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

被引:23
作者
Sarjiya [1 ]
Budi, Rizki Firmansyah Setya [1 ]
Hadi, Sasongko Pramono [1 ]
机构
[1] Univ Gadjah Mada, Dept Elect & Informat Engn, Yogyakarta, Indonesia
关键词
Generation expansion planning; Deregulated market; Game theory; Multi-period framework; Bi-level optimization; GENETIC ALGORITHM; POWER-GENERATION; OPTIMIZATION; NETWORK; INVESTMENTS; DESIGN; SYSTEM;
D O I
10.1016/j.energy.2019.02.105
中图分类号
O414.1 [热力学];
学科分类号
摘要
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. (C) 2019 Published by Elsevier Ltd.
引用
收藏
页码:323 / 330
页数:8
相关论文
共 44 条
[1]  
Ahmed KS, 2016, PROCEEDINGS OF THE 2016 IEEE REGION 10 CONFERENCE (TENCON), P723, DOI 10.1109/TENCON.2016.7848097
[2]  
[Anonymous], 2017, RENC US PEN TEN LIST
[3]   Evaluation of Regulatory Impacts on Dynamic Behavior of Investments in Electricity Markets: A New Hybrid DP/GAME Framework [J].
Barforoushi, Taghi ;
Moghaddam, Mohsen P. ;
Javidi, M. Hossein ;
Sheikh-El-Eslami, Mohammad K. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2010, 25 (04) :1978-1986
[4]  
Birmano MD, 2008, J PENGEMBANGAN ENERG, V10, P77
[5]   Optimal investments in power generation under centralized and decentralized decision making [J].
Botterud, A ;
Ilic, MD ;
Wangensteen, I .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2005, 20 (01) :254-263
[6]  
Chatterjee B, 2009, P INT C METH MOD DEL, DOI DOI 10.1109/ICM2CS.2009.5397970.2009
[7]   Review: Multi-objective optimization methods and application in energy saving [J].
Cui, Yunfei ;
Geng, Zhiqiang ;
Zhu, Qunxiong ;
Han, Yongming .
ENERGY, 2017, 125 :681-704
[8]   REACTIVE POWER OPTIMIZATION BY GENETIC ALGORITHM [J].
IBA, K .
IEEE TRANSACTIONS ON POWER SYSTEMS, 1994, 9 (02) :685-692
[9]   Strategic Generation Investment Under Uncertainty Via Benders Decomposition [J].
Jalal Kazempour, S. ;
Conejo, Antonio J. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2012, 27 (01) :424-432
[10]   A two-stage reactive power optimization in transmission network incorporating reserves from voltage-dependent loads [J].
Jin, Hongyang ;
Li, Zhengshuo ;
Sun, Hongbin ;
Guo, Qinglai ;
Wang, Bin .
ENERGY, 2018, 157 :752-763