CN113704984A

CN113704984A - Method and device for making annual maintenance plan of power system and computer equipment

Info

Publication number: CN113704984A
Application number: CN202110934900.3A
Authority: CN
Inventors: 孙荣富; 徐海翔; 吴林林; 乔颖; 鲁宗相; 林弋莎
Original assignee: Tsinghua University; State Grid Corp of China SGCC; Electric Power Research Institute of State Grid Jibei Electric Power Co Ltd
Current assignee: Tsinghua University; State Grid Corp of China SGCC; Electric Power Research Institute of State Grid Jibei Electric Power Co Ltd
Priority date: 2021-08-16
Filing date: 2021-08-16
Publication date: 2021-11-26
Anticipated expiration: 2041-08-16
Also published as: CN113704984B

Abstract

The application relates to a method and a device for making an annual maintenance plan of a power system, computer equipment and a storage medium. The method comprises the following steps: establishing a production simulation model with the minimum running cost as an optimization target, determining an optimal solution to obtain reference power generation power and reference load shedding power, and determining an electric quantity abandoning expectation and a load shedding expectation; when the maximum value in the electric quantity abandonment expectation is larger than a preset electric quantity abandonment expectation threshold, determining a scheduled maintenance time interval according to the maximum value or the minimum value of the electric quantity abandonment expectation; otherwise, determining a scheduled maintenance time interval according to the expected minimum value of the load loss amount; the preset electricity abandoning amount expected threshold value is determined according to the maximum expected loss load amount and a preset coefficient; and modifying the boundary conditions, and determining the scheduled maintenance time interval of the next equipment to be maintained until the scheduled maintenance time intervals of all the equipment to be maintained are obtained. The method can give consideration to both system reliability and electricity abandonment economy, and is suitable for the annual maintenance schedule formulation of the power system with higher renewable energy power generation ratio.

Description

Method and device for making annual maintenance plan of power system and computer equipment

Technical Field

The present application relates to the field of power system maintenance technologies, and in particular, to a method and an apparatus for making an annual maintenance plan of a power system, a computer device, and a storage medium.

Background

The conventional power system mainly uses thermal power generation, and renewable energy power generation such as wind power generation and solar power generation is increasing in proportion to the power system as the energy problem and the environmental problem are increasingly emphasized. In order to find and remove equipment faults of the power system in time and ensure the safe operation of the power system, preventive maintenance of equipment such as a generator set, a circuit and the like of the power system is necessary. The related equipment stops running in the overhaul period, the supply and demand stability of the power system is influenced, the load loss cost in the overhaul period is also considered, and therefore a reasonable annual overhaul plan is formulated, and the reliability and the economy of the power system are directly influenced.

The traditional annual maintenance plan making method of the power system mainly based on thermal power generation mainly considers the load loss cost, does not consider the electricity abandonment problems of wind energy and solar energy, and has the characteristics of short-time strong fluctuation of the generated power of renewable energy sources and more uncertain factors when making the annual maintenance plan, different from the thermal power generation with higher stability and controllability, so the traditional annual maintenance plan making method is not suitable for the power system with higher power generation percentage of the renewable energy sources.

Disclosure of Invention

In view of the above, it is necessary to provide an annual maintenance scheduling method, an annual maintenance scheduling apparatus, a computer device, and a storage medium suitable for a power system with a high renewable energy power generation ratio.

A method of power system annual service planning, the method comprising:

establishing a power system production simulation model with the minimum running cost as an optimization target, and determining an optimal solution according to preset constraint conditions and current boundary conditions to obtain reference generating power of each generating power source contained in the power system in each first unit time period of the whole year and reference load loss power of each node contained in the power system in each first unit time period;

determining the electricity abandon amount expectation corresponding to each second unit time interval in the whole year according to the reference power generation of the renewable energy power generation source in the power generation sources; determining load loss amount expectation corresponding to each second unit time interval according to the reference load loss power; the second unit period is greater than the first unit period;

when the maximum value in the electric energy abandonment expectation is larger than a preset electric energy abandonment expectation threshold, determining a scheduled maintenance time period of the current equipment to be maintained according to the type of the current equipment to be maintained and the maximum value or the minimum value of the electric energy abandonment expectation; the preset electricity abandoning amount expected threshold value is determined according to the maximum expected load loss amount and a preset coefficient;

when the maximum expected electric energy abandoning value is smaller than or equal to the preset expected electric energy abandoning threshold value, determining the scheduled maintenance time interval of the current equipment to be maintained according to the minimum expected loss load;

and according to the scheduled maintenance time interval of the current equipment to be maintained, modifying the boundary conditions in the constraint conditions, and determining the scheduled maintenance time interval of the next equipment to be maintained until the scheduled maintenance time intervals of all the equipment to be maintained are obtained.

In one embodiment, the method further comprises:

according to the scheduled maintenance time interval of all the equipment to be maintained, modifying the boundary conditions in the constraint conditions, and determining the scheduled generating power of each generating power supply in each first unit time interval;

and determining the annual planned power generation amount of the power system according to the planned power generation amount.

In one embodiment, each power generation power source is a power generation cluster, and each power generation cluster at least comprises a thermal power cluster and at least one renewable energy power generation cluster;

the constraint conditions include: the method comprises the following steps of thermal power cluster power generation capacity and start-stop capacity relation constraint, thermal power cluster power generation capacity range constraint, renewable energy power generation cluster power generation capacity constraint, node power balance constraint, system standby capacity constraint, thermal power cluster start-stop time constraint, thermal power cluster up-hill constraint, thermal power cluster down-hill constraint and direct current flow constraint.

In one embodiment, the establishing a power system production simulation model with the minimum operating cost as an optimization target, and determining an optimal solution according to preset constraint conditions and current boundary conditions to obtain reference generated power of each power generation source included in the power system in each first unit time period of the year and reference off-load power of each node included in the power system in each first unit time period includes:

dividing the whole year into a plurality of time intervals according to preset time length to obtain each third unit time interval; the third unit period is greater than the first unit period;

and respectively establishing a production simulation model with the minimum running cost as an optimization target for each third unit time interval, and determining an optimal solution according to a constraint condition and a current boundary condition to obtain the reference generating power of each generating power source contained in the power system in each first unit time interval in the third unit time interval and the reference load shedding power of each node contained in the power system in each first unit time interval in the third unit time interval.

