Power grid technical improvement and overhaul project management and material management and control method

Abstract

The invention relates to a power grid technical improvement and overhaul project management and material management and control method. The method comprises the following steps: collecting and preprocessing power equipment data and environmental data; constructing a power equipment scoring model, scoring the power equipment through the preprocessed data, sorting the technical renovation and overhaul priorities of the power equipment according to a scoring result, and performing the technical renovation and overhaul of the power equipment according to the priorities; power grid storage data are collected and preprocessed; and constructing a material dynamic scheduling model, and planning a transportation path of materials through the preprocessed power grid storage data and power equipment data.

Description

Technical Field

[0001] The present invention relates to a power grid technical renovation and overhaul project management and material control method, which belongs to the field of electric power technology. Background Art

[0002] With the advancement of digital transformation in the power industry, the management mode of technical transformation and overhaul projects is gradually changing from traditional manual experience-driven to data-driven. The current technical status mainly includes the following points:

[0003] Initial realization of digital management: some power grid companies have launched full-process project management systems, covering demand generation, project planning, implementation and settlement; material management has gradually been electronicized, but the degree of coordination with project needs is low.

[0004] Demand for lean and intelligent management: The management of technical transformation and overhaul projects is transitioning from extensive to lean, which puts forward higher requirements for online, standardized and intelligent management; the full life cycle management of projects and equipment has gradually become the focus of industry attention.

[0005] Although the existing system has achieved digitization to a certain extent, it still has obvious deficiencies in management accuracy, intelligence level and full-process collaboration, as shown in the following:

[0006] Equipment health status assessment lacks scientific basis and is still mainly based on manual experience.

[0007] The determination of technical transformation and overhaul needs is delayed, making it difficult to match actual operating conditions in a timely manner.

[0008] There is a low correlation between materials and equipment, and there is a lack of connection between procurement, transportation, storage and use.

[0009] There is a lack of intelligent analysis and dynamic adjustment capabilities for material inventory and usage efficiency. Summary of the invention

[0010] In order to solve the above problems existing in the prior art, the present invention proposes a power grid technical transformation and overhaul project management and material control method.

[0011] The technical solution of the present invention is as follows:

[0012] On the one hand, the present invention provides a method for power grid technical renovation and overhaul project management and material control, comprising the following steps:

[0013] Collect power equipment data and environmental data and pre-process them;

[0014] Construct a power equipment scoring model to score the power equipment through preprocessed data, sort the priorities of technical renovation and overhaul of the power equipment according to the scoring results, and perform technical renovation and overhaul of the power equipment according to the priorities;

[0015] Collect power grid storage data and pre-process it;

[0016] Construct a dynamic material scheduling model to plan the transportation route of materials through pre-processed power grid storage data and power equipment data.

[0017] As a preferred embodiment of the present invention, the power equipment scoring model F(x) is specifically shown as follows:

[0018]

[0019] Where: R(x) represents the status score of power equipment x; C(x) represents the technical renovation and overhaul cost of power equipment x; L(x) represents the remaining life ratio of power equipment x; w 1 、w 2 、w 3 They represent weight parameters respectively.

[0020] As a preferred embodiment of the present invention, the material dynamic scheduling model is based on the vehicle transportation path optimization problem between the power equipment and the warehouse to minimize the transportation cost Z to construct an objective function, as shown in the following formula:

[0021]

[0022] Where: C ij represents the transportation cost between power equipment i and warehouse j; x ij represents the decision variable between power equipment i and warehouse j; H j represents the operating cost of warehouse j; I represents the number of power equipment; J represents the number of warehouses;

[0023] The construction constraints are as follows:

[0024]

[0025] Where: Q j Represents the total amount of materials in warehouse j.

[0026] As a preferred embodiment of the present invention, a full life cycle cost prediction model for power equipment is constructed, which is specifically shown in the following formula:

[0027]

[0028] Where: T cost Represents the life cycle cost of power equipment; C op (t) represents the operating cost of the power equipment in year t; C mqint (t) represents the maintenance cost of power equipment in year t; C repalce Represents the replacement cost of power equipment at the end of its life;

[0029] The full life cycle cost of power equipment is predicted through the power equipment full life cycle cost prediction model, and the equipment investment decision of the power grid is made based on the full life cycle cost of the power equipment.

[0030] On the other hand, the present invention also provides a power grid technical transformation and overhaul project management and material control system, including a power equipment data acquisition module, a power equipment priority sorting module, a power grid storage data acquisition module, and a material path planning module;

[0031] The power equipment data acquisition module is used to collect power equipment data and environmental data and perform preprocessing;

[0032] The power equipment priority sorting module is used to construct a power equipment scoring model to score the power equipment through the preprocessed data, sort the priorities of the technical transformation and overhaul of the power equipment according to the scoring results, and perform the technical transformation and overhaul of the power equipment according to the priority;

[0033] The power grid storage data acquisition module is used to collect power grid storage data and perform preprocessing;

[0034] The material route planning module is used to construct a material dynamic scheduling model to plan the transportation route of materials through pre-processed power grid storage data and power equipment data.

