New-energy-containing multi-power-source electric power system annual cold and hot standby distribution method and device, terminal equipment and storage medium

Abstract

The invention discloses an annual cold and hot standby distribution method and device for a multi-power-source electric power system containing new energy, terminal equipment and a storage medium, and belongs to the technical field of electric power system operation, and the method comprises the steps: generating an approximate weekly continuous load curve according to a first annual load curve; wherein the approximate weekly continuous load curve comprises a plurality of load segments, and the load of each load segment corresponds to one segment load level; constructing an annual operation model according to all the approximate weekly continuous load curves; and solving the annual operation model under unit maintenance constraint, unit operation constraint, new energy power operation constraint and system operation constraint, and calculating cold reserve capacity and hot reserve capacity of each week according to a model solving result. According to the method, the problem scale is remarkably reduced, the solving efficiency is improved, and the problem of overlong solving time caused by overlarge problem scale in the prior art can be solved.

Description

Technical Field

[0001] This invention relates to the field of power system operation technology, and in particular to a method, apparatus, terminal equipment, and storage medium for annual cold and hot reserve allocation in a multi-source power system containing new energy sources. Background Technology

[0002] To address the environmental pollution, global warming, and resource shortages caused by fossil fuel utilization and to achieve sustainable and healthy energy development, countries worldwide are vigorously developing new energy sources and increasing their proportion in the energy mix as a key development strategy. However, with the increasing proportion of new energy, the seasonal characteristics of new energy sources and the resulting mismatch between supply and demand pose significant challenges to the safe and stable operation of power systems. Therefore, it is urgent to allocate appropriate cold and hot reserves in a reasonable manner to ensure the safe and economical operation of the system. Medium- and long-term simulation is an important component of power system production simulation. Obtaining cold and hot reserve allocation schemes through medium- and long-term simulation is a crucial way to handle and address the seasonal characteristics of clean energy power. However, since the unit maintenance issues in medium- and long-term simulations span a year or several years, using hourly time-series load curves would lead to an excessively large problem scale, resulting in excessively long solution times. Summary of the Invention

[0003] This invention provides a method, apparatus, terminal equipment, and storage medium for annual cold and hot reserve allocation in a multi-source power system with new energy sources. It can solve the problem that the existing technology, which uses hourly time-series load curves, leads to an excessively large problem scale and thus a long solution time.

[0004] An embodiment of the present invention provides a method for annual cold and hot reserve allocation in a multi-source power system containing new energy sources, comprising:

[0005] Obtain the first-year load curve of the power system;

[0006] The first year's load curve is divided into several weekly load curve segments;

[0007] For each weekly load curve, the load data of the weekly load curve is arranged in descending order to obtain an accurate weekly continuous load curve; based on several preset segmented load levels, an approximate weekly continuous load curve with the same power as the accurate weekly continuous load curve is generated; wherein, the approximate weekly continuous load curve contains several load segments, and the load of each load segment corresponds to one segmented load level.

[0008] Based on all the approximate weekly continuous load curves, the duration of each load segment in each week is obtained;

[0009] Based on the duration, an annual operation model is constructed with the objectives of minimizing system operating costs, minimizing load loss, and minimizing renewable energy curtailment.

[0010] Under constraints of unit maintenance, unit operation, new energy power operation, and system operation, the annual operation model is solved to obtain the unit start-up and shutdown status, unit maintenance status, and unit output for each week.

[0011] Based on the unit's start-up and shutdown status, maintenance status, and output, calculate the cold reserve capacity and hot reserve capacity for each week.

[0012] Furthermore, the objective function of the annual operating model is:

[0013] min(C1+αC2+βC3);

[0014]

[0015] In the formula, C1 represents the system operating cost; C2 represents the total power loss due to load; C3 represents the total power curtailment of renewable energy; α represents the system load loss penalty coefficient; β represents the system renewable energy curtailment penalty coefficient; gs represents the gs-th thermal power plant; g′∈gs represents the g′-th thermal power unit belonging to gs; b represents the b-th load segment; B represents the total number of load segments in this week; t represents the t-th week; T represents the number of weeks in a year; f g (·) represents the power generation cost function of thermal power units; p g,t,b D represents the output of the g-th thermal power unit in the b-th load segment of week t; t,b LC represents the duration of the b-th load segment in week t; t,b Represents the load shedding amount in the b-th load segment of week t; RC t,b This represents the amount of renewable energy wasted in the b-th load segment of week t.

[0016] Furthermore, the process of constructing the operational constraints of the new energy power system includes:

[0017] Obtain time-series power output data for new energy sources;

[0018] For each load segment, the renewable energy time-series output data corresponding to the load segment is clustered into a preset number of scenario clusters; based on the number of renewable energy time-series output data corresponding to each scenario cluster and the number of renewable energy time-series output data corresponding to the load segment, the probability of scenario occurrence for each scenario cluster is calculated.

[0019] Based on the duration and the probability of occurrence of the scenario, new energy power operation constraints are constructed;

[0020] The operating constraints of the new energy power are as follows:

[0021]

[0022] In the formula, RE t,b π represents the probabilistic output of new energy scenarios in the b-th load segment of week t; s represents the s-th scenario, i.e., the s-th scenario cluster; π s This represents the probability of a scene occurring in the s-th scene cluster. This represents the renewable energy output of the b-th load segment in week t; This represents the upper limit of renewable energy output for the b-th load segment in week t; D represents the lower limit of renewable energy output for the b-th load segment in week t; t,b LC represents the duration of the b-th load segment in week t; t,b Represents the load shedding amount in the b-th load segment of week t; RC t,b This represents the amount of renewable energy wasted in the b-th load segment of week t.

[0023] Furthermore, the unit maintenance constraints include: unit maintenance frequency constraints, unit maintenance time constraints, unit maintenance capacity constraints, unit maintenance continuity constraints, and unit maintenance time interval constraints.

[0024] The constraint on the number of unit maintenance cycles is:

[0025]

[0026]

[0027] In the formula, g represents the g-th thermal power unit; h represents the h-th hydropower unit; p represents the p-th pumped-storage unit; z g,t z represents a 0-1 variable indicating the start of maintenance for the g-th thermal power unit in week t. When the g-th thermal power unit begins maintenance in week t, z... g,t The value is 1, otherwise z g,t The value is 0; z h,t z represents a 0-1 variable indicating that the h-th hydropower unit begins maintenance in week t. When the h-th hydropower unit begins maintenance in week t, z... h,t The value is 1, otherwise z h,t The value is 0; z p,t This represents a 0-1 variable indicating that the p-th pumped-storage unit begins maintenance in week t. When the g-th pumped-storage unit begins maintenance in week t, z... p,t The value is 1, otherwise z p,t The value is 0; MN g Indicates the number of maintenance operations required for thermal power units during the total study period; MN h Indicates the number of maintenance operations required for each hydroelectric generator unit during the total study period; MN pThis indicates the number of maintenance operations required for the pumped-storage unit during the total study period.

