Reliability Analysis
Reliability calculations are essential for the evaluation and comparison of electrical power systems in terms of both design and operation. Although non-stochastic contingency analyses (for example (n-1)) are able to highlight obviously unacceptable operational events, they cannot rank these events in terms of either frequency or duration. The DIgSILENT PowerFactory Reliability analysis tool incorporates standard reliability assessment features together with sophisticated modeling techniques that enable all forms of reliability assessment to be carried out.
Failure models are defined using mean yearly failure frequency and repair duration data. For lines and cables, this data is entered in per length terms. Detailed models are available for generators that enable derated states to be represented, with maintenance and common mode models also available.
Loads can be grouped into load areas, each of which is described by load forecast and growth curves. Load models are additionally available for hard-to-predict industrial situations, and each can be assigned its own interruption cost using one of the following functions: money/customer/interruption, money/kW/interruption or money/interruption.
All failure and load models can be represented either by the Markov method, where simple mean repair durations are modeled, or by the sophisticated Weibull-Markov method, where repair duration variance is additionally modeled. The Weibull-Markov model also has the unique property that annual interruption cost indices such as load and process (industrial) interruption costs can be calculated both analytically and quickly. Consequently, the DIgSILENT PowerFactory reliability analysis tool enables the comparison and justification of alternative investment proposals on a financial basis.
Finally, the results of all reliability assessments can be presented in text format, as user-defined graphs, or within the single-line graphics environment. The network reliability analysis can be carried out on the basis of a simple connectivity check (primarily intended for distribution networks) or on the basis of AC load flow calculations which consider load curtailments due to overloading or voltage constraints (for bulk power system analysis).
Generation Pool Adequacy Analysis
Generation pool adequacy analysis compares the total available generating capacity with the load demand, considering:
- Generator forced and planned outages (failures and maintenance);
- Generator derated states (partial outage);
- Stochastic load behavior
The purpose of the generation pool adequacy analysis is to identify the ability of generators to fulfill load demand in the case of an infinitely strong transmission and/or distribution system. Results from this analysis include:
- Loss of Load Expectancy (LOLE, hr/yr)
- Loss of Energy Expectancy (LOEE, MWh/yr)
- Loss of Load Duration (LOLD, hr/occ.)
- Loss of Load Frequency (LOLF, occ./yr)
- Expected Energy Not Supplied (EENS, MW)
- Typical generating capacity and reserve curves
Network Reliability Analysis
Distribution and bulk power network analysis are both carried out by the "Network Reliability" analysis function. This comprises the assessment of interruption statistics for individual loads and busbars in distribution, sub-transmission and transmission systems. The calculation method combines fast topological analysis for fault clearance, fault isolation and power restoration, with AC load flow and optimization techniques for addressing energy at risk, load transfer and load shedding
The basic calculation method used is analytical state enumeration. This method is very efficient, produces exact results and is flexible enough for addressing a wide range of reliability calculation problems.
Failure Models
The failure models for network reliability assessment include:
- Failures for
- lines/cables,
- transformers,
- generators/external grids,
- busbars
- Independent second failures ("n-2")
- Common mode failures
- Double earth faults
- Protection/circuit breaker malfunction
- Transient fault model (for momentary interruption indices)
- Scheduled maintenance
Special failure model objects can be used to share failure data for network components. The failure models hold the stochastic failure information (mean yearly failure frequency for sustained, transient and earth faults on a per km basis, as well as mean repair durations). PowerFactory’s user-interface allows for both an easy setup, as well as for simple modification of this input data for various studies.
The Maintenance feature simulates the effects of network reliability under predefined planned outage scenarios. Maintenance of individual network components can be modeled on an hourly basis
.Network Analysis
Based on the network model and the given failure data, the reliability analysis generates and analyses the resulting contingency cases.
In addition, the user can model load forecast and growth curves by imposing time-varying load characteristics. PowerFactory handles the reliability assessment over time with varying load data very efficiently due to the following techniques:
- Clustering of load states in the state enumeration algorithm;
- Analysing load variation correlations and thus fundamentally reducing the overall number of load states;
- Using linear approximation techniques to improve performance in the case of a large number of load states.
Failure Effect Analysis
The Failure Effect Analysis (FEA) simulates both the automatic and manual reactions to faults of installed protection and of the system operators during each reliability assessment. The FEA can be checked and fine-tuned in an interactive way to exactly match the real system and operator reactions.
