CN116595762A

CN116595762A - Low-carbon power grid equipment selection determination method considering energy-saving benefit

Info

Publication number: CN116595762A
Application number: CN202310562910.8A
Authority: CN
Inventors: 陈晖�; 杨至元; 李沛
Original assignee: Energy Development Research Institute of China Southern Power Grid Co Ltd
Current assignee: Energy Development Research Institute of China Southern Power Grid Co Ltd
Priority date: 2023-05-17
Filing date: 2023-05-17
Publication date: 2023-08-15

Abstract

The application relates to a low-carbon power grid equipment type selection determination method considering energy-saving benefits. The method comprises the following steps: acquiring a full life cycle energy consumption model of a power grid to be planned; the full life cycle energy consumption model comprises an equipment energy consumption model, a project energy consumption model and a system energy consumption model; determining a power grid parameter model of the power grid to be planned according to the equipment energy consumption model, the project energy consumption model and the system energy consumption model respectively, and determining candidate equipment selection types of the power grid to be planned according to the power grid parameter model; the power grid parameter model comprises at least one of an item effective energy-saving model, an item future period average energy consumption rate model, a system energy consumption capacity ratio model and a system energy consumption index per unit model; and determining an energy consumption parameter corresponding to the candidate equipment type, and determining the target equipment type of the power grid to be planned from the candidate equipment type according to the energy consumption parameter. By adopting the method, the energy consumption of the power grid can be effectively reduced.

Description

Low-carbon power grid equipment selection determination method considering energy-saving benefit

Technical Field

The application relates to the technical field of smart grids, in particular to a low-carbon power grid equipment type selection determining method considering energy-saving benefits.

Background

The construction of the energy-saving low-carbon power grid is an inherent requirement for realizing low carbonization development in the power industry, and the energy-saving carbon reduction requires the power grid to improve the production, conversion, transmission and use efficiency of energy sources, thereby being beneficial to reducing the operation cost of a power system and the operation cost of the power grid and improving the economic efficiency of enterprises.

The power grid has larger energy saving potential in planning, construction stage and running level, the power grid enterprise belongs to capital-intensive enterprises, the fixed equipment has large specific gravity, the regional distribution is wide, the range is large, the service life period is long, and the enterprise operation activity is targeted at minimizing the cost and maximizing the profit. When the reduced cost is consistent with energy conservation, the power grid enterprise can perform business activity excitation aiming at energy conservation. However, when there is inconsistency between the cost reduction and the energy saving, the energy saving as a positive external effect may not be guaranteed, and it is difficult to effectively reduce the power consumption of the power grid through reasonable planning construction.

Therefore, the current power grid planning technology has the problem that the energy consumption of the power grid is difficult to effectively reduce.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a method, an apparatus, a computer device, a computer readable storage medium, and a computer program product for determining a type selection of a low-carbon power grid device, which can effectively reduce power consumption of the power grid and consider energy saving benefits.

In a first aspect, the application provides a low-carbon power grid equipment type selection determination method considering energy-saving benefits. The method comprises the following steps:

acquiring a full life cycle energy consumption model of a power grid to be planned; the full life cycle energy consumption model comprises an equipment energy consumption model, a project energy consumption model and a system energy consumption model;

determining a power grid parameter model of the power grid to be planned according to the equipment energy consumption model, the project energy consumption model and the system energy consumption model respectively, and determining candidate equipment selection types of the power grid to be planned according to the power grid parameter model; the power grid parameter model comprises at least one of an item effective energy-saving model, an item future period average energy consumption rate model, a system energy consumption capacity ratio model and a system energy consumption index per unit model;

and determining an energy consumption parameter corresponding to the candidate equipment type, and determining the target equipment type of the power grid to be planned from the candidate equipment type according to the energy consumption parameter.

In a second aspect, the application also provides a low-carbon power grid equipment model selection determining device considering energy saving benefits. The device comprises:

the energy consumption model acquisition module is used for acquiring a full life cycle energy consumption model of the power grid to be planned; the full life cycle energy consumption model comprises an equipment energy consumption model, a project energy consumption model and a system energy consumption model;

The candidate equipment type selection module is used for determining a power grid parameter model of the power grid to be planned according to the equipment energy consumption model, the project energy consumption model and the system energy consumption model respectively, and determining candidate equipment type selection of the power grid to be planned according to the power grid parameter model; the power grid parameter model comprises at least one of an item effective energy-saving model, an item future period average energy consumption rate model, a system energy consumption capacity ratio model and a system energy consumption index per unit model;

and the target equipment type selection module is used for determining the energy consumption parameter corresponding to the candidate equipment type selection, and determining the target equipment type selection of the power grid to be planned from the candidate equipment type selection according to the energy consumption parameter.

In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor which when executing the computer program performs the steps of:

In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:

In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of:

The method, the device, the computer equipment, the storage medium and the computer program product for determining the equipment model selection of the low-carbon power grid, which consider the energy-saving benefit, determine a power grid parameter model of the power grid to be planned according to the equipment energy consumption model, the project energy consumption model and the system energy consumption model respectively by acquiring the full life cycle energy consumption model of the power grid to be planned, determine candidate equipment model selection of the power grid to be planned according to the power grid parameter model, determine energy consumption parameters corresponding to the candidate equipment model selection, and determine a target equipment model selection of the power grid to be planned from the candidate equipment model selection according to the energy consumption parameters; in the power grid planning process, the power grid planning system, all projects and all devices in the power grid planning system are simulated based on the full life cycle energy consumption model, the candidate device type which enables the power grid parameters to be optimal is obtained, then the target device type which enables the energy consumption parameters to be minimum is determined from the candidate device type, and the obtained target device type can effectively reduce the power grid energy consumption while meeting the power grid parameters.

Drawings

FIG. 1 is a schematic flow chart of a method for determining the type selection of low-carbon power grid equipment in one embodiment;

FIG. 2 is a flow chart of a method for evaluating a low-carbon power grid planning scheme in one embodiment;

FIG. 3 is a schematic diagram of a device-level full lifecycle energy consumption model, in one embodiment;

FIG. 4 is a schematic diagram of an item level full lifecycle energy consumption model, in one embodiment;

FIG. 5 is a schematic diagram of a system level full lifecycle energy consumption model, in one embodiment;

FIG. 6 is a wiring diagram of an IEEE RTS 24 node test system in one embodiment;

FIG. 7 is a diagram of multi-scenario operating power consumption versus graph in one embodiment;

FIG. 8 is a block diagram of a low-carbon power grid equipment type selection determining device in one embodiment;

fig. 9 is an internal structural diagram of a computer device in one embodiment.

Detailed Description

The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.

In one embodiment, as shown in fig. 1, a method for determining a type of low-carbon power grid equipment considering energy-saving benefit is provided, and this embodiment is illustrated by applying the method to a terminal, it can be understood that the method can also be applied to a server, and can also be applied to a system including the terminal and the server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes the steps of:

Step S110, a full life cycle energy consumption model of a power grid to be planned is obtained; the full life cycle energy consumption model comprises a device energy consumption model, a project energy consumption model and a system energy consumption model.

The system energy consumption model may be a system-level full life cycle energy consumption analysis model of the power grid to be planned, for example, a power grid system.

The project energy consumption model can be a project-level full life cycle energy consumption analysis model of the power grid to be planned.

The equipment energy consumption model can be an equipment-level full life cycle energy consumption analysis model of the power grid to be planned.