[0028] The unit maintenance time constraint is as follows:

[0029]

[0030] In the formula, x g,t A 0-1 variable representing whether the g-th thermal power unit is under maintenance in week t. If the g-th thermal power unit is under maintenance in week t, x... g,t The value is 1, otherwise x g,t The value is 0; x h,t A 0-1 variable representing whether the h-th hydropower unit in week t is under maintenance. If the h-th hydropower unit is under maintenance in week t, x... h,t The value is 1, otherwise x h,t The value is 0; x p,t A 0-1 variable representing whether the p-th pumped-storage unit is under maintenance in week t. If the p-th pumped-storage unit is under maintenance in week t, x... p,t The value is 1, otherwise x p,t The value is 0; MN g MN represents the duration of each maintenance operation for the g-th thermal power unit; h MN represents the duration of each maintenance check for the h-th hydropower unit; p This indicates the duration of each maintenance check for the p-th pumped-storage unit;

[0031] The unit's maintenance capacity constraint is as follows:

[0032] ∑ g′∈gs x g′,t ≤MC gs ;

[0033] ∑ h′∈hs x h′,t ≤MC hs ;

[0034] ∑ p′∈ps x p′,t ≤MC ps ;

[0035] In the formula, gs represents the gs-th thermal power plant; g′∈gs represents the g′-th thermal power unit belonging to gs; hs represents the hs-th hydropower plant; h′∈hs represents the h′-th hydropower unit belonging to hs; ps represents the ps-th pumped storage power plant; p′∈ps represents the p′-th pumped storage unit belonging to ps; MC gs This represents the number of generating units that the gs-th thermal power plant can simultaneously undergo maintenance; MC hs This represents the number of generating units that can be simultaneously maintained at the hs-th hydropower station; MC psThis represents the number of generating units that the p-th pumped storage power station can maintain simultaneously.

[0036] The continuity constraint for unit maintenance is:

[0037]

[0038] The unit maintenance interval constraint is as follows:

[0039]

[0040] In the formula, MG g MG represents the minimum time interval between two consecutive maintenance operations of the g-th thermal power unit; h MG represents the minimum time interval between two consecutive maintenance operations of the h-th hydropower unit; p This represents the minimum time interval between two consecutive maintenance operations of the p-th pumped-storage unit.

[0041] Furthermore, the unit operation constraints include: unit start-up constraints, thermal power unit constraints, hydropower unit constraints, and pumped storage unit constraints;

[0042] The unit start-up constraints are as follows:

[0043] x g,t +u g,t,b ≤1;

[0044] x h,t +u h,t,b ≤1;

[0045]

[0046] In the formula, g represents the g-th thermal power unit; h represents the h-th hydropower unit; p represents the p-th pumped-storage unit; t represents the t-th week; b represents the b-th load segment; x g,t A 0-1 variable representing whether the g-th thermal power unit is under maintenance in week t. If the g-th thermal power unit is under maintenance in week t, x... g,t The value is 1, otherwise x g,t The value is 0; x h,t A 0-1 variable representing whether the h-th hydropower unit in week t is under maintenance. If the h-th hydropower unit is under maintenance in week t, x... h,t The value is 1, otherwise x h,t The value is 0; x p,t A 0-1 variable representing whether the p-th pumped-storage unit is under maintenance in week t. If the p-th pumped-storage unit is under maintenance in week t, x... p,t The value is 1, otherwise x p,t The value is 0; u g,t,bLet u be a 0-1 variable representing the start-up / shutdown status of the g-th thermal power unit in the b-th load segment of week t. If the g-th thermal power unit in the b-th load segment of week t is in the start-up state, then u... g,t,b The value is 1, otherwise u g,t,b The value is 0; u h,t,b Let u be a 0-1 variable representing the start-up / shutdown status of the h-th hydropower unit in the b-th load segment of week t. If the h-th hydropower unit in the b-th load segment of week t is in the start-up state, then u... h,t,b The value is 1, otherwise u h,t,b The value is 0; This is a 0-1 variable representing whether the p-th pumped-storage unit in the b-th load segment of week t is in generating mode. If the p-th pumped-storage unit in the b-th load segment of week t is in generating mode... The value is 1, otherwise x h,t The value is 0; This is a 0-1 variable representing whether the p-th pumped-storage unit in the b-th load segment of week t is in pumping mode. The value is 1, otherwise The value is 0;

[0047] The constraints of the thermal power unit are:

[0048] p g,t,b -pdr g,t,b ≥p g,min u g,t,b ;

[0049] p g,t,b +pur g,t,b ≥p g,max u g,t,b ;

[0050] 0≤pdr g,t,b ≤p g,max u g,t,b ;

[0051] 0≤pur g,t,b ≤p g,max u g,t,b ;

[0052] In the formula, p g,t,b pdr represents the output of the g-th thermal power unit in the b-th load segment of week t; g,t,b This indicates the downward reserve that the g-th thermal power unit can provide in the b-th load segment of week t; pur g,t,b p represents the upward reserve that the g-th thermal power unit can provide in the b-th load segment of week t; g,min p represents the lower limit of the output of the g-th thermal power unit; g,max This represents the upper limit of the output of the g-th thermal power unit;

[0053] The constraints of the hydropower unit are:

[0054] p h,t,b -pdr h,t,b ≥p h,min u h,t,b ;

[0055] p h,t,b +pdr h,t,b ≥p h,max u h,t,b ;

[0056] 0≤pdr h,t,b ≤p h,max u h,t,b ;

[0057] 0≤pur h,t,b ≤p h,max u h,t,b ;

[0058] ∑ h′∈hs (p h′,t,b -pdr h′,t,b )≥HP hs,t,min ;

[0059] ∑ h′∈hs (p h′,t,b +pur h′,t,b )≤HP hs,t,max ;

[0060] 0≤pdr h,t,b ≤p h,max u h,t,b ;

[0061] 0≤pdr h,t,b ≤p h,max u h,t,b ;

[0062]

[0063] HE hs,t,min ≤HE hs,t +HC hs,t ≤HE hs,t,max ;

[0064]

[0065] In the formula, hs represents the hs-th hydropower station; h′∈hs represents the h′-th hydropower unit belonging to hs; B represents the total number of load segments within this week; T represents the number of weeks in a year; p h,t,b pdr represents the output of the h-th hydropower unit in the b-th load segment of week t; h,t,bThis indicates the downward reserve that the h-th hydropower unit can provide in the b-th load segment of week t; pur h,t,b p represents the upward reserve that the h-th hydropower unit can provide in the b-th load segment of week t; h,min p represents the lower limit of the output of the h-th hydropower unit; h,max HP represents the upper limit of the output of the h-th hydropower unit. hs,t,min HP represents the forced output of the hs-th hydroelectric power station in week t; hs,t,max HP represents the projected output of the hs-th hydroelectric power station in week t; hs,t HE represents the power generation of the hs-th hydroelectric power station in week t; hs,t,min HE represents the lower limit of the power output of the hs-th hydropower station in week t; hs,t,max HE represents the maximum power output of the hs-th hydropower station in week t; hs This represents the total annual electricity generation of the hs-th hydropower station;

