Data Catalog

ERCOT·Locational marginal prices from ERCOT's real-time market, published every five minutes by Security Constrained Economic Dispatch (SCED) for resource nodes, load zones, and trading hubs. This table supports observed price levels, rankings, volatility, and basis between settlement points. Total-LMP differences do not identify a congestion component, binding facility, shift factor, or physical topology relationship, so they cannot establish why two points separated without matched attribution data. The official source is ERCOT report NP6-788-CD (Settlement Point Prices at Resource Nodes, Hubs and Load Zones).

ERCOT·Locational marginal prices for each electrical bus in ERCOT, produced by Security Constrained Economic Dispatch (SCED) roughly every five minutes. This is the finest public spatial view of observed ERCOT price variation and supports bus-level ranking, history, and basis analysis. A bus price or price spread alone does not identify a binding constraint, congestion component, or electrical relationship to another entity; those claims require direct component or attribution evidence.

ERCOT·ERCOT's five-minute real-time system lambda, the system-wide marginal energy component of SCED LMP. For a settlement point or electrical bus in the same SCED interval, LMP minus system lambda is the point's congestion component; ERCOT LMP has no marginal-loss component. This supports point-level congestion rankings and history when joined interval by interval to real-time LMP. It does not identify which binding constraint affected a point without shift-factor or other direct attribution evidence.

ERCOT·ERCOT's hourly day-ahead system lambda, the system-wide marginal energy component in the cleared Day-Ahead Market. For the same delivery hour and settlement point, day-ahead SPP minus DAM system lambda is the point's cleared day-ahead congestion component. Paired with SCED system lambda and real-time LMP, it supports day-ahead-versus-real-time congestion basis by point. It does not identify a binding constraint's effect on a point without direct attribution evidence.

ERCOT·Binding transmission constraint and contingency pairs from ERCOT's Security Constrained Economic Dispatch runs, including the named facilities, limits, flows when published, violations, and shadow prices. A row establishes that the named constraint bound in that SCED interval and its marginal system cost. It does not, by itself, identify which settlement point or hub the constraint affected, measure total substation utilization, or explain every contemporaneous LMP separation; those claims require shift-factor or direct attribution evidence. History spans 2017 to present. The official source is ERCOT report NP6-86-CD.

ERCOT·Cleared ERCOT monthly Congestion Revenue Right auction awards, one row per source-to-sink CRR and time-of-use block, including awarded MW and the auction shadow price per MWh. This is public auction evidence for who acquired a path and at what clearing price. It does not contain realized day-ahead congestion settlements, fees, later trades, the holder's full portfolio, or net profit, so auction cost must not be described as payout or profitability. The official source is ERCOT report NP7-803-M.

ERCOT·Hourly settlement point prices cleared in the ERCOT Day-Ahead Market, covering every settlement point in Texas (load zones, hubs, and resource nodes). These are the prices at which energy is bought and sold a day in advance of delivery, set the afternoon before each operating day. They are the day-ahead counterpart to real-time locational prices, and the gap between the two reflects how the market expected conditions to differ from how they actually unfolded. Traders use them to position and hedge, generators and loads use them to plan commitments, and researchers use them to study how congestion and scarcity show up across the grid.

ERCOT·Hourly market clearing prices for the ancillary services ERCOT procures alongside energy in its Day-Ahead Market, broken out by product: Regulation Up (RegUp), Regulation Down (RegDown), Responsive Reserve (RRS), Non-Spinning Reserve (NSPIN), and the ERCOT Contingency Reserve Service (ECRS). These prices represent what the grid pays per megawatt to hold capacity in reserve for frequency control and contingency response, separate from the energy itself. Watching them shows when reserves are scarce and expensive (often during tight or volatile conditions), which informs how generators and storage operators allocate capacity between energy and reserve markets, and gives researchers a read on the cost of keeping the Texas grid reliable. ECRS, added in 2023, is the newest of these products and has at times cleared at notably high levels.

ERCOT·This dataset reports the total quantity of ancillary services ERCOT procured in its Day-Ahead Market, broken out by product (such as Regulation Up, Regulation Down, Responsive Reserve, ECRS, and Non-Spinning Reserve) for each delivery hour. These figures show how much reserve capability ERCOT set aside to keep supply and demand balanced and to respond to contingencies, separate from the energy cleared for actual generation. Paired with the per-product clearing prices, the cleared volumes let traders, researchers, and the public see how reserve requirements shift hour to hour and how much of the market's capacity is committed to grid reliability rather than energy. The data comes from ERCOT report NP4-532-CD (DAM Total AS Sold) and updates with each day-ahead market run.

ERCOT·This dataset reports the total energy sold in ERCOT's Day-Ahead Market, in megawatt-hours, for each delivery hour. It represents the system-wide quantity of energy that cleared the day-ahead auction, where buyers and sellers commit to next-day positions before real-time operations. The hourly shape across a day shows how much of expected Texas demand is locked in financially a day ahead, and tracking it over time reveals shifts in day-ahead market participation and how forward commitments line up against eventual real-time conditions. The figures come from ERCOT report NP4-193-CD.

CAISO·Locational marginal prices from CAISO's real-time pre-dispatch market, published at 15-minute resolution for pricing nodes across the California ISO footprint. Each row carries total LMP and its energy, congestion, and loss components for one node and interval. A non-null component supports attribution of that portion of the node price, but neither total LMP nor the component alone names the binding facility or proves a topology relationship; direct constraint attribution is still required. The official source is CAISO OASIS.

