Multiobjective bilevel optimisation method to solve environmental-economic power generation and dispatch problem with interval data uncertainty. (2016)

• Record Type: Journal Article
• Authors: Pal, Bijay Baran; Kumar, Mousumi
• Is Part Of: International journal of convergence computing. Volume 2: Number 3/4(2016)
• Page Start: 269
• Page End: 288
• Publication Date: 2016
• Subjects: genetic algorithm -- goal programming -- interval goal programming -- IVGP -- mathematical programming -- multiobjective bilevel programming -- MOBLP -- quadratic bilevel programming; Computer science -- Periodicals; 004.05
• Languages: English
• ISSNs: 2048-9129

Abstract

This paper presents a multiobjective bilevel programming (MOBLP) based interval goal programming (IVGP) method for modelling and solving to solve environmental-economic power generation and dispatch (EEPGD) problem using genetic algorithm (GA) in an inexact environment. In the proposed method, the objective functions to be optimised are represented as goals by introducing target intervals for the achievement of objective values in decision horizon. Then, using interval arithmetic rules, the defined planned – interval goals are converted into standard goals as in conventional goal programming (GP) to formulate minsum IVGP model of the problem. In the solution search process, a genetic algorithm (GA) computational scheme is employed in an interactive way to reach the solution of EEPGD problem. The effective use of the approach is illustrated through a case example of the standard IEEE 30-bus 6-generator test system. The model solution is also compared with the solutions obtained by using other approaches studied previously.