[0066] The constraints of the pumped storage unit are:

[0067]

[0068]

[0069] In the formula, ps represents the pth pumped storage power station; p′∈ps represents the p′th pumped storage unit belonging to ps; This represents the power generation of the p-th pumped-storage unit in the b-th load segment of week t; pdr represents the pumping power of the p-th pumped storage unit in the b-th load segment of week t. p,t,b This indicates the downward reserve that the p-th pumped storage unit can provide in the b-th load segment of week t; pur p,t,b This represents the upward reserve that the p-th pumped storage unit can provide in the b-th load segment of week t. This represents the minimum generating capacity of the p-th pumped-storage unit; This represents the upper limit of the output of the p-th pumped-storage unit; This represents the rated pumping power of the p-th pumped storage unit; This is a 0-1 variable representing whether the p-th pumped-storage unit in the b-th load segment of week t is in generating mode. If the p-th pumped-storage unit in the b-th load segment of week t is in generating mode... The value is 1, otherwise x h,t The value is 0; This is a 0-1 variable representing whether the p-th pumped-storage unit in the b-th load segment of week t is in pumping mode. The value is 1, otherwise The value is 0; This represents the power generation efficiency of the p-th pumped-storage unit; This represents the pumping efficiency of the p-th pumped storage unit.

[0070] Furthermore, the system operation constraints include: power balance constraints, energy balance constraints, and reserve constraints;

[0071] The power balance constraint is:

[0072]

[0073] In the formula, g represents the g-th thermal power unit; h represents the h-th hydropower unit; p represents the p-th pumped-storage unit; t represents the t-th week; b represents the b-th load segment; p g,t,b p represents the output of the g-th thermal power unit in the b-th load segment of week t; h,t,b p represents the output of the h-th hydropower unit in the b-th load segment of week t; r,t,b This represents the output level of the r-th new energy unit in the b-th load segment of week t; This represents the power generation of the p-th pumped-storage unit in the b-th load segment of week t; L represents the pumping power of the p-th pumped storage unit in the b-th load segment of week t; t,b This represents the segment load level of the b-th load segment in week t;

[0074] The power balance constraint is:

[0075]

[0076] In the formula, D t,b RE represents the duration of the b-th load segment in week t; t,b Represents the probabilistic output of new energy scenarios in the b-th load segment of week t; RC t,b LC represents the amount of renewable energy wasted in the b-th load segment of week t; t,b L represents the load shedding amount in the b-th load segment of week t; t,b This represents the load level of the b-th load segment in week t;

[0077] The backup constraint is:

[0078]

[0079] In the formula, r represents the r-th new energy unit; pur g,t,b This indicates the upward reserve that the g-th thermal power unit can provide in the b-th load segment of week t; pdr g,t,b This indicates the downward reserve that the g-th thermal power unit can provide in the b-th load segment of week t; pur h,t,bThis indicates the upward reserve that the h-th hydropower unit can provide in the b-th load segment of week t; pdr h,t,b This indicates the downward reserve that the h-th hydropower unit can provide in the b-th load segment of week t; pur p,t,b This indicates the upward reserve that the p-th pumped-storage unit can provide in the b-th load segment of week t; pdr p,t,b This indicates the downward reserve that the p-th pumped storage unit can provide in the b-th load segment of week t. This represents the lower limit of the output of the r-th new energy unit in the b-th load segment of week t; This represents the upper limit of the output of the r-th new energy unit in the b-th load segment of week t; p represents the output of the r-th renewable energy unit in the b-th load segment of week t, with a confidence level of α; g,max u represents the upper limit of the output of the g-th thermal power unit; g,t,b Let u be a 0-1 variable representing the start-up / shutdown status of the g-th thermal power unit in the b-th load segment of week t. If the g-th thermal power unit in the b-th load segment of week t is in the start-up state, then u... g,t,b The value is 1, otherwise u g,t,b The value is 0; ρ represents the reserve coefficient.

[0080] Furthermore, the calculation of weekly cold reserve capacity and hot reserve capacity based on the unit's start-up / shutdown status, maintenance status, and output includes:

[0081] Calculate the hot standby capacity for each week based on the unit's start-up and shutdown status and the unit's output.

[0082] Calculate the cold standby capacity for each week based on the unit's start-up / shutdown status and maintenance status.

[0083] The formula for calculating the hot standby capacity is as follows:

[0084] RH t,b =∑ g u g,t,b (p g,max -p g,t,b )+∑ h u h,t,b (p h,max -p h,t,b )+∑ p u p,t,b (p p,max -p p,t,b );

[0085] In the formula, RH t,b The hot standby capacity of load segment b in week t is represented by: g represents the g-th thermal power unit; h represents the h-th hydropower unit; p represents the p-th pumped-storage unit; t represents week t; ug,t,b This indicates the start-up / shutdown status of the g-th thermal power unit in the b-th load segment of week t; u h,t,b This indicates the start-up and shutdown status of the h-th hydropower unit in the b-th load segment of week t; u p,t,b This indicates the start-up and shutdown status of the p-th pumped-storage unit in the b-th load segment of week t; p g,t,b p represents the generating power of the g-th thermal power unit in the b-th load segment of week t; g,max p represents the upper limit of the output of the g-th thermal power unit; h,t,b p represents the power generation of the h-th hydropower unit in load segment b during week t; h,max p represents the upper limit of the output of the h-th hydropower unit; p,t,b p represents the power generation of the p-th pumped-storage unit in the b-th load segment of week t; p,max This represents the upper limit of the output of the p-th pumped-storage unit;

[0086] The formula for calculating the cold standby capacity is as follows:

[0087] RC t,b =∑ g (1-u g,t,b (1-x) g,t,b )p g,max +∑ h (1-u h,t,b (1-x) h,t,b )p h,max +

[0088] ∑ p (1-u p,t,b (1-x) p,t,b )p p,max ;

[0089] In the formula, RC t,b x represents the cold standby capacity of the b-th load segment in week t; g,t,b A 0-1 variable representing whether the g-th thermal power unit in the b-th load segment of week t is under maintenance. When the g-th thermal power unit is under maintenance in the b-th load segment of week t, x... g,t,b The value is 1, otherwise x g,t,b The value is 0; x h,t,b A 0-1 variable representing whether the h-th hydropower unit in the b-th load segment of week t is under maintenance. When the h-th hydropower unit is under maintenance in the b-th load segment of week t, x... h,t,b The value is 1, otherwise x h,t,b The value is 0; x p,t,b A 0-1 variable representing whether the p-th pumped-storage unit in the b-th load segment of week t is under maintenance. If the p-th pumped-storage unit is under maintenance in the b-th load segment of week t, x... p,t,bThe value is 1, otherwise x p,t,b The value is 0.