CAISO·Hourly locational marginal prices from CAISO's day-ahead market for pricing nodes across the California ISO footprint. These are the prices cleared before the operating day, reflecting the market's expected supply, demand, congestion, and losses for each delivery hour. Comparing this dataset with real-time RTPD prices shows how expectations diverged from actual grid conditions, which is useful for analyzing basis, congestion risk, renewable forecast error, and day-ahead versus real-time market performance. The official source is CAISO OASIS.

CAISO·CAISO OASIS 5-minute real-time shadow prices on intertie / scheduling-point constraints, by tie and flow direction. The shadow price is the marginal cost of a binding intertie limit, so this is the direct signal for congestion between CAISO and neighboring balancing areas: a non-zero price means an import/export path is constrained and is shaping locational prices at the border. Traders use it to explain inter-BAA basis and to see which ties are binding and in which direction, and operators use it to track where transfer limits are actively holding back scheduling. History spans 2015 to present at ~99% daily coverage. The official source is CAISO OASIS.

CAISO·CAISO OASIS 5-minute real-time interval shadow prices on nomogram constraints. A nomogram is a multi-element stability or transfer limit (a relationship across several branches or interfaces rather than a single line), so a binding nomogram shadow price flags where a security constraint — not just one overloaded line — is driving congestion cost. Useful for understanding structural transmission limits and stability-driven congestion in the CAISO footprint, complementing the single-branch and intertie shadow prices. History spans 2015 to present at ~99% daily coverage. The official source is CAISO OASIS.

NYISO·Real-time locational-based marginal prices (LBMP) for NYISO's public load-zone pricing locations, published at five-minute resolution with energy, congestion, and loss components. The map uses these zonal LBMP locations for NYISO's live price dots, with IDs matching NYISO MIS zone names such as WEST, CAPITL, N.Y.C., and LONGIL.

NYISO·Hourly day-ahead locational-based marginal prices (LBMP) for NYISO load zones. These prices clear before the operating day and provide the day-ahead companion to real-time zonal LBMP, useful for DA/RT spreads, congestion expectations, and load-zone market analysis.

NYISO·NYISO real-time ancillary-service prices by pricing location, keyed by PTID, with separate columns for 10-minute spinning reserve, 10-minute non-synchronous reserve, 30-minute operating reserve, regulation capacity, and regulation movement. Use this with energy LBMP when analyzing reserve scarcity, regulation value, or storage/operator behavior beyond energy-only dispatch.

NYISO·NYISO day-ahead ancillary-service prices by pricing location, keyed by PTID, with separate columns for 10-minute spinning reserve, 10-minute non-synchronous reserve, 30-minute operating reserve, and regulation capacity. These prices show the reserve and regulation stack cleared before the operating day, complementing day-ahead energy LBMP for full market-context analysis.

NYISO·NYISO real-time five-minute generator-level LBMP by generator PTID, with energy, congestion, and loss components. Use this for generator-node market analysis where the public zonal LBMP map is too coarse.

NYISO·NYISO hourly day-ahead generator-level LBMP by generator PTID, with energy, congestion, and loss components. It is the generator-level day-ahead companion to zonal day-ahead LBMP.

NYISO·NYISO settlement-style hourly integrated real-time LBMP for generator PTIDs. Use it when hourly generator-level price settlement is more appropriate than raw five-minute LBMP.

NYISO·NYISO settlement-style hourly integrated real-time LBMP for load zones. It complements the raw five-minute zonal LBMP feed used by the live map.

NYISO·NYISO reference-bus LBMP for NYISO_LBMP_REFERENCE / PTID 24008. This gives the system reference price used for normalizing zonal and generator LBMP components.

NYISO·NYISO Coordinated Transaction Scheduling prices by generator PTID and RTC timestep, including NYISO generator LBMP and the paired external RTO CTS price for PJM / ISO-NE coordination analysis.

NYISO·NYISO day-ahead energy-market summary by hour, including load forecast, total scheduled load, generation scheduled, imports, exports, net imports, and virtual load/supply.

NYISO·NYISO hour-ahead market energy summary by hour, including internal bilaterals, generation capacity bid, generation scheduled, imports, exports, and net imports.

PJM·Locational marginal prices from PJM's real-time energy market, published every five minutes for each pricing node (pnode) before settlement verification. Each row carries total LMP plus congestion and marginal-loss components in dollars per MWh. Components support node-level price decomposition, but price differences do not identify a named binding facility or prove topology. This is the freshest PJM price feed; use the settled hourly feed for the verified record published roughly 18 hours later. Point classes span transmission zones, trading hubs, external interfaces, and aggregate nodes. Source: PJM Data Miner 2.

PJM·PJM's verified real-time locational marginal prices at hourly granularity for every pricing node, with total LMP and its system-energy, congestion, and marginal-loss components in dollars per MWh. These are the settled, authoritative real-time prices — published on roughly an 18-hour lag behind the operating hour — and history reaches back to 2018, making this the table for real-time price history, day-over-day basis, and volatility studies. For prices in the current hour use the unverified 5-minute feed instead. Source: PJM Data Miner 2.