In a specific implementation, the equipment energy consumption model, the project energy consumption model and the system energy consumption model of the power grid to be planned can be stored in the terminal, so that the terminal obtains the full life cycle energy consumption model of the power grid to be planned.

In practical application, the equipment-level full Life Cycle Energy Consumption (LCEC) _E ) The analytical model can be decomposed into ECI (construction investment energy consumption), ECO (equipment operation energy consumption), ECM (maintenance overhaul energy consumption), ECF (trouble shooting energy consumption) and ECD (scrapped retirement energy consumption), namely

LCEC _E ＝ECI+ECO+ECM+ECF+ECD，

The ECI can be divided into manufacturing energy consumption ECIm and installation and debugging energy consumption ECIi. Wherein ECIm can be decomposed into: the energy consumption of equipment production, the energy consumption of special tools, the energy consumption of spare parts preparation, the energy consumption of field service, the energy consumption of transportation of suppliers and the energy consumption of configuration of a state detection device. ECIi can be decomposed into: the energy consumption of the transportation of the owner, the energy consumption of the construction and installation of equipment, the energy consumption of debugging and the energy consumption of special tests.

Wherein, the ECO can be decomposed into the device body energy consumption ECO i and the auxiliary device energy consumption ECO a. The energy consumption of the equipment body is the loss when the equipment is operated, for example, the energy consumption of the equipment body of the transformer is the sum of copper loss and iron loss, and the energy consumption of the auxiliary equipment is the loss when the auxiliary equipment is operated. The energy consumption of the device itself can be determined by means of the load data at that time in the past life cycle of the device, and can be estimated by means of load prediction in the future life cycle. Thus can obtain

Wherein P is _LCi Representing the power loss, t, of the device during the ith typical operating period _i Representing the run time of the device at this typical time period.

The ECM may be split into split service energy consumption ECMd and regular maintenance energy consumption ECMr, among other things. The energy consumption of disassembly overhaul is considered for equipment needing disassembly overhaul, and the energy consumption of disassembly overhaul is not considered for equipment needing no disassembly overhaul, and the conventional maintenance energy consumption refers to the energy consumption of regular overhaul, minor overhaul, preventive test and the like of the current power grid equipment.

Wherein, ECF can be decomposed into failure maintenance energy consumption ECFr and failure loss energy consumption ECFl. Wherein ECFr can be decomposed into: and the energy consumption of fault field treatment and the energy consumption of equipment factory return repair. ECFl can be broken down into customer indirect energy consumption expectations and equipment operation parasitic loss expectations. The user indirect energy consumption expectation refers to the product of the indirect energy consumption brought by the user with the fault occurrence and the probability of the fault occurrence, and the calculation formula can be that

E＝a _u E _u ，

In E _u Representing the user indirect energy consumption caused by faults, a _u Indicating the probability of this failure.

The additional loss expected of the equipment operation refers to the expected that the equipment fails and generates additional loss in the later life cycle, and the calculation formula can be that

E＝a _e t _r ΔP _L ，

In DeltaP _L Indicating the extra power loss of operation after a device failure, t _r Representing the run time in the remaining life cycle of the device, a _e Indicating the probability of this failure.

Wherein the ECD can be decomposed into a reject energy ECDs and a final process energy ECDt. ECDs represent the energy consumption caused by the dismantling and transport of the equipment near the end of its life cycle. ECDt represents the energy consumption incurred in the process of being completely discarded or regenerating usable material after the equipment is scrapped and transported to a designated recycling site.

Project level full lifecycle energy consumption (LCEC) _P ) The analytical model can be decomposed into ECI, ECO, ECM, ECF, ECD and Σlcec' (equipment-level full life cycle energy consumption minus equipment operation energy consumption in the project), i.e.

LCEC _P ＝ECI+ECO+ECM+ECF+ECD+∑LCEC′。

Wherein ECI comprises infrastructure material preparation energy consumption and infrastructure energy consumption. ECO means the energy consumption of the operation of the whole project, including the operation loss of all the devices in the project. Future operating conditions of the project may be predicted. The ECM is project maintenance energy consumption and does not include equipment maintenance energy consumption in the project. ECF is project fault energy consumption and does not contain equipment fault energy consumption in the project. ECD is project retirement energy consumption, and does not contain equipment failure energy consumption in the project. Σlcec' is the full life cycle energy consumption of all the devices in the project minus the operating energy consumption.

Full Life Cycle Energy Consumption (LCEC) at system level _S ) The analytical model can be decomposed into ECI, ECO, ECM, ECF, ECD and Σlcec "(device-level full life cycle energy consumption with device operation energy consumption subtracted from the system), i.e

LCEC _s ＝ECI+ECO+ECM+ECF+ECD+∑LCEC″。

Wherein ECI comprises infrastructure material preparation energy consumption and infrastructure energy consumption. ECO means the energy consumption of the overall system operation, including the operational losses of all devices in the system. Future operating conditions of the system may be derived based on the predictions. The ECM is an item maintenance energy consumption that does not include equipment maintenance energy consumption in the system. ECF is system failure energy consumption, without equipment failure energy consumption in the system. ECD is the energy consumption of the system retirement, without the equipment failure energy consumption in the system. Σlcec "is the full life cycle energy consumption with all devices in the system deducting the operating energy consumption.

Step S120, determining a power grid parameter model of a power grid to be planned according to the equipment energy consumption model, the project energy consumption model and the system energy consumption model, and determining candidate equipment selection types of the power grid to be planned according to the power grid parameter model; the power grid parameter model comprises at least one of an project effective energy saving model, an project future period average energy consumption rate model, a system energy consumption capacity ratio model and a system energy consumption index per unit model.

The candidate device type may be a candidate device type in the power grid planning.

In a specific implementation, a device energy consumption average model in a power grid parameter model can be determined according to the device energy consumption model, a device full life cycle energy consumption average value can be determined according to the device energy consumption average model, and a device model with the smallest device full life cycle energy consumption average value is determined as a first candidate device model; the method comprises the steps of determining a project energy consumption average value model in a power grid parameter model according to a project energy consumption model, determining a project full life cycle energy consumption average value according to the project energy consumption average value model, and determining a device model with the minimum project full life cycle energy consumption average value as a second candidate device model; the method comprises the steps of determining a project effective energy-saving energy model in a power grid parameter model according to a project energy-saving model, determining a project full life cycle energy consumption average value considering effective energy-saving energy according to the project effective energy-saving energy model, and determining a device type with the minimum project full life cycle energy consumption average value considering effective energy-saving energy as a third candidate device type; the project future period average energy consumption rate model in the power grid parameter model can be determined according to the project energy consumption model, the system full life period average energy consumption rate after a project scheme is considered can be determined according to the project future period average energy consumption rate model, and the equipment type with the minimum system full life period average energy consumption rate is determined as the fourth candidate equipment type; the system energy consumption capacity ratio model in the power grid parameter model can be determined according to the system energy consumption model, the full life cycle energy consumption capacity ratio of the system can be determined according to the system energy consumption capacity ratio model, and the equipment model with the minimum full life cycle energy consumption capacity ratio is determined as a fifth candidate equipment model; and the system energy consumption index per unit model in the power grid parameter model can be determined according to the system energy consumption model, the system per unit full life cycle energy consumption index can be determined according to the system energy consumption index per unit model, and the equipment type with the minimum system per unit full life cycle energy consumption index is determined as the sixth candidate equipment type.

