Reliability Assessment Studies

Reliability is still Job # 1. Addition of wind, solar and other intermittent technologies add complexity and variability where none had existed before.

ECCO Reliability Assessment Studies

The Problem - Reliability is still Job # 1. Today’s economics are adding pressure to derive maximum value from existing and planned assets. Our industry is experiencing changing needs/requirements, such as change in supply resources with the addition of wind, solar and other intermittent technologies. These are all necessary changes but add complexity and variability where none had existed before.

New Paradigm - New modeling techniques reflecting operational realities open the way for an improved software modeling tool - ProMaxLT™

ECCO LOLP analysis studies are performed using our proprietary energy and transmission software simulation platform, called ProMaxLT™. ProMaxLT™ has extensive capabilities required to perform a variety of studies of reliability of electric power systems, assess the trade-offs between reliability and cost and perform nodal market simulation studies for price forecasting and other purposes. It meets or exceeds all the requirements for reliability studies suggested in a recent report ”G&T RPM Task Force Final Report on Methodology and Metrics“ (prepared by the Generation & Transmission Reliability Planning Models Task Force of the NERC Planning Committee). We utilize this tool to simulate the Study-Region and compute all required forward-looking probabilistic reliability indices. These indices can in turn be used to identify the required reserve margins and any deficit or surplus in the total capacity of the available resources. They also provide a mechanism to compare the ELCC of wind and solar power resources.

The following are examples of the standard required reliability indices that ProMaxLT™ will produce in a typical study:

  • Loss of Load Events (LOLEV): Number of times in a year that available generation was incapable of meeting demand (events/year).
  • Loss of Load Hours (LOLH): Number of hours in a year that available generation was incapable of meeting demand (hrs/year).
  • Expected Un-served Energy (EUE): The total amount of energy demand that could not be met by available generation in a year (MWh/year).
  • Loss of Load Probability (LOLP): The probability that in any given hour the available capacity will be less than the demand.
  • Loss of Load Expectation (LOLE) (days/year): Number of days per year (or hours per year) for which available generating capacity is insufficient to serve the daily peak demand (or the hourly demand).

The above indices are all calculated based on a sequential Monte Carlo simulation of all relevant probabilistic variables including forced outages, load forecast errors, wind energy forecast errors, etc. using ProMaxLT™. There are two types of Monte-Carlo simulation approaches, the sequential and the non-sequential. The non-sequential process considers each hour to be independent of every other hour which means that it cannot accurately model issues that involve time correlation. The sequential simulation approach steps through time chronologically, by recognizing that the status of a system component is not independent of its status in adjacent hours. The problem is treated as a series of real experiments conducted in simulated time steps of one hour which is considered to be adequate for a power system reliability analysis since the number of system changes within that period is generally small. A series of system scenarios is obtained by hourly random drawings on the status of each system component and determining the hourly load demand. The desired reliability indices are calculated for each hour with the process repeated for the remaining hours in the year.

In addition, ProMaxLT™ models hour-by-hour dispatch of generation resources taking into consideration all resource specific operating constraints such as minimum up and down times, minimum operating limits and ramp rates. It also considers the system-wide requirement for energy as well as spinning reserves, regulation up/down capabilities, etc. The impact of power system network constraints on the reliability indices can also be assessed. These features result in a more accurate model of the power system operations and hence to a more accurate assessment of the reliability indices. These Unit Commitment-type of constraints are managed by deploying the advanced Mixed Integer Programming (MIP) capability of ProMaxLT™ which can also accommodate a full-fledged and detailed AC or DC power flow model that models an accurate representation of the transmission grid.

For more information please contact us.  You may also download our brochure describing ProMaxLT™ by selecting this link.