Budi, Rizki Firmansyah Setya and Sarjiya, Sarjiya and Hadi, Sasongko Pramono (2021) Majority–dominant–mixed strategy game theory model for deregulated generation expansion planning problem. International Journal on Electrical Engineering and Informatics, 13 (1). 107 – 131. ISSN 20856830
Full text not available from this repository. (Request a copy)Abstract
Obtaining an optimum solution in a deregulated generation expansion planning (GEP) using a mixed strategy game theory method has faced a computation problem. Therefore, this paper proposes a new method called the majority–dominant–mixed strategy (MDMS) game theory to obtain the optimum solution with an acceptable computation time. The MDMS is a social science optimization-based approach that combines a social science concept called the majority rule and the dominant strategy with the mixed strategy. The research results show that the MDMS saves computation time by reducing the matrix size, as shown in the reduced quadratic coefficient of the time complexity trend line. Compared with the mixed strategy, the MDMS obtains the optimum solution with a significant computation time reduction. The optimum solution of the levelized total cost obtained using the MDMS is similar to that obtained using the mixed strategy and lower than that of the improved genetic algorithm (IGA). The MDMS requires a computation time of 23.1 hours, while the mixed strategy requires nine days. The MDMS computation time only slightly differs from that of the IGA previously used in regulated GEP. © 2021, School of Electrical Engineering and Informatics. All rights reserved.
Item Type: | Article |
---|---|
Additional Information: | Cited by: 4; All Open Access, Gold Open Access |
Uncontrolled Keywords: | Deregulated generation expansion planning; social science; game theory; majority dominant strategy; time complexity |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Faculty of Engineering > Electrical and Information Technology Department |
Depositing User: | Sri JUNANDI |
Date Deposited: | 25 Oct 2024 06:21 |
Last Modified: | 25 Oct 2024 06:21 |
URI: | https://ir.lib.ugm.ac.id/id/eprint/8578 |