Distribution Reliability Assessment

Distribution system reliability assessment deals with the availability and quality of power supply at each customer service entrance.

Analysis of customer failure statistics show that, compared to other portions of electrical power systems, distribution system failures contribute as much as 90% towards the unavailability of supply to a load. These statistics show how important the reliability evaluation of distribution systems can be.

In order to evaluate the severity or significance of a system outage, using the three basic indices mentioned above, two expanded sets of indices listed below must also be calculated. The two expanded sets of indices include the number and average load of customers connected at each load point in the system and the customer interruption cost.

Distribution Reliability Assessment Features

System reliability
Customer oriented indices
Energy (cost) indices
Sensitivity analysis
Single & double contingency

Distribution Reliability Assessment Capabilities

Model reliability characteristics of each component
STATCOM, SVC, UPS, and Wind Turbine modeling
Implement user-defined parameters & settings
Calculate bus and load point reliability indices
Calculate system reliability indices
Calculate reliability energy (cost) indices
Rank element contributions to energy (cost) indices
Calculate effect of simultaneous faults
Select types of components for plotting
Availability & quality of power assessment
Long-term planning & redundancy
Single & double contingency studies
Multiple phase configurations
Unbalanced system reliability calculation
Datablock visualization
GIS Diagram plotting

Reporting

Graphical display of reliability results
Load point/bus reliability indices
System reliability indices
EENS & ECOST sensitivity analysis

Customer Oriented Indices

System Average Interruption
Frequency Index - SAIFI
System Average Interruption
Duration Index - SAIDI
Customer Average Interruption
Duration Index - CAIDI
System Customer Total Average Interruption Duration Index - CTAIDI
Average Load Interrupted per Connected Load Served - ALII
Average Customer Curtailment Index - ACCI
Average Service Availability Index - ASAI
Average Service Unavailability Index - ASUI
Sector interruption cost estimates: Customer Damage Function - CDF
Momentary Average Interruption Frequency Index - MAIFI
Momentary Average Interruption Duration Index - MAIDI

Energy (Cost) Indices

Expected Energy Not Supplied - EENS sensitivity analysis
Expected Interruption Cost - ECOST sensitivity analysis
Element contributions to the EENS & their rankings
Element contributions to the ECOST & their rankings
Order of most contributing components to EENS & ECOST
Interrupted Energy Assessment Rate - IEAR
Interruption cost library
Component parameter library

System Reliability Indices

Average failure rate - l
Average outage duration - r
Annual outage duration - U

The indices EENS, ECOST, and IEAR can be those specifically for each load point or for the overall system. All of these indices can be used to evaluate the reliability of an existing distribution system and to provide useful planning information regarding improvements to existing systems and the design of new distribution systems.

Moreover, in order to analyze the sensitivity of a reliability index EENS or ECOST with respect to failure rate of different elements, element contributions to that index and their rankings can be used. The rankings can be for a load point or the overall system.

All of the indices and rankings given above can be evaluated using the ETAP Reliability Analysis module. This module provides you with the best tool to efficiently model various power system elements and devices to include their effects on the distribution system reliability, such as fault isolation and load restoration through the operation of switching devices.

This module is suitable for reliability analysis of large-scale systems of general configurations. By using this module, you can assess the distribution system reliability, and the merits of various reinforcement schemes that are available to the planner can be quantitatively evaluated to ensure that limited capital resources are used to achieve the greatest possible improvement in system reliability.