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Electric Power Infrastructure Planning: Mixed-Integer Programming Model and Nested Decomposition Algorithm

C. L. Lara (cristianallara***at***cmu.edu)
D. Mallapragada (dharik.s.mallapragada***at***exxonmobil.com)
D. Papageorgiou (dimitri.j.papageorgiou***at***exxonmobil.com)
A. Venkatesh (aranya.venkatesh***at***exxonmobil.com)
I. E. Grossmann (grossmann***at***cmu.edu)

Abstract: This paper addresses the long-term planning of electric power infrastructures considering high renewable penetration. To capture the intermittency of these sources, we propose a deterministic multi-scale Mixed-Integer Linear Programming (MILP) formulation that simultaneously considers annual generation investment decisions and hourly operational decisions. We adopt judicious approximations and aggregations to improve its tractability. Moreover, to overcome the computational challenges of treating hourly operational decisions within a monolithic multi-year planning horizon, we propose a decomposition algorithm based on Nested Benders Decomposition for multi-period MILP problems to allow the solution of larger instances. Our decomposition extends previous nested Benders methods by handling integer and continuous state variables. We apply the proposed modeling framework to a case study in the ERCOT region, and demonstrate massive computational savings from our decomposition.

Keywords: strategic planning, OR in energy, large-scale optimization, mixed-integer linear programming, nested decomposition, dual dynamic programming

Category 1: Integer Programming ((Mixed) Integer Linear Programming )

Category 2: Applications -- Science and Engineering

Citation: Submitted for publication

Download: [PDF]

Entry Submitted: 08/12/2017
Entry Accepted: 08/12/2017
Entry Last Modified: 08/28/2017

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