Optimal Generation and Transmission Expansion Planning Addressing Short-Term Constraints with Co-optimization of Energy and Reserves

TL;DR

This paper presents a MILP model for optimal generation and transmission expansion planning that incorporates hourly constraints, reserves, and short-term operational considerations, enabling efficient long-term planning with manageable computational effort.

Contribution

It introduces a horizon decomposition heuristic and typical day/season representations to handle long planning horizons in a detailed, co-optimized expansion planning model.

Findings

Effective representation of hourly constraints and reserves.

Reduced computational times through horizon decomposition.

Feasible long-term planning with detailed short-term considerations.

Abstract

The penetration of variable renewable energy (VRE) in electrical systems has changed the way the expansion planning is treated. This kind of resource has great variability in small amounts of time, which makes it important to represent hourly constraints that require chronology. Besides that, the generation reserves should also be adjusted in order to capture the intermittent effect, and since many countries use rapid thermal plants as part of these reserves, unit commitment and ramp constraint have also become more significant. In this paper, we propose a MILP expansion planning model that can represent hourly time steps while maintaining reasonable computational times, where both investment and operation problems are simultaneously solved. Because the planning horizons are long (decades), the resolution of the entire horizon in a single optimization problem would be computationally infeasible for large real systems, making it necessary, therefore, to apply a horizon decomposition heuristic in smaller sub-horizons, and use the representation of typical days and seasons to reduces the size of the problem.