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LōD (lod.io) — Two fused layers. (1) Harmonized node-level energy market data across 9 North American grids (PJM, MISO, ERCOT, SPP, CAISO, NYISO, ISO-NE, IESO, AESO) — real-time and historical nodal LMP, demand, available capacity, renewable share and a derived grid-stress index across 20,000+ grid nodes. (2) The non-obvious byproduct: private data-center-side telemetry from LōD IoT (real-time monitoring and remote control of 100+ facility estates, 1,000+ MW under management) and LōD Flexible Compute workload-routing/curtailment decisions — i.e. measured IT load, cooling and GPU/workload migr…
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Two fused layers. (1) Harmonized node-level energy market data across 9 North American grids (PJM, MISO, ERCOT, SPP, CAISO, NYISO, ISO-NE, IESO, AESO) — real-time and historical nodal LMP, demand, available capacity, renewable share and a derived grid-stress index across 20,000+ grid nodes. (2) The non-obvious byproduct: private data-center-side telemetry from LōD IoT (real-time monitoring and remote control of 100+ facility estates, 1,000+ MW under management) and LōD Flexible Compute workload-routing/curtailment decisions — i.e. measured IT load, cooling and GPU/workload migration actions timestamped against nodal price and grid-stress conditions.
Scale Very large time-series store. Stated surface: 20From 6 yearsCoverage Information Technology · Utilities
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LōD (lod.io) — Two fused layers. (1) Harmonized node-level energy market data across 9 North American grids (PJM, MISO, ERCOT, SPP, CAISO, NYISO, ISO-NE, IESO, AESO) — real-time and historical nodal LMP, demand, available capacity, renewable share and a derived grid-stress index across 20,000+ grid nodes. (2) The non-obvious byproduct: private data-center-side telemetry from LōD IoT (real-time monitoring and remote control of 100+ facility estates, 1,000+ MW under management) and LōD Flexible Compute workload-routing/curtailment decisions — i.e. measured IT load, cooling and GPU/workload migr…
LōD (lod.io) offers (Alternative, Price, Supply Chain) — Very large time-series store. Stated surface: 20,000+ grid nodes across 9 markets. At 5-minute market intervals that is ~288 intervals/node/day ≈ 5.8M market rows per day, on the order of 2 billion nodal rows per year for market data alone. On top of that, device telemetry from 100+ facilities at 1,000+ MW of load — a 100 MW campus at even 1-second sensor cadence across a few hundred points is >10^9 points/year/site — so total raw history plausibly reaches hundreds of TB. Plus the full automated decision/execution audit log, which is small in bytes and high in value..
Grid-aware AI compute scheduling and RL training environments (paired grid state → observed routing decision → measured cost/curtailment outcome); data-center power cost and PUE benchmarking; demand-response and curtailment model calibration; power-demand and nodal price forecasting including data-center-driven load spikes; colocation/neocloud siting and 'speed to power' analytics; grid-impact modeling of AI load on specific transmission nodes for utilities and IPPs; inference of data-center construction and ramp timelines from contracted-to-active power transitions.
The data is with 6 years of history.
Coverage spans US, Other; Infrastructure Software, Electric Utilities; alternative, price, supply_chain; equities, commodities, derivatives.
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