5results about How to "Ease volatility" patented technology

The invention discloses a day-ahead-day two-stage optimization scheduling method and system for an RSOC integrated energy system. The method comprises the steps that the RSOC integrated energy system is established based on running characteristics of the RSOC; respectively establishing an RSOC variable working condition operation model, a combined heat and power generation model and a multi-element load demand response model based on the RSOC comprehensive energy system; based on the RSOC variable working condition operation model, the combined heat and power generation model and the multi-element load demand response model, jointly establishing a day-ahead-intra-day two-stage optimization scheduling model; optimizing the day-ahead-intra-day two-stage optimization scheduling model based on a day-ahead plan scheduling target and a day-ahead constraint condition to obtain optimal operation state data of system equipment; and based on the optimal operation state data, the intra-day rolling optimization target and the intra-day constraint condition, performing rolling adjustment on the day-ahead-intra-day two-stage optimization scheduling model to obtain an optimal scheduling operation scheme. Under the condition of ensuring stable and reliable operation of the comprehensive energy system, the operation cost of the system is reduced, and the optimization control precision of the system is improved.

This invention discloses an adsorption refrigeration temperature control system, comprising: an adsorption bed, wherein an adsorption chamber of the adsorption bed is provided with an adsorbent; a cryogenic fluid supply port for supplying cryogenic fluid to a cooling object to absorb heat from the cooling object; a cold storage device, which is connected to the cryogenic fluid supply port to supply cryogenic fluid to the cold storage device; and an evaporator, wherein the evaporation chamber of the evaporator is used to supply gaseous adsorbent to the adsorption chamber, and is further provided with a cryogenic fluid channel capable of exchanging heat with the liquid adsorbent in the evaporation chamber, the cryogenic fluid channel being connected to the cold storage device to supply cryogenic fluid to the cold storage device. The above-described adsorption refrigeration temperature control system can effectively solve the problem of poor temperature control performance in adsorption refrigeration systems. This invention also discloses a liquid cooling system including the above-described adsorption refrigeration device and an adsorption refrigeration temperature control method.

The application discloses an autism auxiliary diagnosis method and system based on gene pathway atlas information, and belongs to the cross field of bioinformatics and machine learning. The application firstly reads original sequencing data and pre-processes to obtain a standardized differential expression gene matrix; introduces pathway function and topological information, constructs a pathway topological adjacency matrix, and dimensionally reduces a pathway feature matrix, transmits a graph signal, and encodes features to obtain gene pathway features; then, the initial training of a multi-modal fusion network is carried out on the foregoing two matrices; Top K key genes are screened according to a gene importance score, and secondary training is carried out in combination with the gene pathway features; finally, the gene expression of a to-be-detected object is input, and an autism auxiliary diagnosis classification result is output. The application introduces the gene pathway atlas as prior knowledge, constructs a multi-modal fusion network with biological interpretability and high robustness, and can improve the autism diagnosis accuracy based on a small number of key features.

This invention discloses an autism-assisted diagnostic method and system based on gene pathway mapping information, belonging to the interdisciplinary field of bioinformatics and machine learning. The invention first reads and preprocesses raw sequencing data to obtain a standardized differentially expressed gene matrix; then, it introduces pathway function and topological information to construct a pathway topological adjacency matrix, and obtains gene pathway features by dimensionality reduction, graph signal propagation, and feature encoding of the pathway feature matrix; subsequently, it performs initial training of a multimodal fusion network on the aforementioned two matrices; then, it selects Top K key genes based on gene importance scores and performs secondary training in conjunction with gene pathway features; finally, it inputs the gene expression levels of the subject to be tested and outputs the autism-assisted diagnostic classification results. By introducing gene pathway mapping as prior knowledge, this invention constructs a multimodal fusion network that combines biological interpretability and high robustness, which can improve the accuracy of autism diagnosis based on a small number of key features.

The invention discloses a flexibility resource adjustment characteristic modeling and aggregation method, which comprises the following steps of: collecting a virtual battery model coefficient matrix reported by each flexibility resource individual by a similar resource aggregation platform, then calculating an element polyhedron coefficient and sending the element polyhedron coefficient to each individual; calculating parameters by each individual, calculating a final equivalent aggregate by the similar resource aggregation platform according to the parameters, and sending the final equivalent aggregate to a scheduling center for decision making; and finally, deaggregating the decision result, and issuing the decision result to each individual for execution. According to the method, the consistency of group behaviors is ensured, and each individual can be controlled to meet the constraint as long as the final equivalent polymer is controlled to be charged and discharged asynchronously. Therefore, the actual behavior of the energy storage system is reflected more accurately, the overall utilization efficiency of flexible resources is improved, and the coping capacity of a power system for the fluctuation and uncertainty of renewable energy sources is enhanced.