A method and system for generating a maintenance plan suitable for a high-load local isolated network

Abstract

The present application relates to the technical field of micro-grid, and provides a maintenance plan generation method and system suitable for high-load local isolated network, comprising: for each month in each maintenance plan date combination, calculating the power shortage when each thermal power unit is shut down; based on the power shortage, combining the new energy output in previous years, calculating the new energy supplement power when each thermal power unit is shut down in each month; based on the new energy supplement power, calculating the daily power purchase amount when each thermal power unit is shut down in each month; for each maintenance plan date combination, accumulating the daily power purchase amount of all days to obtain the grid power purchase amount corresponding to the maintenance plan date combination, and taking the maintenance plan date combination corresponding to the minimum grid power purchase amount as the annual optimal maintenance plan. By using the certain periodicity of new energy in time, the power gap in the power grid power shortage state is made up, the multi-energy complementary effect is realized in the maintenance plan aspect, and the external power purchase amount is reduced.

Description

Technical Field

[0001] This invention belongs to the field of microgrid technology, and in particular relates to a method and system for generating maintenance plans suitable for high-load local isolated grids. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Taking a local power grid (hereinafter referred to as the local power grid) as an example, the local power grid administers three thermal power plants (F1, F2, and F3) with a total of eight operating thermal power units. It also administers the N renewable energy plant with a total of four main transformers and a total installed capacity of 450MW. Together with the three aluminum plants (L1, L2, and L3) under its jurisdiction, it forms a self-supplied power grid with a total rigid load of 1400MW. The electricity generated by thermal power and renewable energy is used for self-consumption, while also being electrically connected to the main power grid via tie lines. When there is a power shortage in its own grid, it purchases electricity through the tie lines to achieve its own power balance.

[0004] The self-owned power grid needs to conduct annual maintenance on the thermal power units within the grid. Depending on the capacity of the out-of-service units, different power shortages will occur. This power shortage is supplemented by purchasing electricity from external sources through the interconnection line or by renewable energy sources. Purchasing electricity from external sources will increase the operating costs of enterprises. Therefore, the formulation of thermal power maintenance plans needs to select periods when renewable energy output is seasonal and can supplement the power gap as much as possible, thereby reducing the amount of electricity purchased from external sources. Moreover, most of the existing maintenance plans are formulated manually based on experience, which makes it impossible to obtain the optimal maintenance plan. Summary of the Invention

[0005] To address the technical problems mentioned above, this invention provides a method and system for generating maintenance plans for high-load, locally isolated grids. By utilizing the periodicity of new energy sources over time, it compensates for power shortages in the power grid, achieving multi-energy complementarity in maintenance planning and reducing the need for external power purchases.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] The first aspect of the present invention provides a method for generating maintenance plans suitable for high-load local isolated networks, comprising:

[0008] For each month within each maintenance schedule date combination, calculate the power deficit for each thermal power unit during shutdown;

[0009] Based on the power shortage and combined with the renewable energy output over the years, calculate the renewable energy supplementary power when each thermal power unit is shut down each month;

[0010] Based on the electricity supplemented by new energy sources, calculate the daily electricity purchase amount for each thermal power unit when it is shut down each month;

[0011] For each maintenance plan date combination, the daily electricity purchases for all days are summed to obtain the online electricity purchases corresponding to the maintenance plan date combination. The maintenance plan date combination with the minimum online electricity purchases is taken as the optimal maintenance plan for the year.

[0012] Furthermore, the power shortage during shutdown of each thermal power unit is as follows:

[0013]

[0014] Among them, PV k PF represents the power shortage when the k-th thermal power unit is shut down; i PL represents the power supply of the i-th thermal power unit; PL represents the total electrical load; a represents the total number of thermal power units.

[0015] Furthermore, the shortfall in electricity PV when the kth thermal power unit shuts down in month m k The absolute value is greater than or equal to the rated maximum output of new energy and PV k When the power generation is less than or equal to 0 MW, the average daily power generation of new energy in the m-th month is the power supplemented by new energy.

[0016] Furthermore, the shortfall in electricity PV when the kth thermal power unit shuts down in month m k The absolute value is less than or equal to the rated maximum output of the new energy source and PV k When the capacity is less than or equal to 0 MW, the supplementary power from renewable energy sources is:

[0017]

[0018] Wherein, P(m,PV) k This indicates that in month m, the output of all new energy sources is lower than P. y The average power at statistical points; P(m,PV) k This indicates that in month m, the output of all new energy sources is lower than P. y The ratio of the statistical points to all statistical points; P y P represents the upper limit power value of the y-th statistical interval; l represents the total number of statistical intervals; max It is rated to the maximum output of new energy sources.