PJM·Cleared day-ahead locational marginal prices for each PJM pricing node by delivery hour, with total LMP and its system-energy, congestion, and marginal-loss components in dollars per MWh. The table supports the posted next-day hourly curve, day-ahead-to-real-time basis, and node-level component attribution. A congestion component does not by itself identify which facility is expected to bind or establish a node-to-constraint relationship. Source: PJM Data Miner 2.

SPP·Locational marginal prices for SPP settlement locations, carrying total LMP and its marginal energy (mec), congestion (mcc), and loss (mlc) components. Covers both the five-minute real-time balancing market and the hourly day-ahead market, distinguished by market_run ('rt_5min' and 'da_hourly'). Around 1,600 settlement locations report on the live feed. Note that location_name and location_type are published empty on this feed, so a location cannot be classified as hub, generator, or interface from this table alone. SPP's two market trading hubs are SPPNORTH_HUB and SPPSOUTH_HUB; other identifiers containing 'HUB' are participant settlement aggregates, not market hubs.

SPP·Real-time locational marginal prices at the individual electrical bus, with total LMP and its marginal energy, congestion, and loss components. This is SPP's finest-grained public price view, well below the settlement-location tier, and is the table to use when a question concerns a specific bus rather than a settlement point. Real-time only: SPP publishes no day-ahead equivalent at bus granularity on this feed.

SPP·Cleared ancillary-service prices by SPP reserve zone for both the real-time balancing market and the day-ahead market. SPP's product set does not map onto other ISOs': regulation clears as a separate service (capacity) price and mileage price in each direction (reg_up_service, reg_up_mile, reg_dn_service, reg_dn_mile), alongside ramp up and down, spinning, supplemental, and uncertainty products. IMPORTANT: reserve_zone mixes two grains. It carries the numeric ancillary reserve zones (1 through 5 under the SPP balancing authority, 21 under the separate SWPW balancing authority) AND the two balancing-authority roll-ups, 'SPP' and 'SWPW', whose prices equal those of their member zones. Aggregating across every value of reserve_zone double-counts the market.

SPP·Cleared ancillary-service quantities in MW by SPP reserve zone: regulation up and down, ramp up and down, spinning, supplemental, and both uncertainty products (unc_up and the short-term sts_unc_up). The quantity counterpart to the ancillary clearing prices. The same reserve_zone caveat applies: the column carries both the numeric reserve zones and the 'SPP' and 'SWPW' balancing-authority roll-ups, so aggregating across every value double-counts.

ERCOT·Hourly weather-zone actual-load history for ERCOT, including the eight weather zones and a system total. Use it for zonal and historical hourly analysis; for the freshest current system-wide demand, prefer System-Wide Demand (ercot_system_wide_demand) after comparing latest timestamps. Analysts use this archive to study load shape and peaks, normalize demand against temperature, and contextualize price moves and reserve conditions. It comes from ERCOT report NP6-345-CD.

ERCOT·ERCOT's mid-term load forecast (MTLF) for the Texas grid, giving the expected electricity demand for each of the next seven days at hourly resolution. The forecast is broken out by ERCOT's eight weather zones plus a system-wide total, and a new vintage is issued every hour, so you can also see how the outlook for a given day shifts as it approaches. Operators use this to plan generation and reserves, while traders and researchers use it to anticipate price and tightness conditions and to study how forecasts evolve and where they miss. The official source is ERCOT report NP3-565-CD, Seven-Day Load Forecast by Weather Zone.

ERCOT·ERCOT's public real-time supply and demand dashboard at five-minute resolution. This is the preferred dataset for a current actual-versus-forecast demand comparison: series='realized' reports observed demand_mw, series='intraday_forecast' reports demand_mw forecast for the same target event_time at successive source_time vintages, and series='forward_forecast' reports forecasted_demand_mw farther ahead. It also carries committed and available capacity. Operators, traders, and researchers use it to measure current forecast error, headroom, and how forecasts converge toward realized demand.

ERCOT·This dataset reports actual system-wide electricity demand across the ERCOT region of Texas, summed to a single total at 15-minute intervals. It comes from ERCOT's official Actual System Load by Weather Zone and system-wide reporting (report NP6-235-CD) and reflects settled demand rather than the faster, provisional real-time readings. Operators, traders, and researchers use it to study how Texas load rises and falls through the day and across seasons, to benchmark forecasts against what the grid actually consumed, and to anchor analyses of peak demand and stress events.

ERCOT·Per-resource, per-interval telemetry for ERCOT's controllable Load Resources — large loads that curtail or provide ancillary services — from the 60-Day SCED Disclosure Reports. Each row is one SCED run (roughly every five minutes) for one load resource and its QSE, showing its real power consumption alongside its maximum and low consumption, its high/low ancillary and dispatch limits (HASL/HDL, LASL/LDL), its SCED dispatch target (base point) and telemetered status, and how much of each ancillary service it was carrying (Reg-Up, Reg-Down, RRS, RRS-FFR, Non-Spin, ECRS). Because Load Resources are how demand-side capacity participates in ERCOT's real-time market and reserves, this dataset shows demand response actually happening at five-minute resolution — how much load was armed for responsive reserve, when it was deployed, and how it followed dispatch. Like the gen file it is published on a 60-day regulatory delay, making it a historical record for studying demand-side flexibility, reserve provision, and load participation in scarcity events. The official source is ERCOT report NP3-965-ER, 60-Day SCED Disclosure Reports.