The first, second, third, fourth, fifth and sixth candidate device types among the first candidate device type, the second candidate device type, the third candidate device type, the fourth candidate device type, the fifth candidate device type and the sixth candidate device type are only used for distinguishing different candidate device types, and do not represent the priority of the candidate device types.

In practical application, based on the full life cycle energy consumption model of the power grid to be planned, the device type selection and project effective energy saving amount of the stage and the average energy consumption rate of the future life cycle can be planned clearly.

Defining the device energy consumption average model as

LCEC in _E Representing the full life cycle energy consumption of the equipment, t _E Representing the full life cycle time length of the device,representing the full life cycle energy consumption average value of the equipment. Because the full life cycle energy consumption of different devices is different, the life cycle years are different, so that the full life cycle energy consumption of the devices cannot be considered only, and the full life cycle energy consumption average value of the devices can be considered at the moment. The energy consumption average index of the whole life cycle of the equipment represents the energy consumption of the average unit time length in the whole life cycle of the equipment. The index is mainly applicable to equipment type selection, and equipment-level type selection schemes with smaller energy consumption average values in the whole life cycle of equipment are selected preferentially.

Defining project energy consumption average model as

LCEC in _P Representing the full life cycle energy consumption of an item, t _p Representing the full life cycle time length of the item,and representing the full life cycle energy consumption average value of the project. Because the full life cycle energy consumption of different projects is different, the life cycle years are different, so that the full life cycle energy consumption of the projects cannot be considered only, and the full life cycle energy consumption average value of the projects can be considered at the moment. The energy consumption average index of the whole life cycle of the project represents the energy consumption of the average unit time length in the whole life cycle of the project. The index is mainly applied to project scheme selection, and the method should preferably select the project with smaller energy consumption average value in the whole life cycleItem level selection scheme.

The ideal energy saving amount of each period of the whole life cycle of the project is

In view of the fact that the project is not necessarily able to reach the lowest energy consumption level in each time period, it is possible to disable t _k Actual energy consumption E (t) _k ) Reduce to and t _k Reference energy consumption E of time period _b (t _k ) And are consistent. Thus, coefficients can be definedFor the energy-saving effectiveness ratio of each period of the project full life cycle, the energy-saving effectiveness ratio of the kth period is expressed as the proportion of the energy-saving energy to the ideal energy-saving energy, so that a project effective energy-saving energy model can be defined

Wherein, the liquid crystal display device comprises a liquid crystal display device,representing the effective energy saving amount of the project full life cycle, and further defining the project full life cycle energy consumption average value considering the effective energy saving amount as

The index is mainly used for project schemes. If the energy saving potential and the corresponding technical means of the project can be obtained in the project scheme comparison and selection stage, and effective estimation can be made on the energy saving energy of the whole life cycle in the future, the index can be applied in the project scheme comparison and selection, and the project-level selection scheme with smaller energy consumption average value of the whole life cycle of the project considering the effective energy saving energy can be selected preferentially.

Defining future period average energy consumption rate model of project as

Wherein E is _SC (t) is a system full life cycle energy consumption accumulation curve after considering a project scheme, E _SC (≡) means after considering only the project scheme the total energy consumption that the system can eventually accumulate,the time of the initial construction of the project is indicated,indicating the end time of the project discard->Representing the average energy consumption rate of future life cycles. And pre-evaluating the project according to the average energy consumption rate of the life cycle in the future. The operation mode of the whole system is influenced by the construction of the line and the transformer substations along the way, so that the influence of each scheme of the project on the system is required to be considered, and the molecules of the average energy consumption rate of the future life cycle represent the energy consumption of the future life cycle of the whole system after the construction of a certain scheme; since the lifecycle time length may be different for each item, the time span of the item also needs to be considered, so the denominator of the average energy consumption rate of the future lifecycle represents the item lifecycle time length. The average energy consumption rate of future life cycle characterizes the system energy loss of average unit time length in the whole life cycle of the project after the project is built. The index is mainly used for selecting project schemes, and project-level selection schemes with smaller average energy consumption rate in future life cycle should be selected preferentially when the schemes are selected.

The energy consumption capacity ratio model of the system is as follows

Wherein LCECs represents the full life cycle energy consumption of the system, S represents the capacity of the system, and k represents the full life cycle energy consumption capacity ratio. Different power grids have different capacities and also have different full life cycle energy consumption at the system level. Therefore, the comparison and evaluation of the power grid needs to comprehensively consider the full life cycle energy consumption of the power grid and the capacity of the system. The full life cycle energy consumption capacity ratio index characterizes the energy consumption corresponding to the unit system capacity, and a system level selection scheme with smaller full life cycle energy consumption capacity should be selected preferentially when the scheme is selected.

Defining a per-unit full life cycle energy consumption curve of a system

Wherein E (t) _k ) Is a full life cycle energy consumption curve, and EB is a basic value which should be selected by the power grid system. Accordingly, a system energy consumption index per unit model can be defined

Wherein B represents the per-unit full life cycle energy consumption parameter, and a system level selection scheme with smaller per-unit full life cycle energy consumption parameter should be preferentially selected when the scheme is selected.

And step S130, determining energy consumption parameters corresponding to the candidate equipment types, and determining the target equipment type of the power grid to be planned from the candidate equipment types according to the energy consumption parameters.

The energy consumption parameters include, but are not limited to, construction energy consumption parameters, operation and maintenance energy consumption parameters, fault energy consumption parameters and comprehensive energy consumption parameters.

The target device type can be a device type finally determined for power grid planning.

In a specific implementation, for the determined first candidate device type, second candidate device type, third candidate device type, fourth candidate device type, fifth candidate device type and sixth candidate device type, energy consumption parameters corresponding to the candidate device types can be determined, and according to the determined energy consumption parameters, a target device type is determined from the candidate device types, and the target device type is used as a planning scheme of a power grid to be planned. Specifically, the second candidate equipment selection type, the third candidate equipment selection type and the fourth candidate equipment selection type are candidate equipment selection types aiming at the project, and the target equipment selection type with the minimum energy consumption parameter is selected from the candidate equipment selection types; the fifth candidate equipment type and the sixth candidate equipment type are both candidate equipment types aiming at the system, and the target equipment type with the minimum energy consumption parameter is selected from the candidate equipment types.

In practical application, the investment energy consumption I, the operation and maintenance energy consumption R, the fault energy consumption F and the comprehensive energy consumption C can be determined according to each candidate equipment type, the total energy consumption index T corresponding to each candidate equipment type is obtained, and the candidate equipment type corresponding to the minimum value in the total energy consumption index T is determined as the target equipment type.

Wherein the calculation formula of the total energy consumption index T is as follows

T＝f _l (I)+f _R (R)+f _F (F)+f _C (C)，

Wherein f _I 、f _R 、f _F 、f _C The formula can be simplified into if the four indexes can be quantized into the energy consumption quantization indexes of the same dimension

T＝I+R+F+C，

For the index which can not be converted into energy consumption, the simplified processing mode can take the conversion function as a primary function, namely multiplying the calculated non-energy consumption quantization index by a certain weight coefficient, wherein the weight coefficient is as shown in the following formula

f _a (a)＝α·a，

Wherein a represents I, R, F or C index; alpha represents the coefficient of the index, and the qualitative analysis of the index satisfies the requirement that the time value is 1, and if the time value is not satisfied, 0 is obtained.