[0019] Furthermore, when the power deficit of the kth thermal power unit in the mth month is less than or equal to 0MW, the daily purchased electricity is the difference between the electricity generated from the power deficit and the electricity supplemented by new energy sources.

[0020] Furthermore, when the power deficit of the kth thermal power unit in the mth month is greater than 0MW, the supplementary power is 0.

[0021] Furthermore, when the power deficit of the kth thermal power unit in the mth month is greater than 0MW, the daily power purchase is 0.

[0022] A second aspect of the present invention provides a maintenance plan generation system suitable for high-load local isolated networks, comprising:

[0023] The power deficit calculation module is configured to calculate the power deficit for each thermal power unit during shutdown for each month in each maintenance schedule date combination;

[0024] The renewable energy supplementary power calculation module is configured to: calculate the renewable energy supplementary power when each thermal power unit is shut down each month, based on the power deficit and combined with the renewable energy output over the years.

[0025] The daily electricity purchase calculation module is configured to calculate the daily electricity purchase for each thermal power unit when it is shut down each month, based on the electricity replenished by new energy sources.

[0026] The optimal maintenance plan selection module is configured as follows: for each maintenance plan date combination, the daily purchased electricity of all days is added up to obtain the online purchased electricity corresponding to the maintenance plan date combination, and the maintenance plan date combination corresponding to the minimum online purchased electricity is taken as the annual optimal maintenance plan.

[0027] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the maintenance plan generation method for a high-load local isolated network as described above.

[0028] A fourth aspect of the present invention provides a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the maintenance plan generation method for a high-load local isolated network as described above.

[0029] Compared with the prior art, the beneficial effects of the present invention are:

[0030] This invention provides a maintenance plan generation method suitable for high-load local isolated grids. Based on historical renewable energy generation output and grid power balance, it constructs daily electricity purchase meters for each thermal power unit after shutdown over an annual timescale. It then uses an enumeration method to list all date combinations for maintenance plans and determines the maintenance plan with the minimum electricity purchase based on the daily electricity purchase meters. By utilizing the periodicity of renewable energy to compensate for power shortages in the grid, it achieves multi-energy complementarity in maintenance planning, further improving the operational economy of self-owned grids with a large proportion of renewable energy. Attached Figure Description

[0031] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0032] Figure 1 This is a flowchart of date arrangement acquisition according to Embodiment 1 of the present invention. Detailed Implementation

[0033] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0034] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0035] Example 1

[0036] This embodiment provides a method for generating maintenance plans suitable for high-load, locally isolated power grids. It calculates the supplementary electricity from renewable energy sources during different power shortages based on historical renewable energy output statistics, calculates the daily electricity purchase for different capacity thermal power units during different months of shutdown, further arranges the maintenance cycles of all out-of-service units within a year into a full permutation, and then calculates the annual electricity purchase for each permutation based on the daily electricity purchase for unit shutdowns. The permutation with the minimum electricity purchase is selected as the optimal annual maintenance plan. The method includes the following steps:

[0037] Step 1: Statistical analysis of wind resource data over the years.

[0038] Step 101: Set the maximum rated output force to P. max The monthly wind resource data is divided into l statistical intervals according to a certain power, and the upper limit power value of the nth statistical interval is... Where n = 1, 2, ..., l, for example, for a 300,000 kW new energy source, if l = 6, it is divided into 6 statistical intervals: 50,000, 100,000, 150,000, 200,000, 250,000, and 300,000. Where P... max For new energy installed capacity, the rated output is fixed in the absence of incremental new energy sources.

[0039] Step 102: Calculate the average daily power generation Q of new energy sources in the m-th month. m With m = 1, 2, ..., 12, we obtain the first matrix:

[0040]

[0041] In the formula, Q m Let m represent the average daily power generation of new energy sources in the m-th month, where m = 1, 2, ..., 12.

[0042] Step 103: Obtain the renewable energy output of all statistical points (statistical points refer to the sampling points of renewable energy output recorded in the monitoring system, with the period based on the statistical period, for example, recording one point every 5 minutes, recording 288 power points throughout the day). In the m-th month, extract the upper limit power value P of renewable energy output that is lower than the n-th statistical interval. n Calculate the average output P of all extracted statistical points. m,n The second matrix is ​​obtained as follows:

[0043]

[0044] Step 104: In the m-th month, extract the upper limit power value P for new energy output that is lower than the n-th statistical interval. n The statistical points are calculated, and the proportion R of the extracted statistical points to all statistical points is calculated. m,n The third matrix is ​​obtained as follows:

[0045]

[0046] Among them, R m,n This indicates that the output of new energy sources in month m is lower than P in month m. n The proportion of statistical points to the total number of statistical points.