In one embodiment, the types of the equipment to be overhauled comprise a thermal power generating unit and a line; the determining the scheduled maintenance time interval of the current equipment to be maintained according to the type of the current equipment to be maintained and the expected maximum value or minimum value of the electric energy abandon quantity comprises the following steps:

under the condition that the current equipment to be overhauled is a thermal power generating unit, determining a scheduled overhaul time period of the current equipment to be overhauled according to a second unit time period corresponding to the maximum expected electric quantity abandoning value;

and under the condition that the current equipment to be overhauled is a line, determining the scheduled overhaul time period of the current equipment to be overhauled according to a second unit time period corresponding to the minimum expected electric quantity abandoning value.

In one embodiment, when the current equipment to be overhauled is a thermal power generating unit, determining the scheduled overhaul time period of the current equipment to be overhauled according to the second unit time period corresponding to the maximum expected electric energy curtailment amount includes:

under the condition that the current equipment to be overhauled is a thermal power generating unit, determining each time period combination which comprises the second unit time period corresponding to the maximum expected electric energy abandonment and meets the condition of the overhaul time period according to the overhaul time period of the current equipment to be overhauled;

determining the electric energy abandon amount corresponding to each time period combination according to the reference power generation of the renewable energy power generation source and the maximum power generation power of the renewable energy power generation source in each first unit time period all the year around;

and determining the time interval combination corresponding to the maximum electric energy discard amount as the scheduled maintenance time interval of the current equipment to be maintained.

In one embodiment, the types of the equipment to be overhauled comprise a thermal power generating unit and a line; the method further comprises the following steps:

and determining the scheduled maintenance time interval of each device to be maintained according to the priority sequence of each device to be maintained, wherein the priority of the line is higher than that of the thermal power generating unit.

An apparatus for scheduling annual maintenance in an electrical power system, the apparatus comprising:

the production simulation model establishing module is used for establishing a power system production simulation model taking the minimum running cost as an optimization target, determining an optimal solution according to a preset constraint condition and a current boundary condition, and obtaining reference generating power of each generating power source contained in the power system in each first unit time period of the whole year and reference load loss power of each node contained in the power system in each first unit time period;

the flexibility index determining module is used for determining the electricity abandoning amount expectation corresponding to each second unit time interval in the whole year according to the reference power generation of the renewable energy power generation source in the power generation source; determining load loss amount expectation corresponding to each second unit time interval according to the reference load loss power; the second unit period is greater than the first unit period;

the scheduled maintenance time interval determining module is used for determining the scheduled maintenance time interval of the current equipment to be maintained according to the type of the current equipment to be maintained and the expected maximum value or minimum value of the electric energy abandonment when the maximum value of the electric energy abandonment expectation is greater than a preset electric energy abandonment expectation threshold; the preset electricity abandoning amount expected threshold value is determined according to the maximum expected load loss amount and a preset coefficient;

the scheduled maintenance determining module is further configured to determine a scheduled maintenance time period of the current equipment to be maintained according to the minimum expected loss load when the maximum expected loss electric quantity is smaller than or equal to the preset expected loss electric quantity threshold;

and the boundary condition modifying module is used for modifying the boundary conditions in the constraint conditions according to the scheduled maintenance time interval of the current equipment to be maintained and determining the scheduled maintenance time interval of the next equipment to be maintained until the scheduled maintenance time intervals of all the equipment to be maintained are obtained.

A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:

determining a power curtailment expectation corresponding to each second unit time interval of the whole year according to the reference power generation of the renewable energy power generation source in the power generation sources; determining load loss amount expectation corresponding to each second unit time interval according to the reference load loss power; the second unit period is greater than the first unit period;

A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:

According to the method, the device, the computer equipment and the storage medium for making the annual maintenance plan of the power system, the electric quantity abandoning expectation corresponding to each second unit time interval of the whole year is calculated by calculating the reference generating power of each first unit time interval of the whole year of the renewable energy power generation source, and the load losing expectation corresponding to each second unit time interval is calculated according to the reference load losing power of each first unit time interval of the whole year. When the maximum expected abandoned electric quantity is larger than the preset coefficient proportion of the maximum expected lost load quantity, the cost of the abandoned electric quantity is higher than the lost load by the preset coefficient proportion, the electricity abandoning economy of the power system needs to be considered, and the equipment overhaul time interval is arranged by taking the electricity abandoning risk as a measurement index; otherwise, the equipment maintenance time interval is arranged by taking the load loss risk as a measurement index, so that the reliability of the system power utilization is mainly guaranteed. The method introduces two low-flexibility expectation indexes of electric quantity abandonment expectation and load loss expectation as the measurement of system flexibility, comprehensively considers the problems of system reliability and electric energy abandonment, heuristically selects the scheduled maintenance time interval of the equipment to be maintained according to the low-flexibility expectation of each preset time interval in the whole year, minimizes the low-flexibility expectation index difference in each preset time interval, and achieves the purpose of making an annual maintenance plan which gives consideration to the system reliability and the electricity abandonment economy and is suitable for a power system with a high renewable energy power generation ratio.

