PowerApps Energy Management System Solution [EMS]
This is a brief functional description of the EMS modules available with
PowerApps suite of software. For more information, reader is encouraged to
contact us through email.
Only some relevant module functions are described in this page. For most other
things the off-line modules listed under PowerApps Calculatin Engine is good
enough even for real time EMS applications.
This is a tool whereby the computer model of the electrical network is updated along with the single line diagram of the network and single line diagram of the substation arrangements.
At substation level, all breakers, isolators, switches , line connectivity, transformer connectivity, any other electrical equipment connectivity such as reactors, capacitors, generators etc can be shown through a Graphical user interface.
The necessary data needed for system analysis , tags needed for various equipments and measurements can also be entered.
At network level, it is a connectivity diagram or single line diagram showing various substation interconnection.
The PowerGUI of PowerApps provides suitable facilities for computer model update as described. PowerGUI is a windows based GUI tool that supports multiple drawing pages of any standard
or custom size and orientation.
Network topology processors takes the power system model data created from the PowerGUI and the real time status information of the breakers/ isolators and switches from SCADA measurement database.
This function works at two levels
a) Substation level: wherein based on breaker/switch status it determines the number of effective electrical nodes
b) System Level: Wherein it determines the number of network islands and electrical buses/nodes associated with each network island.
Also it assigns reference bus to the largest generator within each island identified.
PowerApps uses network topology processor as the base function to prepare the network model for analysis. The network topology processor establishes the system positive, negative and zero sequence network models. For Transient stability solution and short circuit calculations, network model is further updated with synchronous machine models and induction motor models as needed for relevant studies.
PowerApps uses weighted least square method [WLS] as well as Normal equation with Equality Constraints method for state estimation, with bad data detection and removal. There is provision available wherein both real time data , user defined pseudo measurements and high confidence zero bus injections can be considered in the state estimation algorithm of the PowerApps. The phasor measurements if available with a reference bus voltage, can also be incorporated into the PowerApps state estimation algorithm.
PowerApps uses coupled formulation of P-Delta and Q-V jacobian rather than
the decoupled variations.
An optional observability module is available , which
estimates the network observability based on available measurements in a given
network island. User can place additional measurements in the network and
examine the network observability
By default, PowerApps state estimation assumes MW,
MVAR measurements for all lines, transformers, bus injections. In addition bus
voltage measurements are also handled in the state estimation algorithm.
Like all state estimation algorithms, PowerApps state
estimation algorithm needs sufficient redundancy for reasonable static system
state estimation. The redundancy can be generated by offline load flow results
database if needed. PowerApps load flow solution can store such several typical
load flow results in the database from which pseudo measurements can be
generated. It is also possible to fit the real time measurements to available
load flow results and choose best possible pseudo measurements where needed
In case of bad data detection and removal, PowerApps
carries out state estimation once again till all bad data is sufficiently
removed. In case of observability problems, rather than removing the bad data
PowerApps simply reduces the confidence level assigned to the bad data to
achieve satisfactory state estimation results.
There is a provision in PowerApps wherein the state
estimation is first carried out for observable islands only and later performed
for the entire system along with the pseudo measurements
Bus injection measurements can also be obtained as
forecast values for a given hour to be used at the time of state estimation as a
pseudo measurement.
PowerApps supports a generic trend as well as generic
regression model for bus load forecast.
Historical data of the bus loads at a given time of the day can be stored in the database along with the other parameters such as temperature, time of the day, type of day, rain fall, humidity, bus voltage, bus frequency etc..
A simple trend model will use only the bus loads with or without noise model. Noise is the difference between the model
of prediction and actual sample. When the noise model is added to the mathematical model, this difference
[or noise] is further reduced and prediction is more accurate.
The regression model on the other hand uses other parameters other than purely bus powers and estimates the influence of other parameters on the bus load powers. The results from bus load forecast can be used for offline power system analysis as well as for online state estimation for pseudo measurements as needed. This can also be used for short term operational planning using economic dispatch and optimal power flow solution of PowerApps.
The method of bus load forecast used in PowerApps is also applicable to the system wide load forecast
The description for most other modules may be obtained from the relevant links from PowerApps Calculation Engine Page.
Overview of PowerApps EMS Solution
Overview of PowerApps EMS Solution