[0090] Another embodiment of the present invention provides an annual cold and hot reserve allocation device for a multi-source power system with new energy sources, comprising: a data acquisition module, a continuous load curve generation module, a model building and solving module, and a cold and hot reserve calculation module;

[0091] The data acquisition module is used to acquire the first-year load curve of the power system;

[0092] The continuous load curve generation module is used to divide the first annual load curve into several weekly load curves; for each weekly load curve, the load data of the weekly load curve is arranged in descending order to obtain an accurate weekly continuous load curve; based on several preset segmented load levels, an approximate weekly continuous load curve with the same power consumption as the accurate weekly continuous load curve is generated; wherein, the approximate weekly continuous load curve includes several load segments, and the load of each load segment corresponds to one segmented load level;

[0093] The model building and solution module is used to obtain the duration of each load segment in each week based on all the approximate weekly continuous load curves; based on the duration, an annual operation model is constructed with the objectives of minimizing system operating costs, minimizing load loss, and minimizing renewable energy curtailment; under unit maintenance constraints, unit operation constraints, renewable energy operation constraints, and system operation constraints, the annual operation model is solved to obtain the unit start-up and shutdown status, unit maintenance status, and unit output for each week;

[0094] The cold and hot standby calculation module is used to calculate the cold standby capacity and hot standby capacity for each week based on the unit's start-up and shutdown status, unit maintenance status, and unit output.

[0095] Another embodiment of the present invention provides a terminal device, including: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the steps of the annual cold and hot reserve allocation method for multi-source power systems with new energy sources as described above in the present invention.

[0096] Another embodiment of the present invention also provides a computer-readable storage medium item, including: a stored computer program, which, when the computer program is running, controls the device where the computer-readable storage medium is located to perform the steps of the annual cold and hot reserve allocation method for multi-source power systems containing new energy sources as described above.

[0097] The following benefits can be obtained by implementing the present invention:

[0098] This invention introduces a segmented load curve to simplify the first-year load curve, generating an approximate weekly continuous load curve. The approximate weekly continuous load curve comprises several load segments, each corresponding to a specific load level. An annual operating model is constructed based on all the approximate weekly continuous load curves. Under constraints of unit maintenance, unit operation, renewable energy operation, and system operation, the annual operating model is solved. The cold and hot reserve capacities for each week are calculated based on the model's solution results. This invention uses an approximate weekly continuous load curve for load modeling, employing a weekly load segment as the time resolution. Compared to traditional techniques using an hourly time resolution, this significantly reduces the problem size, improves solution efficiency, and solves the problem of excessively long solution times caused by large problem sizes in existing technologies. Attached Figure Description

[0099] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0100] Figure 1 This is a flowchart illustrating an annual cold and hot reserve allocation method for a multi-source power system containing new energy sources, provided by an embodiment of the present invention.

[0101] Figure 2 This is a schematic diagram of load modeling based on an approximate weekly continuous load curve and the probability of new energy output for each load segment.

[0102] Figure 3 This is a schematic diagram of hot standby capacity allocation provided in an embodiment of the present invention.

[0103] Figure 4 This is a schematic diagram of cold standby capacity allocation provided by an embodiment of the present invention.

[0104] Figure 5 This is a schematic diagram of the structure of an annual cold and hot backup distribution device for a multi-power system with new energy sources, provided in an embodiment of the present invention. Detailed Implementation

[0105] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0106] Unless otherwise defined, 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 application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the term "comprising" and any variations thereof in the specification, claims and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0107] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "several" means two or more, unless otherwise explicitly defined.

[0108] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0109] See Figure 1 To address the problem that existing technologies cannot solve problems with excessively large scales, resulting in excessively long solution times, an embodiment of the present invention provides a method for annual cold and hot reserve allocation in a multi-source power system containing new energy sources, comprising:

[0110] S1. Obtain the first-year load curve and renewable energy output data of the power system.

[0111] It should be noted that the first-year load curve refers to the 8760-hour time-series load curve for the entire year.

[0112] S2. Divide the first year's load curve into several weekly load curve segments.

[0113] In step S2, the first year's load curve is divided into 52 weekly load curve segments.

[0114] S3. For each weekly load curve, the load data of the weekly load curve is arranged in descending order to obtain an accurate weekly continuous load curve; based on several preset segmented load levels, an approximate weekly continuous load curve with the same power as the accurate weekly continuous load curve is generated; wherein, the approximate weekly continuous load curve includes several load segments, and the load of each load segment corresponds to one segmented load level.

[0115] It should be noted that a load segment contains several load data points, and all load data points within the same load segment have the same load value. The segment load level refers to the load value of a load segment.

[0116] In step S3, for each weekly load curve segment, its load data is arranged in descending order to form the accurate weekly continuous load curve for each week. Next, an appropriate number of segments and corresponding segment load levels are preset according to the research needs. During this process, the maximum and minimum loads within the week should be retained. That is, the value of the largest segment load level is equal to the maximum load within the week, and the value of the smallest segment load level is equal to the minimum load within the week. Then, the duration of each segment load level is adjusted to ensure that the total load corresponding to the approximate weekly continuous load curve and the accurate weekly continuous load curve is equal. That is, the total load of a week obtained from the approximate weekly continuous load curve should be consistent with the total load of the week obtained from the accurate weekly continuous load curve.

[0117] Suppose we have a set of load data arranged from largest to smallest: [2,3,3,4,5,5,6,7,9]. The preset segmented load levels are 2, 5, 7, and 9. Dividing this load data into segments yields: [(2,2),(5,5),(7,7),(9,9)]. The total load remains the same before and after segmentation.

[0118] It should be noted that traditional techniques, due to the long time span of unit maintenance issues in medium- and long-term simulations (which can last for a year or several years), often employ hourly time-series load curves, leading to excessively large problem sizes and long solution times. This invention uses approximate weekly continuous load curves for load modeling, with a weekly load segment as the time resolution. Compared to traditional techniques using an hourly time resolution, this invention significantly reduces the problem size.

[0119] S4. Based on all the approximate weekly continuous load curves, obtain the duration of each load segment in each week.

[0120] S5. Based on the duration, construct an annual operation model with the objectives of minimizing system operating costs, minimizing power loss due to load, and minimizing power curtailment from renewable energy sources.

[0121] In step S5, an annual operation model is constructed, taking into account three objectives: minimizing system operating costs, minimizing load loss, and minimizing renewable energy curtailment.

[0122] It should be noted that when constructing the annual operation model, in addition to the duration parameter, some known parameters also need to be obtained, including: the upper limit of output of various types of units, the minimum technical output of various types of units, the maintenance time of various types of units, the maintenance capacity of various types of power plants, the forced output of hydropower plants, the expected output of hydropower plants, the upper limit of power generation of hydropower stations, the annual total power generation of hydropower stations, the power generation efficiency of pumped storage units, and the pumping efficiency of pumped storage units.