Drawings

FIG. 1 is a schematic flow chart diagram illustrating a method for scheduling annual maintenance in an electrical power system in one embodiment;

FIG. 2 is a schematic illustration of an annual energy production plan for wind power generation in one example;

FIG. 3 is a schematic diagram of an annual energy production plan for solar power generation in one example;

fig. 4 is a diagram showing the result of an annual power generation amount plan of the thermal power generation in one example;

FIG. 5 is a block diagram showing the construction of an annual overhaul scheduling device of the power system in one embodiment;

FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

First, before specifically describing the technical solution of the embodiment of the present application, a technical background or a technical evolution context on which the embodiment of the present application is based is described. The conventional power system mainly uses thermal power generation, and renewable energy power generation such as wind power generation and solar power generation is increasing in proportion to the power system as the energy problem and the environmental problem are increasingly emphasized. In order to find and remove equipment faults of the power system in time and ensure the safe operation of the power system, preventive maintenance of equipment such as a generator set, a circuit and the like of the power system is necessary. During the maintenance period, the related equipment stops running, the supply and demand stability of the power system is influenced, the load loss cost is also considered, and therefore a reasonable annual maintenance plan is formulated, and the reliability and the economy of the power system are directly influenced. The traditional annual maintenance plan making method of the power system mainly based on thermal power generation mainly considers the load loss cost, does not consider the electricity abandonment problems of wind energy and solar energy, and has the characteristics of short-time strong fluctuation of the generated power of renewable energy sources and more uncertain factors when making the annual maintenance plan, different from the thermal power generation with higher stability and controllability, so the traditional annual maintenance plan making method is not suitable for the power system with higher power generation percentage of the renewable energy sources. Based on the background, the applicant provides the method for making the annual maintenance plan of the power system, introduces two expected indexes of low flexibility, namely expected electric quantity abandonment and expected load loss, as measures of system flexibility, comprehensively considers the problems of system reliability and electricity abandonment, and heuristically selects the planned maintenance time interval of the line to be maintained or the thermal power generating unit according to the expected low flexibility in each preset time interval in the whole year, so that the difference of the expected indexes of low flexibility in each preset time interval is minimum, and the purpose of making the annual maintenance plan which considers both the system reliability and the electricity abandonment economy and is suitable for the power system with higher renewable energy power generation ratio is achieved. In addition, it should be noted that the applicant has paid a lot of creative efforts in finding the technical problems of the present application and the technical solutions described in the following embodiments.

The method for making the annual maintenance plan of the power system can be applied to a terminal, a server and a system comprising the terminal and the server, and is realized through interaction of the terminal and the server. The terminal can be, but is not limited to, various personal computers, notebook computers, smart phones and tablet computers, and the server can be implemented by an independent server or a server cluster formed by a plurality of servers.

In one embodiment, an annual overhaul plan making method for a power system is provided, which is described by taking as an example an annual overhaul plan applied to a terminal for making a power system including a thermal power generation power source and a renewable energy power generation power source, wherein the renewable energy power generation power source includes wind power generation and solar power generation. The terminal may obtain related data parameters for subsequently executing the method of the present application, where in one example, the related data parameters include:

a reference capacity of the power system;

node information: the method comprises the steps of determining the type (determining a balance node of the direct current load flow calculation), the name, the reference voltage and the active load (actual value);

generator set information of each power generation source: the method comprises the following steps of (1) including the type of a unit, a node to which the unit belongs, the unit capacity (MW) of the unit, the number of units, the minimum technical output (%) of a thermal power unit, the percentage limit of the climbing capacity per hour (%/h) of the thermal power unit, the percentage limit of the climbing capacity per hour ((%/h) of the thermal power unit, the percentage limit of the descending climbing capacity per hour (h) of the thermal power unit, the minimum starting time (h) of the thermal power unit, the starting cost (thousand yuan/MW) of the thermal power unit, the variable operation cost (thousand yuan/MWh/year) of the thermal power unit, the predicted hourly output maximum value (MW) of annual wind power generation, and the predicted hourly output maximum value (MW) of annual solar power generation;

line information: the power transmission device comprises end nodes, reference voltage, reactance, active transmission power limit, power angle range and reference nodes;

cost penalty coefficient: the method comprises the steps of (1) loss load penalty cost (thousand yuan/MWh), wind abandoning and light abandoning penalty cost (thousand yuan/MWh);

the maintenance information of the machine set: the method comprises the steps of including a unit cluster to be overhauled, the number of the units to be overhauled in the cluster, and the overhaul time of the units to be overhauled;

line maintenance information: the number of the line to be overhauled and the overhaul time of the line to be overhauled are long;

arranging the maintenance sequence;

the importance parameters of energy abandonment and load loss amount are 1.2 as default.

As shown in fig. 1, the method comprises the steps of:

step 101, establishing a power system production simulation model with the minimum running cost as an optimization target, and determining an optimal solution according to preset constraint conditions and current boundary conditions to obtain reference generated power of each power generation source contained in the power system in each first unit time period of the year and reference load loss power of each node contained in the power system in each first unit time period.

In implementation, the terminal may build a power system production simulation model with a minimum optimization goal of operating costs, including operating costs and loss-of-load costs of the power generation source. And then determining the optimal solution of the production simulation model according to the preset constraint conditions and the current production boundary conditions to obtain the reference generating power of each generating power supply in each first unit time interval of the whole year and the reference load shedding power of each node in each first unit time interval. The step size of the first unit time interval can be determined according to the predicted fluctuation situation of the wind power generation and the solar power generation all the year around, for example, the step size can be set to be 1 hour, 2 hours, 3 hours and the like, and the shorter the step size is, the stronger the depicting ability of the short-time fluctuation of the wind power generation and the solar power generation is, and the higher the calculation accuracy is relatively.

Further, the power generation source may be a power generation cluster. The power generation cluster means that power generation power supplies under the same node are equivalently integrated according to type aggregation, and the calculated reference power generation power of the power generation cluster is the sum of the reference power generation power of each power generation power supply in the power generation cluster. Specifically, thermal power generation power supplies at the same node are aggregated into a thermal power cluster, and renewable energy power generation power supplies at the same node are aggregated into a renewable energy power generation cluster. If the same node contains multiple renewable energy sources, the renewable energy sources are respectively aggregated according to the types of the renewable energy sources, namely the wind power generation power supplies are aggregated into a wind power generation cluster, and the solar power generation power supplies are aggregated into a solar power generation cluster. Technical and economic parameters of the power generation cluster can be determined according to each power generation source in the cluster, for example, parameters of each power generation source in the power generation cluster can be simply summed or weighted and averaged according to the parameter type, or the parameter of one power generation source is specified as the standard. For example, the generating capacity of the generating cluster is the sum of the generating capacities of all the generating power sources in the cluster, and the unit generating cost coefficient, the climbing rate, the minimum technical output and other technical parameters can adopt weighted average or be specified by taking the parameter of a certain generating power source in the cluster as a reference. The power generation power supplies under each node are equivalently aggregated into a power generation cluster, so that the data volume participating in calculation is reduced, and the calculation efficiency can be improved.

