A framework to expedite joint energy-reserve payment cost minimization using a custom-designed method based on Mixed Integer Genetic Algorithm

被引:293
作者
Hamian, Melika [1 ]
Darvishan, Ayda [2 ]
Hosseinzadeh, Mehdi [3 ]
Lariche, Milad Janghorban [4 ]
Ghadimi, Noradin [5 ]
Nouri, Alireza [6 ]
机构
[1] PNU, Dept Engn, Tehran, Iran
[2] Univ Houston, Dept Ind Engn, Houston, TX 77204 USA
[3] Univ Human Dev, Comp Sci, Sulaimaniyah, Iraq
[4] Abadan Sch Med Sci, Abadan, Iran
[5] Islamic Azad Univ, Young Researchers & Elite Club, Ardabil Branch, Ardebil, Iran
[6] Univ Coll Dublin, Sch Elect Elect & Commun Engn, Dublin, Ireland
关键词
Auction mechanisms; Branch and cut; Locational marginal price (LMP); Mixed Integer Genetic Algorithm; Payment cost minimization (PCM); OPERATOR; POWER; MODEL;
D O I
10.1016/j.engappai.2018.03.022
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, a methodology has been proposed to decrease the solution time of the joint energy-reserve market clearing problem under Payment Cost Minimization (PCM) mechanism. PCM mechanism is recently proposed to replace the available economically-inefficient clearing mechanisms in electricity markets. While the exact methods have been successfully applied to solve the market clearing problem under available mechanisms, their computational efficiency is poor when applied to solve this problem under PCM mechanism due to special characteristics of PCM formulation. The proposed solution methodology uses linear programming along with Mixed Integer Genetic Algorithm (MIGA) to minimize the payment cost. Most of efforts are focused on speeding up the applied optimization technique, since the available frameworks for solving the PCM problem suffer from very slow convergence. Different custom-designed functions have been added to the basic MIGA to decrease the solution time. The results are compared to those obtained using branch and cut technique.
引用
收藏
页码:203 / 212
页数:10
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