Scenario Matrix with Scenario Names for PyPSA-USA Energy System Modeling

Trevor Barnes created a scenario matrix dataset for analyzing demand response in multi-sector energy planning. The dataset, last updated in May 2026, is derived from the open-source PyPSA-USA energy system optimization model and contains results from a 2030 case study of California and New England. It compares two demand response pricing strategies and their impact on system-level metrics and net-load characteristics.

Use Cases

• Compare energy carrier-specific versus carrier-independent demand response pricing based on the described strategies.
• Analyze system-level cost savings from electrical and thermal demand response based on the described model outputs.
• Investigate the impact of demand response on service sector space heating capacity investment based on the described findings.
• Perform sensitivity analysis on demand response adoption levels based on the described methodology.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Results are based on the open-source PyPSA-USA energy system optimization model.
• Includes a sensitivity analysis on demand response adoption, as mentioned in the description.
• Explicitly compares two distinct demand response pricing strategies.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (5.5 KB), indicating limited scope and likely summary-level results.

Provenance

Source

figshare

Collection Method

Derived from simulations using the PyPSA-USA energy system optimization model.

Time Range

Future 2030 energy system scenario.

Freshness

Last updated 2026-05-08 17:41:40; freshness should be verified.

Geography

Case study of California and New England, USA.