A method and system for regulating a multi-component power distribution network with high proportion of distributed power sources. The method includes: the distribution network regulation center acquiring user voltage information; the information and optimization model, performing iterative calculation of corresponding preset control objectives for the distribution network regulation center in the optimization model by a Lagrange algorithm, simultaneously controlling errors of the control objectives in the iterative calculation process by a Proportional-Integral-Differential (PID) algorithm, for acquiring a regulation signal of a user side local load, and sending the user side's local load regulation signal to the user side; and performing iterative calculation of control objectives based on the regulation signal of the local load and the calculation part of the optimization model user side, and simultaneously controlling errors of the control objectives in the iterative calculation process by the PID controller, to regulate the local load.

A method and system for regulating a multi-component power distribution network with high proportion of distributed power sources. The method includes: the distribution network regulation center acquiring user voltage information; the information and optimization model, performing iterative calculation of corresponding preset control objectives for the distribution network regulation center in the optimization model by a Lagrange algorithm, simultaneously controlling errors of the control objectives in the iterative calculation process by a Proportional-Integral-Differential (PID) algorithm, for acquiring a regulation signal of a user side local load, and sending the user side's local load regulation signal to the user side; and performing iterative calculation of control objectives based on the regulation signal of the local load and the calculation part of the optimization model user side, and simultaneously controlling errors of the control objectives in the iterative calculation process by the PID controller, to regulate the local load.

According to one embodiment, a method, computer system, and computer program product for smoothing one or more surfaces of a 3D-printed object in reduced gravity is provided. The present invention may include positioning one or more radiative heating elements to evenly heat one or more surfaces of a 3D-printed object based on a shape of the 3D-printed object; determining, for at least one of the one or more radiative heating elements, a desired heat output necessary to melt the outermost layers of the one or more surfaces; and pulsing the one or more radiative heating elements to melt the one or more surfaces, wherein the duration and frequency of the pulsing is configured to achieve the desired heat output.

According to one embodiment, a method, computer system, and computer program product for smoothing one or more surfaces of a 3D-printed object in reduced gravity is provided. The present invention may include positioning one or more radiative heating elements to evenly heat one or more surfaces of a 3D-printed object based on a shape of the 3D-printed object; determining, for at least one of the one or more radiative heating elements, a desired heat output necessary to melt the outermost layers of the one or more surfaces; and pulsing the one or more radiative heating elements to melt the one or more surfaces, wherein the duration and frequency of the pulsing is configured to achieve the desired heat output.

A computer is provided for a fuel cell propulsion system of a motor vehicle. The computer includes one or more processors receiving a temperature signal from one or more temperature sensors and a pressure signal from one or more pressure sensors. The computer further includes a non-transitory computer readable storage medium including instructions, such that the processor is programmed to determine a feedback correction based on the temperature of the coolant and the pressure drop of the coolant across the fuel cell stack. The processor is further programmed to generate a pump command signal based on the feedback correction and a nominal pump command, with the pump command signal actuating a pump to pump coolant at a target pump speed.

A computer is provided for a fuel cell propulsion system of a motor vehicle. The computer includes one or more processors receiving a temperature signal from one or more temperature sensors and a pressure signal from one or more pressure sensors. The computer further includes a non-transitory computer readable storage medium including instructions, such that the processor is programmed to determine a feedback correction based on the temperature of the coolant and the pressure drop of the coolant across the fuel cell stack. The processor is further programmed to generate a pump command signal based on the feedback correction and a nominal pump command, with the pump command signal actuating a pump to pump coolant at a target pump speed.

An example device comprises a reference model module, an adaptation law module, and an adaptive control module. The reference model module is configured to receive a setpoint input and a reference model input, and to generate a reference model output. The adaptation law module is configured to receive the reference model output from the reference model module, to perform a signum projection tensor operation based at least in part on the reference model output, and to generate a signum projection adaptation law output. The adaptive control module is configured to receive the adaptation law output from the adaptation law module, to receive the setpoint input, and to receive a sensor system output from a sensor system, and to generate an adaptive control signal.

An example device comprises a reference model module, an adaptation law module, and an adaptive control module. The reference model module is configured to receive a setpoint input and a reference model input, and to generate a reference model output. The adaptation law module is configured to receive the reference model output from the reference model module, to perform a signum projection tensor operation based at least in part on the reference model output, and to generate a signum projection adaptation law output. The adaptive control module is configured to receive the adaptation law output from the adaptation law module, to receive the setpoint input, and to receive a sensor system output from a sensor system, and to generate an adaptive control signal.

The invention discloses a field detection device and system for achieving no maintenance of a gas density relay. The field detection device comprises a temperature adjusting mechanism and an intelligent control unit, wherein rise and fall of the temperature of the temperature adjusting mechanism are controlled by the intelligent control unit, thereby making the temperature of a temperature compensation component of the density relay rise and fall to complete the field detection of the gas density relay, and no maintainer is needed to operate on site, which achieves no maintenance of the gas density relay, and greatly improves the efficiency and reliable and safe running of power grids. The invention further provides a field detection method for supporting normal running of the field detection device above.

The invention discloses a field detection device and system for achieving no maintenance of a gas density relay. The field detection device comprises a temperature adjusting mechanism and an intelligent control unit, wherein rise and fall of the temperature of the temperature adjusting mechanism are controlled by the intelligent control unit, thereby making the temperature of a temperature compensation component of the density relay rise and fall to complete the field detection of the gas density relay, and no maintainer is needed to operate on site, which achieves no maintenance of the gas density relay, and greatly improves the efficiency and reliable and safe running of power grids. The invention further provides a field detection method for supporting normal running of the field detection device above.