CAISO·Hourly actual electricity demand from CAISO OASIS, reported for the CAISO system total and TAC load areas such as PG&E, SCE, and SDG&E. This settlements-grade series is published after the operating interval rather than as a live five-minute reading. It supports forecast benchmarking, historical load shape, and aligned hourly net-load analysis. The official source is CAISO OASIS.

CAISO·CAISO load forecasts for the system and TAC load areas, including the near-term RTM 5-minute load forecast used by the application map. Each forecast row gives expected megawatt demand for a target interval and forecast label, so the data can be compared with actual load as conditions evolve. Operators and analysts use these horizons to understand expected ramping needs, assess forecast miss, and anticipate tight net-load periods before they show up in realized demand. The public source is CAISO Today's Outlook.

NYISO·NYISO integrated actual load by load zone at hourly resolution. The table covers the eleven NYISO zones and is the settlements-grade actual-load series used by the NYISO map cards; system actual load is computed by summing the zone rows.

NYISO·NYISO hourly load forecast by load zone plus a NYISO system-total row, with source_time preserving forecast vintage. The application uses the latest vintage per target hour to compare expected load against realized hourly actuals.

NYISO·NYISO preliminary real-time actual load by load zone at five-minute resolution. This is the higher-cadence load series for intraday grid movement, while hourly integrated actual load remains the settlement-quality hourly view.

NYISO·NYISO day-ahead zonal bid-load components by zone: energy bid load, bilateral load, price-cap load, virtual load, and virtual supply. Use it to compare bid-in demand with forecasts and realized load.

PJM·PJM metered load sampled every five minutes by area, where 'PJM RTO' is the whole-RTO system total and the remaining areas are the transmission-zone operating regions (AEP, COMED, DOM, PSEG, and so on). Because it posts within minutes, this is the live demand signal for PJM — system load, zonal load, and the shape of the daily peak — unlike the hourly metered-load tables that settle on a delay. Source: PJM Data Miner 2.

PJM·PJM's very-short-term load forecast by forecast area, covering roughly the next two hours at fine granularity. Rows are keyed by their target time (event_time) with the issue time in evaluated_at_utc, so the latest vintage for each target comes from an argMax over evaluated_at_utc. Forecast areas use utility names (AE/MIDATL, DOMINION, and RTO_COMBINED for the system total). Use it for the immediate demand trajectory; for tomorrow and the week ahead use the 7-day forecast. Source: PJM Data Miner 2.

PJM·PJM's seven-day-ahead hourly load forecast by forecast area, refreshed through the day. Rows are keyed by target time (event_time) with the issue time in evaluated_at_utc; take the latest vintage per target hour via an argMax over evaluated_at_utc. Forecast areas match the very-short-term feed (utility names, RTO_COMBINED for the system total). This is the table for tomorrow's peak and the week-ahead demand outlook. Source: PJM Data Miner 2.

SPP·SPP's realized system-wide demand in MW at five-minute resolution, the actual-load counterpart to the short-term and mid-term load forecasts. Note that the feed republishes the same event_time on successive polls with a fresh ingested_at, so a read should collapse repeats on ingested_at before use.

SPP·SPP's short-term load forecast in MW. Bitemporal: each row carries both the delivery interval (event_time) and the vintage the forecast was issued at (publish_time), so successive forecasts for the same interval are retained rather than overwritten. That makes the table usable for forecast-error and forecast-convergence analysis, not only for the latest view.

SPP·SPP's mid-term load forecast in MW, running roughly seven days ahead, carried alongside the realized actual for the same interval so forecast error can be computed within the table. Bitemporal: each row records the delivery interval and the vintage the forecast was published at, retaining every successive forecast for a given hour.

ERCOT·ERCOT's Fuel Mix Report (IntGenByFuel) gives actual electricity generation across the Texas grid broken out by fuel type, for every 15-minute settlement interval. Each interval lists output for categories such as gas, coal, nuclear, wind, solar, hydro, and storage, with values first published as initial readings and later restated as settlement-quality finals. It shows what physically ran on the system and in what proportion, letting operators, traders, and researchers track the real-time generation mix, gauge renewable penetration against load, and study how the fuel stack shifts hour to hour and season to season. The SQL agent queries this through the unified `ercot_fuel_mix` view (quality='settled') rather than this table directly.

US reference·Realized ERCOT generation in megawatts by fuel type (coal, hydro, nuclear, storage, solar, wind, gas, other), one row per (event_time, fuel_type, quality). Long-format unification of the live 5-minute feed and the settlement-grade Fuel Mix Report — but quality='settled' is TEMPORARILY DISABLED: ercot.fuel_mix_report's gen_mw was found to be ~4x too low (ERCOT publishes MWh delivered per 15-min interval, not average MW, and the writer didn't convert). The write-path bug is fixed, but existing report rows are still wrong pending a full historical backfill, so this view currently emits quality='live' only (the 5-minute feed, which reads a separate MW-native source and is correct). The settled branch will return once the backfill is verified. Always filter by event_time; this is a view, and an unbounded scan is expensive. This is the table the SQL agent actually queries; ercot_fuel_mix_report and ercot_fuel_mix_5min remain in the public catalog as the underlying raw sources.

