CN-122022398-A - Energy circulation optimization method and system based on cross-domain cooperation

CN122022398ACN 122022398 ACN122022398 ACN 122022398ACN-122022398-A

Abstract

The invention discloses an energy circulation optimization method and system based on cross-domain cooperation, and relates to the technical field of environmental protection and biomass energy intersection. The intelligent early warning system comprises a collaborative data interaction unit, an AI cross-domain optimization unit and an intelligent early warning unit, wherein the collaborative data interaction unit is used for obtaining synchronous cross-domain data of a water treatment end and a biomass natural gas end, the AI cross-domain optimization unit is used for matching sludge supply and demand with wastewater reuse according to a standardized cross-domain data set by utilizing a resource matching prediction model, global parameter optimization is carried out on a matching result by utilizing a cross-domain process optimization model, corresponding execution parameters are generated according to the optimized global parameters by utilizing a flora sludge adaptation model and a water quality wastewater adaptation model respectively in combination with an actual energy circulation scene, and the intelligent early warning unit is used for carrying out linkage fault risk recognition on the cross-domain data based on a cross-domain fault association model. The invention can greatly improve the cross-domain operation efficiency and the resource utilization rate, and realize the full-chain closed-loop circulation optimization of various cross-domain data such as sludge, energy, water resources and the like.

Inventors

ZHANG JINGWEI
WANG YANRUI
LI LEYAN
CHEN DEJUN

Assignees

山东厚濡环保设备有限公司

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (10)

1. An energy cycle optimization system based on cross-domain cooperation, which is characterized by comprising: The collaborative data interaction unit is used for obtaining synchronous cross-domain data of the water treatment end and the biomass natural gas end, and preprocessing the cross-domain data to obtain a standardized cross-domain data set; the AI cross-domain optimization unit is used for matching the sludge supply and demand with the wastewater reuse according to the standardized cross-domain data set by utilizing the resource matching prediction model, performing global parameter optimization on the matching result by utilizing the cross-domain process optimization model, and respectively generating corresponding execution parameters according to the optimized global parameters by combining the flora sludge adaptation model and the water quality wastewater adaptation model with the actual energy circulation scene; and the intelligent early warning unit is used for carrying out cascading failure risk identification on the cross-domain data based on the cross-domain failure association model, pushing early warning information according to a preset grade according to an identification result and generating an emergency scheduling scheme.
2. The cross-domain collaboration-based energy cycle optimization system of claim 1, wherein the collaboration data interaction unit comprises: the data acquisition module is used for acquiring synchronous cross-domain data of the water treatment end and the biomass natural gas end; The data standardization module is used for preprocessing the synchronous cross-domain data, and specifically, the preprocessing comprises abnormal value elimination, missing value complementation and standardization operation; And the cross-domain data interface module is used for constructing a bidirectional data interaction interface based on the communication protocol.
3. The energy circulation optimization system based on cross-domain synergy according to claim 1, wherein in the AI cross-domain optimization unit, a resource matching prediction model utilizes an LSTM algorithm with a cross-domain feature cross-attention mechanism to carry out weight distribution of a water treatment end and a biomass natural gas end according to process causal relationship, the cross-domain process optimization model utilizes a reinforcement learning algorithm with a dynamic weight multi-objective reward function to dynamically adjust the matching degree obtained by the resource matching prediction model in combination with a genetic algorithm, a flora sludge adaptation model utilizes a CNN and LSTM fusion algorithm of double input branches to calculate sludge pretreatment optimization parameters, and a water quality wastewater adaptation model utilizes a random forest algorithm with a dynamic feature matching rule to calculate fermentation wastewater pretreatment parameters.
4. The cross-domain collaboration-based energy cycle optimization system of claim 1, wherein the intelligent pre-warning unit comprises: the cross-domain fault correlation module is used for identifying cascading risks by using a cross-domain fault correlation model of the built-in cross-domain fault correlation map; the multi-stage early warning module is used for generating a multi-stage early warning mechanism according to a preset fault threshold value and generating early warning information according to a fault recognition result; and the emergency scheduling module is used for generating an emergency scheduling scheme according to the early warning information and a preset parameter rule.
5. The energy circulation optimization system based on cross-domain collaboration according to claim 4, wherein the specific steps of identifying the linkage risk by using a cross-domain fault correlation model of a built-in cross-domain fault correlation map are as follows: extracting core features of the cross-domain faults by utilizing XGBoost algorithm; Analyzing core characteristics based on a transmission rule of the cross-domain fault by using the cross-domain fault transmission association map, and constructing a fault map structural model; And (3) performing graph feature learning on the fault graph structural model by using a graph neural network, and identifying a cross-domain propagation rule, propagation speed and a chain reaction path of the fault.
6. The energy circulation optimization system based on cross-domain cooperation according to claim 1, further comprising a resource circulation execution unit, wherein the resource circulation execution unit is used for carrying out sludge transportation and wastewater recycling according to the execution parameters, and simultaneously feeding back the execution data to the cooperation data interaction unit.
7. The energy circulation optimization system based on cross-domain collaboration according to claim 1, further comprising a digital twin unit, wherein the digital twin unit is used for performing simulation verification on optimization parameters, and performing remote parameter adjustment and emergency scheduling.
8. The energy source circulation optimization method based on cross-domain cooperation is characterized by comprising the following steps of: Synchronous cross-domain data of the water treatment end and the biomass natural gas end are obtained, and the cross-domain data are preprocessed to obtain a standardized cross-domain data set; Matching the sludge supply and demand with the wastewater reuse according to a standardized cross-domain data set by utilizing a resource matching prediction model, performing global parameter optimization on a matching result by utilizing a cross-domain process optimization model, and respectively generating corresponding execution parameters according to the optimized global parameters by combining a flora sludge adaptation model and a water quality wastewater adaptation model with an actual energy circulation scene; and performing cascading failure risk identification on the cross-domain data based on the cross-domain failure association model, pushing early warning information according to a preset grade according to an identification result, and generating an emergency scheduling scheme.
9. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program adapted to be loaded by a processor and to perform the cross-domain synergy-based energy cycle optimization method of claim 8.
10. A computer device, comprising: a processor adapted to execute a computer program; A computer readable storage medium having stored therein a computer program which, when executed by the processor, implements a cross-domain synergy-based energy cycle optimization method as claimed in claim 8.

