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Game theory for multi-objective and multi-period framework generation expansion planning in deregulated markets

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  • Sarjiya,
  • Budi, Rizki Firmansyah Setya
  • Hadi, Sasongko Pramono

Abstract

A model that can optimize the generation expansion planning in deregulated market by using economic and reliability objective function is needed to meet the requirements of current expansion planning. An optimization model based on economic and reliability objective functions is the purpose in this research. To achieve this goal, this research combines multi-objective function and multi-period framework into game theory. The reliability objective function represented by limitation function, while the economic objective function is a function to find the minimum cost. Therefore, both functions cannot be combined, so that a bi-level optimization method is needed to solve the problem. To find the optimum solution, it uses probability values of a mixed strategy. The values in a mixed strategy are calculated using sequential quadratic program-based quasi-newton method. The optimum solution is the strategy that has the greatest probability values. Reliability Test System is used as the case study. The optimization results show that the game theory multi-period framework multi-objective function can be used and produce optimum planning. This is indicated by the total levelized cost in this research. The cost is 2.96% smaller than the benchmark. All of the reliability indices are still within the standard limit.

Suggested Citation

  • Sarjiya, & Budi, Rizki Firmansyah Setya & Hadi, Sasongko Pramono, 2019. "Game theory for multi-objective and multi-period framework generation expansion planning in deregulated markets," Energy, Elsevier, vol. 174(C), pages 323-330.
    • Handle: RePEc:eee:energy:v:174:y:2019:i:c:p:323-330
    DOI: 10.1016/j.energy.2019.02.105
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    6. Setya Budi, Rizki Firmansyah & Sarjiya, & Hadi, Sasongko Pramono, 2022. "Indonesia's deregulated generation expansion planning model based on mixed strategy game theory model for determining the optimal power purchase agreement," Energy, Elsevier, vol. 260(C).
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