The formula of the production simulation model established in this embodiment is:

wherein p is_c，b，tRepresenting the generated power of the thermal power cluster c under the node b in a first unit time period t; s_c，b，tRepresenting the capacity of the thermal power cluster c under the node b, which is converted from a shutdown state to a startup state in a first unit time period t; p is a radical of_r，b，tRepresenting the generated power of a renewable energy power generation cluster r under a node b contained in the power system in a first unit time period t; u. of_b，tRepresenting the power loss of a node b contained in the power system in a first unit time period t; f. of_c，b，tRepresenting a unit electric quantity power generation cost coefficient of the thermal power cluster c under the node b in a first unit time period t; v. of_c，b，tRepresenting a unit electric quantity start-stop cost coefficient of the thermal power cluster c under the node b in a first unit time period t;

representing the maximum generated power of the renewable energy power generation cluster r under the node b in a first unit time period t; w represents a unit electric quantity electricity abandoning cost coefficient of the renewable energy power generation cluster; q represents a unit electric quantity load loss cost coefficient of the power system; Δ t represents a step size of the first unit period t; c represents a thermal power cluster set contained in the power system; b represents a node set contained in the power system; r represents a renewable energy power generation cluster contained in a power systemGathering; t denotes a set of the respective first unit periods.

The constraints employed include:

(1) thermal power cluster power generation capacity and start-stop capacity relation constraint

Wherein o is_c，b，tRepresents the capacity, S, of the thermal power cluster c at the node b in the first unit time period t_c，b，tAnd z_c，b，tAnd capacities of the thermal power cluster c under the node b from shutdown to startup and from startup to shutdown in the first unit time period t are respectively represented.

(2) Range constraints on generating capacity of thermal power cluster

Wherein,C _c，brepresenting the minimum technical output percentage requirement of the thermal power cluster c under the node b,

representing the maximum generated power N of the thermal power cluster c under the node b in a first unit time period t_c，bAnd the installed capacity of the thermal power cluster c under the node b is shown.

(3) Power generation capability constraints for renewable energy power generation clusters

(4) Node power balance constraints

Wherein f is_ib，tRepresenting active power flowing from other nodes to node b in the first unit time period tTidal current, f_dj，tRepresenting the active power flow from node b for a period t, d_b，tRepresenting the load power, u, at node b for a first unit period of time, t_b，tRepresenting the power off load at node b for the first unit period of time t.

(5) System spare capacity constraint

Where ρ is_tRepresenting the minimum spare capacity requirement for time period t.

(6) Start-stop time constraint of thermal power cluster

Wherein, UT_cRepresenting the minimum time interval requirement of the thermal power cluster c for switching from the shutdown state to the startup state; DT_cIndicating a minimum time interval requirement for the thermal power cluster c to transition from the on-state to the off-state.

(7) Uphill restriction of thermal power cluster

Wherein,

and (4) representing the percent limitation of the climbing capacity of the thermal power cluster c under the node b in unit time.

(8) Downhill slope constraint of thermal power cluster

Wherein,R _c，band (4) representing the percent limitation of the climbing capacity of the thermal power cluster c under the node b in unit time.

(9) DC power flow solution

Wherein f is_jk，tRepresenting the active power flow of a line with j and k as endpoints from a node j to a node k in a time period t; theta_j，tRepresenting the power angle of the node j in the time period t; x is the number of_jkRepresenting the reactance values of the lines with j and k as endpoints; f_jkThe maximum allowable active power flow on the line with j and k as end points;θ _iand

the minimum value and the maximum value of the work angle are respectively expressed;

representing the power angle of the reference node in time period t; b_bjRepresenting the inverse reactance of each branch connected to node b.

In this embodiment, the step length of the first unit time interval may be set to 1 hour, and the optimal solution of the production simulation model is calculated by using the constraint condition and the current boundary condition, so that the hourly reference generated power of each power generation cluster and the hourly reference off-load power of each node can be obtained. The boundary conditions comprise the generating capacity of the thermal power cluster and the maximum allowable flowing active power flow on the line between the nodes. The production simulation model is a linear programming problem and can be directly called a commercial solver to solve.

102, determining expected electricity abandon quantity corresponding to each second unit time interval of the whole year according to reference power generation of a renewable energy power generation source in the power generation source; determining the load loss amount expectation corresponding to each second unit time interval according to the reference load loss power; the second unit period is greater than the first unit period.

In an implementation, the terminal may calculate the expected amount of electricity curtailment corresponding to each second unit period of the year based on the reference generated power hourly through the year obtained in step 101 for each renewable energy power generation source (if the power generation source is a power generation cluster in step 101, each renewable energy power generation cluster). And calculating the load loss amount expectation corresponding to each second unit time interval according to the reference load loss power hourly throughout the year obtained in the step 101. The step length of the second unit time interval can be determined according to the step length of the first unit time interval and the time length required by maintenance equipment, is generally longer than the first unit time interval and shorter than the time length required by maintenance equipment, and can be 1 day, 3 days, 1 week, 2 weeks and the like.

In this embodiment, the step size of the second unit time interval may be set to 1 week, and the expected amount of electricity left and the expected amount of load lost in each week in 52 weeks of the year may be calculated. For example, the power curtailment expectation (which may be noted as week w) of

) And expected loss of load (which can be recorded as

) Respectively as follows:

where W denotes a set of first unit periods t corresponding to the W-th week. In this embodiment, if the step size of the first unit time period t is 1 hour, W represents a set of every hour corresponding to the W-th week.

