Abstract: An apparatus for performing the following: the apparatus maintains, in a database, one or more trained machine learning algorithms for predicting an optimal charging strategy for a time interval based on one or more values of a set of prediction parameters relating to a point of common coupling and one or more electrical load devices and on a state of charge level of the battery energy storage system. The apparatus obtains one or more recent values of the set of prediction parameters relating to one or more previous time intervals and predicts, using the one or more trained machine learning algorithm, an optimal charging strategy for a next time interval based on the one or more recent values and a current state of charge level of the battery energy storage system. Finally, the apparatus operates the battery energy storage system using the predicted optimal charging strategy.

Abstract: A switch for a medium or high voltage traction line testing device includes a plurality of normally-opened pairs of contacts connected in series, wherein each pair of contacts is equipped with a separate control coil. The switch further comprises a wireless power transfer supply module being on ground potential for supplying cascaded wireless power transfer receivers comprising the transmitting coil, high frequency inverter and microcontroller, a plurality of cascaded wireless power transfer receivers for supplying control coil of pairs of contacts. Each of the wireless power transfer receivers is referenced to the floating potential and comprises a receiving coil. Each of the control coils is connected to one of the wireless power transfer receivers. The receiving coils of the wireless power transfer receivers are magnetically coupled, and a wireless power transfer supply module is located in the middle of the cascaded wireless power transfer receivers.

Abstract: An apparatus for performing the following: the apparatus maintains, in a database, one or more trained machine learning algorithms for predicting an optimal charging strategy for a time interval based on one or more values of a set of prediction parameters relating to a point of common coupling and one or more electrical load devices and on a state of charge level of the battery energy storage system. The apparatus obtains one or more recent values of the set of prediction parameters relating to one or more previous time intervals and predicts, using the one or more trained machine learning algorithm, an optimal charging strategy for a next time interval based on the one or more recent values and a current state of charge level of the battery energy storage system. Finally, the apparatus operates the battery energy storage system using the predicted optimal charging strategy.

Abstract: A switch for a medium or high voltage traction line testing device includes a plurality of normally-opened pairs of contacts connected in series, wherein each pair of contacts is equipped with a separate control coil. The switch further comprises a wireless power transfer supply module being on ground potential for supplying cascaded wireless power transfer receivers comprising the transmitting coil, high frequency inverter and microcontroller, a plurality of cascaded wireless power transfer receivers for supplying control coil of pairs of contacts. Each of the wireless power transfer receivers is referenced to the floating potential and comprises a receiving coil. Each of the control coils is connected to one of the wireless power transfer receivers. The receiving coils of the wireless power transfer receivers are magnetically coupled, and a wireless power transfer supply module is located in the middle of the cascaded wireless power transfer receivers.