The comprehensive index C consists of three parts, namely unit newly-increased electric quantity energy consumption M, power generation right trading unit energy saving energy L and new energy power generation energy consumption ratio W.

f _C (C)＝f _M (M)+f _L (L)+f _W (W)，

Wherein M is the new electric quantity energy consumption of unit, its computational formula is: newly increased total energy consumption/newly increased power generation capacity of the power grid; l is the energy saving amount of the power generation right transaction unit, and the calculation formula is as follows: the power generation right replaces the energy consumption difference/power generation right transaction amount before and after; w is the power generation energy consumption ratio of the new energy, and the total power generation energy consumption of the new energy/the total power generation amount of the new energy in the statistical period. It should be noted that when the total time for new energy power generation is calculated, the total electric energy generated by the new energy power generation equipment in the operation time limit needs to be deducted, so as to embody the energy saving and emission reduction benefits brought by the renewable clean energy instead of the conventional fossil energy.

According to the method for determining the equipment type selection of the low-carbon power grid taking the energy-saving benefit into consideration, through obtaining the full life cycle energy consumption model of the power grid to be planned, the power grid parameter model of the power grid to be planned is determined according to the equipment energy consumption model, the project energy consumption model and the system energy consumption model, the candidate equipment type selection of the power grid to be planned is determined according to the power grid parameter model, the energy consumption parameters corresponding to the candidate equipment type selection are determined, and the target equipment type selection of the power grid to be planned is determined from the candidate equipment type selection according to the energy consumption parameters; in the power grid planning process, the power grid planning system, all projects and all devices in the power grid planning system are simulated based on the full life cycle energy consumption model, the candidate device type which enables the power grid parameters to be optimal is obtained, then the target device type which enables the energy consumption parameters to be minimum is determined from the candidate device type, and the obtained target device type can effectively reduce the power grid energy consumption while meeting the power grid parameters.

In one embodiment, the step S120 may specifically include: determining an item effective energy-saving energy model corresponding to the item energy consumption model; determining a project full life cycle energy consumption average value of a power grid to be planned according to the project effective energy-saving model; and determining candidate equipment types of the power grid to be planned according to the project full life cycle energy consumption average value.

In specific implementation, ideal energy conservation amount of each period of the full life cycle of the project

In view of the fact that the project is not necessarily able to reach the lowest energy consumption level in each time period, it is possible to disable t _k Actual energy consumption E (t) _k ) Reduce to and t _k Reference energy consumption E of time period _b (t _k ) In agreement, coefficients can be definedFor the energy-saving effectiveness ratio of each period of the project full life cycle, the energy-saving effectiveness ratio of the kth period is expressed as the proportion of the energy-saving energy to the ideal energy-saving energy, so that a project effective energy-saving energy model can be defined

When determining candidate device types of the power grid to be planned, the device type with the smallest project full life cycle energy consumption average value considering the effective energy saving amount can be selected as the candidate device type.

In the embodiment, an item effective energy saving model corresponding to an item energy consumption model is determined; determining a project full life cycle energy consumption average value of a power grid to be planned according to the project effective energy-saving model; according to the energy consumption average value of the whole life cycle of the project, candidate equipment types of the power grid to be planned are determined, and the equipment types can be selected according to the effective energy-saving energy of the whole life cycle of the project, so that the power grid energy consumption is effectively reduced.

In one embodiment, the step S120 may specifically further include: determining an average energy consumption model of a project future period corresponding to the project energy consumption model; obtaining the average energy consumption rate of the future life cycle of the power grid to be planned according to the average energy consumption model of the future period of the project; and determining candidate equipment types of the power grid to be planned according to the average energy consumption rate of the life cycle in the future.

In specific implementation, the future period average energy consumption rate model of the project can be determined as

Wherein E is _SC (t) is a system full life cycle energy consumption accumulation curve after considering a project scheme, E _SC (≡) means after considering only the project scheme the total energy consumption that the system can eventually accumulate,the time of the initial construction of the project is indicated,indicating the end time of the project discard->Representing the average energy consumption rate of future life cycles. The average energy consumption rate of the future life cycle represents the system energy consumption of the average unit time length in the whole life cycle of the project after the project is built, the project is pre-evaluated according to the average energy consumption rate of the future life cycle, and when the candidate equipment type of the power grid to be planned is determined, the equipment type with the minimum average energy consumption rate of the future life cycle can be selected as the candidate equipment type.

In the embodiment, an average energy consumption model of a project future period corresponding to the project energy consumption model is determined; obtaining the average energy consumption rate of the future life cycle of the power grid to be planned according to the average energy consumption model of the future period of the project; and determining candidate equipment types of the power grid to be planned according to the average energy consumption rate of the future life cycle, and carrying out equipment type selection according to the average energy consumption rate of the future life cycle, so that the energy consumption of the power grid is effectively reduced.

In one embodiment, the step S120 may specifically further include: determining a system energy consumption capacity ratio model corresponding to the system energy consumption model; determining the full life cycle energy consumption capacity ratio of the power grid to be planned according to the system energy consumption capacity ratio model; and determining candidate equipment types of the power grid to be planned according to the full life cycle energy consumption capacity ratio.

In specific implementation, the energy consumption and capacity ratio model of the system can be determined as

Wherein LCECs represents the full life cycle energy consumption of the system, S represents the capacity of the system, and k represents the full life cycle energy consumption capacity ratio. The full life cycle energy consumption capacity ratio index characterizes the energy consumption corresponding to the unit system capacity, the system is pre-evaluated according to the full life cycle energy consumption capacity ratio index, and when the candidate equipment type of the power grid to be planned is determined, the equipment type with the minimum full life cycle energy consumption capacity ratio can be selected to be used as the candidate equipment type.

In the embodiment, a system energy consumption capacity ratio model corresponding to a system energy consumption model is determined; determining the full life cycle energy consumption capacity ratio of the power grid to be planned according to the system energy consumption capacity ratio model; and determining candidate equipment type selection of the power grid to be planned according to the full life cycle energy consumption capacity ratio, and carrying out equipment type selection according to the full life cycle energy consumption capacity ratio so as to effectively reduce the power grid energy consumption.

In one embodiment, the step S120 may specifically further include: determining a system energy consumption index per unit model corresponding to the system energy consumption model; according to the per-unit model of the system energy consumption index, determining the per-unit full life cycle energy consumption parameter of the power grid to be planned; and determining candidate equipment types of the power grid to be planned according to the per-unit full life cycle energy consumption parameters.

In specific implementation, a per-unit full life cycle energy consumption curve of the system is defined

Wherein E (t) _k ) Is a full life cycle energy consumption curve E _B Is the basic value that should be selected by the grid system. Accordingly, the per-unit model of the system energy consumption index can be determined

In the embodiment, a system energy consumption index per unit model corresponding to the system energy consumption model is determined; according to the per-unit model of the system energy consumption index, determining the per-unit full life cycle energy consumption parameter of the power grid to be planned; and determining candidate equipment type selection of the power grid to be planned according to the per-unit full life cycle energy consumption parameters, and carrying out equipment type selection according to the per-unit full life cycle energy consumption indexes so as to effectively reduce the power grid energy consumption.