[0035] As a preferred embodiment of the present invention, the power equipment scoring model F(x) is specifically shown as follows:

[0036]

[0037] Where: R(x) represents the status score of power equipment x; C(x) represents the technical renovation and overhaul cost of power equipment x; L(x) represents the remaining life ratio of power equipment x; w 1 、w 2 、w 3 They represent weight parameters respectively.

[0038] As a preferred embodiment of the present invention, the material dynamic scheduling model is based on the vehicle transportation path optimization problem between the power equipment and the warehouse to minimize the transportation cost Z to construct an objective function, as shown in the following formula:

[0039]

[0040] Where: C ij represents the transportation cost between power equipment i and warehouse j; x ij represents the decision variable between power equipment i and warehouse j; H j represents the operating cost of warehouse j; I represents the number of power equipment; J represents the number of warehouses;

[0041] The construction constraints are as follows:

[0042]

[0043] Where: Q j Represents the total amount of materials in warehouse j.

[0044] As a preferred embodiment of the present invention, the system further includes an equipment investment decision module, which is used to construct a full life cycle cost prediction model for power equipment, as shown in the following formula:

[0045]

[0046] Where: T cost Represents the life cycle cost of power equipment; C op (t) represents the operating cost of the power equipment in year t; C maint (t) represents the maintenance cost of power equipment in year t; C repalce Represents the replacement cost of power equipment at the end of its life;

[0047] The full life cycle cost of power equipment is predicted through the power equipment full life cycle cost prediction model, and the equipment investment decision of the power grid is made based on the full life cycle cost of the power equipment.

[0048] On the other hand, the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any embodiment of the present invention when executing the program.

[0049] In yet another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any embodiment of the present invention.

[0050] The present invention has the following beneficial effects:

[0051] 1. The present invention uses a panoramic equipment history and health scoring model to fully grasp the equipment status and generate accurate technical improvement / overhaul requirements.

[0052] 2. The present invention introduces a multi-objective optimization algorithm and a vehicle path optimization model to solve complex decision-making problems such as material scheduling and project priority sorting. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] It should be understood that the step numbers used in this document are only for convenience of description and are not intended to limit the order in which the steps are executed.

[0056] It should be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0057] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0058] The term "and / or" means and includes any and all possible combinations of one or more of the associated listed items.

[0059] Embodiment 1:

[0060] See also Figure 1 , a power grid technical transformation and overhaul project management and material control method, comprising the following steps:

[0061] Collect power equipment data and environmental data and pre-process them;

[0062] Construct a power equipment scoring model to score the power equipment through preprocessed data, sort the priorities of technical renovation and overhaul of the power equipment according to the scoring results, and perform technical renovation and overhaul of the power equipment according to the priorities;

[0063] Collect power grid storage data and pre-process it;

[0064] Construct a dynamic material scheduling model to plan the transportation route of materials through pre-processed power grid storage data and power equipment data.

[0065] As a preferred implementation of this embodiment, the power equipment scoring model F(x) is specifically shown in the following formula:

[0066]

[0067] Where: R(x) represents the status score of power equipment x; C(x) represents the technical renovation and overhaul cost of power equipment x; L(x) represents the remaining life ratio of power equipment x; w 1 、w 2 、w 3 Respectively represent weight parameters;

[0068]

[0069] Where: S n Indicates the nth status indicator (such as failure rate, operating life); n represents weight;

[0070]

[0071] Where: C init It represents the initial cost of technical renovation and overhaul;

[0072]

[0073] Where: L exp Indicates the design life or technical life of the equipment. Usually provided by the equipment manufacturer based on design parameters and standard operating conditions, such as the design life of a transformer is 25 years; used Indicates the time (or accumulated load) that the equipment has been used in actual operation. This value can be estimated by the difference between the installation date and the current time, or the accumulated workload in the operation record;

[0074] As a preferred implementation of this embodiment, the material dynamic scheduling model is based on the vehicle transportation path optimization problem between the power equipment and the warehouse to minimize the transportation cost Z to construct an objective function, as shown in the following formula:

[0075]

[0076] Where: C ij represents the transportation cost between power equipment i and warehouse j; x ij represents the decision variable between power equipment i and warehouse j; H j represents the operating cost of warehouse j; I represents the number of power equipment; J represents the number of warehouses;

[0077] The construction constraints are as follows:

[0078]

[0079] Where: Q j Represents the total amount of materials in warehouse j.

