Determination of security-constrained optimal power flow

A method of operating a power grid assisted by an artificial intelligence (AI) module, the method comprising, by at least one processor executing at least one program element:

• during a first phase, generating a training data set that comprises a plurality of solutions of at least one security-constrained optimal power flow (SC-OPF) problem associated with at least one power grid scenario, the training data set comprising training input data and corresponding training output data, the training output data being the expected output when the corresponding input data is input;
• during a second phase, training the AI-module by supplying the training data set to the AI-module;
• and
• during a third phase, operating the power grid in a power grid scenario, the operation at least partly depending on SC-OPF problem solution output data obtained by solving a modified optimization problem that has a size that has been reduced by the trained AI-module in response to input data associated with the power grid scenario.

A method of training an artificial intelligence (AI) module to determine a security-constrained optimal power flow (SC-OPF) of a power grid, the method comprising, by at least one processor executing at least one program element:

• providing input data associated with a power grid scenario, the input data defining a security-constrained optimization problem;
• generating a training data set, the training data set comprising a plurality of solutions of a SC-OPF problem associated with at least one given power grid scenario, the training data set comprising training input data and corresponding training output data, the training output data being the expected output when the corresponding input data is input;
• and
• providing the training data set to the AI-module;
• receiving output data from the AI-module resulting from the input of the training data set;
• comparing the output data and the training output data corresponding to the training input data of the training data set;
• and
• adjusting parameters of the AI-module based on the comparison.

A power grid, comprising:

• a plurality of distributed electrical generators;
• a plurality of distributed loads;
• a plurality of branches, adapted to electrically connect the electrical generators and/or the loads to each other;
• and
• a control apparatus, adapted to control operation of at least a part of the power grid and to determine a security-constrained optimal power flow (SC-OPF) of the power grid, the control apparatus comprising an artificial intelligence (AI) module and a solver module;
• wherein the AI-module is adapted to automatically generate SC-OPF problem solution output data associated with the SC-OPF,
• wherein the AI-module is further adapted to, in response to received input data, from a central and/or decentralized monitoring device, measuring device, or computer model, associated with a power grid scenario, reduce the SC-OPF problem to a modified optimization problem which is smaller than the SC-OPF problem;
• wherein the solver module is adapted to solve, the modified optimization problem;
• and
• wherein the control apparatus is further adapted to operate the power grid based on at least the SC-OPF problem solution output data.