103, when the maximum value in the electric quantity abandoning expectation is larger than a preset electric quantity abandoning expectation threshold, determining a scheduled maintenance time period of the current equipment to be maintained according to the type of the current equipment to be maintained and the maximum value or the minimum value of the electric quantity abandoning expectation; the preset electricity abandoning amount expected threshold value is determined according to the maximum expected loss load amount and a preset coefficient.

In implementation, the terminal may determine a maximum value of the expected electric energy curtailment amount according to the expected electric energy curtailment amount of the whole year per week and the expected off-load amount of the whole year per week obtained in step 102 (which may be recorded as:

) The formula is expressed as:

and the expected maximum value of the loss load (which can be written as:

) The formula is expressed as:

then according to the expected maximum value of the load loss amount

And a preset coefficient (can be recorded as eta), determining a preset expected threshold of the abandoned electric quantity, wherein the preset coefficient eta is an importance parameter and can take values of 1.1, 1.2, 1.5, 2 and the like. When the expected maximum value of the electricity abandon quantity

When the power is larger than the preset expected power abandon threshold, the formula is as follows: when in use

And determining the scheduled maintenance time interval of the current equipment to be maintained according to the type of the current equipment to be maintained and the second unit time interval corresponding to the maximum value or the minimum value of the expected electric quantity abandon. For example, the first day of the period corresponding to the expected maximum of the electric discard quantity may be used as the maintenance starting time of the current equipment to be maintained.

And step 104, when the expected maximum value of the electric energy abandonment is smaller than or equal to a preset electric energy abandonment expected threshold value, determining the scheduled maintenance time interval of the current equipment to be maintained according to the expected minimum value of the load loss.

In implementation, the terminal may determine the minimum expected loss capacity value according to the expected loss capacity value obtained in step 102 every week (which may be expressed as:

) The formula is expressed as:

when in use

When the load is not enough, the expected minimum value is obtained according to the load loss

And determining the scheduled maintenance time interval of the current equipment to be maintained according to the corresponding second unit time interval. For example, the first day of the period corresponding to the expected minimum value of the loss load amount may be used as the maintenance start time of the current equipment to be maintained.

And 105, modifying the boundary conditions in the constraint conditions according to the planned overhaul time interval of the current equipment to be overhauled, and determining the planned overhaul time interval of the next equipment to be overhauled until the planned overhaul time intervals of all the equipment to be overhauled are obtained.

In implementation, the terminal may modify a corresponding boundary condition in the constraint condition according to the scheduled maintenance time interval of the current equipment to be maintained determined in step 103 or step 104, for example, if the current equipment to be maintained is a thermal power generating unit, setting an amount of generated energy of the thermal power generating unit in the scheduled maintenance time interval thereof one by one (step size of the first unit time interval is 1 hour in this embodiment) to be 0, and accordingly, an amount of generated energy of the power generation cluster to which the thermal power generating unit belongs is changed; and if the current equipment to be overhauled is a line, setting the maximum allowable active power flow of the line to be 0 in the corresponding scheduled overhaul time interval of the line. And according to the modified production simulation boundary conditions, calculating the optimal solution of the production simulation model again, and determining the planned maintenance time interval of the next equipment to be maintained until the planned maintenance time intervals of all the equipment to be maintained are obtained, namely finishing the formulation of the annual maintenance plan of the power system.

In this embodiment, a production simulation model with the minimum running cost as an optimization target is established, reference generated power of each power generation power source and reference off-load power of each node included in the power system are calculated, and an expected index with insufficient flexibility is calculated according to the reference generated power and the reference off-load power of the renewable energy power generation power source: when the maximum value of the expected abandoned electric quantity is larger than the preset coefficient proportion of the maximum value of the expected lost load, the cost of the abandoned electric quantity is higher than the lost load by the preset proportion, and the electricity abandoning economy of the power system needs to be considered, so the electricity abandoning risk is used as a measurement index to arrange an equipment overhaul period; otherwise, considering the reliability of the power utilization of the system as a main factor, and arranging the equipment overhaul time period by taking the load loss risk as a measurement index. In the embodiment, two low-flexibility expected indexes of expected electric quantity abandoning and expected load losing are introduced as the measurement of the flexibility of the system, the problems of system reliability and electricity abandoning are considered comprehensively, the overhaul time of the equipment to be overhauled is determined in a heuristic manner according to the low-flexibility expected indexes of all preset time intervals in the whole year, so that the low-flexibility expected index difference in all the preset time intervals is minimum, the system reliability and electricity abandoning economy can be considered, and the method is suitable for the annual overhaul plan formulation of the power system with higher renewable energy power generation ratio.

In one embodiment, the method further comprises the steps of:

according to the scheduled maintenance time interval of all the equipment to be maintained, modifying the boundary conditions in the constraint conditions, and determining the scheduled generating power of each generating power supply in each first unit time interval; and determining the annual planned power generation amount of the power system according to the planned power generation amount.

In implementation, the terminal modifies corresponding boundary conditions in the constraint conditions in step 101 according to the planned maintenance time periods of all the equipment to be maintained obtained in step 105, calculates the optimal solution of the production simulation model, and then obtains the planned generating power of each generating power source hourly all year around, and determines the planned generating capacity of the power system all year around according to the planned generating power. For example, the planned power generation amount of each type of power generation source can be calculated year by year according to the planned power generation amount hour by hour all year around, and the calculation formula is as follows:

wherein E is_thermal，w，E_wind，wAnd E_solar，wThe planned power generation amounts in the w-th week of the thermal power generation, wind power generation, and solar power generation power sources are shown, respectively.

According to the embodiment, a annual power generation plan can be further formulated according to a formulated result of an annual maintenance plan, and the annual power generation plan formulated by the method can be calculated by adopting fine time precision simulation with the step length of hour, so that the depicting capability of short-time fluctuation of wind power generation and solar power generation is ensured, and the method is more suitable for calculating the power generation of the renewable energy power generation power supply with the characteristic of short-time strong fluctuation. In addition, the annual energy production plan cares about the consumption potential of wind power generation and solar power generation in the future year, so that the spatial resolution of production simulation is reduced, and the aggregation equivalence of the same type of units is feasible, so that the calculation efficiency of the annual energy production plan and the maintenance plan can be improved by aggregating power generation power supplies into a power generation cluster and adopting a heuristic maintenance optimization method.

