7results about How to "Guarantee power supply reliability" patented technology

The invention belongs to the field of power system monitoring and fault diagnosis, and particularly relates to a cable branch box health early warning method based on fusion of insulation resistance and leakage current. The method comprises the following steps: acquiring insulation resistance and leakage current signals which are synchronously aligned by using a sensing monitoring unit, and extracting deterministic characteristics through nonlinear preprocessing; performing phase-space reconstruction on the leakage current signal, and calculating the maximum Lyapunov exponent, correlation dimension and other dynamic characteristic indexes so as to quantify the chaotic evolution degree responded by the insulating medium; and constructing an evaluation model based on fusion of insulation resistance and dynamic indexes, calculating a comprehensive health index, comparing the comprehensive health index with a threshold value, and determining an early warning level. According to the method, the qualitative change omen at the initial stage of insulation degradation can be sensitively captured by fusing the macroscopic electrical parameters and the microdynamics evolution characteristics, the advancement and the anti-interference capability of early warning are improved, reliable support is provided for refined operation and maintenance of the cable branch box, and the power supply reliability of a power system is guaranteed.

This invention relates to the field of power system energy storage technology, specifically to a method and device for site selection and capacity determination of computing-powered energy storage based on grid-connected green electricity direct connection. The method includes: acquiring 8760 hours of time-series operational data and line data from a computing center and new energy power plants, setting the connected grid as an infinite power source; using K-means clustering to obtain typical daily scenarios; constructing a parallel computing framework for three energy storage deployment scenarios, with the minimum life-cycle cost as the objective function, combined with constraints such as power balance; and solving the problem using particle swarm optimization and determining the optimal solution through economic comparison. The corresponding system includes modules for annual historical data acquisition, typical daily scenario clustering, parallel optimization framework, optimization problem solving, and solution acquisition, with each module collaboratively executing the above method. This invention fills a technological gap, improves computational efficiency, achieves optimal economic energy storage configuration, ensures power supply reliability, and facilitates the full absorption of green electricity.

This invention discloses a distribution network scheduling optimization method based on an energy storage system, belonging to the field of power system optimization and scheduling. With the goal of minimizing photovoltaic curtailment, load shedding, and the operating costs of mobile energy storage (MESS), a traffic-distribution network coupled optimization model is constructed. Based on the traffic uncertainty at each time period on the road, a constraint relationship is established between path state variables and driving state variables to simulate the traffic congestion delay of the MESS, while ensuring sufficient charging and discharging time for the MESS at each node. The coupling between the transportation network and the distribution network is achieved through the path state variables, driving state variables, and output power of the MESS. Traffic uncertainty is transformed into an opportunity constraint on congestion delay. By simulating the congestion delay of the MESS through path state variables and driving state variables, the driving behavior and power scheduling of the MESS are optimized, thereby improving the distribution network's capacity to support photovoltaic power generation and residential loads.

This invention provides a frequency-to-analog safety barrier, comprising a voltage conversion circuit, a transformer coil drive circuit, a transformer, a first AC voltage rectification and filtering circuit, a frequency signal processing circuit, a NAMUR signal processing circuit, an NPNPNP signal processing circuit, a frequency processing circuit, an MCU control circuit, a TTL output interface, an isolation chip, a square wave processing circuit, a filtering circuit, a DC output circuit, and an alarm relay. The voltage conversion circuit is connected to the transformer via the transformer coil drive circuit. The transformer supplies power to the hazardous and safe zones via the first AC voltage rectification and filtering circuit. Multiple intrinsically safe terminals in the hazardous zone are connected to the frequency processing circuit via three signal processing circuits. The frequency processing circuit outputs to the MCU control circuit. The MCU output sequentially passes through the TTL interface, the isolation chip, the square wave processing circuit, and the filtering circuit to the DC output circuit. This invention achieves frequency signal to analog quantity conversion and safety isolation, increasing system stability.

This invention provides a YOLO-based method for identifying fault types in 10kV distribution network lines, comprising: constructing a fault image dataset and data augmentation; constructing an improved YOLOv8 fault identification model architecture; constructing a multi-task loss function for fault identification; training the line fault identification model; inference detection based on line inspection images; post-processing optimization of fault detection results; and outputting identification results. This invention achieves high-precision, robust, and real-time intelligent identification and classification of various types of line faults in 10kV distribution networks, effectively improving the efficiency of intelligent inspections and the timeliness of fault early warnings, and ensuring the safe and stable operation of the distribution network.

This invention belongs to the field of power line fault detection technology and discloses a method, system, equipment, and medium for diagnosing power distribution line faults. The method includes: acquiring initial fault signal data corresponding to the power distribution line, preprocessing the initial fault signal data, and outputting fault signal data; decomposing the fault signal data using joint decomposition technology to obtain intrinsic mode components (IMCs); introducing information mining technology to extract the distribution change feature vector of the fault signal and fusing it with the IMCs to obtain a change image; extracting local features of the change image through a convolutional neural network and combining it with a strategy function optimized by a Huffman tree for fault classification, and outputting the fault diagnosis result. This invention applies the Softmax strategy of Huffman trees, improving the efficiency and accuracy of judgment, enabling early identification and warning of fault signals in power distribution lines, and improving the efficiency of power distribution line fault diagnosis.

This invention discloses an energy-saving control method for new energy substations based on digital management, belonging to the field of power system automation and energy management technology. The method includes: constructing a multi-source data fusion sensing layer to collect data such as main transformer operating parameters, reactive power compensation status, auxiliary system load, and ambient temperature and humidity; establishing a dynamic energy efficiency evaluation model with the goal of minimizing comprehensive energy consumption, integrating main transformer losses, reactive power switching losses, auxiliary system energy efficiency, and ambient temperature correction factors; generating a coordinated control strategy for main transformer tap positions, reactive power switching, and cooling system start / stop using a rolling optimization algorithm, and verifying safety boundaries and action frequency constraints; executing closed-loop control and online correction strategies based on deviation feedback; and adaptively updating model parameters using the recursive least squares method, combined with an energy efficiency knowledge base to improve response speed. This invention achieves accurate modeling of the entire substation's energy consumption and multi-factor coordinated optimization, significantly reducing the substation's electricity consumption while ensuring safety and new energy consumption.