Deterministic electric power infrastructure planning: Mixed-integer programming model and nested decomposition algorithm
Cristiana L. Lara,
Dharik S. Mallapragada,
Dimitri J. Papageorgiou,
Aranya Venkatesh and
Ignacio E. Grossmann
European Journal of Operational Research, 2018, vol. 271, issue 3, 1037-1054
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 adapts previous nested Benders methods by handling integer and continuous state variables, although at the expense of losing its finite convergence property due to potential duality gap. We apply the proposed modeling framework to a case study in the Electric Reliability Council of Texas (ERCOT) region, and demonstrate massive computational savings from our decomposition.
Keywords: Strategic planning; OR in energy; Large-scale optimization (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:271:y:2018:i:3:p:1037-1054
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