[0080] As a preferred implementation of this embodiment, a full life cycle cost prediction model for power equipment is constructed, as shown in the following formula:

[0081]

[0082] Where: T cost Represents the life cycle cost of power equipment; C op (t) represents the operating cost of the power equipment in year t; C maint (t) represents the maintenance cost of power equipment in year t; C repalce Represents the replacement cost of power equipment at the end of its life;

[0083] The full life cycle cost of power equipment is predicted through the power equipment full life cycle cost prediction model, and the equipment investment decision of the power grid is made based on the full life cycle cost of the power equipment.

[0084] Embodiment 2:

[0085] A power grid technical renovation and overhaul project management and material control system, including a power equipment data acquisition module, a power equipment priority sorting module, a power grid storage data acquisition module, and a material path planning module;

[0086] The power equipment data acquisition module is used to collect power equipment data and environmental data and perform preprocessing;

[0087] The power equipment priority sorting module is used to construct a power equipment scoring model to score the power equipment through the preprocessed data, sort the priorities of the technical transformation and overhaul of the power equipment according to the scoring results, and perform the technical transformation and overhaul of the power equipment according to the priority;

[0088] The power grid storage data acquisition module is used to collect power grid storage data and perform preprocessing;

[0089] The material route planning module is used to construct a material dynamic scheduling model to plan the transportation route of materials through pre-processed power grid storage data and power equipment data.

[0090] As a preferred implementation of this embodiment, the power equipment scoring model F(x) is specifically shown in the following formula:

[0091]

[0092] Where: R(x) represents the status score of power equipment x; V(x) represents the technical renovation and overhaul cost of power equipment x; L(x) represents the remaining life ratio of power equipment x; w 1 、w 2 、w 3 They represent weight parameters respectively.

[0093] As a preferred implementation of this embodiment, the material dynamic scheduling model is based on the vehicle transportation path optimization problem between the power equipment and the warehouse to minimize the transportation cost Z to construct an objective function, as shown in the following formula:

[0094]

[0095] Where: C ij represents the transportation cost between power equipment i and warehouse j; x ij represents the decision variable between power equipment i and warehouse j; H j represents the operating cost of warehouse j; I represents the number of power equipment; J represents the number of warehouses;

[0096] The construction constraints are as follows:

[0097]

[0098] Where: Q j Represents the total amount of materials in warehouse j.

[0099] As a preferred implementation of this embodiment, the system further includes an equipment investment decision module, which is used to construct a full life cycle cost prediction model for power equipment, as shown in the following formula:

[0100]

[0101] Where: T cost Represents the life cycle cost of power equipment; C op (t) represents the operating cost of the power equipment in year t; C maint (t) represents the maintenance cost of power equipment in year t; C repalce Represents the replacement cost of power equipment at the end of its life;

[0102] The full life cycle cost of power equipment is predicted through the power equipment full life cycle cost prediction model, and the equipment investment decision of the power grid is made based on the full life cycle cost of the power equipment.

[0103] In this embodiment, the system is built on a cloud platform, and the system login permission is obtained by accessing the unified permission authentication and business organization role authorization. The user password mode of the oauth2.0 authentication system is adopted, and the application is registered through the business middle-end operation management system. After registration, the unique access appid and key are obtained for middle-end access permission authentication. In terms of application security, the gateway in the microservice is used to provide the only entry method for system access. It receives external requests, forwards and routes to the back-end microservices, and realizes the routing and load balancing of service requests. The gateway is the only entry for internal services, and the control of login authentication and authorization is performed on the gateway, and the function of centralized management of user sessions is provided. Login authentication and authentication are implemented through interceptor technology. The permission interceptor obtains all front-end requests, and determines whether the current URL needs login authentication and authentication based on pattern matching. If there is no authentication information in the session, it jumps to the unified authentication service login authentication. After login authentication, the permission of the fine-grained URL needs to be determined according to "role-resource-authority". The gateway records the login authentication data in the centralized session, and the downstream microservices can obtain the currently logged-in user and organization data through the centralized session. In terms of host security, the operating system (Linux system) and database system of the required servers (including virtual machines) are deployed in the telecommunications computer room of the Fujian Provincial Company. The telecommunications company is responsible for security management and performs protection in accordance with national and company network security protection requirements. In terms of data security, the HTTPS protocol is used to encrypt important business data to ensure the confidentiality and integrity of the transmission channel. The data is stored in the database and is prohibited from being stored in other areas of the server or on the client. The data itself uses the SM4 encryption algorithm to ensure the confidentiality of transmission. When sensitive data is involved, differentiated desensitization is performed according to user roles and permissions, and corresponding page digital watermarks are added;

[0104] The standard specifications of the system are as follows:

[0105]

[0106]

[0107] Embodiment three:

[0108] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any embodiment of the present invention when executing the program.

