• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.60-62
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• 2001

This paper shows the optimal bidding strategy determination method using Nash equilibrium concept by defining bidding strategy vector. This vector is 2-dimension vector whose components are generation amount and generation cost. Thereby we are able to make all possible strategies and their's payoff table. And then we erase dominated strategies one by one so that we obtain Nash equilibrium, the optimal bidding strategy of generation bidding game.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.4
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• pp.202-208
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• 2002

In a dynamic game where the players move in a periodical sequence, each player observes the strategy of the others. So the players who move later in a game get to know the moves of others having made before them. Those who move earlier must take this into account in devising their optimal strategy. In the Poolco model, the bidding game is executed periodically. The player participating in the bidding game accumulates the information of its own and others'strategies, and payoffs through the repeated bidding process. Thereby, the players in this game would be able to map out how get the maximum profit, and get closer to the optimal strategy. This paper presents a mathematical modeling for a player to determine his or her optimal strategy at period T, based on the information acquired from the previous rounds for the periods, T-1, T-2, and so on. The proposed modeling is demonstrated with a dynamic fame theory.

• KIEE International Transactions on Power Engineering
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• v.3A no.1
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• pp.47-52
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• 2003

This paper presents a schematic process based on the method of eliminating dominated strategies to obtain the optimal bidding strategy Pursuing the Nash equilibrium Point. The Proposed approach is demonstrated for a bidding game in a generation competitive market with 2-dimensional bidding strategy vectors constituting a price-quantity strategy curve.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.19-21
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• 2000

This paper presents a game theory application for analyzing power transactions and market design in a deregulated energy marketplace such as PoolCo. The conventional least-cost approaches for the generation resource schedule can not exactly handle recent real-world situations. A systematic tool using game theory for the market participants is presented such that it determines the net profits through the optimal bidding strategies including the strategies for the bidding prices and bidding generations. We treat this power transaction game as incomplete information one, which means each market participants does not know other's cost function. And the demand elasticity of the energy price is considered for the realistic modeling of the deregulated marketplace.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1738-1743
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• 2007

This paper addresses the bidding strategies of a pumped-storage hydro plant in an electricity market. Competitive bidding of pumping and generating of a pumped-storage plant is formulated in a game theoretic problem in accordance with the three different ownership of scheduling; Market Operator(MO), generating company(Genco), and combined type of MO and Genco. Optimal conditions for Nash Equilibrium are derived in the form of market prices during the scheduling periods. Simulation results show the different ownership models produce different schedules of pumping and generating, which correspond to the objective of the scheduling owner of a pumped-storage hydro plant.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.6
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• pp.266-271
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• 2000

The electric power industries are moving from the conventional monopolistic or vertically integrated environments to deregulated and competitive environments, where each participant is concerned with profit maximization rather than system-wide costs minimization. Consequently, the conventional least-cost approaches for the generation resource schedule can not exactly handle real-world situations. This paper presents a game theory application for analyzing power transactions and market design in a deregulated energy marketplace, where the market participants determine the net profits through the optimal bidding strategies. The demand elasticity of the energy price is considered for the realistic modeling of the deregulated marketplace.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.403-405
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• 2000

This paper presents a N-player game theory application for analyzing power transactions in a deregulated energy marketplace such as PoolCo, where, participants, especially, generating entities, maximize their net profits through optimal bidding strategies (i.e., bidding prices and bidding generations). In this paper, the electricity market for power transactions is modeled as a non-cooperative. N-player game with complete information, where the solution is determined in a continuous strategy domain having recourse to the Nash equilibrium idea.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.63-66
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• 2001

In the Poolco model, the bidding game is executed periodically. The player participating to the bidding game accumulates the information of others' strategies and payoffs through the repeated process. Thereby, he is able to map out how he gets his maximum profit, and proceed to the optimal strategy region. This paper shows the algorithm for a player to determine his strategy in t period based the information of the game results of t-1, t-2 period. And this algorithm can be formulated by using Dynamic game theory.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.7
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• pp.352-357
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• 2005

In competitive electricity markets, the System Operator (SO) coordinates the overall maintenance schedules when the collective maintenance schedule reported to 50 by Gencos not satisfy the specified operating criteria, such as system reliability or supply adequacy. This paper presented a method that divides generator maintenance scheduling of the 50 into a master-problem and a sub-problem. Master-problem is schedule coordination and sub-problem is DC-optimal power flow. If sub-problem is infeasible, we use the algorithm of modifying operating criteria of master-problem. And, the 50 should use the open information only, because the information such as cost function of a generator and bidding Price is highly crucial for the strategies of profit maximization.