In one embodiment, step 101 specifically includes the following steps:

dividing the whole year into a plurality of time intervals according to preset time length to obtain each third unit time interval; the third unit period is greater than the first unit period; and respectively establishing a production simulation model with the minimum running cost as an optimization target for each third unit time interval, and determining an optimal solution according to the constraint condition and the current boundary condition to obtain the reference generating power of each generating power source contained in the power system in each first unit time interval in the third unit time interval and the reference load shedding power of each node contained in the power system in each first unit time interval in the third unit time interval.

In implementation, the step size of the third unit period may be set to 1 week, i.e., the whole year may be divided into 52 weeks. And for each week of the whole year, the terminal respectively establishes a production simulation model taking the minimum running cost as an optimization target, and simultaneously calculates the optimal solution of each production simulation model according to the constraint conditions and the current boundary conditions, so that the reference generating power of each generating power supply in each hour of each week and the reference load loss power of each node in each hour of each week can be obtained. And integrating the data of each week to obtain the reference generating power of each generating power supply hourly all year and the reference load loss power hourly all year.

Because the results of the annual overhaul plan and the annual power generation plan are more in stress on the feasibility of the results and allow deviation of execution on a short time scale, the method can consider searching a production simulation model suboptimal solution rather than an optimal solution, namely segmenting a sequence to be simulated and introducing parallel computation. Therefore, the embodiment divides the long-time sequence of the whole year into a plurality of time intervals according to the preset intervals, so that the large-scale solution model is divided into a plurality of optimization solution problems of the short-time sequence, the association of physical quantities among the optimization problems of the short-time sequence can be ignored, the parallel computing strategy is adopted, the solution is accelerated, and the computing efficiency is improved.

In one embodiment, the types of equipment to be overhauled comprise a thermal power generating unit and a line; the determination of the planned overhaul period in step 103 specifically includes the following steps:

under the condition that the current equipment to be overhauled is a thermal power generating unit, determining a scheduled overhaul time period of the current equipment to be overhauled according to a second unit time period corresponding to the maximum expected electric quantity abandoning value; and under the condition that the current equipment to be overhauled is a line, determining the scheduled overhaul time period of the current equipment to be overhauled according to the second unit time period corresponding to the minimum expected electric quantity abandoning value.

In the implementation, the thermal power generating unit has a large power generation scale, the overhaul time is relatively long and generally needs several weeks, the renewable energy has the characteristic of intermittence, and the existing single renewable energy generating unit has a small scale and relatively short overhaul time and can be overhauled by using an energy intermittence period, so the annual overhaul schedule of the thermal power generating unit and a line is mainly considered in the annual overhaul plan of the power system of the embodiment.

The terminal can acquire the type of the current equipment to be overhauled, and if the current equipment to be overhauled is a thermal power generating unit, the scheduled overhaul time period of the current equipment to be overhauled is determined according to the time period corresponding to the maximum expected electric quantity abandoning value; and under the condition that the current equipment to be overhauled is a line, determining the scheduled overhaul time period of the current equipment to be overhauled according to the time period corresponding to the minimum expected electric quantity abandoning value.

Considering that the thermal power generating unit stops generating power during the overhaul period, the time period corresponding to the expected maximum value of the abandoned power amount is selected to determine the planned overhaul time period of the thermal power generating unit to be overhauled, so that wind power and solar power can be fully utilized to generate power during the overhaul period, a large amount of wind and light energy which are abandoned originally is consumed, the power which can be generated by the thermal power generating unit originally is supplemented, and the cost of abandoned power can be reduced while the system is kept stable. In addition, considering that the line cannot transmit electric energy during maintenance, in order to avoid further increasing the electricity abandonment cost, a time interval corresponding to the minimum expected value of the electricity abandonment quantity is selected to determine the planned maintenance time interval of the current line to be maintained, so that the system is ensured to be stable as much as possible, and meanwhile, the sinking cost in the maintenance period is reduced.

In one embodiment, the determining the planned maintenance period of the train in step 103 specifically includes the following steps:

under the condition that the current equipment to be overhauled is a thermal power generating unit, determining each time period combination which comprises a second unit time period corresponding to the maximum expected electric quantity abandoning value and accords with the condition of overhauling time period according to the overhauling time period of the current equipment to be overhauled; determining the electric quantity abandoned corresponding to each time interval combination according to the reference power generation of the renewable energy power generation source and the maximum power generation power of the renewable energy power generation source in each first unit time interval of the whole year; and determining the time interval combination corresponding to the maximum electric quantity discarded as the scheduled maintenance time interval of the current equipment to be maintained.

In implementation, the terminal can obtain the type and the overhaul duration of the current equipment to be overhauled and the maximum power generation power of each renewable energy power generation source in each first unit time period all the year around. The maintenance of waiting to overhaul equipment is long for overhauing the required basic time of this equipment, and long generally is the week if the maintenance of thermal power generating unit and circuit, and it can be appointed by the manual work to overhaul time, and the terminal directly acquires can. Under the condition that the current equipment to be overhauled is a thermal power generating unit, the expected maximum value of the abandoned electric quantity

And taking the corresponding second unit time interval as a target time interval, and determining each time interval combination which comprises the target time interval and meets the overhaul time length condition. The overhaul length condition may be equal to the overhaul length. The renewable energy power generation sources obtained according to step 101 are then at each timeThe reference generated power per hour (the step size of the first unit period is set to 1 hour in this embodiment) in the combination of the segments, and the aforementioned maximum generated power, calculate the amount of electricity discarded corresponding to each combination of the segments. And then determining the time interval combination corresponding to the maximum electric quantity discarded as the planned maintenance time interval of the thermal power generating unit to be maintained.