ERCOT·Realized generation in megawatts across ERCOT's eight headline fuel categories (such as gas, wind, solar, nuclear, coal, and hydro), reported at five-minute intervals for the Texas grid. This is the live operational view of where power is actually coming from at any moment, the faster companion to the settlement-grade Fuel Mix Report. It lets operators, traders, and researchers watch the resource mix shift in near real time, track renewable ramps and gas response intraday, and see how generation composition moves with load and prices. The official upstream source is ERCOT report NP6-788-CD (Fuel Mix Report). The SQL agent queries this through the unified `ercot_fuel_mix` view (quality='live') rather than this table directly.

ERCOT·Hourly wind generation across the ERCOT footprint in Texas, broken out by geographic region (five regions plus the system-wide total), with both observed output and the successive forecast vintages ERCOT publishes ahead of each hour. Because wind is concentrated in specific parts of the state, the regional split shows where the generation is physically coming from and how it shifts with weather. Comparing the forecast vintages against the realized values reveals how wind expectations firmed up as the operating hour approached, which informs net-load estimates, congestion and ramping risk, and price formation. Sourced from ERCOT report NP4-742-CD (Wind Power Production).

ERCOT·Solar generation across the ERCOT footprint, broken out by geographic region and rolled up system-wide, at hourly resolution. Alongside metered actuals, it carries the successive forecast vintages ERCOT publishes for each region, including the capacity-based high sustained limit (COP HSL) and the two physical solar production forecasts (STPPF and PVGRPP), so you can see what was expected versus what was delivered. This is the basis for tracking how solar output ramps through the day, how forecasts evolve as an operating hour approaches, and where regional solar buildout is concentrating across Texas. It comes from ERCOT report NP4-745-CD, Solar Power Production, Hourly Averaged Actual and Forecasted Values by Geographical Region.

ERCOT·ERCOT's Hourly Resource Outage Capacity report — the amount of generation capacity out of service across the Texas grid, projected hour by hour over a rolling seven-day horizon. Each posting from the Outage Scheduler breaks the outaged megawatts out by weather zone (South, North, West, Houston) and by category: Total Resource (a proxy for thermal outages), Total IRR (intermittent wind and solar), and Total New Equipment Resource (units still in commissioning). It is bitemporal — every row carries both the projected delivery hour (event_time) and the publishing vintage (source_time), and because ERCOT revises the projection every hour, successive vintages accumulate as distinct rows rather than overwriting. This is the core dataset for seeing how much capacity is unavailable at any moment, how outage expectations shift as an operating hour approaches, and how planned and forced outages concentrate by region — a direct input to scarcity, reserve adequacy, and reliability-unit-commitment analysis. The official source is ERCOT report NP3-233-CD, Hourly Resource Outage Capacity.

ERCOT·ERCOT's operating-day Resource Planned Outage Limit (RPOL) and the aggregate planned-outage megawatts already approved or received for that day. The report separates non-IRR/non-PUN generation, Energy Storage Resources (ESR), and Intermittent Renewable Resources (IRR), and publishes successive vintages from seven days through 60 months ahead. It is grid-level scheduling evidence: it does not identify the resources behind the approved or received totals. The official source is NP3-161-CD, Available Resource Planned Outage Capacity Margin 7 Day Plus.

ERCOT·The ERCOT Generation Outages dashboard feed, recorded as system snapshots. It reports total, planned, and forced or unplanned generation-capability reductions, with dispatchable and renewable breakdowns. These are aggregate MW values submitted by Market Participants and can include full outages and partial reductions; they are not per-resource outage identities. The dashboard covers the current day and previous six days.

ERCOT·How much generation capacity ERCOT's Reliability Unit Commitment (RUC) process has effectively forced online, hour by hour. For each hour of the RUC study period, ERCOT publishes the sum of the High Sustained Limits (HSLs) of resources that are online in the most recent SCED execution but were indicated as offline in their Current Operating Plan (COP) — i.e. capacity RUC committed beyond what the market self-committed. This is a direct hourly proxy for RUC-committed MW, the signal behind reliability commitments on tight days. From 2021 the megawatts are broken out by weather zone (South, North, West, Houston) with committed_capacity_mw as the system total; earlier vintages (back to October 2018) carry the system-wide total only, since ERCOT did not publish the zonal split before then. It is bitemporal — every row carries both the study delivery hour (event_time) and the publishing vintage (source_time), so successive hourly RUC runs accumulate as distinct rows. The official source is ERCOT report NP3-764-CD, Hourly RUC Online In SCED Offline In COP.

ERCOT·Per-resource, per-interval telemetry for every generating unit in ERCOT, taken from the 60-Day SCED Disclosure Reports. Each row is one SCED run (roughly every five minutes) for one generation resource and its QSE, so you can see exactly what the market told each unit to do and what it was physically doing: the SCED dispatch target (base point), the unit's telemetered net output, its high and low sustainable/ancillary/dispatch limits (HSL/HASL/HDL, LSL/LASL/LDL), its output schedule and telemetered status, and how much of each ancillary service it was responsible for (Reg-Up, Reg-Down, RRS, RRS-FFR, Non-Spin, ECRS). ERCOT publishes these disclosures with a 60-day regulatory delay, so this is a rich historical record rather than a live feed — the single best source for studying how individual plants were dispatched, how close they ran to their limits, how they followed SCED base points, and how ancillary-service obligations were spread across the fleet. It is the highest-volume subreport in the bundle (~250k rows per disclosure day). The official source is ERCOT report NP3-965-ER, 60-Day SCED Disclosure Reports.