[0109] Embodiment 4:

[0110] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method described in any embodiment of the present invention is implemented.

[0111] In the embodiments of the present application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can be represented by: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, c can be single or multiple.

[0112] Those of ordinary skill in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented in a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0113] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0114] In several embodiments provided in the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory; hereinafter referred to as: ROM), random access memory (Random Access Memory; hereinafter referred to as: RAM), disk or optical disk, and other media that can store program codes.

[0115] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for power grid technical renovation and overhaul project management and material control, characterized in that: The following steps are involved: Collect power equipment data and environmental data and pre-process them; Construct a power equipment scoring model to score the power equipment through preprocessed data, sort the priorities of technical renovation and overhaul of the power equipment according to the scoring results, and perform technical renovation and overhaul of the power equipment according to the priorities; Collect power grid storage data and pre-process it; Construct a dynamic material scheduling model to plan the transportation route of materials through pre-processed power grid storage data and power equipment data.

2. A method for power grid technical renovation and overhaul project management and material control according to claim 1, characterized in that: The power equipment scoring model F(x) is specifically shown in the following formula: Where: R(x) represents the status score of power equipment x; V(x) represents the technical transformation and overhaul cost of power equipment x; L(x) represents the remaining life ratio of power equipment x; w1, w2, and w3 represent weight parameters respectively.

3. A method for power grid technical renovation and overhaul project management and material control according to claim 1, characterized in that: The material dynamic scheduling model is based on the vehicle transportation path optimization problem between power equipment and warehouses, and constructs the objective function by minimizing the transportation cost Z, as shown in the following formula: Where: C ij represents the transportation cost between power equipment i and warehouse j; x ij represents the decision variable between power equipment i and warehouse j; H j represents the operating cost of warehouse j; I represents the number of power equipment; J represents the number of warehouses; The construction constraints are as follows: Where: Q j Represents the total amount of materials in warehouse j.

4. A method for power grid technical renovation and overhaul project management and material control according to claim 1, characterized in that: Construct a cost prediction model for the entire life cycle of power equipment, as shown in the following formula: Where: T cost Represents the life cycle cost of power equipment; C op (t) represents the operating cost of the power equipment in year t; C maint (t) represents the maintenance cost of power equipment in year t; C repalce Represents the replacement cost of power equipment at the end of its life; The full life cycle cost of power equipment is predicted through the power equipment full life cycle cost prediction model, and the equipment investment decision of the power grid is made based on the full life cycle cost of the power equipment.

5. A power grid technical renovation and overhaul project management and material control system, characterized in that: It includes power equipment data collection module, power equipment priority sorting module, power grid storage data collection module and material route planning module; The power equipment data acquisition module is used to collect power equipment data and environmental data and perform preprocessing; The power equipment priority sorting module is used to construct a power equipment scoring model to score the power equipment through the preprocessed data, sort the priority of technical renovation and overhaul of the power equipment according to the scoring results, and perform technical renovation and overhaul of the power equipment according to the priority; The power grid storage data acquisition module is used to collect power grid storage data and perform preprocessing; The material route planning module is used to construct a material dynamic scheduling model to plan the transportation route of materials through pre-processed power grid storage data and power equipment data.

6. A power grid technical renovation and overhaul project management and material control system according to claim 5, characterized in that: The power equipment scoring model F(x) is specifically shown in the following formula: Where: R(x) represents the status score of power equipment x; C(x) represents the technical transformation and overhaul cost of power equipment x; L(x) represents the remaining life ratio of power equipment x; w1, w2, and w3 represent weight parameters respectively.

7. A power grid technical renovation and overhaul project management and material control system according to claim 5, characterized in that: The material dynamic scheduling model is based on the vehicle transportation path optimization problem between power equipment and warehouses, and constructs the objective function by minimizing the transportation cost Z, as shown in the following formula: Where: C ij represents the transportation cost between power equipment i and warehouse j; x ij represents the decision variable between power equipment i and warehouse j; H j represents the operating cost of warehouse j; I represents the number of power equipment; J represents the number of warehouses; The construction constraints are as follows: Where: Q j Represents the total amount of materials in warehouse j.

8. A method for power grid technical renovation and overhaul project management and material control according to claim 5, characterized in that: The system also includes an equipment investment decision module, which is used to construct a full life cycle cost prediction model for power equipment, as shown in the following formula: Where: T cost Represents the life cycle cost of power equipment; C op (t) represents the operating cost of the power equipment in year t; C maint (t) represents the maintenance cost of power equipment in year t; C repalce Represents the replacement cost of power equipment at the end of its life; The full life cycle cost of power equipment is predicted through the power equipment full life cycle cost prediction model, and the equipment investment decision of the power grid is made based on the full life cycle cost of the power equipment.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 4 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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