In a specific example, the step length of the first unit period is set to be 1 hour, the step length of the second unit period is set to be 1 week, and the overhaul time length condition of the thermal power generating unit to be overhauled at present is set to be 3 weeks. Obtaining the expected maximum value of the electricity abandonment quantity according to the calculation

The corresponding target period is week 17, so that three eligible combinations of periods can be determined, respectively: weeks 15 to 17, weeks 16 to 18, weeks 17 to 19. And calculating the electricity abandonment amount in the 15 th to 17 th weeks, the electricity abandonment amount in the 16 th to 18 th weeks and the electricity abandonment amount in the 17 th to 19 th weeks respectively according to the reference generated power of each renewable energy source hourly in the 15 th to 19 th weeks obtained in the step 101. And determining the 17 th week, the 18 th week and the 19 th week as the scheduled maintenance time interval of the thermal power generating unit to be maintained currently if the value of the electricity abandonment amount in the 17 th week to the 19 th week is relatively maximum.

In this embodiment, when the current device to be overhauled is a thermal power generating unit, according to a target time period corresponding to a maximum expected electric quantity and an overhaul time length condition of the current device to be overhauled, each time period combination including the target time period and meeting the overhaul time length condition is determined. And then calculating the electricity abandonment amount of each time interval combination, and determining the time interval combination corresponding to the maximum value of the electricity abandonment amount as a scheduled maintenance time interval. The embodiment further optimizes the selection method of the scheduled maintenance time interval, and can improve the system reliability and electricity abandonment economy in the maintenance period.

In one embodiment, the step 103 of determining the scheduled maintenance time period of the line specifically includes the following steps:

under the condition that the current equipment to be overhauled is a line, determining each time period combination which comprises a second unit time period corresponding to the minimum expected electric quantity abandoning value and accords with the condition of overhauling time period according to the overhauling time period of the current equipment to be overhauled; determining the electric quantity abandoned corresponding to each time interval combination according to the reference power generation of the renewable energy power generation source and the maximum power generation power of the renewable energy power generation source in each first unit time interval of the whole year; and determining the time interval combination corresponding to the minimum electric quantity discarded as the scheduled maintenance time interval of the current equipment to be maintained.

In implementation, the terminal can obtain the type and the overhaul duration of the current equipment to be overhauled and the maximum power generation power of each renewable energy power generation source in each first unit time period all the year around. When the current equipment to be overhauled is a line, the expected minimum value of the electricity abandonment quantity is

And taking the corresponding second unit time interval as a target time interval, and determining each time interval combination which comprises the target time interval and meets the overhaul time length condition. And then, calculating the electricity abandon amount corresponding to each time interval combination according to the reference generated power of the renewable energy power source obtained in the step 101 in each first unit time interval in each time interval combination and the maximum generated power. And then combining the time intervals corresponding to the minimum value of the electric quantity abandon to determine the time interval as the scheduled maintenance time interval of the current line to be maintained.

In this embodiment, when the current device to be overhauled is a line, according to a target time period corresponding to a minimum expected electric quantity and an overhaul time length condition of the current device to be overhauled, each time period combination including the target time period and meeting the overhaul time length condition is determined. And then calculating the electricity abandonment amount of each time interval combination, and determining the time interval combination corresponding to the minimum value of the electricity abandonment amount as a scheduled maintenance time interval. The embodiment further optimizes the selection method of the scheduled maintenance time interval, and can improve the system reliability in the maintenance period.

In one embodiment, the determining of the planned overhaul period in step 104 specifically includes the following steps:

determining a second unit time interval corresponding to the expected minimum value of the load loss amount and each time interval combination which meets the condition of the overhaul time interval according to the overhaul time interval of the current equipment to be overhauled; determining the load loss amount corresponding to each time period combination according to the reference load loss power; and determining the time interval combination corresponding to the minimum value of the load loss amount as the scheduled maintenance time interval of the current equipment to be maintained.

In implementation, the terminal can obtain the overhaul duration of the current equipment to be overhauled and the expected minimum value of the load loss amount

And taking the corresponding second unit time interval as a target time interval, and determining each time interval combination which comprises the target time interval and meets the overhaul time length condition. And then, calculating the load loss amount corresponding to each time interval combination according to the load loss amount of each node in each first unit time interval in each time interval combination obtained in the step 101. And then determining the time interval combination corresponding to the minimum value of the load loss amount as the planned maintenance time interval of the current line to be maintained.

In a specific example, the step length of the first unit period is set to be 1 hour, the step length of the second unit period is set to be 1 week, and the overhaul time length condition of the current equipment to be overhauled is set to be 5 weeks. Obtaining the expected minimum value of the load loss amount according to calculation

The corresponding target period is week 45, so that 5 eligible combinations of periods can be determined, respectively: weeks 41 to 45, weeks 42 to 46, weeks 43 to 47, weeks 44 to 48, weeks 45 to 49. And respectively calculating the load loss amount in each time interval combination according to the load loss amount of each node in 41 th to 49 th weeks in step 101. Wherein, the value of the load loss amount in the 43 th to 47 th weeks is relatively minimum, so that the 43 th week is taken as the maintenance starting week of the current equipment to be maintained, and the 47 th week is taken as the maintenance finishing week of the current equipment to be maintained.

In this embodiment, when

And then determining each time interval combination which comprises the target time interval and meets the condition of the overhaul time interval according to the target time interval corresponding to the expected minimum value of the load loss and the overhaul time interval of the current equipment to be overhauled. And then calculating the load loss amount of each time interval combination, and determining the time interval combination corresponding to the minimum value of the load loss amount as a planned maintenance time interval. The embodiment further optimizes the selection method of the scheduled maintenance time interval, and can improve the system reliability in the maintenance period.

In one embodiment, the method further comprises the steps of:

and determining the scheduled maintenance time interval of each equipment to be maintained according to the priority sequence of each equipment to be maintained, wherein the priority of the line is higher than that of the thermal power generating unit.

In implementation, each device to be overhauled may be prioritized first and numbered in sequence. The priority of the line is higher than that of the thermal power generating unit, namely the number of the thermal power generating unit is behind that of the line. The terminal can obtain the serial number of each device to be overhauled, and the scheduled overhaul time interval of the devices to be overhauled is determined one by one according to the serial number sequence.

