A method for operating a wind turbine generator connected to a power network to account for recurring voltage faults on the power network caused by automatic reclosure of at least one circuit breaker following a short-circuit. The method comprises: identifying a deviation of voltage level of the power network from a normal operational voltage level of the network; determining that the identified deviation fulfils criteria for automatic reclosure; and operating the wind turbine generator in a recurring fault mode if automatic reclosure criteria are fulfilled. When operating the wind turbine generator in recurring fault mode, the method comprises: monitoring the recovery of the voltage level from the deviation; categorising the recovery of the voltage as one of at least a strong recovery or a weak recovery; and implementing a ride-through protocol according to the category of recovery.

The present invention provides a system for compliance of an edifice with safety and environmental regulations. The system comprises at least one computer server integrated by mean of the Internet of things (IoT) with sensors and controllers, wherein the sensors and controllers are coupled to corresponding edifice's devices, structures and mechanisms. The sensors register environmental and safety measures in the edifice. The sensors also register the operational parameters of the devices, structures and mechanisms in the edifice. The computer server receives the registers from the sensors and based on these registers dictate, by means of actuating instructions to the controllers, the operation of the devices, structures and mechanisms of the edifice. The system also records logs of usage history and usage patterns for the devices, structures and mechanisms of the edifice. The computer server is programmed, based in the usage history and usage patterns, to predict potential failures of the devices, structures and mechanisms of the edifice. In case of potential failure of a device, structure, or mechanism, the computer server commands replacement or repair of the device, structure or mechanism. By anticipating the failure of devices, structures and mechanism in the edifice, the system of the present invention assures the flawless operation of the edifice and full compliance with safety and environmental regulations.

Cooperation in supply and demand balance of renewable energy in a region is implemented by operation of infrastructures of an infrastructure service such as water supply. In an energy management system including: a processor; and a storage device, the processor predicts an electric power supply amount utilizing renewable energy in a predetermined region, predicts an electric power demand amount in the region, predicts a demand amount of an infrastructure service different from an electric power service in the region, predicts an electric power demand amount corresponding to the infrastructure service on the basis of the predicted demand amount of the infrastructure service in the region, and determines use time of electric power corresponding to the infrastructure service such that the electric power demand amount in the region approaches the electric power supply amount.

An electronic sensing and allocation system is provided for a distributed water infrastructure containing a plurality of differing appliances. The system may receive, from at least one sensor upstream of the plurality of differing appliances, a plurality of signals indicative of water usage within the distributed water infrastructure. The system may output a first indication of a first volume of water together with an indicator attributing the first volume of water to a first rate schedule, and output a second indication of a second volume of water together with an indicator attributing the second volume of water to a second rate schedule. The system may enable billing of the first and second volumes of water to a consumer at differing rates based on differing uses.

A home appliance can operate in a future time frame. Information is obtained from a power distributor in order to determine a time when to operate the home appliance in this future time frame. The home appliance then operates at the time determined with information from the power distributor.

A system for automatically learning and adapting to the energy usage of an equipment operating according to a control input including at least one sensor for measuring an energy usage of the equipment an generating a baseline energy usage over time signature that is used to compare active energy usage measurements to so as to determine operational deviations. The system includes software that matches and compares equipment operation to established norms and can modify the functioning of the equipment when threshold deviations are detected. The system includes the ability to learn the functioning of the equipment and can adjust for dynamically changing conditions to avoid generation of false alerts or alarms while at the same time detecting longer term deviations that if left unchecked, could shorten the lifespan of the equipment and increase the costs associated with running the equipment.

A machine learning device is provided with: an input data obtaining unit that, in burnishing process in which a processing surface of an arbitrary workpiece is surface-treated with an arbitrary tool, obtains as input data processing information including information of the workpiece prior to the burnishing process and information of a processing condition; a label obtaining unit that obtains label data indicating processed state information including a processed state of the workpiece after the burnishing process and surface roughness of the workpiece when the processed state is normal; and a learning unit that carries out supervised learning using the input data and the label data thus obtained to generate a learned model to which processing information of an upcoming burnishing process is input and which outputs processed state information for the burnishing process.

Methods and systems for power management are disclosed. The disclosed power management may facilitate the use of different components that may have different electrical current capacity limitations. The current capacity limitations may be based on, for example, physical limitations of the components, regulatory limitations, organizational limitations, and/or other considerations. It may not be desirable to exceed the current capacity limitations. By implementing the disclosed power management methods, systems, and/or devices, operation of devices may be less likely to result in the current drawn through devices such as power cables exceeding the current capacity limitations even while other devices operably connected to the cables do not have such current capacity limitations.

A method for predicting when energy consumption will exceed normal production capacity for buildings including generating data sets for each of the buildings, where energy consumption values within each set are shifted by one of a plurality of lag values relative to time and temperature values, and where each lag value is different; performing a regression model analysis on each set to yield corresponding regression model parameters and a corresponding residual; determining a least valued residual indicating a corresponding energy lag for each of the buildings; using outside temperatures, regression model parameters, and energy lags for all of the buildings to estimate a cumulative energy consumption for the buildings, and to predict the time when energy consumption will exceed normal production capacity; and receiving the time when energy consumption will exceed normal production capacity, and preparing and commencing exceptional measures required to manage the energy consumption.

An external control FPGA device includes a command receiving terminal configured to receive command data, a control outputting terminal configured to output a functioning control signal, and a plurality of FPGA connection terminals, and a data processing FPGA device that transmits a control command from an external command data receiver to a control signal outputter. The data processing FPGA device is connected to one of the plurality of FPGA connection terminals through a data processing line that is independent of a command transmission pathway including an external command data receiver, a command data line, the external control FPGA device, a functioning control signal line and the control signal outputter. The data processing FPGA device inputs data that is to be processed from the external control FPGA device through the data processing line, and outputs the processed data to the external control FPGA device.