Generation Expansion Planning with Upstream Supply Chain Constraints on Materials, Manufacturing, and Deployment

TL;DR

This paper presents a supply chain-constrained generation expansion planning model that incorporates material, manufacturing, and deployment constraints, revealing significant impacts on technology choices, costs, and system reliability.

Contribution

It introduces a novel multi-stage supply chain-constrained planning model and an efficient solution algorithm, addressing a gap in traditional generation expansion models.

Findings

Supply chain constraints influence technology selection and deployment timing.

Constraints can increase investment costs by over $1 billion.

Ignoring upstream constraints risks system reliability under high demand.

Abstract

Rising electricity demand underscores the need for secure and reliable generation expansion planning that accounts for upstream supply chain constraints. Traditional models often overlook limitations in materials, manufacturing capacity, lead times for deployment, and field availability, which can delay availability of planned resources and thus to threaten system reliability. This paper introduces a multi-stage supply chain-constrained generation expansion planning (SC-GEP) model that optimizes long-term investments while capturing material availability, production limits, spatial and temporal constraints, and material reuse from retired assets. A decomposition algorithm efficiently solves the resulting MILP. A Maryland case study shows that supply chain constraints shift technology choices, amplify deployment delays caused by lead times, and prompt earlier investment in shorter lead-time, low-material-intensity options. In the low-demand scenario, supply chain constraints raise investment costs by $1.2 billion. Under high demand, persistent generation and reserve shortfalls emerge, underscoring the need to integrate upstream constraints into long-term planning.