Metode Teori Permainan Kooperatif Dengan Mempertimbangkan Ketidakpastian Pada Pengembangan Rencana Induk Kelistrikan

Putri, Wiwit Marta Pangesty (2020) Metode Teori Permainan Kooperatif Dengan Mempertimbangkan Ketidakpastian Pada Pengembangan Rencana Induk Kelistrikan. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pemodelan ketidakpastian melalui operasi stokastik dalam masalah economic dispatch dapat memberikan formulasi yang lebih baik, khususnya pada masalah pengambilan keputusan di dunia nyata. Metode ini juga dapat membantu mengurangi biaya penjadwalan sumber daya jika dibandingkan dengan pendekatan deterministik tradisional. Terlebih, keterlibatan energi terbarukan seperti pembangkit listrik tenaga air, dapat mengurangi biaya lebih jauh. Studi ini mengusulkan pemodelan economic dispatch dengan pendekatan stokastik (SED) pada pembangkit listrik tenaga air dan uap untuk mencari biaya distribusi listrik minimum. Model teori permainan kooperatif juga diformulasikan untuk menentukan koalisi yang menghasilkan biaya investasi minimum. Namun, karena masalah optimasi stokastik membutuhkan komputasi yang tinggi, maka model SED dalam penelitian ini didekomposisi menjadi dua tahap berdasarkan Improved Aggregating-Rule-based Stochastic Optimization (I-ARSO). Pada tahap pertama, sejumlah N skenario Monte Carlo yang mempertimbangkan permintaan daya dan ketersediaan generator digenerasi, kemudian distribusi daya dioptimalkan menggunakan algoritma hibrid berdasarkan optimasi particle swarm dan algoritma artificial fish swarm. Pada tahap kedua, setiap skenario yang optimal disimulasikan untuk mengevaluasi biaya operasi yang sesungguhnya. Akhirnya, teori permainan kooperatif akan memilih skenario terbaik untuk semua pemain untuk mendapatkan total biaya minimum. Biaya ini meliputi biaya operasi, biaya tetap, biaya variabel, dan biaya investasi serta alokasi biaya. ========================================================= Modeling uncertain behavior through stochastic operating strategies in economic dispatch problems may better formulate the nature of real-world decisions and help reduce cost in resource scheduling compared to traditional deterministic approaches. Moreover, the involvement of renewable energy, such as hydro power plant, may further reduce the cost. This study proposes a stochastic economic dispatch (SED) model in thermal and hydro power plants to seek minimum dispatch costs. A cooperative game-theoretic model was also formulated to determine the coalition that will lead to minimum investment cost. In particular, for tackling the issue of high computational requirements when the stochastic optimization problem becomes bigger, SED model in this study was decomposed into two stages based on an improved aggregating-rule-based stochastic optimization (I-ARSO) approach. At the first stage, N Monte Carlo scenarios of power demand and generator availability were generated, and then power dispatch was optimized using the hybrid intelligent algorithm based on particle swarm optimization and artificial fish swarm algorithm. At the second stage, each optimal scenario is simulated to evaluate the corresponding expected operating cost. Finally, cooperative game theory will pick the best arrangement for all players to get the minimum total cost, which includes expected operating cost, fixed cost, variable cost, and investment cost as well as the cost allocation.

Item Type: Thesis (Masters)
Uncontrolled Keywords: economic dispatch, improved aggregating-rule-based stochastic optimization (I-ARSO), teori permainan kooperatif, ketidakpastian, economic dispatch, improved aggregating-rule-based stochastic optimization (I-ARSO), cooperative game theory, uncertainties
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD30.23 Decision making. Business requirements analysis.
H Social Sciences > HD Industries. Land use. Labor > HD30.24 Feasibility studies. Feasibility appraisals
H Social Sciences > HD Industries. Land use. Labor > HD30.28 Planning. Business planning. Strategic planning.
Divisions: Faculty of Industrial Technology and Systems Engineering (INDSYS) > Industrial Engineering > 26101-(S2) Master Thesis
Depositing User: Wiwit Marta Pangesty Putri
Date Deposited: 20 Aug 2020 08:39
Last Modified: 20 Aug 2020 08:39
URI: http://repository.its.ac.id/id/eprint/79323

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