In one embodiment, the step S130 may specifically include: determining construction energy consumption parameters, operation and maintenance energy consumption parameters and fault energy consumption parameters corresponding to candidate equipment types, and obtaining comprehensive energy consumption parameters according to unit newly-increased electric quantity energy consumption, unit energy saving quantity and new energy power generation energy consumption ratio corresponding to the candidate equipment types; and determining the energy consumption parameters corresponding to the candidate equipment selection according to the sum of the construction energy consumption parameters, the operation and maintenance energy consumption parameters, the fault energy consumption parameters and the comprehensive energy consumption parameters.

In specific implementation, corresponding construction energy consumption parameters, operation and maintenance energy consumption parameters and fault energy consumption parameters can be determined for each candidate equipment type, and comprehensive energy consumption parameters corresponding to the candidate equipment type can be obtained according to unit newly-increased electric quantity energy consumption, unit energy saving energy and new energy power generation energy consumption ratio, and the sum of the construction energy consumption parameters, the operation and maintenance energy consumption parameters, the fault energy consumption parameters and the comprehensive energy consumption parameters is determined as the energy consumption parameters corresponding to the candidate equipment type.

In practical application, the calculation formula of the total energy consumption index T is as follows

T＝f _l (I)+f _R (R)+f _F (F)+f _C (C)，

T＝I+R+F+C，

f _a (a)＝α·a，

f _C (C)＝f _M (M)+f _L (L)+f _W (W)，

Wherein M is the new electric quantity energy consumption of unit, its computational formula is: newly increased total energy consumption/newly increased power generation capacity of the power grid; l is the energy saving amount of the power generation right transaction unit, and the calculation formula is as follows: the power generation right replaces the energy consumption difference/power generation right transaction amount before and after; w is the power generation energy consumption ratio of the new energy, and the total power generation energy consumption of the new energy/the total power generation amount of the new energy in the statistical period.

In the embodiment, the comprehensive energy consumption parameter is obtained by determining the construction energy consumption parameter, the operation and maintenance energy consumption parameter and the fault energy consumption parameter corresponding to the candidate equipment type, and according to the unit newly-increased electric quantity energy consumption, the unit energy saving energy and the new energy power generation energy consumption ratio corresponding to the candidate equipment type; and determining the energy consumption parameter corresponding to the candidate equipment type according to the sum of the construction energy consumption parameter, the operation and maintenance energy consumption parameter, the fault energy consumption parameter and the comprehensive energy consumption parameter, so that the determined energy consumption parameter is associated with the construction energy consumption, the operation and maintenance energy consumption, the fault energy consumption and the comprehensive energy consumption, and the accuracy of the equipment type selection is improved.

In order to facilitate a thorough understanding of embodiments of the present application by those skilled in the art, the following description will be provided in connection with a specific example.

In order to provide practical guidance for energy conservation and carbon reduction of the power industry, aiming at the current situation that energy consumption and energy conservation potential analysis are lacking in full life cycle planning in the existing power system planning, the low-carbon power system planning energy conservation evaluation method from equipment type selection to project-level full life cycle energy consumption analysis to system-level full life cycle energy consumption analysis is provided, the power grid planning scheme is subjected to selection and evaluation from the full life cycle angle, and an effective evaluation means is provided for the power system to realize energy conservation and carbon reduction.

Fig. 2 provides a flow chart of a low-carbon power grid planning scheme evaluation method considering energy-saving benefits. According to fig. 2, the method for evaluating the low-carbon power grid planning scheme considering the energy-saving benefit specifically may include the following steps:

step S210, a three-level full life cycle energy consumption model of equipment, projects and systems is established.

First, a device-level full life cycle energy consumption model as shown in fig. 3 is established, and the device-level full life cycle energy consumption model can be decomposed into ECI, ECO, ECM, ECF and ECD.

ECO can be decomposed into plant body energy consumption ECO, and auxiliary plant energy consumption ECO a. The energy consumption of the equipment body is the loss when the equipment is operated, for example, the energy consumption of the equipment body of a transformer is the sum of copper loss and iron loss. The energy consumption of the device itself can be determined by means of the load data at that time in the past life cycle of the device, and can be estimated by means of load prediction in the future life cycle. Thus can obtain

The ECM may be broken down into split service energy consumption ECMd and regular maintenance energy consumption ECMr. The energy consumption of disassembly overhaul is considered for equipment needing disassembly overhaul, and the energy consumption of disassembly overhaul is not considered for equipment needing no disassembly overhaul.

The ECF may be decomposed into a fault maintenance energy consumption ECFr and a fault loss energy consumption ECFl. Wherein ECFr can be decomposed into: and the energy consumption of fault field treatment and the energy consumption of equipment factory return repair. ECFl can be broken down into customer indirect energy consumption expectations and equipment operation parasitic loss expectations. The user indirect energy consumption expectation refers to the product of the indirect energy consumption brought by the user with the fault occurrence and the probability of the fault occurrence, and the calculation formula can be that

E＝a _u E _u ，

The additional loss of operation expectancy of a device refers to the expectation that the device will fail and will experience additional loss in later life cycles. The device operational parasitic loss expectations may be calculated by:

E＝a _e t _r ΔP _L ，

The ECD can be decomposed into scrap energy ECDs and finishing energy ECDt. ECDs represent the energy consumption caused by the dismantling and transport of the equipment near the end of its life cycle. ECDt represents the energy consumption incurred in the process of being completely discarded or regenerating usable material after the equipment is scrapped and transported to a designated recycling site.

Item level and system level full lifecycle energy consumption analysis is similar to the equipment level, with differences highlighted here. The project-level full life cycle energy consumption can be divided into 6 items of ECI, ECO, ECM, ECF, ECD and Σlcec'. I.e.

LCEC _P ＝ECI+ECO+ECM+ECF+ECD+∑LCEC′。

Wherein ECI comprises infrastructure material preparation energy consumption and infrastructure energy consumption. ECO means the energy consumption of the operation of the whole project, including the operation loss of all the devices in the project. Future operating conditions of the project may be predicted. The ECM is project maintenance energy consumption and does not include equipment maintenance energy consumption in the project. ECF is project fault energy consumption and does not contain equipment fault energy consumption in the project. ECD is project retirement energy consumption, and does not contain equipment failure energy consumption in the project. Σlcec' is the full life cycle energy consumption of all the devices in the project minus the operating energy consumption. Schematic diagrams of the project-level full life cycle energy consumption model and the system-level full life cycle energy consumption model are shown in fig. 4 and 5, respectively.

Step S220, based on the established energy consumption model, equipment model selection is determined, and effective energy saving of the whole life cycle of the project and average energy consumption rate of the future cycle are calculated.

Based on the full life cycle model constructed in step S210, the stage equipment type selection, project effective energy saving and future life cycle average energy consumption rate can be explicitly planned.

Defining the energy consumption average value of the whole life cycle of equipment as

LCEC in _E Representing the full life cycle energy consumption of the equipment, t _E Representing the full life cycle time length of the device. LCEC (liquid crystal display controller) _E Is calculated as

t _E Is calculated as t _E ＝t _end -t _ini 。

Because the full life cycle energy consumption of different devices is different, the life cycle years are also different, so that the full life cycle energy consumption of the devices cannot be only considered. And the average energy consumption of the full-winning period of the device can solve the problem. The energy consumption average index of the whole life cycle of the equipment represents the energy consumption of the average unit time length in the whole life cycle of the equipment. The index is mainly applicable to equipment type selection, and should be selected preferentially when the equipment type is selectedA device with a smaller value.

