Solution of Economic and Environmental Power Dispatch Problem of an Electrical Power System using BFGS-AL Algorithm

被引:11
作者
Talbi, El Hachmi [1 ]
Abaali, Lhoussine [1 ]
Skouri, Rachid [2 ]
El Moudden, Mustapha [3 ]
机构
[1] Univ Moulay Ismail Meknes, Fac Sci & Tech Errachidia, Dept Phys, Lab Energie Renouvelable Traitement & Transmiss I, Meknes, Morocco
[2] Univ Moulay Ismail Meknes, Ecole Super Technol Meknes, Dept Genie Elect, Lab Etud Mat Avances & Applicat LEM2A, Meknes, Morocco
[3] Univ Mohammed VI Polytech UM6P, Lab Modelisat Simulat & Anal Donnees MSDA, Benguerir, Morocco
来源
11TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 3RD INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS | 2020年 / 170卷
关键词
economic-environmental power dispatch; multi-objective optimization; constraints; convergence; electric power system; OPTIMIZATION ALGORITHM; EMISSION;
D O I
10.1016/j.procs.2020.03.144
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a deterministic optimization strategy to solve the economic-environmental power dispatch (EEPD) problem of an electrical power system, using a Broyden Fletcher Goldfarb Shanno based on the augmented Lagrangian (BEGS-AL) algorithm. This problem is a nonlinear constrained multi-objective optimization. The objectives of this optimization are minimized the total fuel cost and emission amount for thermal generators while satisfying electric power systems equality and inequality constraints. The proposed approach is applied on the standard IEEE 30 bus test system, where the power transmission losses are taken into account. Simulation results proved that the proposed approach gives better-quality solution in terms of accuracy and convergence to the best compromise solution compared to other deterministic and meta-heuristic optimization techniques. (C) 2020 The Authors. Published by Elsevier B.V.
引用
收藏
页码:857 / 862
页数:6
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