[0123] In a preferred embodiment, the objective function of the annual operating model is:

[0124] min(C1+αC2+βC3);

[0125]

[0126] In the formula, C1 represents the system operating cost; C2 represents the total power loss due to load; C3 represents the total power curtailment of renewable energy; α represents the system load loss penalty coefficient; β represents the system renewable energy curtailment penalty coefficient; gs represents the gs-th thermal power plant; g′∈gs represents the g′-th thermal power unit belonging to gs; b represents the b-th load segment; B represents the total number of load segments in this week; t represents the t-th week; T represents the number of weeks in a year; f g (·) represents the power generation cost function of thermal power units; p g,t,b D represents the output of the g-th thermal power unit in the b-th load segment of week t; t,b LC represents the duration of the b-th load segment in week t; t,b Represents the load shedding amount in the b-th load segment of week t; RC t,b This represents the amount of renewable energy wasted in the b-th load segment of week t.

[0127] S6. Under the constraints of unit maintenance, unit operation, new energy power operation and system operation, solve the annual operation model to obtain the unit start-up and shutdown status, unit maintenance status and unit output for each week.

[0128] It should be noted that the decision variables of the annual operation model include: 0-1 variables for the start-up and shutdown status of thermal power units, 0-1 variables for the start-up and shutdown status of hydropower units, 0-1 variables for the start-up and shutdown status of pumped storage units, 0-1 variables for the start of maintenance of thermal power units, 0-1 variables for the start of maintenance of hydropower units, 0-1 variables for the start of maintenance of pumped storage units, output of thermal power units, output of hydropower units, power generation of pumped storage units, pumping power of pumped storage units, upward reserve of thermal power units, upward reserve of hydropower units, upward reserve of pumped storage units, downward reserve of thermal power units, downward reserve of hydropower units, downward reserve of pumped storage units, water wastage of hydropower units, renewable energy wastage of renewable energy units, load loss, output of renewable energy units, upper limit of renewable energy output absorption range, and lower limit of renewable energy output absorption range.

[0129] The annual operating model is a mixed-integer linear programming problem, which can be solved directly using the commercial solver Gurobi.

[0130] In a preferred embodiment, the process of constructing the operating constraints of the new energy power source includes:

[0131] Obtain time-series power output data for new energy sources;

[0132] For each load segment, the renewable energy time-series output data corresponding to the load segment is clustered into a preset number of scenario clusters; based on the number of renewable energy time-series output data corresponding to each scenario cluster and the number of renewable energy time-series output data corresponding to the load segment, the probability of scenario occurrence for each scenario cluster is calculated.

[0133] Based on the duration and the probability of occurrence of the scenario, new energy power operation constraints are constructed;

[0134] The operating constraints of the new energy power are as follows:

[0135]

[0136] In the formula, RE t,b π represents the probabilistic output of new energy scenarios in the b-th load segment of week t; s represents the s-th scenario, i.e., the s-th scenario cluster; π s This represents the probability of a scene occurring in the s-th scene cluster. This represents the renewable energy output of the b-th load segment in week t; This represents the upper limit of renewable energy output for the b-th load segment in week t; D represents the lower limit of renewable energy output for the b-th load segment in week t; t,b LC represents the duration of the b-th load segment in week t;t,b Represents the load shedding amount in the b-th load segment of week t; RC t,b This represents the amount of renewable energy wasted in the b-th load segment of week t.

[0137] In this embodiment, based on step S3, the time-series output data of new energy sources for each load segment are statistically analyzed, and probabilistic modeling of new energy output is performed, such as... Figure 2 The diagram shown illustrates load modeling based on an approximate continuous load curve and the modeling probability of renewable energy output in each segment. The modeling process is as follows:

[0138] First, statistical analysis is performed based on the time-series output data of renewable energy sources. The renewable energy output data for each load segment each week is obtained according to the information of the load segment to which the time belongs. For each load segment in each week, the time-series output data of renewable energy sources belonging to that load segment are clustered into a preset number of scenarios. The time-series output data of renewable energy sources from other load segments does not affect the clustering results of that load segment. Finally, the probability corresponding to each scenario is calculated based on the ratio of the number of time-series output data points of renewable energy sources in each scenario's corresponding cluster to the total number of time-series output data points of renewable energy sources in that load segment. Generally, the number of scenario clusters is set to 5.

[0139] The formula for clustering is:

[0140]

[0141] In the formula, s represents the scene number; n represents the total number of scenes; π represents the renewable energy output of the b-th load segment in week t under scenario s; s Ω represents the probability of scenario s occurring; Cluster(·) is a clustering function that can output the typical values ​​and corresponding probabilities of all scenarios based on the dataset and the required number of scenarios; Ω is a set of new energy output data.

[0142] It should be noted that the probabilistic modeling of new energy output in this invention can reflect the uncertainty of new energy output, making the model solution more accurate.

[0143] In a preferred embodiment, the unit maintenance constraints include: unit maintenance frequency constraints, unit maintenance time constraints, unit maintenance capacity constraints, unit maintenance continuity constraints, and unit maintenance time interval constraints.

[0144] The constraint on the number of unit maintenance cycles is:

[0145]

[0146] In the formula, g represents the g-th thermal power unit; h represents the h-th hydropower unit; p represents the p-th pumped-storage unit; z g,tz represents a 0-1 variable indicating the start of maintenance for the g-th thermal power unit in week t. When the g-th thermal power unit begins maintenance in week t, z... g,t The value is 1, otherwise z g,t The value is 0; z h,t z represents a 0-1 variable indicating that the h-th hydropower unit begins maintenance in week t. When the h-th hydropower unit begins maintenance in week t, z... h,t The value is 1, otherwise z h,t The value is 0; z p,t This represents a 0-1 variable indicating that the p-th pumped-storage unit begins maintenance in week t. When the g-th pumped-storage unit begins maintenance in week t, z... p,t The value is 1, otherwise z p,t The value is 0; MN g Indicates the number of maintenance operations required for thermal power units during the total study period; MN h Indicates the number of maintenance operations required for each hydroelectric generator unit during the total study period; MN p This indicates the number of maintenance operations required for the pumped-storage unit during the total study period.

