Overview

View averaged hourly LMP data for a pricing node across multiple days (up to 60). Each hour shows the average DA, RT, and spread values across all selected days.

Selectors

• Pricing Node: Type to search (predictive autocomplete) or pick from the list. The name must exist — unknown names are rejected
• End Date: The most recent date to include
• Days: Number of days to average (1-60), counting back from end date

Table Columns

• HE: Hour Ending (1-24)
• DA LMP: Average Day-Ahead total LMP across selected days
• RT LMP: Average Real-Time total LMP across selected days
• Spread: Average DA - RT price difference
• DA CC: Average Day-Ahead congestion component
• RT CC: Average Real-Time congestion component
• °F / mph: Average temperature and wind at the node's nearest NOAA airport (zone-level; sparse coverage shows a dash)
• N °F / S °F / IL °F / IN °F / MI °F / AR °F: Average footprint-wide reference temperatures (identical across nodes) — MISO North (Minneapolis, KMSP) and South (New Orleans, KMSY) beside the node-local °F; Illinois (Chicago, KORD), Indiana (Indianapolis, KIND), Michigan (Detroit, KDTW) and Arkansas (Little Rock, KLIT) hubs at the right
• DA Ld / RT Ld: Average MISO system day-ahead forecast vs actual load in GW (EIA-930) — system-wide, identical across nodes

Load Options

• Consecutive: the last N calendar days
• Weekdays: the last N Mon-Fri days, weekends skipped
• Same Day: the last N of the end date's weekday (7 Fridays, 43 Fridays, …) — so N days spans roughly N weeks, and a node commissioned recently will not have that much history

When Fewer Days Come Back Than You Asked For

Dates the node has no data for are dropped, and the Days card then reads loaded / requested with an amber note saying why — the node's own first and last market date, how many requested dates fall outside it, and any gaps inside it. It is a fact about the node's history, not a cap on the selector.

Use Case

Useful for identifying hourly patterns and typical spreads at a node. Averaging multiple days smooths out daily volatility to reveal trends.