The priority of the circuit is higher than that of the thermal power generating unit, the planned maintenance time intervals of the circuit are determined one by one, after all the circuits are determined, the circuits in the time intervals can be determined, electric energy cannot be transmitted, the planned maintenance time intervals of the thermal power generating unit are determined one by one, and the accuracy of maintenance planning can be improved.

It should be understood that, although the steps in the flowchart of fig. 1 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 1 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.

The application also provides a specific example, and the method for making the annual maintenance plan of the power system is applied to a personal computer and used for making the annual maintenance plan and the annual power generation plan of an HRP-38 example system. All required data parameters were taken from region 5 of the HRP-38 algorithm. The region comprises 36 thermal power generating units, 444 solar generating units and 216 wind generating units, and the installation ratio is respectively 51%, 33% and 16%.

The system configuration of the personal computer is as follows: 3.20GHz CPU, 16GB memory. And calculated based on the commercial solvers MATLAB R2018a and CPLEX 12.9. The following are the calculation results:

(1) result of maintenance plan

The results of the maintenance schedule for all the equipment to be maintained are shown in table 1.

TABLE 1 maintenance planning results for the equipment to be maintained

Maintenance equipment	Initial period of maintenance	Week after the completion of maintenance
			1 node next 1000MW thermal power generating unit	17	19
1 node next 1000MW thermal power generating unit	43	47
			Connecting a return line between nodes 1 and 2	12	14

(2) Planned result of electric quantity

The results of the 52-cycle power generation planning of wind power generation, solar power generation and thermal power generation in this application example scenario are shown in fig. 2, 3 and 4, respectively.

(3) Time of use result of calculation

The calculation time is 564.0287 s.

According to the results, the method for making the annual maintenance plan of the power system and the method for making the annual power generation plan of the power system are applicable to the power system with high wind power and solar power generation ratio, and the planning efficiency is high.

In one embodiment, as shown in fig. 5, there is provided an annual overhaul scheduling device for a power system, including: a production simulation model establishing module 501, a flexibility index determining module 502, a scheduled maintenance period determining module 503 and a boundary condition modifying module 504, wherein:

the production simulation model establishing module 501 is configured to establish a power system production simulation model with the minimum operation cost as an optimization target, and determine an optimal solution according to a preset constraint condition and a current boundary condition to obtain reference generated power of each power generation source included in the power system in each first unit time period of the year and reference lost load power of each node included in the power system in each first unit time period.

A flexibility index determination module 502, configured to determine, according to a reference power generation power of a renewable energy power generation source in the power generation sources, a power curtailment expectation corresponding to each second unit time period of the year; determining the load loss amount expectation corresponding to each second unit time interval according to the reference load loss power; the second unit period is greater than the first unit period.

A scheduled maintenance time interval determining module 503, configured to determine a scheduled maintenance time interval of the current equipment to be maintained according to the type of the current equipment to be maintained and the maximum value or the minimum value of the expected electric energy discard amount when the maximum value of the expected electric energy discard amount is greater than a preset electric energy discard amount expected threshold; the preset electricity abandoning amount expected threshold value is determined according to the maximum expected loss load amount and a preset coefficient.

The scheduled maintenance time interval determination module 503 is further configured to determine a scheduled maintenance time interval of the current equipment to be maintained according to the expected minimum value of the loss load amount when the expected maximum value of the loss electric quantity is less than or equal to a preset expected threshold value of the loss electric quantity.

And the boundary condition modifying module 504 is configured to modify the boundary conditions in the constraint conditions according to the planned maintenance time period of the current equipment to be maintained, and determine the planned maintenance time period of the next equipment to be maintained until the planned maintenance time periods of all the equipment to be maintained are obtained.

In one embodiment, the apparatus further comprises:

the annual planned power generation determining module is used for modifying boundary conditions in the constraint conditions according to planned maintenance time intervals of all equipment to be maintained and determining planned power generation power of each power generation power supply in each first unit time interval; and determining the annual planned power generation amount of the power system according to the planned power generation amount.

In one embodiment, the production simulation model building module 501 is specifically configured to:

In one embodiment, the scheduled overhaul period determination module 503 is specifically configured to:

In one embodiment, the boundary condition modification module 504 is specifically configured to:

For specific limitations of the power system annual overhaul planning device, reference may be made to the above limitations of the power system annual overhaul planning method, which is not described herein again. All or part of each module in the annual overhaul planning device for the power system can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 6. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile 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 an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a method of scheduling annual maintenance of an electrical power system. The display screen of the computer equipment 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, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.

Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the above-described method embodiments when executing the computer program.

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

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims

1. A method for making an annual maintenance plan of a power system is characterized by comprising the following steps:

2. The method of claim 1, further comprising:

3. The method of claim 1, wherein each of the power generation sources is a power generation cluster, each of the power generation clusters including at least a thermal power cluster and at least one renewable energy power generation cluster;

4. The method according to claim 1, wherein the establishing of the power system production simulation model with the minimum operation cost as the optimization target and the determining of the optimal solution according to the preset constraint condition and the current boundary condition to obtain the reference generated power of each power generation source included in the power system in each first unit time period of the year and the reference lost load power of each node included in the power system in each first unit time period comprises:

5. The method of claim 1, wherein the types of equipment to be overhauled include thermal power generating units and electrical lines; the determining the scheduled maintenance time interval of the current equipment to be maintained according to the type of the current equipment to be maintained and the expected maximum value or minimum value of the electric energy abandon quantity comprises the following steps:

6. The method according to claim 5, wherein the determining the scheduled maintenance time interval of the current equipment to be maintained according to the second unit time interval corresponding to the maximum expected electric energy curtailment amount when the current equipment to be maintained is a thermal power generating unit comprises:

7. The method according to any one of claims 1 to 6, wherein the types of equipment to be overhauled include thermal power generating units and lines; the method further comprises the following steps:

8. An electric power system annual maintenance planning device, characterized in that the device includes:

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.