[0147] The unit maintenance time constraint is as follows:

[0148]

[0149] In the formula, x g,t A 0-1 variable representing whether the g-th thermal power unit is under maintenance in week t. If the g-th thermal power unit is under maintenance in week t, x... g,t The value is 1, otherwise x g,t The value is 0; x h,t A 0-1 variable representing whether the h-th hydropower unit in week t is under maintenance. If the h-th hydropower unit is under maintenance in week t, x... h,t The value is 1, otherwise x h,t The value is 0; x p,t A 0-1 variable representing whether the p-th pumped-storage unit is under maintenance in week t. If the p-th pumped-storage unit is under maintenance in week t, x... p,t The value is 1, otherwise x p,t The value is 0; MN g MN represents the duration of each maintenance operation for the g-th thermal power unit; h MN represents the duration of each maintenance check for the h-th hydropower unit; p This indicates the duration of each maintenance check for the p-th pumped-storage unit;

[0150] The unit's maintenance capacity constraint is as follows:

[0151] ∑ g′∈gs x g′,t ≤MC gs ;

[0152] ∑ h′∈hs x h′,t ≤MC hs ;

[0153] ∑ p′∈ps x p′,t ≤MC ps ;

[0154] In the formula, gs represents the gs-th thermal power plant; g′∈gs represents the g′-th thermal power unit belonging to gs; hs represents the hs-th hydropower plant; h′∈hs represents the h′-th hydropower unit belonging to hs; ps represents the ps-th pumped storage power plant; p′∈ps represents the p′-th pumped storage unit belonging to ps; MC gs This represents the number of generating units that the gs-th thermal power plant can simultaneously undergo maintenance; MC hs This represents the number of generating units that can be simultaneously maintained at the hs-th hydropower station; MC ps This represents the number of generating units that the p-th pumped storage power station can maintain simultaneously.

[0155] The continuity constraint for unit maintenance is:

[0156]

[0157] The unit maintenance interval constraint is as follows:

[0158]

[0159] In the formula, MG g MG represents the minimum time interval between two consecutive maintenance operations of the g-th thermal power unit; h MG represents the minimum time interval between two consecutive maintenance operations of the h-th hydropower unit; p This represents the minimum time interval between two consecutive maintenance operations of the p-th pumped-storage unit.

[0160] It should be noted that the duration of training is generally taken as an integer value. The maintenance capacity of various power plants refers to the number of generating units that the power plant can maintain simultaneously, which is usually 1.

[0161] In a preferred embodiment, the unit operation constraints include: unit start-up constraints, thermal power unit constraints, hydropower unit constraints, and pumped storage unit constraints;

[0162] The unit start-up constraints are as follows:

[0163] x g,t +u g,t,b ≤1;

[0164] x h,t +u h,t,b ≤1;

[0165]

[0166] In the formula, g represents the g-th thermal power unit; h represents the h-th hydropower unit; p represents the p-th pumped-storage unit; t represents the t-th week; b represents the b-th load segment; x g,t A 0-1 variable representing whether the g-th thermal power unit is under maintenance in week t. If the g-th thermal power unit is under maintenance in week t, x... g,t The value is 1, otherwise x g,t The value is 0; x h,t A 0-1 variable representing whether the h-th hydropower unit in week t is under maintenance. If the h-th hydropower unit is under maintenance in week t, x... h,t The value is 1, otherwise x h,t The value is 0; x p,t A 0-1 variable representing whether the p-th pumped-storage unit is under maintenance in week t. If the p-th pumped-storage unit is under maintenance in week t, x... p,t The value is 1, otherwise x p,t The value is 0; u g,t,b Let u be a 0-1 variable representing the start-up / shutdown status of the g-th thermal power unit in the b-th load segment of week t. If the g-th thermal power unit in the b-th load segment of week t is in the start-up state, then u... g,t,b The value is 1, otherwise u g,t,b The value is 0; u h,t,b Let u be a 0-1 variable representing the start-up / shutdown status of the h-th hydropower unit in the b-th load segment of week t. If the h-th hydropower unit in the b-th load segment of week t is in the start-up state, then u... h,t,b The value is 1, otherwise u h,t,b The value is 0; This is a 0-1 variable representing whether the p-th pumped-storage unit in the b-th load segment of week t is in generating mode. If the p-th pumped-storage unit in the b-th load segment of week t is in generating mode... The value is 1, otherwise x h,t The value is 0; This is a 0-1 variable representing whether the p-th pumped-storage unit in the b-th load segment of week t is in pumping mode. The value is 1, otherwise The value is 0;

[0167] The constraints of the thermal power unit are:

[0168] p g,t,b -pdr g,t,b ≥p g,min u g,t,b ;

[0169] pg,t,b +pur g,t,b ≤p g,max u g,t,b ;

[0170] 0≤pdr g,t,b ≤p g,max u g,t,b ;

[0171] 0≤pur g,t,b ≤p g,max u g,t,b ;

[0172] In the formula, p g,t,b pdr represents the output of the g-th thermal power unit in the b-th load segment of week t; g,t,b This indicates the downward reserve that the g-th thermal power unit can provide in the b-th load segment of week t; pur g,t,b p represents the upward reserve that the g-th thermal power unit can provide in the b-th load segment of week t; g,min p represents the lower limit of the output of the g-th thermal power unit; g,max This represents the upper limit of the output of the g-th thermal power unit;

[0173] The constraints of the hydropower unit are:

[0174] p h,t,b -pdr h,t,b ≥p h,min u h,t,b ;

[0175] p h,t,b +pdr h,t,b ≥p h,max u h,t,b ;

[0176] 0≤pdr h,t,b ≤p h,max u h,t,b ;

[0177] 0≤pur h,t,b ≤p h,max u h,t,b ;

[0178] ∑ h′∈hs (p h′,t,b -pdr h′,t,b )≥HP hs,t,min ;

[0179] ∑ h′∈hs (p h′,t,b +pur h′,t,b )≤HP hs,t,max ;

[0180] 0≤pdr h,t,b≤p h,max u h,t,b ;

[0181] 0≤pdr h,t,b ≤p h,max u h,t,b ;

[0182]

[0183] HE hs,t,min ≤HE hs,t +HC hs,t ≤HE hs,t,max ;

[0184]

[0185] In the formula, hs represents the hs-th hydropower station; h′∈hs represents the h′-th hydropower unit belonging to hs; B represents the total number of load segments within this week; T represents the number of weeks in a year; p h,t,b pdr represents the output of the h-th hydropower unit in the b-th load segment of week t; h,t,b This indicates the downward reserve that the h-th hydropower unit can provide in the b-th load segment of week t; pur h,t,b p represents the upward reserve that the h-th hydropower unit can provide in the b-th load segment of week t; h,min p represents the lower limit of the output of the h-th hydropower unit; h,max HP represents the upper limit of the output of the h-th hydropower unit. hs,t,min HP represents the forced output of the hs-th hydroelectric power station in week t; hs,t,max HP represents the projected output of the hs-th hydroelectric power station in week t; hs,t HE represents the power generation of the hs-th hydroelectric power station in week t; hs,t,min HE represents the lower limit of the power output of the hs-th hydropower station in week t; hs,t,max HE represents the maximum power output of the hs-th hydropower station in week t; hs This represents the total annual electricity generation of the hs-th hydropower station;

[0186] The constraints of the pumped storage unit are:

[0187]

[0188]

[0189] In the formula, ps represents the pth pumped storage power station; p′∈ps represents the p′th pumped storage unit belonging to ps; This represents the power generation of the p-th pumped-storage unit in the b-th load segment of week t; pdr represents the pumping power of the p-th pumped storage unit in the b-th load segment of week t.p,t,b This indicates the downward reserve that the p-th pumped storage unit can provide in the b-th load segment of week t; pur p,t,b This represents the upward reserve that the p-th pumped storage unit can provide in the b-th load segment of week t. This represents the minimum generating capacity of the p-th pumped-storage unit; This represents the upper limit of the output of the p-th pumped-storage unit; This represents the rated pumping power of the p-th pumped storage unit; This is a 0-1 variable representing whether the p-th pumped-storage unit in the b-th load segment of week t is in generating mode. If the p-th pumped-storage unit in the b-th load segment of week t is in generating mode... The value is 1, otherwise x h,t The value is 0; This is a 0-1 variable representing whether the p-th pumped-storage unit in the b-th load segment of week t is in pumping mode. The value is 1, otherwise The value is 0; This represents the power generation efficiency of the p-th pumped-storage unit; This represents the pumping efficiency of the p-th pumped storage unit.