CAISO·Hourly renewable generation actuals for the CAISO footprint, broken out by renewable resource type such as solar and wind. This dataset shows how much renewable output was physically contributing to the California grid in each hour, making it central to net-load analysis and to understanding ramps around sunrise and sunset. Paired with actual load and real-time prices, it helps explain when renewable production is easing supply conditions or when falling output is creating evening ramp pressure. The public source is CAISO Today's Outlook.

CAISO·Observed five-minute net output from standalone and hybrid battery storage across the CAISO footprint. The total supply_mw field is positive when batteries are discharging into the grid and negative when they are charging from the grid; standalone_batteries_mw and hybrid_batteries_mw are components of that total, not additional generation to add on top. This is the live operating series published in CAISO Today's Outlook, not nameplate capacity or state of charge.

NYISO·Real-time NYISO system generation by fuel category every five minutes, including Dual Fuel, Natural Gas, Nuclear, Hydro, Wind, Other Renewables, and Other Fossil Fuels. This is the live generation-mix source for the NYISO status strip and fuel-stack questions.

NYISO·NYISO estimated behind-the-meter solar actual generation by load zone at hourly resolution. This is the distributed PV contribution that does not appear as utility-scale generation.

NYISO·NYISO day-ahead behind-the-meter solar forecast by load zone at hourly resolution. Use it to compare expected distributed PV output against estimated actual BTM solar.

NYISO·NYISO estimated behind-the-meter solar installed capacity by load zone. This tracks distributed PV nameplate growth over time.

NYISO·NYISO real-time implied marginal emission rate by zone, including CO2 and NOx rates derived from real-time LBMP, VOM, and implied heat rate.

NYISO·NYISO day-ahead implied marginal emission rate by zone, including CO2 and NOx rates derived from day-ahead LBMP, VOM, and implied heat rate.

NYISO·NYISO rolling forecast of total generator maintenance outage MW by future date. This is a forward outage/availability context feed and currently has no full historical archive writer.

US reference·A generator-level inventory of every operable utility-scale electric generator in the United States, drawn from EIA Form 860. Each record describes one generating unit, including its nameplate capacity, technology and prime mover, primary energy source, operating status, owner or operator, balancing authority, and the latitude and longitude of its plant. It is the standard reference for understanding what physical generation exists on the grid, where it sits, and how it is fueled. Annual final filings give the authoritative year-end picture, while the monthly EIA-860M updates track newly proposed, added, and retired units between annual releases, making it useful for tracking the fleet's evolving capacity mix and the buildout of new resources.

US reference·This is the utility-scale solar slice of the EIA-860 generator inventory, listing every operating solar generating unit along with its plant, location, owner, nameplate and net capacity, and in-service dates. It adds solar-specific attributes such as panel tracking type (fixed, single-axis, or dual-axis) and tilt angle. Researchers and analysts can use it to map where solar capacity sits on the grid, gauge how design choices shape generation profiles, and track the buildout of utility-scale solar over time. The source is the EIA-860 annual survey, with the inventory refreshed monthly between full annual snapshots.

US reference·A national inventory of utility-scale wind generators drawn from EIA-860, the Energy Information Administration's annual survey of electric generating units. Each record carries the standard generator attributes (plant, operator, location, nameplate capacity, operating status, and online date) plus wind-specific detail such as hub height and turbine manufacturer and model. This is the authoritative reference for who owns which wind fleet, where the turbines stand, and what hardware is installed, which lets operators, traders, and researchers map installed wind capacity, gauge buildout by region or developer, and connect equipment characteristics to generation behavior. It updates monthly for status changes and is consolidated in the annual EIA-860 release.

US reference·This is the subset of utility-scale battery and energy storage resources reported in the EIA-860 generator inventory, covering plant and owner identifiers, location, capacity, and operating status alongside storage-specific attributes such as maximum charge and discharge rates, useful-life energy in MWh, and storage technology. It is updated annually with a full snapshot and refreshed monthly between cycles. The duration and power ratings let you separate short-duration frequency-regulation assets from longer-duration shifting resources, and tracking new entries over time shows where storage is being added across the grid. Operators, traders, and researchers use it as the authoritative reference for what storage exists, where it sits, and how much energy and power it can move.

US reference·Plant-level monthly net generation and fuel consumption from EIA Form 923, the Power Plant Operations Report. Each record captures how much electricity a single utility-scale facility actually produced in a given month, broken out by energy source (fuel type) and prime mover, alongside the fuel it burned to do so — net and gross generation in MWh, physical fuel consumption, the consumption attributable to electricity generation, the equivalent heat input in MMBtu, and the average heat content of the fuel. Unlike nameplate inventories, this is realized output, so it is the standard reference for what plants really generated over time and how efficiently they ran. The plant code is the ORISPL/EIA plant id, the same join key used by the EIA-860 generator inventory, so realized monthly generation here joins directly to a plant's capacity, technology, location, and ownership in eia860. History runs back to 2001. EIA restates recent months as late survey data arrives, so the table is bitemporal: bronze is append-only and silver keeps the latest vintage per plant-month-fuel.

US reference·A plant-level inventory of US electric generating facilities, with one record per plant carrying its operator, location (latitude and longitude), primary fuel, and installed capacity broken out by fuel type. The underlying data is authored by the Energy Information Administration and distributed through the Homeland Infrastructure Foundation-Level Data (HIFLD) catalog, serving as the geographic companion to the EIA-860 generator inventory. It lets anyone place the generating fleet on a map and ask where capacity sits, what fuels it runs on, and who operates it, which is the starting point for siting studies, fuel-mix analysis, interconnection context, and resource-adequacy work.