The Failure Effect Analysis comprises:
- Automatic fault clearance by protection devices
- Automatic or manual fault isolation
- Automatic or manual power restoration by network reconfiguration.
This includes sophisticated sectionalizing and strategic power restoration methods that operate in three distinct phases:- Phase 1: Sectionalizing by remote controlled switch devices
- Phase 2: Subsectionalizing of strategic areas
- Phase 3: Full system restoration
- Overload alleviation by optimized load transfer and load shedding, using both load priorities and load shedding properties.
- Under-voltage load-shedding
For classical bulk power analysis, it is assumed that post-fault overloads may occur. A full AC load flow, incorporating basic generator re-dispatch and automatic tap changing, is used to analyse post-fault system conditions. Additional load transfer and/or load shedding will then be simulated.
In cases where it can be assumed that system restoration will not lead to any overloading, the overload alleviation can be omitted and a fast network connectivity analysis is sufficient.
Results/ System Indices
Network Reliability analysis assessment calculates all common reliability indices. Among others, the following indices are available:
System indices (also available for user-defined Feeders, Zones, and Areas):
- SAIFI, System Average Interruption Frequency Index
- CAIFI, Customer Average Interruption Frequency Index
- SAIDI, System Average Interruption Duration index
- CAIDI, Customer Average Interruption Duration Index
- ASIFI, Average System Interruption Frequency Index
- ASIDI, Average System Interruption Duration Index
- ASAI, Average Service Availability Index
- ASUI, Average Service Unavailability Index
- ENS, Energy Not Supplied
- AENS, Average Energy Not Supplied
- ACCI, Average Customer Curtailment Index
- EIC, Expected Interruption Cost
- IEAR, Interrupted Energy Assessment Rate
- SES, System energy shed
- LOLE, Loss of Load Expectancy
- LOEE, Loss of Energy Expectation
- LOLF, Loss of Load Frequency
- LOLD, Loss of Load Duration
- MAIFI, Momentary Average Interruption Frequency Index
Load Indices:
- AID, Average Interruption Duration
- ACIF, Average Customer Interruption Frequency
- ACIT, Average Customer Interruption Time
- LPIT, Load Point Interruption Time
- LPIF, Load Point Interruption Frequency
- LPENS, Load Point Energy Not Supplied
- LPEIC, Load Point Expected Interruption Costs
- LPCNS, Load Point Customers not Supplied
- LPPNS, Load Point Power not Supplied
- LPPS, Load Point Power Shed
- LPES, Load Point Energy Shed
- LPIC, Load Point Interruption Costs
- TCIF, Total Customer Interruption Frequency
- TCIT, Total Customer Interruption Time
Busbar Indices:
- AID, Average Interruption Duration
- LPIF, Yearly Interruption Frequency
- LPIT, Yearly Interruption Time
Special Features
The Network Reliability Assessment is fully integrated into PowerFactory, thus profiting from the extremely flexible data management and data handling to set up distinct studies.
High Flexibility
Each contingency case is created and analysed based on events (switch events, load shedding events, generator redispatch events,…). In this way, the user can analyse, adjust and fine-tune the individual cases in a very flexible manner.
Tracing of Individual Cases
The user can examine the results of a single fault by running the fault case of interest in the trace mode, a step-by-step analysis that sweeps over the individual actions of the FEA. The switching actions and load shedding / generator dispatch events created by the reliability calculation will then be applied to the network and the results can be viewed and analysed after each time step.
Powerful Output Tools for Result Representation
Results are available as calculation parameters that can be viewed in distinct ways:
- Formatted reports;
- Tabular result views (integrated into the PowerFactory Data Manager);
- Graphical result representations;
- Various colouring modes.
Result Post-Processing
Contribution to Reliability Indices
Post-processing tools allow the calculation of the individual components’ contributions to the system indices. In this way the user can study the impact of certain network components (such as lines/cables, transformers, etc…) to the overall system indices. Likewise, loads can be grouped into load classes (industrial, agricultural, domestic, etc…) and their contribution to, e.g., energy indices can be evaluated.
Development of Indices Over Years.
Taking into account the evolution of the network model and the failure data over time, PowerFactory supports the calculation and visualization of the given indices over years.