Abstract:
A method for feeding a grid by a group of wind turbines (WT1, WT2, WT3, WT4, WT5) in a wind farm and controller (10) and wind farm using the same is provided. The method includes: (a) obtaining first real-time SCADA data and first real-time constant variables concerning each of the wind turbines (WT1, WT2, WT3, WT4, WT5) in the group for a first time point, and first calculating fatigue degree of the wind turbine using the obtained first real-time SCADA data and the first real-time constant variables thereof; and (b) first distributing the grid load among the wind turbines (WT1, WT2, WT3, WT4, WT5) in the group using the calculated fatigue degrees thereof. By having the solutions as mention above, during the operation period of "Crack Generation", it provides output data indicative of a load distribution among the wind turbines (WT1, WT2, WT3, WT4, WT5) of the wind farm in relation to the fatigue degrees of the wind turbines (WT1, WT2, WT3, WT4, WT5). This allows achieving an optimal load distribution among the wind turbines from time to time (i.e. at each execution cycle thereof) always taking into account the fatigue degrees of the wind turbines (WT1, WT2, WT3, WT4, WT5), which represent the operating conditions of the wind turbine prior to occurrence of defect. During "crack generation" operation period of wind turbines, this is helpful for controlling in a mode designed based on fatigue minimization so as to postpone defect occurrence as much as possible which is able to extend lifetime of wind farm with fixed capital cost.
Abstract:
A method and system for circuit breaker condition monitoring are disclosed. The method comprises: obtaining an image of a circuit breaker(202); extracting from the image one or more features related to a state of the circuit breaker(204); comparing the extracted one or more features with benchmark data characterizing a predetermined state of the circuit breaker(206); determining a health condition of the circuit breaker based on the comparison(208).
Abstract:
It provides a method for controlling cooling system of a power equipment and a system using the same. The method includes steps of: obtaining a first data set representing operational cost related parameters specific to the power equipment and its cooling system at a series of time intervals of a first load cycle in a history profile; obtaining a second data set representing operational cost related parameters specific to the power equipment and its cooling system at a series of time intervals of a second load cycle in the history profile, where the second load cycle follows the first load cycle; in consideration of the parameters represented by the first data set, through knowledge-based predetermined numerical and/or logical linkages, establishing a third data set representing optimal cooling capacity parameters for the cooling system at the series of time intervals of the first load cycle according to criteria for operational cost optimization of the power equipment; in consideration of the parameters represented by the second data set, through knowledge-based predetermined numerical and/or logical linkages, establishing a fourth data set representing optimal cooling capacity parameters for the cooling system at the series of time intervals of the second load cycle according to criteria for operational cost optimization of the power equipment; establishing a fifth data set representing a cooling capacity parameter difference between the established cooling capacity parameters concerning the first load cycle and the second load cycle; establishing a sixth data set representing cooling capacity parameters for the cooling system at a series of time intervals of a present load cycle by computationally correcting the established cooling capacity parameter concerning the time intervals of the second cycle load with use of the cooling capacity parameter difference; and controlling the cooling system to operate at a series of time intervals of the present load cycle at the established cooling capacity parameters concerning the present load cycle represented by the sixth data set.
Abstract:
A method for monitoring a circuit breaker is provided. The method comprises: detecting at least one operation of a circuit breaker to obtain at least one vibration signal of the circuit breaker, each vibration signal being represented as one-dimensional data of a vibration amplitude over time during the operation of the circuit breaker; transforming the vibration signal to two-dimensional frequency-time data; comparing the transformed frequency-time data with benchmark data characterizing the at least one operation of the circuit breaker; and determining a health condition of the circuit breaker at least in part based on the comparison. A device for monitoring a circuit breaker is also provided. Both the frequency component and the time component in the detected test vibration signals are considered in condition determination of the circuit breaker. The condition can be determined with high accuracy.
Abstract:
It provides a method for monitoring condition of a fleet of circuit breakers and a system and an internet of things using the same. The method includes: (a) measuring at least one type of operating condition related signal for the respective circuit breakers during their operation; (b) obtaining a set of feature data representing the respective measurements of operating condition related signal; (c) performing cluster analysis of the set of feature data based on a similarity threshold; and (d) generating a signal indicating the condition of the fleet of circuit breakers based on the cluster number resulted from the step (c). Rather than comparing the data representing the measurements of operating condition related signal to a reference model built on CB's normal data, The method applies cluster analysis of the set of feature data representing the respective measurements of operating condition related signal, does not need a reference "normal" database for comparison.
Abstract:
It provides a method for monitoring a circuit breaker and an apparatus and an internet of things using the same. The method includes: obtaining a first data set representing force applied to a fixed point of an element of an actuating mechanism of the circuit breaker in present operation cycle, judging a health condition of the circuit breaker in consideration of normal operating condition related parameters of the element according to a history profile when the circuit breaker operated normally and current operating condition related parameters of the element in the present operation cycle extracted from the force represented by the first data set, and generating a signal indicating the health condition of the actuating mechanism of the circuit breaker the circuit breaker. The force applied to the fixed point of the actuating mechanism of the circuit breaker, which corresponds to a health condition of mechanical parts of the circuit breaker as a whole, is selected as an indicator for condition monitoring of the mechanical parts of the circuit breaker. The operating condition related parameters derived from the measurements of the force are considered giving a relatively high accurate judgement of the whole mechanical parts of the circuit breaker.
Abstract:
It is therefore an objective of the invention to provide a method for controlling cooling system of a power equipment and a system using the same. The method includes obtaining a first data set representing operational cost related parameters specific to the power equipment and its cooling system forecasted for a series of time intervals of present load cycle in consideration of a second data set representing operational condition related parameters for the power equipment forecasted for a series of time intervals of present load cycle; in consideration of the parameters represented by the first data set, through knowledge-based predetermined numerical and/or logical linkages, establishing a third data set representing cooling capacity parameters for the cooling system at the series of time intervals of the present load cycle according to criteria for operational cost optimization of the power equipment and its cooling system for the present load cycle; and in the present load cycle, controlling the cooling system to operate at the cooling capacity parameters at the series of time intervals represented by the established third data set. By considering the correlations between different time intervals into and making the cooling optimization valid not only at the specific time interval but also in an entire load cycle, the cooling capacities in the next at least one load cycle is optimized.