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Accelerating the Composite Power System Planning by Benders Decomposition

This paper presents an application of Benders decomposition to deal with the complexities in the simultaneous Generation Expansion Planning (GEP) and Transmission Expansion Planning (TEP). Unlike the power system operation fields of study, the power system planning methods are not expected to be fast. However, it is always preferable to speed up computations to provide more analysis options for the planner. In this study, Benders decomposition has been applied to solve a mixed integer linear programming formulation of simultaneous GEP & TEP problem. The method has been tested on two test systems: Garver 6-bus system and IEEE 30-bus system. The results are compared to the unified solution of the problem formulation to show the consequent improvements from Benders decomposition.
TK1001-1841, Reliability evaluation, Benders decomposition, TK1-9971, Integrated power system planning, Production of electric energy or power. Powerplants. Central stations, Generation Expansion Planning, Transmission expansion planning, Electrical engineering. Electronics. Nuclear engineering
TK1001-1841, Reliability evaluation, Benders decomposition, TK1-9971, Integrated power system planning, Production of electric energy or power. Powerplants. Central stations, Generation Expansion Planning, Transmission expansion planning, Electrical engineering. Electronics. Nuclear engineering
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
