State Estimation Main Run Settings

The state estimation settings should be provided as input arguments of the function runse. Here, we provide the main settings to run the module, however, we draw your attention to the additional settings where measurement values and sets can be changed.

The state estimation algorithms (METHOD) use the weighted least-squares estimation by default settings, but it is also possible to use the least absolute value estimation.

Although the syntax is given in a certain order, for methodological reasons, only DATA must appear as the first input argument, and the order of other inputs is arbitrary, as well as their appearance.

Examples:

runse('ieee14_20', 'nonlinear', 'warm', 'maxIter', 100, 'main');
runse('ieee14_20', 'pmu', 'pmuOptimal', 'pmuUnique', 10^-12, 'save');
runse('ieee14_20', 'dc', 'lav' 'main');
runse('ieee14_20', 'dc', 'legDevice', [10 0 4 0], 'estimate');
runse('ieee14_20', 'dc', 'legUnique', 10^-4, 'estimate');

Syntax:

runse(DATA, METHOD)
runse(DATA, METHOD, START)
runse(DATA, METHOD, START, ATTACH)
runse(DATA, METHOD, START, ATTACH, DISPLAY, EXPORT) 

Description:

runse(DATA, METHOD) computes the state estimation problem
runse(DATA, METHOD, START) initializes the Gauss-Newton method
runse(DATA, METHOD, START, ATTACH) maximum number of iterations, bad data processing and least absolute value state estimation
runse(DATA, METHOD, START, ATTACH, DISPLAY, EXPORT) showing results and export models

Input Arguments:

DATA

Example	Description
'ieee30_41'	first input argument in the runse function

METHOD

Command	Description
'nonlinear'	non-linear state estimation based on the weighted least-squares
'pmu'	linear weighted least-squares state estimation only with PMUs
'dc'	linear weighted least-squares DC state estimation

START

Command	Description
'warm'	the Gauss-Newton initial point defined as the one applied in AC power flow
'exact'	the Gauss-Newton initial point defined from the exact values, if those exist
'flat',value	the Gauss-Newton initial point defined according voltage angles in degrees [x] and magnitudes in per-units [y] value = [x y], default setting: [0 1]
'random',value	the Gauss-Newton initial point defined using random perturbation between the minimum [x] and maximum [y] values of voltage angles in degrees, and minimum [z] and maximum [v] values of voltage magnitudes in per-units value = [x y z v], default setting: [-0.5 0.5 0.95 1.05]

ATTACH

Command	Description
'maxIter',value	the Gauss-Newton maximum number of iterations [x] value = x
'bad',value	bad data processing according to the identification threshold [x] value = x, default setting: 3 bad data processing according to the identification threshold [x, with the maximum number of passes [y] throughout the state estimation algorithm <br> value = [x y]`
'lav'	least absolute value state estimation

DISPLAY

Command	Description
'main'	bus data display
'flow'	power flow data display
'estimate'	estimation data display
'error'	evaluation data display

EXPORT

Command	Description
'save'	save display data
'export'	export the system model without slack bus (for linear state estimation problems, exports in data.extras)
'exportSlack'	export the system model with slack bus (for the DC state estimation, exports in data.extras)

Flowchart

The state estimation flowchart depicts the algorithm process according to main and additional user settings.