PJM·PJM system generation broken out by fuel type every five minutes — gas, nuclear, coal, solar, wind, hydro, storage, and others — with each fuel's output in MW, its share of the total, and a renewable flag. This is the live fuel-mix signal for the PJM footprint: read it for current renewable output, the marginal fuel, and how the mix shifts across the day. Source: PJM Data Miner 2.

PJM·PJM's daily generator-outage outlook by report date, target forecast date, and region. Each row separates total, planned, maintenance, and forced outage capacity in MW for PJM RTO, Western, or Mid Atlantic - Dominion. This is generation availability evidence from PJM Data Miner 2, not distribution-customer outage data. Source: PJM Data Miner 2.

SPP·SPP system generation by fuel, published every five minutes. Unlike markets that publish one row per fuel, SPP publishes one row per interval with a column per fuel: wind, solar, natural gas, coal, nuclear, hydro, diesel, waste, and other, alongside total load and wind's percentage share. Wind is the defining series in this market and regularly supplies a larger share of demand than in any other US market. Solar can read slightly negative overnight, which reflects real station-service draw rather than a data error.

SPP·SPP's short-term wind generation forecast in MW, carried alongside the realized wind actual for the same interval. Bitemporal, retaining each successive vintage against its delivery interval. Wind is the single most consequential series in SPP, so forecast error here propagates directly into net load, congestion, and price formation.

SPP·SPP's mid-term wind generation forecast in MW, running roughly seven days ahead with the realized actual carried for the same interval. Bitemporal, retaining each published vintage, which makes it suitable for measuring how wind forecast skill degrades with horizon across the Great Plains footprint.

SPP·SPP's short-term solar generation forecast in MW with the realized solar actual for the same interval. Bitemporal, retaining each successive vintage against its delivery interval. Solar is a much smaller share of the SPP mix than wind and can read slightly negative overnight from station-service draw.

SPP·SPP's mid-term solar generation forecast in MW, running roughly seven days ahead with the realized actual carried alongside. Bitemporal, retaining each published vintage against its delivery interval.

NYISO·NYISO real-time limiting-constraint records that identify the limiting facility, facility PTID, contingency, and constraint cost shaping dispatch and price separation. Use alongside real-time LBMP components to explain congestion rather than just observing price spreads.

NYISO·NYISO day-ahead limiting-constraint records for the market-clearing plan, including limiting facility, facility PTID, contingency, and constraint cost. Paired with day-ahead LBMP components, it helps explain expected congestion and transfer limits before real-time operations.

NYISO·NYISO five-minute external interface flows and positive/negative transfer limits by interface point. This is the live interchange and transfer-limit context behind import/export stress and congestion.

NYISO·NYISO available transfer capability and total transfer capability by interface and market run. The source rows are melted so DAM and HAM timesteps can be compared by interface over time.

NYISO·NYISO long-term pre-scheduled available transfer capability and total transfer capability by interface. Use it for forward interface-capability context rather than live flows.

NYISO·NYISO real-time five-minute Lake Erie loop-flow circulation. Positive values indicate clockwise / into-NYISO circulation, an important transfer-path context for New York imports and congestion.

NYISO·NYISO day-ahead hourly scheduled Lake Erie loop-flow circulation. It provides the forward scheduled counterpart to real-time Lake Erie circulation.

PJM·The transmission constraints that bound in PJM's day-ahead market: the monitored facility, the contingency facility, the duration, and the congestion event. It names which elements are expected to limit flows for the next operating day. Note that PJM does not publish a real-time binding-constraint/shadow-price feed, so real-time congestion is read from the congestion component of the LMP tables rather than from a constraints table. Source: PJM Data Miner 2.

SPP·Transmission constraints binding in SPP's real-time balancing market, published every five minutes with the constraint name, its shadow price, the constrained direction, and the monitored limit and actual flow in MW. A non-zero shadow price is direct evidence that the named constraint was binding and pricing congestion in that interval. SPP publishes no associated contingency or monitored-facility name on this feed, so a constraint name cannot be resolved to a physical facility from this table alone.

SPP·Transmission constraints binding in SPP's day-ahead market, published hourly for the delivery day with the constraint name, shadow price, direction, and the monitored limit and flow in MW. Pairs with the real-time binding-constraint table to compare which constraints the day-ahead market anticipated against those that actually bound in real time. As with the real-time table, no contingency or monitored-facility name is published.

ERCOT·ERCOT's public large-generation interconnection queue, with project identity, developer, proposed point of interconnection, transmission owner, technology, requested MW, queue status, and proposed or actual completion dates. Each posting is a snapshot, so current project claims must use the latest snapshot rather than count every vintage. Queue inclusion and proposed dates do not establish available transmission headroom, study outcome, approval, construction probability, or an operating asset. The official source is ERCOT's GIS Report.

ERCOT·ERCOT's weekly registration crosswalk between resource nodes and registered generation units. It can establish the published node-to-unit relationship for a particular snapshot. It does not establish dispatch, ownership, substation topology, constraint exposure, or the cause of a nodal price move. This table is listed in the public catalog but is not exposed to agent SQL until its snapshot and identity semantics are fully contracted. The source is ERCOT report NP4-160-SG.