Similar to defining the device full life cycle energy consumption average value, defining the project full life cycle energy consumption average value as

LCEC in _P Representing the full life cycle energy consumption of an item, t _p Representing the full life cycle time length of the item.

The time of the full life cycle energy consumption curve E (t) is a discrete value, and the full life cycle energy consumption accumulation curve E _C The time of (t) is a continuous amount. And accumulating the full life cycle energy consumption curve E (t) from the initial period to a certain period, and obtaining the energy consumption accumulation amount at each moment corresponding to the period. Thus, the full life cycle energy consumption curve E (t) can be deduced to be the full life cycle energy consumption accumulation curve E _C (t). I.e.

Wherein t is a certain time; t is t _k Indicating that the kth period of time,indicating the start and end times of the period, respectively.

The value of the full life cycle energy consumption curve E (t) in a certain period can be calculated by the full life cycle energy consumption accumulation curve E _C (t) the difference between the value at the end of the period and the value at the start of the period. Thus, the full life cycle energy consumption curve E (t) can also be calculated from the full life cycle energy consumption accumulation curve E _C (t) push out, i.e

The average energy consumption intensity of the full life cycle energy consumption curve E (t) in a certain period can be taken as the value of the full life cycle energy consumption intensity curve at any time of the period. Thus, the full lifecycle energy consumption curve E (t) can be derived as the full lifecycle energy consumption intensity curve I (t), i.e

The energy consumption of each period of the full life cycle energy consumption curve E (t) can also be regarded as being formed by the accumulation of the full life cycle energy consumption intensity curve I (t) during that period. Thus, the full life cycle energy consumption curve E (t) can be deduced from the full life cycle energy consumption intensity curve I (t), i.e

Full life cycle energy consumption accumulation curve E _C The (t) has a well-defined mathematical relationship between derivative and integral with the full life cycle energy consumption intensity curve I (t):

i.e. I (t) is E _C (t) derivative with respect to time, E _C And (t) is the integral of I (t) with respect to time.

Thus, LCEC _E Is calculated as

/>

t _p Is calculated as t _P ＝t _end -t _ini 。

Since the full life cycle energy consumption of different projects is different, the life cycle years are also different, so that only LCEC of the projects cannot be considered. And the project full life cycle energy consumption average value can solve the problem. The energy consumption average index of the whole life cycle of the project represents the energy consumption of the average unit time length in the whole life cycle of the project. The index is mainly applicable to project scheme selection, and project schemes with smaller values should be preferentially selected when the project schemes are selected.

Ideal energy saving per period of the full life cycle of an item

However, it is considered that the project may not necessarily be able to reach the lowest energy consumption level in each period, i.e. E (t) _k ) Reduce to and E _b (t _k ) And consistent. Thus, the coefficients are definedThe energy saving effectiveness ratio for each period of the project represents the proportion of the energy saving amount which can be achieved in the kth period to the ideal energy saving amount.

So far, the project full life cycle effective energy saving can be defined

Therefore, the project full life cycle energy consumption average value considering the effective energy saving amount can be defined as

The index is mainly used for project schemes. If the energy saving potential and corresponding technical means of the project can be obtained in the project scheme comparison and selection stage and effective estimation can be made on the energy saving energy of the whole life cycle in the future, the index can be applied in the project scheme comparison and selection stage and should be selected preferentiallyItem schemes with smaller values.

Defining average energy consumption rate of future life cycle as

Wherein E is _SC (t) is a system full life cycle energy consumption accumulation curve after considering a project scheme, E _SC (≡) means after considering only the project scheme and finally, the system can accumulate all energy consumption.The time of the initial construction of the project is indicated,and indicating the rejection ending time of the project. This index is defined primarily for pre-evaluation of the item. The operation mode of the whole system is influenced by the construction of the line and the transformer substations along the way, so that the influence of each scheme of the project on the system is considered, and the future life cycle energy consumption of the whole system after the construction of a certain scheme is realized on the molecule of the index; and the life cycle time length of each project may be different, thus evaluating The time span of the project must also be considered when the project is concerned, so the denominator of the index is the life cycle time length of the project. The average energy consumption rate of future life cycle characterizes the system energy loss of average unit time length in the whole life cycle of the project after the project is built. The index is mainly used for selecting project schemes, and the +.>Item schemes with smaller values.

Step S230, performing system-level full life cycle energy consumption index per unit processing and energy consumption capacity ratio judgment.

On the basis of step S210, a power grid full life cycle per unit energy consumption index is established. I _S (0) The energy consumption intensity at the current moment of the system. I when comparing and evaluating a plurality of power grids with approximately the same power grid capacity _S (0) The smaller power grid has better energy consumption state at the current moment.

The definition of the full life cycle energy consumption capacity ratio is that

Wherein LCECs represent the full life cycle energy consumption of the system, its calculation method and LCECs in the previous step _E Similarly. S denotes the capacity of the system. Different power grids have different capacities and also have different full life cycle energy consumption at the system level. Therefore, the comparison and evaluation of the power grid needs to comprehensively consider the full life cycle energy consumption of the power grid and the capacity of the system. The full life cycle energy consumption capacity ratio index represents the energy consumption corresponding to the unit system capacity. The index can be mainly applied to comparison and evaluation between different power grids. The power consumption level of the power grid with smaller k value is lower.

The full life cycle energy consumption capacity ratio is a relatively rough index for evaluating the power grid. In contrast, the per-unit full life cycle energy consumption index of the system can be defined to describe and compare the energy consumption levels of different power grids more accurately. To define the per-unit full life cycle energy consumption index of the system, the per-unit full life cycle energy consumption curve of the system is defined first

Wherein E (t) _k ) Is a full life cycle energy consumption curve E _B Is the basic value that should be selected by the grid system. Accordingly, the system per unit full life cycle energy consumption index can be defined as

Can be deduced

The key of the system per unit full life cycle energy consumption index is the per unit basic value E of the power grid system _B Is selected from the group consisting of (a). E (E) _B The obtained (C) can be obtained by adopting regression analysis to obtain a proper function form and then calculating a fitting value.

First, obtain the capacities S of different scale grids _i Energy consumption E corresponding to a certain typical period _i . Then a certain function form is selected to enable E _i For S _i Regression is performed to obtain a regression equation expressed by the estimated quantity

E _Bi ＝f(S _i )。

Substituting the capacity S of a certain power grid into the obtained regression equation _X The energy consumption base value E corresponding to the power grid can be estimated _BX And then the system per unit full life cycle energy consumption index of the power grid can be obtained.

As is apparent from the above analysis, when the relation between EB and S is set as E _B When S, the full life cycle energy consumption capacity ratio k is the same as the system per unit full life cycle energy consumption index B. Therefore, the full life cycle energy consumption capacity ratio k is a special case of the system per unit full life cycle energy consumption index B.

And step S240, evaluating the power grid planning scheme by adopting a mode of combining quantification and qualitative.

