Inside the Electricity Auction

The Israeli electricity market uses a day-ahead auction to determine which generators run and at what price.

העקרונות מאחורי מכרז החשמל

שוק החשמל בישראל מבוסס על מכרז יומי שנוגה מפעילה כל בוקר. המכרז קובע אילו תחנות כוח יפעלו ובאיזה מחיר.

Every morning, Israel's System Operator (Noga) runs a day-ahead auction. Generators submit their offers (how much electricity they can produce and at what price), and the system determines the cheapest way to meet tomorrow's demand.

The result is a dispatch schedule: which generators run during each half-hour interval and at what output level. The price that emerges from this process is the Market Clearing Price (MCP).

This is a uniform pricing system. Every dispatched generator receives the same MCP, regardless of their individual bid. The MCP equals the cost of the most expensive generator needed to meet demand, the "marginal unit."

Key Insight. The MCP is not set by any single generator. It emerges from the interaction of all bids, demand levels, and system constraints. Change any one input, and the entire dispatch, and price, can shift.

The auction is solved as a Mixed-Integer Linear Program (MILP). "Mixed-integer" means the solver works with two types of decisions simultaneously:

  • Continuous variables: how much power each generator produces (e.g., 350.5 MW)
  • Binary variables: whether a generator is on or off (1 or 0)

The objective is to minimize total generation cost while satisfying all system constraints. The solver considers thousands of variables and constraints across all 48 half-hour intervals of the next day.

This is what makes the problem hard, and interesting. A simple merit-order stack can't capture the real-world physics of power plants that take hours to start up, have minimum output levels, or face fuel delivery limits.

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Power Balance

Supply must equal demand at every interval

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Reserve Requirements

Safety margins for unexpected changes

Ramp Rates

Generators can't change output instantly

Min Up/Down Times

Thermal units need time to start and stop

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Fuel Supply

Gas pipeline constraints limit total gas generation

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Storage Dynamics

Batteries couple decisions across time periods

How is the electricity price actually determined? Once the solver decides which generators run, the Market Clearing Price (MCP) is set by asking one question: if we needed one more megawatt right now, who would supply it and at what cost? That generator, the marginal unit, sets the price for everyone.

This works cleanly when all generators compete on cost alone. But Israel's regulator chose to put additional values into the system. Environmental policy requires coal plants to dispatch last, regardless of their low cost, a deliberate decision to phase out coal even though it's cheap. Energy security concerns mean that when gas pipelines fail or hit capacity, the market doesn't punish consumers with diesel-level prices for a problem they didn't cause. These regulatory choices mean the basic pricing rule needs exceptions. There are 7 scenarios that govern how the MCP is actually set:

# Condition MCP Rule Example
1 Normal operation Marginal gas unit price (cheapest unit that can respond) Example 0, 1
2 Coal unit is marginal Highest gas price already purchased (coal excluded from price setting) Example 2
3 Shortage (no demand management) Energy: highest purchased offer; Deviations: VOLL Example 8
4 Renewable curtailment: solar or wind deliberately reduced for system stability MCP = 0 NIS/MWh (the cheapest fix is to restore the free renewables that were cut) N/A
5 Gas capacity shortage (units unavailable) If coal set price → highest gas purchased; otherwise → diesel unit price Example 4
6 Gas supply shortage (supplier unavailable) Highest gas price purchased Example 5
7 Gas transmission failure Highest gas price purchased N/A
Why do these rules exist? Behind these rules is a balancing act. The regulator wants market prices that are economically honest, reflecting real supply and demand. But they also want prices that don't reward pollution (coal) or penalize consumers for infrastructure limitations (gas shortages). The 7 scenarios are the mechanism that holds these competing goals together.

Three Paths Forward

GUIDED EXAMPLES

Guided Examples

Walk through pre-built scenarios that illustrate key auction concepts, from simple merit order to complex gas constraints and storage optimization.

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BUILD YOUR OWN

Custom Scenario

Configure your own generators, set demand profiles, define constraints, and run the full MILP optimization. Full control over every parameter.

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REAL-WORLD DATA

Real-World Data

Load actual market data from the Israeli electricity system. See how real generators, demand patterns, and constraints shape the market clearing price.

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