[0047] Step 2: Calculate the system power balance.

[0048] For each month, calculate the power balance of the system when the kth unit out of a total of a thermal power units is out of service:

[0049]

[0050] Among them, PF i PV represents the power output of the i-th thermal power unit. k PL represents the power shortage when the k-th thermal power unit is shut down; PL is the total power load; k = 0, 1, 2, ..., a. In particular, when k = 0, it means that all units are running.

[0051] Step 3: Determine the average power and percentage of wind power to supplement the power shortage.

[0052] (1) When the m-th month and the k-th thermal power unit are shut down, the power imbalance PV is generated. k The absolute value is greater than or equal to the rated maximum output P of the new energy source. max And PV k When the power generation is less than or equal to 0 MW, it means that all the electricity generated by the new energy sources makes up for the power shortage. It is assumed that when the k-th thermal power unit is shut down in the m-th month, the average daily power generation of the new energy sources in that month is all supplementary power, i.e., Qs(k,m)=Q mThe self-consumption rate of new energy sources is extremely low and negligible in calculations; the power generation equals the power supply.

[0053] (2) When the kth thermal power unit is shut down in the mth month, when the power imbalance PV k The absolute value is less than or equal to the rated maximum output P of the new energy source. max And PV k When the power output is less than or equal to 0 MW, it indicates that the system experiences a certain power deficit when the k-th thermal power unit shuts down. However, this deficit can be completely compensated by the output of renewable energy sources once they reach a certain power level. The average output and proportion of renewable energy sources are as follows:

[0054]

[0055] Where y = min(X1,X2,…,X) j ,…), X j Representing P1, P2, ..., P l Medium greater than abs(PV) k The j-th value among all values ​​of ); P(m,PV k This indicates that in month m, the output of all new energy sources is lower than P. y The average power at statistical points; R(m,PV) k This indicates that in month m, the output of all new energy sources is lower than P. y The ratio of the statistical points to all statistical points; P y This represents the upper limit power value of the y-th statistical interval.

[0056] At this point, it is assumed that the supplementary power consists of two parts, and the output of the new energy source in month m is lower than the minimum power statistical node P. m,y The probability is R(m,PV) k The corresponding average output is P(m,PV). k The other part corresponds to the statistical node P with power not lower than the minimum power. m,y The power, with a probability of (1-R(m, PV)). k Therefore, the electricity replenishment from new energy sources can be expressed as:

[0057]

[0058] Where l represents the total number of statistical intervals.

[0059] (3) When the kth thermal power unit is shut down in the mth month, the power imbalance PV k When the power supply is greater than or equal to 0 MW, there is no power shortage, and the supplementary power supply Qs(k,m) = 0.

[0060] Step 4: Construct a daily electricity meter

[0061] (1) When the power imbalance PVk The absolute value of PV is greater than or equal to the rated maximum output P of the new energy source and PV k When the capacity is less than or equal to 0 MW, if the k-th unit shuts down in month m, the daily electricity purchase for that month should be the difference between the electricity generated by the system's power deficit and the electricity supplemented by new energy sources, that is:

[0062] Qp(k,m)=abs(PV k )×24-Q m

[0063] (2) When the power imbalance PV k,1 The absolute value is less than the rated maximum output P of the new energy source and PV k Daily electricity purchase when MW is less than or equal to:

[0064] Qp(k,m)=abs(PV k )×24-Qs(k,m)

[0065] (3) When the power imbalance PV k,1 Daily electricity purchase amount when there is no power shortage (greater than or equal to 0):

[0066] Qp(k,m)=0

[0067] Step 5: Create a full permutation of dates, where {S(a),F(a)} represents a date permutation (a combination of maintenance schedule dates).

[0068] Let the number of maintenance days for unit a be:

[0069] S(a) = [S1,S2,…,S] a ]

[0070] Among them, S i This represents the maintenance time for the i-th generating unit.