Description

Energy circulation optimization method and system based on cross-domain cooperation Technical Field The invention relates to the technical field of environment protection and biomass energy intersection, in particular to an energy circulation optimization method and system based on cross-domain cooperation. Background Based on the principle that the residual sludge generated by water treatment can be used as a raw material for anaerobic fermentation of biomass, and the high-concentration organic wastewater generated by biomass fermentation can be reused for water supplementing of a water treatment system after being treated, the sludge harmless treatment in the water treatment industry can form a natural resource circulation complementary relationship with the raw material supply and wastewater digestion in the biomass natural gas industry. In the prior art, two industries are in independent operation and rough linkage for a long time, the cross-domain resource matching accuracy is low, and the cross-domain collaborative optimization capability is avoided. At present, the yield, the water content and the carbon-nitrogen ratio of the water treatment sludge are not intelligently matched with the requirements of biomass fermentation raw materials, so that the problems of accumulation spoilage and secondary pollution caused by excessive sludge supply or the problems of fermentation raw material shortage and gas production efficiency reduction caused by insufficient supply are easy to occur. In addition, the water quality of the biomass fermentation wastewater is not matched with the water treatment water supplementing standard, the pretreatment parameters are directly recycled and are realized through the existing single general algorithm, the cross correlation of the two field parameters cannot be identified, the core problems of cross-domain supply and demand matching, global multi-objective optimization, linkage fault early warning and the like cannot be solved, and the application effect cannot reach the requirement of collaborative operation. In addition, in the collaborative optimization process, the water treatment process parameters and the biomass fermentation parameters are mutually split, global optimization cannot be realized through linkage adjustment, excessive dehydration of the water treatment end often occurs, energy consumption is increased, the biomass fermentation end is required to be diluted by adding water, the medicine consumption is reduced by the water treatment end, the organic matters of the sludge are reduced, the fermentation gas production rate is greatly reduced, and the whole energy consumption is high. Disclosure of Invention Aiming at the defects of the prior art, the invention aims to provide a cross-domain collaborative energy circulation optimization method and system, which are used for constructing an AI-driven full-closed loop cross-domain collaborative optimization system, so that the cross-domain operation efficiency and the resource utilization rate can be greatly improved, and the full-chain closed loop circulation optimization of various cross-domain data such as sludge, energy, water resources and the like can be realized. In order to achieve the above object, the present invention is realized by the following technical scheme: The first aspect of the invention provides an energy circulation optimization system based on cross-domain cooperation, which comprises the following components: The collaborative data interaction unit is used for obtaining synchronous cross-domain data of the water treatment end and the biomass natural gas end, and preprocessing the cross-domain data to obtain a standardized cross-domain data set; the AI cross-domain optimization unit is used for matching the sludge supply and demand with the wastewater reuse according to the standardized cross-domain data set by utilizing the resource matching prediction model, performing global parameter optimization on the matching result by utilizing the cross-domain process optimization model, and respectively generating corresponding execution parameters according to the optimized global parameters by combining the flora sludge adaptation model and the water quality wastewater adaptation model with the actual energy circulation scene; and the intelligent early warning unit is used for carrying out cascading failure risk identification on the cross-domain data based on the cross-domain failure association model, pushing early warning information according to a preset grade according to an identification result and generating an emergency scheduling scheme. Further, the collaborative data interaction unit includes: the data acquisition module is used for acquiring synchronous cross-domain data of the water treatment end and the biomass natural gas end; The data standardization module is used for preprocessing the synchronous cross-domain data, and specifically, the preprocessing comprises abnormal value