Abstract: A method for regenerating a deactivated denitration catalyst includes steps of preparing a washing fluid including a water-contained liquid and entrained carbon dioxide bubbles, and subjecting the deactivated denitration catalyst to a treatment with the washing fluid. An apparatus for regenerating the deactivated denitration catalyst is also provided.

Abstract: A power system includes multiple power units (PUs), each including a circuit breaker (CB), a local controller (LC) and an intelligent electronic device (IED). For any one of the PUs, the IED, when determining that the CB has mechanically failed, outputs a disconnect message via a network to the IED(s) of the remaining PU(s). For each of the remaining PU(s), based on the disconnect message, the IED thereof, when determining that the corresponding CB is a relevant CB, outputs a trip control signal that indicates to trip for receipt by the corresponding LC, so that the LC causes the CB to switch to an open state.

Abstract: A power generation prediction system using a first and second neural networks is provided, and the first neural network is connected to the second neural network. The first neural network receives first input data, and generates the amount prediction data according to the first input data. The first input data is used to determine amount prediction data, and the amount prediction data is used to determine power generation prediction data. The second neural network receives the amount prediction data, and calculates the power generation prediction data according to the amount prediction data. When a device in a selected area is deteriorated or reinstalled, the second neural network is fine-tuned and trained again. The power generation prediction data is a power generation prediction bound having a maximum and minimum power generation prediction values, and thus the power deployment terminal in a power grid can deploy power more precisely.

Abstract: A power generation prediction system using a first neural network and a second neural network is provided, and the first neural network is connected to the second neural network. The first neural network receives first input data, and generates the amount prediction data according to the first input data. The first input data is used to determine amount prediction data, and the amount prediction data is used to determine power generation prediction data. The second neural network receives the amount prediction data, and calculates the power generation prediction data according to the amount prediction data. When a device in a selected area is deteriorated or reinstalled, the second neural network is fine-tuned and trained again.

Abstract: An anti-biofouling system adapted to be used for an underwater structure immersed in seawater is disclosed. The anti-biofouling system includes a conductive layer, comprising carbon fiber, graphite powder and binder, formed on a surface of the underwater structure for serving as an anode, a cathode, and a power supply for providing a current, thereby performing an electrolytic reaction for the anti-biofouling system such that a fouling organism is prohibited from attaching on the surface of the underwater structure.