SERVM: The industry-leading model trusted by entities across the globe to help answer their resource adequacy questions


How Strategic Energy & Risk Valuation Model (SERVM) Works

SERVM’s Reserve Margin analysis provides a dramatically improved understanding of resource adequacy risks, determining not only if a reliability event could happen, but also quantifies the likelihood, magnitude, and economic cost of each event. To perform this analysis, SERVM utilizes historical weather, economic load growth forecast error, historical hydro and other energy-limited resource data, and unit performance history to perform hundreds of thousands of independent hourly chronological simulations of any system. The results of the model deliver a full distribution of expected reliability events and their costs, allowing system planners to mitigate reliability concerns and economically plan the expansion of their system.

SERVM allows users to balance capacity cost, unserved energy societal costs, production costs and import purchases costs. The following figure can be created on the weighted average probability of all cases or at any confidence level. The economic results can be easily compared to physical reliability metrics such as Loss of Load Expectation (LOLE). The results can also be developed at different confidence levels.


SERVM Forecasts, Studies, and Metrics

Probabilistic Production Cost Forecasts

Produce S Curve Analysis for future production cost years for any number of zones

Intermittent ELCC Studies

Calculate the Effective Load Carrying Capability of intermittent resources on the system

Probabilistic Market Price Forecasts

Produce S Curve Analysis for future energy price forecasts for any number of zones

System Flexibility Requirement Studies

Calculate the flexible resource needs for a system under varying intermittent penetration levels

Probabilistic Energy Margin Forecasts

Produce S Curve Analysis for future energy margins by resource dispatch price for any number of zones

Demand Response Resource Valuation

Understand the reliability contribution of various demand response programs at varying different penetration levels

Physical Reliability Metrics

Produce Loss of Load Expectation (LOLE), Loss of Load Hours (LOLH), Expected Unserved Energy (EUE) for any number of zones

Demand Response Call Expectation Studies

Provides expectation of actual demand response calls under varying weather, load, and penetration levels

Intermittent Penetration Studies

Understand reliability impact of increased intermittent generation

Fuel Availability Studies

Understand the reliability impact of the electric system as fuel supply availability is captured and as there is an increase reliance on natural gas infrastructure


SERVM Key Features

Fast, Hourly Chronological Model with Full Commitment and Dispatch

Takes into account heat rate curves, fuel prices, unit outages and maintenance, all variable operating costs, ramp rates, startup costs, ancillary service requirements

Simulates Full Distribution of:

  • Weather Years and its impact on Load and Resources (i.e. hydro, wind, and PV)
  • Load Growth Uncertainty
  • Fuel Prices
  • Environmental Policy Plans
  • Intermittent Resources