CN-122022332-A - Enterprise business layout optimization system and method

CN122022332ACN 122022332 ACN122022332 ACN 122022332ACN-122022332-A

Abstract

The application relates to the technical field of power service management and resource optimization, in particular to an enterprise service layout optimization system and method, the method comprises the steps of obtaining power service multi-source basic data, constructing a power service layout multi-target optimization model, carrying out parameter initialization on the power service layout multi-target optimization model based on the power service multi-source basic data, and solving and generating an initial service layout planning scheme; and monitoring the running state of the power grid and service response feedback in real time, and carrying out dynamic weight adjustment and parameter correction on the power service layout multi-objective optimization model according to the dynamic change curve of the power grid load and the saturation of the service work order, so as to output a service layout optimization decision instruction. The application ensures that the generated optimization scheme can be directly applied to the production scheduling and operation management practice of power enterprises by converting the complex power grid operation logic into the pure Chinese engineering description and the strict logic operation, and has extremely high technical redundancy and fault tolerance.

Inventors

LAO YONGCHANG
WANG HONGLIANG
YANG JUNJIA
ZHU YAOQI
SHI XINYUAN
WU JIAHUI
ZHANG QINGYUN

Assignees

国网浙江省电力有限公司经济技术研究院

Dates

Publication Date: 20260512
Application Date: 20260130

Claims (10)

1. An enterprise business layout optimization method, comprising the steps of: Acquiring power business multisource basic data, wherein the power business multisource basic data comprises power grid topological structure data, power marketing full-caliber business data and power production operation and maintenance actual measurement data; Constructing a power service layout multi-objective optimization model, taking minimum operation cost, maximum resource coverage rate and optimal power supply reliability index of each power service module as objective functions, and presetting a power grid safe operation boundary and service processing time limit as constraint conditions; carrying out parameter initialization on the power service layout multi-objective optimization model based on the power service multi-source basic data, and solving to generate an initial service layout planning scheme; And monitoring the running state of the power grid and service response feedback in real time, carrying out dynamic weight adjustment and parameter correction on the power service layout multi-objective optimization model according to the dynamic change curve of the power grid load and the saturation of the service work order, carrying out dynamic optimization iteration through a closed loop feedback mechanism, and outputting a service layout optimization decision instruction.
2. The method for optimizing an enterprise business layout according to claim 1, wherein for the power marketing network layout, the constructing a power business layout multi-objective optimization model comprises: extracting geographic spatial distribution characteristics and historical report connection electricity quantity of electricity consumers in the electric power marketing full-caliber service data; Establishing a nonlinear mapping relation between a marketing service radius and a client density by combining a regional load prediction result; and optimizing a collaborative layout scheme of the entity marketing network point and the digital online channel according to the nonlinear mapping relation, and realizing balanced configuration of marketing resources in a geographic space.
3. The method for optimizing enterprise business layout according to claim 2, wherein extracting the geospatial distribution characteristics of the customers in the electricity marketing full-caliber business data comprises calibrating the stored electricity customers by using a geographic information system, generating an electricity utilization map, and predicting the center position of the to-be-established marketing network point according to the heat center drift track of the electricity utilization map.
4. The method of claim 1, wherein the grid safe operation boundary comprises an upper limit of transformer capacity ratio, a line voltage deviation range and a short circuit current verification limit.
5. The method for optimizing an enterprise business layout according to claim 1, wherein the step of obtaining the power business multisource base data comprises: acquiring client-side time-sharing electricity consumption information and service evaluation data through an electric power marketing management system interface; Acquiring real-time power flow direction and equipment load rate data of a power grid side through a dispatching automation system; and acquiring position information of the emergency repair vehicle at the operation and maintenance side and stock data of spare parts through the production management system.
6. The method for optimizing an enterprise business layout according to claim 1, wherein for the emergency repair resource scheduling layout, the constructing a power business layout multi-objective optimization model includes: analyzing the time-space distribution characteristics of historical faults in the actual measurement data of the power production operation and maintenance, and establishing a fault probability density field; Calculating the average rush-repair time length under different traffic conditions, and constructing a rush-repair resource efficiency evaluation function by combining the professional skill level of the rush-repair team; and (3) optimizing the position of the repair residence point and the configuration scale of the repair team in each residence point by taking the shortest fault average repair time as a target, and realizing the dynamic adaptation of the repair resource and the power grid risk distribution.
7. The method of claim 6, wherein the dynamically adapting includes automatically increasing a risk weight of the local area in the emergency repair resource effectiveness evaluation function and generating an emergency repair resource pre-modeling and defense arrangement scheme when an extreme weather disaster early warning is detected in the local area.
8. The enterprise business layout optimization method of claim 1, wherein the dynamic optimization iterations comprise: Setting an evaluation period of a layout scheme, and comparing deviation values of actual operation indexes and expected targets after service layout optimization at the end of each evaluation period; And if the deviation value exceeds the preset threshold value, remolding the proportionality coefficient of the objective function by utilizing a negative feedback regulation algorithm, and triggering model recalculation.
9. The method of claim 1, wherein outputting the business layout optimization decision instruction comprises outputting a marketing site migration advice list, a rush-repair team cross-zone scheduling path plan, and a spare part center inventory replenishment plan.
10. An enterprise business layout optimization system comprising a plurality of functional modules configured to perform the enterprise business layout optimization method of any of claims 1-9, said functional modules comprising at least: the data acquisition module is used for acquiring the multi-source basic data of the power service; The model construction module is used for constructing a power service layout multi-objective optimization model; The initial planning module is used for solving and generating an initial service layout planning scheme; and the dynamic iteration module is used for monitoring the running state of the power grid and feeding back service response in real time, carrying out dynamic optimization iteration on the power service layout multi-objective optimization model and outputting a service layout optimization decision instruction.