[0190] It should be noted that the constraints of thermal power units are as follows:

[0191] Thermal power units also include nuclear power units. Upward and downward reserves in thermal power units are used to cope with sudden increases or decreases in renewable energy output. When considering the unit's ramp-up capacity limitations, the constraints on thermal power units can be modified to further limit the range of unit reserve capacity. For non-start-stop peak-shaving nuclear power and large coal-fired power units, it is also necessary to ensure that the start-up and shutdown status remains unchanged under different load levels within the same time period (e.g., one week), as shown in the following formula:

[0192] u g,t,1 =u g,t,2 =…=u g,t,B .

[0193] Regarding constraints on hydropower units: The upper and lower limits of the weekly power output of a hydropower station mainly depend on the water inflow in different seasons.

[0194] In a preferred embodiment, the system operating constraints include: power balance constraints, energy balance constraints, and reserve constraints;

[0195] The power balance constraint is:

[0196]

[0197] In the formula, g represents the g-th thermal power unit; h represents the h-th hydropower unit; p represents the p-th pumped-storage unit; t represents the t-th week; b represents the b-th load segment; p g,t,b p represents the output of the g-th thermal power unit in the b-th load segment of week t; h,t,b p represents the output of the h-th hydropower unit in the b-th load segment of week t; r,t,b This represents the output of the r-th new energy unit in the b-th load segment of week t; This represents the power generation of the p-th pumped-storage unit in the b-th load segment of week t; L represents the pumping power of the p-th pumped storage unit in the b-th load segment of week t; t,b This represents the segment load level of the b-th load segment in week t;

[0198] The power balance constraint is:

[0199]

[0200] In the formula, D t,b RE represents the duration of the b-th load segment in week t; t,b Represents the probabilistic output of new energy scenarios in the b-th load segment of week t; RC t,b LC represents the amount of renewable energy wasted in the b-th load segment of week t; t,b L represents the load shedding amount in the b-th load segment of week t; t,b This represents the load level of the b-th load segment in week t;

[0201] The backup constraint is:

[0202]

[0203] In the formula, r represents the r-th new energy unit; pur g,t,b This indicates the upward reserve that the g-th thermal power unit can provide in the b-th load segment of week t; pdr g,t,b This indicates the downward reserve that the g-th thermal power unit can provide in the b-th load segment of week t; pur h,t,b This indicates the upward reserve that the h-th hydropower unit can provide in the b-th load segment of week t; pdr h,t,b This indicates the downward reserve that the h-th hydropower unit can provide in the b-th load segment of week t; pur p,t,b This indicates the upward reserve that the p-th pumped-storage unit can provide in the b-th load segment of week t; pdr p,t,b This indicates the downward reserve that the p-th pumped storage unit can provide in the b-th load segment of week t. This represents the lower limit of the output of the r-th new energy unit in the b-th load segment of week t; This represents the upper limit of the output of the r-th new energy unit in the b-th load segment of week t; p represents the output of the r-th renewable energy unit in the b-th load segment of week t, with a confidence level of α; g,max u represents the upper limit of the output of the g-th thermal power unit; g,t,b Let u be a 0-1 variable representing the start-up / shutdown status of the g-th thermal power unit in the b-th load segment of week t. If the g-th thermal power unit in the b-th load segment of week t is in the start-up state, then u... g,t,b The value is 1, otherwise u g,t,b The value is 0; ρ represents the reserve coefficient.

[0204] S7. Calculate the cold standby capacity and hot standby capacity for each week based on the unit's start-up and shutdown status, unit maintenance status, and unit output.

[0205] It should be noted that, based on the solution results, the weekly cold and hot reserves of the system can be calculated to obtain the annual cold and hot reserve allocation plan. The cold reserve is provided by the units that are not in operation and are not under maintenance, while the hot reserve is the difference between the upper limit of the output of the units that are in operation and the actual output.

[0206] In a preferred embodiment, calculating the weekly cold reserve capacity and hot reserve capacity based on the unit's start-up / shutdown status, maintenance status, and output includes:

[0207] Calculate the hot standby capacity for each week based on the unit's start-up and shutdown status and the unit's output.

[0208] Calculate the cold standby capacity for each week based on the unit's start-up / shutdown status and maintenance status.

[0209] The formula for calculating the hot standby capacity is as follows:

[0210] RH t,b =∑ g u g,t,b (p g,max -p g,t,b )+∑ h u h,t,b (p h,max -p h,t,b )+∑ p u p,t,b (p p,max -p p,t,b );

[0211] In the formula, RH t,b The hot standby capacity of load segment b in week t is represented by: g represents the g-th thermal power unit; h represents the h-th hydropower unit; p represents the p-th pumped-storage unit; t represents week t; u g,t,bThis indicates the start-up / shutdown status of the g-th thermal power unit in the b-th load segment of week t; u h,t,b This indicates the start-up and shutdown status of the h-th hydropower unit in the b-th load segment of week t; u p,t,b This indicates the start-up and shutdown status of the p-th pumped-storage unit in the b-th load segment of week t; p g,t,b p represents the generating power of the g-th thermal power unit in the b-th load segment of week t; g,max p represents the upper limit of the output of the g-th thermal power unit; h,t,b p represents the power generation of the h-th hydropower unit in load segment b during week t; h,max p represents the upper limit of the output of the h-th hydropower unit; p,t,b p represents the power generation of the p-th pumped-storage unit in the b-th load segment of week t; p,max This represents the upper limit of the output of the p-th pumped-storage unit;

[0212] The formula for calculating the cold standby capacity is as follows:

[0213] RC t,b =∑ g (1-u g,t,b (1-x) g,t,b )p g,max +∑ h (1-u h,t,b (1-x) h,t,b )p h,max +

[0214] ∑ p (1-u p,t,b (1-x) p,t,b )p p,max ;

[0215] In the formula, RC t,b x represents the cold standby capacity of the b-th load segment in week t; g,t,b A 0-1 variable representing whether the g-th thermal power unit in the b-th load segment of week t is under maintenance. When the g-th thermal power unit is under maintenance in the b-th load segment of week t, x... g,t,b The value is 1, otherwise x g,t,b The value is 0; x h,t,b A 0-1 variable representing whether the h-th hydropower unit in the b-th load segment of week t is under maintenance. When the h-th hydropower unit is under maintenance in the b-th load segment of week t, x... h,t,b The value is 1, otherwise x h,t,b The value is 0; x p,t,b A 0-1 variable representing whether the p-th pumped-storage unit in the b-th load segment of week t is under maintenance. If the p-th pumped-storage unit is under maintenance in the b-th load segment of week t, x... p,t,b The value is 1, otherwise xp,t,b The value is 0.