CAISO·CAISO pricing-node (PNode) reference map: pricing-node id, aggregate-node id, name, voltage, node type, and the effective-date window each definition is valid for. This is a dimension / reference table, not a time series — it is a slow-moving registry snapshotted periodically (a handful of vintages), so use it to resolve and label pricing nodes and their attributes rather than for time-based analysis. Join it to the CAISO LMP and shadow-price tables to give nodes human-readable names and group them. The official source is CAISO OASIS.

NYISO·NYISO scheduled generator and transmission outage records by PTID and equipment name, including scheduled out and scheduled in timestamps.

NYISO·NYISO real-time transmission line outage records by line PTID and equipment name, including the outage timestamp for currently de-energized or outaged lines.

NYISO·NYISO scheduled transmission line outages by line PTID and equipment name, including scheduled out and scheduled in timestamps.

NYISO·NYISO out-of-merit operator-initiated commitment records by resource PTID and event start time, including requester, commitment type, load zone, reason, ARR, UOL, and committed MW fields.

NYISO·NYISO real-time grid event messages, including operating reserve activations, state changes, and advisories. Use it to contextualize unusual price, reserve, or reliability conditions.

NYISO·NYISO operational announcements and dispatcher-issued messages, including interface scheduling changes, manual reductions, and market notices.

US reference·Live county-level customer outage snapshots from ORNL/DOE's ODIN public county map API. Ask the Grid queries the nationwide grid='us' archive and derives each live product map from its exact state-FIPS scope, so every supported grid uses the same accumulated history. Each row is an active county outage at that snapshot with county FIPS, state FIPS, affected meters, contributing utility rows, and the ODIN county polygon. Missing county rows at a snapshot mean zero or cleared public ODIN outage, not stale carry-forward. This is distribution/customer outage data, not ISO generation or resource outage data.

US reference·Coverage and health snapshots from ORNL/DOE's ODIN status API. Each poll records the utility feeds ODIN reports, their spatial resolution, outage-feed metadata, current total outages, vendor, received timestamp, and error flag. Use this to understand whether ODIN coverage is complete for a state or utility before treating the county outage layer as comprehensive.

US reference·NYSERDA Integrated Energy Data Resource (IEDR) per-county DER hosting-capacity rollup for New York State's 62 counties. Each snapshot row carries DER counts by status, feeder count, and min/max/total hosting capacity for generic DER, ESS charging, ESS discharging, and EV load, plus county population and centroid. `county_id` is an IEDR-internal identifier, NOT a FIPS code — join to county geometry by normalized county name. Bitemporal snapshot: use ROW_NUMBER() OVER (PARTITION BY county_id ORDER BY event_time DESC) = 1 (or an equivalent argMax(..., event_time) per county_id) to get the current snapshot. ESS charging and discharging hosting capacity are asymmetric: a battery can only charge into a wire's spare import capacity, but can discharge more than the wire's rating when serving co-located load.

US reference·A point-level inventory of electric substations across the United States, drawn from the Homeland Infrastructure Foundation-Level Data (HIFLD) program. Each record locates a substation and describes its name, city and county, voltage class (minimum and maximum kV), the number of transmission lines connecting to it, its type, and its operating status. Substations are the nodes where voltage is stepped up or down and where transmission and distribution meet, so this dataset lets operators, planners, traders, and researchers see where the grid's switching and transformation points sit, gauge the relative importance of a node by its voltage and line count, and tie generation and load to the network that connects them.

US reference·This dataset maps the physical transmission backbone of the US power grid as polyline geometry, tracing each line from one substation endpoint to the other. Each segment carries attributes including the owning utility and a voltage class, distinguishing the high-voltage bulk transmission corridors from lower-voltage feeders. With it you can see how regions interconnect, identify the major paths that move power across long distances, and reason about constraints, interties, and where new generation or load would need to tie in. The source is the Homeland Infrastructure Foundation-Level Data (HIFLD) electric power transmission lines layer.

NYISO·NYISO station-level weather forecast feed used by the load model, including maximum/minimum temperature and wet-bulb forecasts by station and vintage date.

US reference·Hourly historical weather sampled on a regular 0.25 degree latitude and longitude grid, covering 2 meter air temperature, precipitation, and 10 meter wind. The data is ERA5 reanalysis, which trails real time by several days — this table never carries the current hour or the future, so questions about weather right now or ahead belong on the Weather Forecast Grid instead. Because load, wind output, and solar output all track these variables closely, the grid lets operators, traders, and researchers tie past demand and renewable generation to the temperature and wind conditions that drove them. Source: Open-Meteo.

US reference·Hourly weather forecasts on the same 0.25 degree latitude and longitude grid as the history table, extending about two days ahead — this is the dataset for current conditions and the hours in front of them, since the ERA5 history trails real time by several days. Rich per-point coverage: temperature, apparent and wet-bulb temperature, humidity, cloud cover, shortwave and direct radiation, wind speed and direction at 10, 80, 120, and 180 meters, gusts, precipitation, and CAPE — the drivers behind load, wind output, and solar output. Rows are vintage-stamped by lead_days (days between forecast issue and the valid hour); multiple vintages coexist per valid hour, so take the minimum lead_days per (valid_time, location_id) for the freshest view of any hour. Source: Open-Meteo.