SERVM accounts for the explicit consideration of economic factors such as the cost of emergency purchases, the cost of integrating intermittent or energy-limited resources, the cost of demand side resource dispatch, and the economic and reliability value of tie line capacity to neighboring power systems. SERVM is a powerful reliability planning tool that has helped utilities such as the Tennessee Valley Authority, Southern Company, Louisville Gas & Electric, and Kentucky Utilities to answer questions such as:

• What should my target reserve margin be so that I can provide resource adequacy at the lowest total cost?
• What is the capacity value of wind, pumped storage, or other renewable resources?
• How should interruptible, energy efficiency or other demand side programs be priced?
• What is my risk of not being able to serve firm load customers in upcoming seasons?
• How much should I be willing to pay for short term capacity and how much should I buy?

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 Reliability Studies

Reserve Margin Study
SERVM allows users to balance capacity cost, unserved energy societal costs, reliability costs (costs above the marginal cost of a high heat rate gas CT), and emergency purchase costs. This graph can be created on the weighted average of all cases or at any confidence level. A reserve margin study will allow you to isolate what percentages of your reserves are assignable to load forecast error, unit outages uncertainty, energy limited resource unavailability, and weather uncertainty.

The above figure shows the probability-weighted average cost of various reliability-related cost elements as a function of planning reserve margin. The lowest-average-cost reserve margin can be determined, for example, based on the point at which total reliability-related costs plus the cost of carrying additional reserves is the lowest, ignoring the uncertainty of costs around the weighted average costs shown in the chart. In the case study shown above, this lowest-average-cost reserve margin is 12%. However, this result will vary significantly across regions based on their size, load shape, resource mix, and many other factors.

While this figure is informative, it over-simplifies the problem by only comparing fixed capacity costs with the long-term averages of very uncertain market exposures. To perform a more informed comparison, the uncertainty of market exposure needs to be considered as well. >> Read more in 'The Value of Resource Adequacy'

Capacity Benefit Margin Study
After performing a reserve margin study to set an optimum reserve margin, capacity benefit margins can be varied across ties to determine what CBM levels would cause a shift in the optimum reserve margin. This can be isolated to individual ties or consolidated across ties.

Seasonal Reliability Assessments
Using near-term load forecasts and capacity projections, a wide range of weather, economic growth, and unit outage scenarios can be modeled to determine what the relative risks are for upcoming seasons. The distribution of expected reliability purchases can be used to determine how much capacity should be purchased at what costs to minimize risk and total reliability costs.

Energy Limited/Non-Dispatchable Resource Valuation (Applies to all renewable energy resources)
From a base case simulation, two incremental units can be modeled separately. A CT with no restrictions and an energy limited resource (for example, a solar thermal plant). The CT will produce some amount of reliability cost savings (not measuring production cost). In the other case, the solar unit will produce some savings as well but because of the limitations, the reliability cost savings will be lower. This will demonstrate the capacity worth of the resource relative to a CT. This can also be performed with wind, hydro and other energy limited resources. (The graph is merely illustrative and not in any way indicative of the capacity value of any actual hydro or wind resource.)

Demand Side Option Valuation
Similarly, demand side options can be valued with completely different sets of restrictions from how physical resources are limited. Currently, the model can simulate the following restrictions for demand side options: hours per day, days per week, hours per year, hours per call, market price threshold for calling, and response time. Other restrictions can also possibly be handled. This can demonstrate the relative value that different contracts with different restrictions might provide.

Interruptible Call Summary
SERVM clients can produce distributions of estimated interruptible contract calls by year. This can be a powerful tool in marketing interruptible programs to new customers and informing existing customers what they can expect for upcoming seasons.

>> Download a PDF detailing the complete range of SERVM Reliability Studies