TY - JOUR
T1 - Zigzag search for multi-objective optimization considering generation cost and emission
AU - Zhang, Qiwei
AU - Li, Fangxing
AU - Wang, Honggang
AU - Xue, Yaosuo
N1 - Funding Information:
This work was supported in part by the US Department of Energy , Office of Electricity , Advanced Grid Modeling under contract DE-AC05-00OR22725 and in part by CURENT, a US NSF/DOE Engineering Research Center under the NSF award EEC-1041877 .
Publisher Copyright:
© 2019
PY - 2019/12/1
Y1 - 2019/12/1
N2 - The zigzag search algorithm has been applied in engineering fields, such as oil well placement, with satisfactory results. In this paper, the zigzag search algorithm is introduced, modified with enhancement, and effectively applied to solve an economic emission dispatch problem and to demonstrate its practicability in power systems. The problem is formulated as a non-linear multi-objective optimization model taking energy constraints, generation limits, and transmission constraints into consideration. A set of non-dominant solutions can be obtained to form the Pareto front. Case studies are carried out with the IEEE 30-bus system and IEEE 118-bus system. The results indicate that the proposed zigzag search algorithms have the ability to deal with relevant power system problems. Comparisons are made with algorithms which have been widely used in literatures, such as the genetic algorithm (GA) and particle swarm optimization (PSO). This demonstrates that the zigzag search is easy to implement and is superior to other multi-objective (MO) techniques in both accuracy and efficiency.
AB - The zigzag search algorithm has been applied in engineering fields, such as oil well placement, with satisfactory results. In this paper, the zigzag search algorithm is introduced, modified with enhancement, and effectively applied to solve an economic emission dispatch problem and to demonstrate its practicability in power systems. The problem is formulated as a non-linear multi-objective optimization model taking energy constraints, generation limits, and transmission constraints into consideration. A set of non-dominant solutions can be obtained to form the Pareto front. Case studies are carried out with the IEEE 30-bus system and IEEE 118-bus system. The results indicate that the proposed zigzag search algorithms have the ability to deal with relevant power system problems. Comparisons are made with algorithms which have been widely used in literatures, such as the genetic algorithm (GA) and particle swarm optimization (PSO). This demonstrates that the zigzag search is easy to implement and is superior to other multi-objective (MO) techniques in both accuracy and efficiency.
KW - Economic emission dispatch
KW - Multi-objective optimization
KW - Non-dominated sorting genetic algorithm
KW - Particle swarm optimization
KW - Zigzag search algorithm
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U2 - 10.1016/j.apenergy.2019.113814
DO - 10.1016/j.apenergy.2019.113814
M3 - Article
AN - SCOPUS:85072024338
SN - 0306-2619
VL - 255
JO - Applied Energy
JF - Applied Energy
M1 - 113814
ER -