Based on the step S220 and the step S230, the evaluation method based on the full life cycle energy consumption theory uniformly and comprehensively considers more evaluation indexes and gradually goes deep into quantization to enable analysis and evaluation to be more scientific and reasonable, and the technical energy consumption evaluation system of the planning scheme is used for reflecting the basic idea of the planning principle by referring to the related principle of power transmission network planning, so that the quantitatively evaluated indexes reflect the qualitatively described planning principle. For this purpose, in connection with the implementation of full life cycle management, an evaluation model of the grid planning scheme is constructed from four aspects of investment (I), operation and maintenance (R), fault (F) and synthesis (C). The total life cycle energy consumption is adopted to reflect the total energy consumed by the planning project in the life cycle, and the fine analysis and management are beneficial to the decision making and optimization work of the power company on each content of the planning scheme, so that the energy saving and the efficiency improvement of the power company are promoted. And an energy consumption quantization calculation formula is given to the mature quantization evaluation index; qualitative analysis is still adopted for evaluation indexes which are difficult to quantify or cannot be quantified into energy consumption results.

The overall T index formula is as follows:

T＝f _l (I)+f _R (R)+f _F (F)+f _C (C)。

T＝I+R+F+C，

For the index which can not be converted into energy consumption, the simplified processing mode can take a conversion function as a primary function, namely multiplying the calculated non-energy consumption quantization index by a certain weight coefficient, wherein the weight coefficient is as shown in the following formula:

f _a (a)＝α·a。

f _C (C)＝f _M (M)+f _L (L)+f _W (W)，

Wherein: m is the newly increased electric quantity energy consumption of the unit, and the calculation formula is as follows: newly increased total energy consumption/newly increased power generation capacity of the power grid; l is the energy saving amount of the power generation right transaction unit, and the calculation formula is as follows: the power generation right replaces the energy consumption difference/power generation right transaction amount before and after; w is the power generation energy consumption ratio of the new energy, and the total power generation energy consumption of the new energy/the total power generation amount of the new energy in the statistical period. It should be noted that when the total time for new energy power generation is calculated, the total electric energy generated by the new energy power generation equipment in the operation time limit needs to be deducted, so as to embody the energy saving and emission reduction benefits brought by the renewable clean energy instead of the conventional fossil energy.

The specific application steps of the index are as follows:

1. according to the historical energy consumption analysis data, carrying out analysis and calculation on the investment energy consumption I, the operation and maintenance energy consumption R, the fault energy consumption F and the comprehensive energy consumption index C of the N power grid planning schemes to be selected by adopting the calculation method;

2. substituting the investment energy consumption index I, the operation and maintenance energy consumption index R, the fault energy consumption index F and the comprehensive energy consumption index C of the N power transmission network planning schemes into T=I+R+F+C respectively to obtain N comprehensive indexes T;

3. and comparing the obtained N comprehensive indexes T, wherein the scheme corresponding to the minimum numerical value is the optimal scheme, and the scheme corresponding to the comprehensive indexes T with infinite numerical value is the invalid scheme.

Fig. 6 provides a wiring diagram of an IEEE RTS 24 node test system. According to fig. 6, the proposed energy consumption evaluation method was verified, the system being divided into two voltage classes, the reference voltages being 138kV and 230kV, respectively. The generator set comprises a thermal power unit, a fuel oil unit and a nuclear power unit. The active power of the load of the whole year is given according to the periods of seasons, weeks, days and the like, and the time interval is per hour (8760 tide sections). The power factor of each load busbar of a typical tidal current section is shown in table 1:

table 1 IEEE RTS 24 node test system load data

Node	Proportion of active load	Load power factor
			1	3.8	0.980
2	3.4	0.979
			3	6.3	0.980
4	2.6	0.980
			5	2.5	0.981
6	4.8	0.979
			7	4.4	0.981
8	6	0.980
			9	6.1	0.979
10	6.8	0.980
			13	9.3	0.980
14	6.8	0.980
			15	11.1	0.980
16	3.5	0.981
			18	11.7	0.980
19	6.4	0.980
			20	4.5	0.980

Under the assumption that the power factor of the load is unchanged, the corresponding reactive load condition of 8760 periods can be obtained. In the case of analyzing the actual calculation example, future load data is unknown and it is necessary to obtain the load data by using a load prediction algorithm. Since the load prediction algorithm is relatively mature and is not the focus of the present application, the known 8760-period load data is used instead of the "load prediction data" to participate in the calculation in this embodiment.

The application also supplements a plurality of reactive power regulating devices on the basis of an IEEE RTS 24 node system, comprising a shunt capacitor and a shunt reactor, as shown in table 2:

table 2 IEEE RTS 24 node test system load data

After supplementing the reactive power regulation equipment shown in table 2, all node voltage magnitudes can be satisfied between 0.9p.u. and 1.1p.u. in a one year (8760 power flow section) simulation performed on the test system.

In the multi-scene comparison, the test system is subjected to one-year operation simulation, and the network loss of the system in one year (8760 hours) is 5553.298p.u. by simulating the start-stop and the output of each unit and estimating the electric energy loss by utilizing the power generation output simulation thought under a certain load level. A list of several power lines with more prominent power loss is given in table 3:

Table 3 loss of electric energy in transmission line

Head node	End node	Loss of electric energy (p.u.)
			15	24	570.125
14	16	537.4756
			12	23	507.1342
13	23	464.2
			8	9	460.0581
16	17	299.3201
			8	10	277.1864
1	3	273.4342
			15	21	256.433
15	21	256.433

According to the electric energy loss of the meter, the section with tension transmission can be judged. A new double-loop overhead transmission line is built, and the problem of tension in transmission is solved. The specific parameters are shown in Table 4:

table 4 list of alternative lines

Alternate line name	Head node	End node	Reference voltage (kV)	Line length (km)
					A ₁	14	16	230	43.5
A ₂	15	24	230	57.9
					A ₃	12	23	230	107.8
A ₄	13	23	230	96.6

The alternative line has the same voltage level as the typical line, so it is assumed that the alternative line uses the same equipment type as the typical line, including wires, ground, towers, insulation, etc. The construction energy consumption of each alternative line can be estimated according to the length of the transmission line:

CEC_A ₁ ＝14056÷33.8×43.5＝18089.8MWh

CEC_A ₂ ＝14056÷33.8×57.9＝24078.2MWh

CEC_A ₃ ＝14056÷33.8×107.8＝44829.5MWh

CEC_A ₄ ＝14056÷33.8×96.6＝40171.9MWh

wherein CEC represents construction energy consumption. Assuming that one of the alternative lines needs to be selected, a multi-scene comparison operation needs to be performed. Respectively set hypothesis scenes S ₁ ，S ₂ ，S ₃ ，S ₄ The subscript thereof indicates that the alternative circuit having the same subscript is built and put into operation. In addition, a reference scene S is set ₀ Indicating that no additional lines were present, the system was running for 8760 hours with estimated energy consumption (OEC ₀ ) Will be the reference value for the system operating energy consumption.

The degree of loss reduction of the whole system after any one transmission line is put into operation is examined, and the operation energy consumption under each assumed scene and the reference scene needs to be estimated respectively.

Fig. 7 provides a comparison of energy consumption for a multi-scenario operation. According to fig. 7, there is shown the comparison of the 8760 hours of operation energy consumption of the system in each hypothetical scenario with the reference scenario, for comparison with the construction energy consumption, in MWh. From the figure, scene S can be seen ₃ The corresponding operation energy consumption is the lowest.

After a new transmission line is erected, the electric distance between the power generation and load sides of the system is shortened, and the total network loss (operation energy consumption) of the system tends to be reduced.

It should be noted that the service life of overhead transmission lines exceeds 30 years, and the time span is too large to accurately consider various uncertain factors, so that the annual mode is only used as a simplified method. Scenario 3 may be employed as an optimal solution if considering the full life cycle of overhead transmission lines from build up to destruction, for decades.

