LACE-S uses a neural representation with a projection layer and Jacobian regularization to produce locational carbon emission metrics that remain consistent with total emissions and sensitivities, leading to reliable system-wide emission reductions in load-shifting tests unlike prior metrics.
Balancing energy market integration considering grid constraints,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SY 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
LACE-S: Toward Sensitivity-consistent Locational Average Carbon Emissions via Neural Representation
LACE-S uses a neural representation with a projection layer and Jacobian regularization to produce locational carbon emission metrics that remain consistent with total emissions and sensitivities, leading to reliable system-wide emission reductions in load-shifting tests unlike prior metrics.