-148
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• 2002

The variations of real time electric price in competitive electricity markets have influence on electric power demands of the consumers. Residential, commercial, and industrial consumers with different characteristics cause the different price elasticity of the demand due to changing the pattern of consumption. Therefore, this paper analyze the effects of spot pricing for the change of the electric power demand based on the demand elasticity of each loads in competitive electricity market.

• Journal of Electrical Engineering and Technology
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• v.7 no.5
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• pp.681-688
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• 2012

This paper presents the application of Differential Evolution (DE) algorithm to obtain a solution for Bid Based Dynamic Economic Dispatch (BBDED) problem including the transmission losses and to maximize the social profit in a deregulated power system. The IEEE-30 bus test system with six generators, two customers and two trading periods are considered under various bidding strategies in a day-ahead electricity market. By matching the bids received from supplying and distributing entities, the Independent System Operator (ISO) maximize the social profit, (with the choices available). The simulation results of DE are compared with the results of Particle swarm optimization (PSO). The results demonstrate the potential of DE algorithm and show its effectiveness to solve BBDED.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.855-857
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• 2005

Transmission congestion is one of the Key factor to local market power in competitive electricity markets. Financial transmission rights provide the financial protection to their holders by paying back the congestion cost. However, the market participants who have market power can exacerbate their market power. This paper analyzes the effect of exercising local market power with the rights on the market price. The proposed methodology was demonstrated with the Optimal Power Flow(OPF). Case study is fulfilled by GAMS simulation. The simulation are condusted in case of Nodal Pricing.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.775-777
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• 2005

In this paper, effects of the subsidy in the electricity market on the market equilibrium are analyzed. The generation competition markets are considered as the basic market structure. The market equilibrium with Cournot game model is derived, first. Then, the variation of Nash equilibrium is investigated when the subsidies to generation companies are provided. The market equilibrium with the subsidy in the electricity market, which is equivalent to the subgame perfect equilibrium, is analytically derived using Stackelberg game model and backward induction method. From this, how the provisions of subsidy to generation companies can affect the strategic behaviors of the generation companies and corresponding market equilibrium are explored, in this paper. Numerical examples are provided to illustrate the basic idea of this paper.