[0071] Meanwhile, the set of days between the maintenance and repair of each unit is as follows:

[0072] F(a) = [F1, F2, ..., F a ,F a+1 ]

[0073] Among them, F i Let F(a) represent the number of days before the maintenance of the i-th unit, and ∑F(a) = 365 - ∑S(a); ∑F(a) represents the sum of all elements in F(a); ∑S(a) represents the sum of all elements in S(a); that is, the sum of all elements in F(a) should be the difference between 365 days in a year and the total number of days for maintenance of all units. Therefore, the annual maintenance plan can be expressed as:

[0074] [F1,S1,F2,S2,...,F a ,Sa ,F a+1 ]

[0075] If the maintenance time for Unit #1 is d1 days, the maintenance time for Unit #2 is d2 days, and so on, the maintenance time for Unit #a is d... a Then S(a) is about d1, d2, ..., d a The full permutation, such as Figure 1 As shown, F(a) can be calculated using the following procedure:

[0076] (1) Calculate T = 365 - ∑S(a), and let F1, F2, ..., F a F a+1 All are 0, let i = 1, the enumeration range of M(1) is from 0 to T;

[0077] (2) Let M(i) take any value within its enumeration range; and assign the value of M(i) to F. i ;

[0078] (3) Calculate the remaining days T' = T - ∑F i That is, the total number of remaining downtime interval days;

[0079] (4) If the remaining days T' = 0, then all subsequent intervals F i+1 To F a+1 All values ​​are zero, completing this loop.

[0080] (5) If T' is not zero, then check if i has reached a. If it has, then assign the remaining number of days T' to F. a+1 At the same time, the current loop ends; if i does not reach a, then let i = i + 1, adjust the enumeration range of M(i) to 0 to the remaining days T', and return to step (2) to continue executing the loop.

[0081] Repeat steps (1)-(5) until the interval f is calculated. i All combinations.

[0082] Step 6: Calculate the electricity consumption for online shopping.

[0083] After obtaining the combination of planned maintenance days for the entire year, the first step is to determine whether it is a leap year or a common year. The number of days in each month is added up sequentially until it is greater than or equal to the current number of days. This number is the day of the current month when the number of planned days is subtracted from the number of days in the preceding complete months, thus determining the start and end dates of each period. Next, the number of days within the corresponding month is determined, and the daily online purchase electricity consumption for the month corresponding to Qp(k,m) is found. These are then added together to obtain the online purchase electricity consumption under the current planned combination.

[0084] Finally, the combination of maintenance schedule dates corresponding to the minimum online purchase volume is the desired result.

[0085] This embodiment constructs a daily electricity purchase meter for each thermal power unit after shutdown on an annual timescale based on historical renewable energy generation output and grid power balance. It then uses an enumeration method to list all date combinations for maintenance plans and, combined with the daily electricity purchase meter data, determines the maintenance plan with the minimum electricity purchase. This embodiment utilizes the periodicity of renewable energy to compensate for power shortages in the grid, achieving multi-energy complementarity in maintenance planning and further improving the operational economy of self-owned grids containing a large proportion of renewable energy.

[0086] This embodiment calculates the power balance of each thermal power unit in the grid under the N-1 condition and the local new energy statistics over the years, establishes the output and proportion of new energy in different output ranges for each month, and then determines the daily electricity purchase situation in the current month by combining the corresponding gap with the output and proportion of new energy, and finally obtains the daily electricity purchase meter for each month in the whole year cycle.

[0087] Based on the expected number of units to be inspected and the inspection period, this embodiment lists all possible arrangements for the unit inspection dates. That is, it uses an enumeration method to obtain all date combinations of the units to be inspected on a yearly time scale, determines the annual electricity purchase amount for each date arrangement by querying the daily electricity purchase meter, and finally selects the date combination with the minimum electricity purchase amount as the optimal inspection plan.

[0088] This embodiment defines a specific date corresponding to a certain generating unit under a certain number of statistical days, thereby effectively using the table lookup method to accurately calculate the purchased electricity.

[0089] Example 2

[0090] This embodiment provides a maintenance plan generation system suitable for high-load local isolated networks, which specifically includes the following modules:

[0091] The power deficit calculation module is configured to calculate the power deficit for each thermal power unit during shutdown for each month in each maintenance schedule date combination;

[0092] The renewable energy supplementary power calculation module is configured to: calculate the renewable energy supplementary power when each thermal power unit is shut down each month, based on the power deficit and combined with the renewable energy output over the years.

[0093] The daily electricity purchase calculation module is configured to calculate the daily electricity purchase for each thermal power unit when it is shut down each month, based on the electricity replenished by new energy sources.

[0094] The optimal maintenance plan selection module is configured as follows: for each maintenance plan date combination, the daily purchased electricity of all days is added up to obtain the online purchased electricity corresponding to the maintenance plan date combination, and the maintenance plan date combination corresponding to the minimum online purchased electricity is taken as the annual optimal maintenance plan.

[0095] It should be noted that each module in this embodiment corresponds one-to-one with each step in Embodiment 1, and their specific implementation processes are the same, so they will not be repeated here.

[0096] Example 3

[0097] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the maintenance plan generation method for a high-load local isolated network as described in Embodiment 1 above.

