Title :
Distributed utility planning using probabilistic production costing and generalized Benders decomposition
Author :
McCusker, Susan A. ; Hobbs, Benjamin F. ; Ji, Yuandong
Abstract :
Summary form only given, as follows. Regulatory changes and advances in distributed resources (DR) technology have lead utilities to consider DRs as alternatives to central station generation and T&D investments. This paper presents a comprehensive planning and production simulation model that simultaneously evaluates central and local investments to determine the optimal mix for long-term expansion. The model can also be viewed as optimizing DRs while simulating a perfectly competitive wholesale power market. The model is a mixed integer linear stochastic program that enforces Kirchhoff´s current and voltage laws, and is solved using generalized Benders decomposition (GBD). The formulation includes multiarea probabilistic production costing as a subproblem. DRs and local distribution reinforcements are modeled as integer variables, while transmission and central generation options are represented as continuous variables. The model is applied to a ten-year multi-area example that suggests that DRs are able to modify capacity additions and production costs by changing demand and power flows.
Keywords :
costing; electricity supply industry; investment; optimisation; power distribution economics; power distribution planning; power generation economics; power generation planning; probability; Kirchhoff´s current laws; Kirchhoff´s voltage laws; capacity additions; competitive wholesale power market; continuous variables; distributed resources technology; distributed utility planning; electric utilities; generalized Benders decomposition; integer variables; investments; local distribution reinforcements; long-term expansion; mixed integer linear stochastic program; multiarea probabilistic production costing; probabilistic production costing; production simulation model; Costing; Costs; Distributed power generation; Investments; Load flow; Optimized production technology; Power markets; Production planning; Stochastic processes; Voltage;
Conference_Titel :
Power Engineering Society Winter Meeting, 2002. IEEE
Print_ISBN :
0-7803-7322-7
DOI :
10.1109/PESW.2002.985230