The power system planning method provided by the application can fully consider the related carbon constraint of the power system, also proves the effectiveness of the planning method, and provides an effective means for the energy consumption evaluation of the novel power system planning.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides a low-carbon power grid equipment type selection determining device considering the energy-saving benefit, which is used for realizing the low-carbon power grid equipment type selection determining method considering the energy-saving benefit. The implementation scheme of the device for solving the problem is similar to the implementation scheme described in the method, so the specific limitation in the embodiment of the low-carbon power grid equipment type selection determining device for considering the energy-saving benefit provided below can be referred to the limitation of the low-carbon power grid equipment type selection determining method for considering the energy-saving benefit hereinabove, and is not repeated herein.

In one embodiment, as shown in fig. 8, there is provided a low-carbon power grid equipment model selection determining device considering energy saving benefits, including: an energy consumption model acquisition module 310, a candidate device type selection module 320, and a target device type selection module 330, wherein:

an energy consumption model obtaining module 310, configured to obtain a full life cycle energy consumption model of a power grid to be planned; the full life cycle energy consumption model comprises an equipment energy consumption model, a project energy consumption model and a system energy consumption model;

a candidate device type selection module 320, configured to determine a power grid parameter model of the power grid to be planned according to the device energy consumption model, the project energy consumption model and the system energy consumption model, and determine a candidate device type of the power grid to be planned according to the power grid parameter model; the power grid parameter model comprises at least one of an item effective energy-saving model, an item future period average energy consumption rate model, a system energy consumption capacity ratio model and a system energy consumption index per unit model;

And the target equipment type selection module 330 is configured to determine an energy consumption parameter corresponding to the candidate equipment type, and determine the target equipment type of the power grid to be planned from the candidate equipment types according to the energy consumption parameter.

In one embodiment, the candidate device selection module 320 is further configured to determine the project energy efficiency model corresponding to the project energy consumption model; determining a project full life cycle energy consumption average value of the power grid to be planned according to the project effective energy-saving model; and determining the candidate equipment type of the power grid to be planned according to the project full life cycle energy consumption average value.

In one embodiment, the candidate device selection module 320 is further configured to determine a future period average energy consumption rate model of the project corresponding to the project energy consumption model; obtaining the average energy consumption rate of the future life cycle of the power grid to be planned according to the average energy consumption rate model of the future period of the project; and determining the candidate equipment type of the power grid to be planned according to the average energy consumption rate of the future life cycle.

In one embodiment, the candidate device selection module 320 is further configured to determine the system energy consumption capacity ratio model corresponding to the system energy consumption model; determining the full life cycle energy consumption capacity ratio of the power grid to be planned according to the system energy consumption capacity ratio model; and determining the candidate equipment type of the power grid to be planned according to the full life cycle energy consumption capacity ratio.

In one embodiment, the candidate device type selection module 320 is further configured to determine a per-unit model of the system energy consumption index corresponding to the system energy consumption model; according to the system energy consumption index per unit model, determining per unit full life cycle energy consumption parameters of the power grid to be planned; and determining the candidate equipment type of the power grid to be planned according to the per-unit full life cycle energy consumption parameter.

In one embodiment, the target device type selection module 330 is further configured to determine a construction energy consumption parameter, an operation and maintenance energy consumption parameter, and a fault energy consumption parameter corresponding to the candidate device type selection, and obtain a comprehensive energy consumption parameter according to a unit newly-increased electric quantity energy consumption, a unit energy saving energy, and a new energy power generation energy consumption ratio corresponding to the candidate device type selection; and determining the energy consumption parameter corresponding to the candidate equipment type according to the sum of the construction energy consumption parameter, the operation and maintenance energy consumption parameter, the fault energy consumption parameter and the comprehensive energy consumption parameter.

The above-mentioned low-carbon power grid equipment model selection determining device considering energy-saving benefits can be implemented by all or part of software, hardware and their combination. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 9. The computer device includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input means. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program, when executed by the processor, implements a low-carbon power grid equipment type selection determination method taking into account energy-saving benefits. The display unit of the computer device is used for forming a visual picture, and can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be a key, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.

It will be appreciated by persons skilled in the art that the architecture shown in fig. 9 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting as to the computer device to which the present inventive arrangements are applicable, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

In an embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method embodiments described above.

In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.

It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data need to comply with the related laws and regulations and standards of the related country and region.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.

Claims

1. The utility model provides a low-carbon power grid equipment type selection determining method considering energy-saving benefit, which is characterized by comprising the following steps:

2. The method according to claim 1, wherein the determining a grid parameter model of the grid to be planned according to the device energy consumption model, the project energy consumption model and the system energy consumption model, and determining a candidate device selection of the grid to be planned according to the grid parameter model, respectively, comprises:

determining the project effective energy model corresponding to the project energy model;

determining a project full life cycle energy consumption average value of the power grid to be planned according to the project effective energy-saving model;

and determining the candidate equipment type of the power grid to be planned according to the project full life cycle energy consumption average value.

3. The method of claim 1, wherein the determining the grid parameter model of the grid to be planned according to the device energy consumption model, the project energy consumption model, and the system energy consumption model, and determining the candidate device option of the grid to be planned according to the grid parameter model, further comprises:

Determining an average energy consumption rate model of the future period of the project corresponding to the project energy consumption model;

obtaining the average energy consumption rate of the future life cycle of the power grid to be planned according to the average energy consumption rate model of the future period of the project;

and determining the candidate equipment type of the power grid to be planned according to the average energy consumption rate of the future life cycle.

4. The method of claim 1, wherein the determining the grid parameter model of the grid to be planned according to the device energy consumption model, the project energy consumption model, and the system energy consumption model, and determining the candidate device option of the grid to be planned according to the grid parameter model, further comprises:

determining the system energy consumption capacity ratio model corresponding to the system energy consumption model;

determining the full life cycle energy consumption capacity ratio of the power grid to be planned according to the system energy consumption capacity ratio model;

and determining the candidate equipment type of the power grid to be planned according to the full life cycle energy consumption capacity ratio.

5. The method of claim 1, wherein the determining the grid parameter model of the grid to be planned according to the device energy consumption model, the project energy consumption model, and the system energy consumption model, and determining the candidate device option of the grid to be planned according to the grid parameter model, further comprises:

Determining a per-unit model of the system energy consumption index corresponding to the system energy consumption model;

according to the system energy consumption index per unit model, determining per unit full life cycle energy consumption parameters of the power grid to be planned;

and determining the candidate equipment type of the power grid to be planned according to the per-unit full life cycle energy consumption parameter.

6. The method of claim 1, wherein the determining the energy consumption parameter corresponding to the candidate device type comprises:

determining construction energy consumption parameters, operation and maintenance energy consumption parameters and fault energy consumption parameters corresponding to the candidate equipment types, and obtaining comprehensive energy consumption parameters according to unit newly-increased electric quantity energy consumption, unit energy saving energy and new energy power generation energy consumption ratio corresponding to the candidate equipment types;

and determining the energy consumption parameter corresponding to the candidate equipment type according to the sum of the construction energy consumption parameter, the operation and maintenance energy consumption parameter, the fault energy consumption parameter and the comprehensive energy consumption parameter.

7. A low-carbon power grid equipment type selection determining device considering energy-saving benefits, which is characterized by comprising:

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.

9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.