Description

Enterprise business layout optimization system and method Technical Field The application relates to the technical field of power business management and resource optimization, in particular to an enterprise business layout optimization system and method. Background With the deep promotion of energy Internet construction, an electric power enterprise is transformed from a traditional planning type production mode to a comprehensive service mode taking a customer as a center and taking power grid safety as a basis, and under the environment of a novel electric power system, the source network and the load storage are highly interactive, the customer demands tend to be diversified, and the electric power enterprise needs to be optimized through scientific service layout, so that the overall efficiency of the electric power enterprise in the service fields of power grid operation, marketing service, emergency repair and the like is improved. In the prior art, the power business layout generally adopts a method based on static planning, for example, the fixed site selection of a transformer substation or a marketing network point is determined through average load increase data of historical years, or an optimization model is built by utilizing a single economic index such as investment construction cost minimization, and part of the prior art refers to patents such as a power network point static site selection method based on a geographic information system, and the logic of the method is that resource allocation is carried out through a preset administrative division. However, the prior art has obvious technical defects in practical application, the first aspect is characterized in that the rapid change of dynamic load of a power grid cannot be adapted, the static layout scheme is difficult to match with the non-uniform distribution of the power load in the space-time dimension, so that part of network point resources are idle and part of regional service is overloaded, the second aspect is characterized in that data among service systems has a chimney structure, marketing and operation and maintenance resources lack of coordination, the resource utilization rate is low, and the response speed and the accuracy are difficult to meet the operation requirements of a modern power grid when the sudden fault or large-scale power load fluctuation is faced. Disclosure of Invention The application aims to provide an enterprise business layout optimization method which comprises the steps of obtaining power business multi-source basic data, wherein the power business multi-source basic data comprise power grid topological structure data, power marketing full-caliber business data and power production operation and maintenance actual measurement data, constructing a power business layout multi-target optimization model, taking operation cost minimization, resource coverage maximization and power supply reliability index optimization of each power business module as target functions, presetting a power grid safe operation boundary and business processing time limit as constraint conditions, carrying out parameter initialization on the power business layout multi-target optimization model based on the power business multi-source basic data, solving and generating an initial business layout planning scheme, monitoring power grid operation state and business response feedback in real time, carrying out dynamic weight adjustment and parameter correction on the power business layout multi-target optimization model according to a power grid load dynamic change curve and business work order saturation, carrying out dynamic optimization iteration through a closed loop feedback mechanism, and outputting business layout optimization decision instructions. By adopting the technical scheme, the multi-source data fusion and dynamic closed-loop feedback mechanism is adopted, so that the service layout scheme can respond to power grid load fluctuation and service demand change in real time, the timeliness and adaptability of decision making are improved, in addition, a multi-objective optimization model integrating operation cost, resource coverage rate and power supply reliability is constructed, and clear safety and time limit constraint are preset, so that the final layout scheme can realize systematic balance and integral optimization of a plurality of core service indexes on the premise of ensuring power grid safety and service quality, and the comprehensive efficiency of resource utilization is improved. The method comprises the steps of establishing a power business layout multi-target optimization model, wherein the power business layout multi-target optimization model comprises the steps of extracting power consumer geographic space distribution characteristics and historical report connection electricity quantity in power marketing full-caliber business data, establishing a nonlinear mapping relation between marketing servic