Least-Cost Structuring of 24/7 Carbon-Free Electricity Procurements

ArXiv ID: 2312.07733 “View on arXiv”

Authors: Unknown

Abstract

We consider the construction of renewable portfolios targeting specified carbon-free (CFE) hourly performance scores. We work in a probabilistic framework that uses a collection of simulation scenarios and imposes probability constraints on achieving the desired CFE score. In our approach there is a fixed set of available CFE generators and a given load customer who seeks to minimize annual procurement costs. We illustrate results using a realistic dataset of jointly calibrated solar and wind assets, and compare different approaches to handling multiple loads.

Keywords: Renewable Portfolios, Carbon-Free Energy (CFE), Probabilistic Constraints, Procurement Costs

Complexity vs Empirical Score

• Math Complexity: 7.5/10
• Empirical Rigor: 8.0/10
• Quadrant: Holy Grail
• Why: The paper employs advanced mathematical concepts like probabilistic constraints, quantile approximations, and SLSQP optimization, indicating high complexity. It is empirically rigorous, featuring realistic data calibration, scenario-based backtesting, and multi-load case studies that simulate real-world procurement structuring.

  flowchart TD
    A["Research Goal: Minimize annual cost of 24/7 CFE procurement"]
    B["Key Inputs: Available CFE generators; Hourly load & renewable data"]
    C["Methodology: Probabilistic framework with CFE score constraints"]
    D["Computational Process: Stochastic optimization across multiple scenarios"]
    E["Outcomes: Optimal renewable portfolio; Cost comparison across strategies"]
    A --> B
    B --> C
    C --> D
    D --> E