Deterministic approach for solving multi-objective non-smooth Environmental and Economic dispatch problem

被引:22
|
作者
Goncalves, Elis [1 ]
Balbo, Antonio Roberto [2 ]
da Silva, Diego Nunes [3 ]
Nepomuceno, Leonardo [1 ]
Baptista, Edrnea Cassia [2 ]
Soler, Edilaine Martins [2 ]
机构
[1] Unesp Univ Estadual Paulista, Fac Engn FEB, Dept Elect Engn, BR-17033360 Bauru, SP, Brazil
[2] Unesp Univ Estadual Paulista, FC, Dept Math, BR-17033360 Bauru, SP, Brazil
[3] Univ Sao Paulo, Sao Carlos Sch Engn EESC, Dept Elect Engn, BR-13566590 Sao Carlos, SP, Brazil
基金
巴西圣保罗研究基金会;
关键词
Economic/environmental dispatch; Multi-objective programming; Modified logarithmic barrier function; Interior/exterior-point; Smoothing functions methods; PARTICLE SWARM OPTIMIZATION; EXTERIOR POINT METHOD; POWER DISPATCH; ALGORITHM; OBJECTIVES; CONSTRAINTS;
D O I
10.1016/j.ijepes.2018.07.056
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The Environmental and Economic Dispatch Problem with Valve-Point loading effect representation (EEDP-VP) is a multi-objective, nonconvex and non-differentiable optimization problem. Due to these difficulties, it has been solved in the literature mainly by heuristic approaches, while deterministic approaches are scarce. Therefore, the main objectives of this paper are to propose a deterministic approach for solving this problem and compare its solutions with the ones obtained by some heuristic and deterministic approaches. The deterministic approach proposed has the following features: the multi-objective nature of the problem is handled by the Progressive Bounded Constraints (PBC) strategy, while the modified logarithmic barrier function method is used to solve the subproblems resulting from the PBC strategy; a smoothing technique is used to handle non-differentiability issues, while the inertia correction strategy is used so that only descent directions are generated. The methodology is applied to five generation systems and the results show that the Pareto-curve is obtained more efficiently when compared to other heuristic and deterministic optimization approaches.
引用
收藏
页码:880 / 897
页数:18
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