Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

On the Selection of Intermediate Length Representative Periods for Capacity Expansion

Osten Anderson, Nanpeng Yu, Konstantinos Oikonomou, Di Wu

TL;DR

This work addresses the gap in capacity expansion modeling for representing interday energy sharing by introducing a snippet-based method to select representative periods of arbitrary length, rather than just days. Building on MPdist-inspired distance concepts, it defines subsequences and a distance matrix, and optimizes a set of $k$ representative periods via a mixed-integer program, with weights reflecting annual coverage. The method is validated on CA-focused CEMs and production-cost models, comparing against representative-day clustering and exploring lengths $s \in \{24,48,72,96,120\}$ hours; results show intermediate-length periods enable interday storage use and can reduce emissions, though too-long periods reduce the representation quality and raise costs. The study demonstrates that period length substantially affects storage sizing, emissions, and investment strategies, offering a practical approach to balance fidelity and tractability in decarbonization planning.

Abstract

As the decarbonization of power systems accelerates, there has been increasing interest in capacity expansion models for their role in guiding this transition. Representative period selection is an important component of capacity expansion modeling, enabling computational tractability of optimization while ensuring fidelity between the representative periods and the full year. However, little attention has been devoted to selecting representative periods longer than a single day. This prevents the capacity expansion model from directly simulating interday energy sharing, which is of key importance as energy generation becomes more variable and storage more important. To this end, we propose a novel method for selecting representative periods of any length. The method is validated using a capacity expansion model and production cost model based on California's decarbonization goals. We demonstrate that the representative period length has a substantial impact in the results of the capacity expansion investment plan.

On the Selection of Intermediate Length Representative Periods for Capacity Expansion

TL;DR

This work addresses the gap in capacity expansion modeling for representing interday energy sharing by introducing a snippet-based method to select representative periods of arbitrary length, rather than just days. Building on MPdist-inspired distance concepts, it defines subsequences and a distance matrix, and optimizes a set of representative periods via a mixed-integer program, with weights reflecting annual coverage. The method is validated on CA-focused CEMs and production-cost models, comparing against representative-day clustering and exploring lengths hours; results show intermediate-length periods enable interday storage use and can reduce emissions, though too-long periods reduce the representation quality and raise costs. The study demonstrates that period length substantially affects storage sizing, emissions, and investment strategies, offering a practical approach to balance fidelity and tractability in decarbonization planning.

Abstract

As the decarbonization of power systems accelerates, there has been increasing interest in capacity expansion models for their role in guiding this transition. Representative period selection is an important component of capacity expansion modeling, enabling computational tractability of optimization while ensuring fidelity between the representative periods and the full year. However, little attention has been devoted to selecting representative periods longer than a single day. This prevents the capacity expansion model from directly simulating interday energy sharing, which is of key importance as energy generation becomes more variable and storage more important. To this end, we propose a novel method for selecting representative periods of any length. The method is validated using a capacity expansion model and production cost model based on California's decarbonization goals. We demonstrate that the representative period length has a substantial impact in the results of the capacity expansion investment plan.
Paper Structure (11 sections, 7 equations, 6 figures)

This paper contains 11 sections, 7 equations, 6 figures.

Table of Contents

  1. Introduction
  2. Background & Problem Statement
  3. Related Work & Paper Contribution
  4. Technical Method
  5. Overview of time series snippets
  6. Proposed Method
  7. Experimental Validation
  8. Experimental Setup
  9. Simulation Models
  10. Results and Discussions
  11. Conclusion

Figures (6)

  • Figure 1: Visualization of distance profiles and minimization of area under the curve of selected profiles.
  • Figure 2: Visualization of an example time series $T$ and subsequences $S_j$ with $u=2$, $s=3$.
  • Figure 3: Fullspace emissions
  • Figure 4: Impact of representative period length on duration and capacity of installed energy storage.
  • Figure 5: Investment and operation costs of differing representative periods
  • ...and 1 more figures