[0098] Example 4

[0099] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the maintenance plan generation method for a high-load local isolated network as described in Embodiment 1 above.

[0100] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0101] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0102] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0103] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0104] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0105] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for generating maintenance plans suitable for high-load local isolated networks, characterized in that, include: For each month within each maintenance schedule date combination, calculate the power deficit for each thermal power unit during shutdown; Based on the power shortage and combined with the renewable energy output over the years, calculate the renewable energy supplementary power when each thermal power unit is shut down each month; When the m The month of k Power shortage during shutdown of Taiwan's thermal power units The absolute value is less than or equal to the rated maximum output of the new energy source and When the capacity is less than or equal to 0 MW, the supplementary power from renewable energy sources is: in, Indicates the first m All new energy outputs were below [a certain level] for the month. The average power of the statistical points; Indicates the first m All new energy outputs were below [a certain level] for the month. The ratio of statistical points to all statistical points; Indicates the first y The upper limit power value of the statistical interval for each power dimension; l This indicates the total number of statistical intervals in the power dimension; Maximum rated output for new energy sources; Based on the electricity supplemented by new energy sources, calculate the daily electricity purchase amount for each thermal power unit during its monthly shutdown; when the first... m The month of k When the power deficit of a thermal power unit is less than or equal to 0MW when it is shut down, the daily purchased electricity is the difference between the electricity generated by the power deficit and the electricity supplemented by new energy sources. For each maintenance plan date combination, the daily electricity purchases for all days are summed to obtain the online electricity purchases corresponding to the maintenance plan date combination. The maintenance plan date combination with the minimum online electricity purchases is taken as the optimal maintenance plan for the year.

2. The maintenance plan generation method for high-load local isolated networks as described in claim 1, characterized in that, The power shortage during shutdown of each thermal power unit is as follows: in, Indicates the first k Taiwan's thermal power units experienced power shortages when they were shut down; Indicates the first i The power supply capacity of the thermal power unit; Total electrical load; a This indicates the total number of thermal power units.

3. The maintenance plan generation method for high-load local isolated networks as described in claim 1, characterized in that, When the m The month of k Power shortage during shutdown of Taiwan's thermal power units The absolute value is greater than or equal to the rated maximum output of the new energy source and When less than or equal to 0MW, the first m The average daily power generation from new energy sources over the past month is used to supplement the electricity supply from new energy sources.

4. The maintenance plan generation method for high-load local isolated networks as described in claim 1, characterized in that, When the m The month of k When the power deficit of a thermal power unit is greater than 0MW during a shutdown, the supplementary power is 0.

5. The maintenance plan generation method for high-load local isolated networks as described in claim 1, characterized in that, When the m The month of k When the power deficit of a thermal power unit is greater than 0MW during shutdown, the daily power purchase amount is 0.

6. A maintenance plan generation system suitable for high-load local isolated networks, characterized in that, include: The power deficit calculation module is configured to calculate the power deficit for each thermal power unit during shutdown for each month in each maintenance schedule date combination; The renewable energy supplementary power calculation module is configured to: calculate the renewable energy supplementary power when each thermal power unit is shut down each month, based on the power deficit and combined with the renewable energy output over the years. When the m The month of k Power shortage during shutdown of Taiwan's thermal power units The absolute value is less than or equal to the rated maximum output of the new energy source and When the capacity is less than or equal to 0 MW, the supplementary power from renewable energy sources is: in, Indicates the first m All new energy outputs were below [a certain level] for the month. The average power of the statistical points; Indicates the first m All new energy outputs were below [a certain level] for the month. The ratio of statistical points to all statistical points; Indicates the first y The upper limit power value of the statistical interval for each power dimension; l This indicates the total number of statistical intervals in the power dimension; Maximum rated output for new energy sources; The daily electricity purchase calculation module is configured to: calculate the daily electricity purchase for each thermal power unit during its monthly shutdown, based on the electricity supplemented by new energy sources; when the... m The month of k When the power deficit of a thermal power unit is less than or equal to 0MW when it is shut down, the daily purchased electricity is the difference between the electricity generated by the power deficit and the electricity supplemented by new energy sources. The optimal maintenance plan selection module is configured as follows: for each maintenance plan date combination, the daily purchased electricity of all days is added up to obtain the online purchased electricity corresponding to the maintenance plan date combination, and the maintenance plan date combination corresponding to the minimum online purchased electricity is taken as the annual optimal maintenance plan.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the maintenance plan generation method for a high-load local isolated network as described in any one of claims 1-5.

8. A computer 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, it implements the steps in the maintenance plan generation method for high-load local isolated networks as described in any one of claims 1-5.

Images