2021
DOI: 10.3390/designs5010003
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Finding Multiple Equilibria for Raiffa–Kalai–Smorodinsky and Nash Bargaining Equilibria in Electricity Markets: A Bilateral Contract Model

Abstract: In a deregulated market, energy can be exchanged like a commodity and the market agents including generators, distributors, and the end consumers can trade energy independently settling the price, volume, and the supply terms. Bilateral contracts (BCs) have been applied to hedge against price volatility in the electricity spot market. This work introduces a model to find all solutions for the equilibria implementing the Raiffa–Kalai–Smorodinski (RKS) and the Nash Bargaining Solution (NBS) approaches in an elec… Show more

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Cited by 2 publications
(1 citation statement)
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“…In the primary-secondary game problem, the payoff optimization problem of the game participants at each level is a nonlinear optimization problem, and it is known from the nonlinear programming theory that the necessary condition for the solution of a nonlinear optimization problem is the Karush-Kuhn-Tucker (KKT) condition; therefore, the solution of a nonlinear optimization problem can be obtained by solving the KKT condition of that nonlinear optimization problem [28]. The KKT condition consists of the constraints of the original lower-level problem, the constraints of the dual problem, the complementary relaxation condition, and the gradient of the Lagrangian function [29]. Thus, optimization can be achieved using KKT conditions.…”
Section: Measurement Of the Double Game Modelmentioning
confidence: 99%
“…In the primary-secondary game problem, the payoff optimization problem of the game participants at each level is a nonlinear optimization problem, and it is known from the nonlinear programming theory that the necessary condition for the solution of a nonlinear optimization problem is the Karush-Kuhn-Tucker (KKT) condition; therefore, the solution of a nonlinear optimization problem can be obtained by solving the KKT condition of that nonlinear optimization problem [28]. The KKT condition consists of the constraints of the original lower-level problem, the constraints of the dual problem, the complementary relaxation condition, and the gradient of the Lagrangian function [29]. Thus, optimization can be achieved using KKT conditions.…”
Section: Measurement Of the Double Game Modelmentioning
confidence: 99%