Method and arrangement for estimating a grid state of a power distribution grid
AssigneeSiemens Aktiengesellschaft
InventorSylwia Henselmeyer
Life of this patent
Estimating the term…
Abstract
A method estimates a grid state of an electrical power distribution grid having a multiplicity of network sections, in which a central computer arrangement is used to receive measured values from measuring devices. A state estimation device is used to make a prediction of a future grid state, wherein a voltage and a phase angle are respectively ascertained for each network section, and in that a naive Bayes method is used for the prediction.
Claims14
A method for estimating a grid state of an electrical power distribution grid having a plurality of network sections, where a grid state contains a statement about the voltage magnitude or a voltage and the voltage angle or phase angle on each network section, which comprises the steps of:
- measuring, with measuring devices, a voltage and a phase angle for each of the plurality of network sections of the electrical power distribution grid and generating corresponding measured values;
- receiving, via a central computer configuration, the measured values from the measuring devices;
- using a state estimation device to make a prediction of a future grid state based on the measured values, wherein a voltage and a phase angle are respectively ascertained for each of the network sections;
- and
- using a machine learning method, being a naive Bayes method, for formulating the prediction;
- taking into consideration, for the prediction, specific predictions for individual ones of the measuring devices that each have a measurement-location-specific degree of error;
- and
- determining a measurement-location-specific weighting factor, using a respective degree of error, such that the specific predictions are weighted all more highly a lower their degree of error;
- and
- presenting the predictions to a central controller, and initiating countermeasures to the grid based on the predictions when necessary.
A central computer configuration for estimating a grid state of an electrical power distribution grid having a plurality of network sections, where a grid state contains a statement about the voltage magnitude or a voltage and the voltage angle or phase angle on each network section, the central computer configuration comprising:
- measuring devices configured to measure a voltage and a phase angle for each of the plurality of network sections of the electrical power distribution grid and generating corresponding measured values
- a receiving device for receiving the measured values from said measuring devices disposed in the electrical power distribution grid;
- and
- a state estimation device configured to make a prediction of a future grid state based on the measured values, wherein a voltage and a phase angle are respectively ascertained for each of the network sections, said state estimation device is configured to use a machine learning method, being a naive Bayes method, for formulating the prediction, and specific predictions for individual ones of the measuring devices that each have a measurement-location-specific degree of error are taken into consideration for the prediction, and a respective degree of error is used to determine a measurement-location-specific weighting factor such that the specific predictions are weighted all more highly a lower their degree of error;
- and
- a central controller configured for presenting the predictions, and initiating countermeasures to the grid based on the predictions when necessary.
A non-transitory computer readable medium having computer executable instructions for performing a method for estimating a grid state of an electrical power distribution grid having a plurality of network sections, where a grid state contains a statement about the voltage magnitude or a voltage and the voltage angle or phase angle on each network section, which comprises the steps of:
- measuring, with measuring devices, a voltage and a phase angle for each of the plurality of network sections of the electrical power distribution grid and generating corresponding measured values;
- receiving, via a central computer configuration, the measured values from the measuring devices;
- using a state estimation device to make a prediction of a future grid state based on the measured values, wherein a voltage and a phase angle are respectively ascertained for each of the network sections;
- and
- using a machine learning method, being a naive Bayes method, for generating the prediction;
- and
- taking into consideration, for the prediction, specific predictions for individual ones of the measuring devices that each have a measurement-location-specific degree of error;
- and
- determining a measurement-location-specific weighting factor, using a respective degree of error, such that the specific predictions are weighted all more highly a lower their degree of error;
- and
- presenting the predictions via a central controller, and initiating countermeasures to the grid based on the predictions when necessary.
Dependencies are inferred from the claim text.