Case Study

Using @RISK to Optimize the Timing of a GXP Reinforcement for a Utility – Palisade

Using @RISK to Optimize the Timing of a GXP Reinforcement for a Utility – Palisade

Pages 7 Pages

Customers & Industries: Tesla Consultants Industry: Utilities Product(s): @RISK Application: Assessing Needs for Equipment Upgrades Summary Tesla Consultants and Delta Utilities of New Zealand demonstrate how to use probabilistic Monte Carlo simulation in @RISK to assess the need for and the timing of an upgrade of the GXP (the substation that connects a regional area to the transmission grid). Forecast demand data combined with historical failure modes including snow, natural events and equipment failures are considered. The result is a probability density function representing the range of costs to customers for non-supply during contingencies. This is then fed into a Net Present Value (NPV) calculation to determine the maximum amount of capital that could be spent to mitigate these ‘los

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