[0216] The following simple example illustrates the implementation process of this method:

[0217] This calculation is based on an adapted IEEE-RTS1979 system's annual (52-week) scheduling plan. The system's maximum annual load is 2850MW, including 7 thermal power plants with 24 units and a total capacity of 2305MW; 1 nuclear power plant with 2 units and a total capacity of 800MW; 1 hydropower plant with 6 units and a total capacity of 300MW; 1 pumped storage power plant with 4 units and a total capacity of 200MW, with pumping efficiency and power generation efficiency of 0.833 and 0.9, respectively; and 800MW of wind power capacity. Units undergo maintenance for 3-4 weeks annually, and each power plant can only maintain one unit at a time. Thermal power includes coal-fired, gas-fired and oil-fired units, and the minimum output of nuclear power units is 60% of the installed capacity; the annual power generation of hydropower stations is 1200GWh; the power characteristics and expected output of each season are shown in Table 1, and the power adjustable range is 0.8-1.2 times the initial power

[20] ; the wind power output is selected from the annual statistical data of a certain place in Northwest my country, and the wind power output sequence in the example is calculated according to the capacity ratio, and the annual power generation is about 1637GWh.

[0218] Table 1 Seasonal Characteristics of Hydropower Stations

[0219]

[0220]

[0221] Step 1: Obtain the annual 8760-hour time-series load curve of the power system and the time-series output data of new energy sources.

[0222] Step Two: Based on the 8760-hour time-series load curve and renewable energy output data obtained in Step One, the hourly load curve data is first arranged from largest to smallest to construct an accurate weekly continuous load curve. Then, under the premise of retaining the maximum and minimum load levels and ensuring that the total electricity consumption of the constructed approximate weekly continuous load curve is equal to that of the accurate weekly continuous load curve, the appropriate number of segments, the duration of each segment, and the segment load level are determined. On this basis, the renewable energy output data corresponding to each segment are statistically analyzed, and a clustering algorithm is used to cluster the renewable energy time-series output data of each load segment, reducing it to a preset number of typical scenarios and calculating the probability corresponding to each scenario.

[0223] Step 3: Based on the approximate weekly continuous load curve and renewable energy probability modeling in Step 2, considering the three objectives of minimizing system operating costs, minimizing load shedding risk, and minimizing renewable energy curtailment, as well as unit maintenance constraints, unit operation constraints, and system operation constraints, a multi-objective annual operation simulation model is constructed. This model is a mixed integer programming model, which can be directly solved using the commercial solver Gurobi. The solution yields various operating indicators and unit operating conditions. The operating indicator data are shown in Table 2.

[0224] Table 2. Operating Indicators and Calculation Results

[0225]

[0226] Step Four: Based on the model solution results in Step Three, calculate the allocation of cold and hot reserve for each week to form a cold and hot reserve allocation plan. Cold reserve is the sum of the capacities of units not in operation, and hot reserve is the sum of the capacities of units in operation minus the actual output of the units. The hot reserve allocation results for each week are as follows: Figure 3 As shown, the cold standby allocation results are as follows: Figure 4 As shown.

[0227] Depend on Figure 3 It can be seen that during weeks with higher peak loads, the hot reserve capacity is higher, providing a good guarantee for power supply. Figure 4 It is known that the cold reserve allocation meets the annualized reliability standard (e.g., LOLE≤1 day / year). Therefore, this invention provides a reasonable cold and hot reserve allocation scheme under the premise of reducing the model size and improving the solution efficiency, which provides strong support for solving the annual cold and hot reserve allocation model of multi-source power systems with a high proportion of new energy sources.

[0228] like Figure 5 As shown, based on the above-mentioned method embodiments, an embodiment of the present invention provides an annual cold and hot reserve allocation device for a multi-source power system with new energy sources, including: a data acquisition module, a continuous load curve generation module; a model construction and solution module and a cold and hot reserve calculation module;

[0229] The data acquisition module is used to acquire the first-year load curve of the power system;

[0230] The continuous load curve generation module is used to divide the first annual load curve into several weekly load curves; for each weekly load curve, the load data of the weekly load curve is arranged in descending order to obtain an accurate weekly continuous load curve; based on several preset segmented load levels, an approximate weekly continuous load curve with the same power consumption as the accurate weekly continuous load curve is generated; wherein, the approximate weekly continuous load curve includes several load segments, and the load of each load segment corresponds to one segmented load level;

[0231] The model building and solution module is used to obtain the duration of each load segment in each week based on all the approximate weekly continuous load curves; based on the duration, an annual operation model is constructed with the objectives of minimizing system operating costs, minimizing load loss, and minimizing renewable energy curtailment; under unit maintenance constraints, unit operation constraints, renewable energy operation constraints, and system operation constraints, the annual operation model is solved to obtain the unit start-up and shutdown status, unit maintenance status, and unit output for each week;

[0232] The cold and hot standby calculation module is used to calculate the cold standby capacity and hot standby capacity for each week based on the unit's start-up and shutdown status, unit maintenance status, and unit output.

[0233] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can realize the annual cold and hot reserve allocation method for multi-source power systems containing new energy provided by any of the above-described method embodiments of the present invention.

[0234] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0235] Based on the above-described method embodiments, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the annual cold and hot reserve allocation method for a multi-source power system with new energy sources according to any embodiment of the present invention.

[0236] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0237] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0238] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0239] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the annual cold and hot reserve allocation method for a multi-source power system with new energy sources as described in any of the above-described method embodiments of the present invention.

[0240] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0241] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for annual cold-standby allocation of a multi-source power system containing new energy, characterized in that, The method comprises the following steps: obtaining a first annual load curve of a power system; dividing the first annual load curve into several weekly load curves; for each weekly load curve, arranging the load data of the weekly load curve in descending order to obtain an accurate weekly continuous load curve, and generating an approximate weekly continuous load curve with the same amount of electricity as the accurate weekly continuous load curve according to a plurality of preset segmented load levels; wherein the approximate weekly continuous load curve comprises a plurality of load segments, and the load of each load segment corresponds to a segmented load level; obtaining the duration of each load segment in each week according to all the approximate weekly continuous load curves; constructing an annual operation model with the minimum system operation cost, the minimum load loss and the minimum new energy curtailment as the target according to the duration; solving the annual operation model under the constraints of unit maintenance, unit operation, new energy power operation and system operation to obtain the unit start-stop state, unit maintenance state and unit output of each week; calculating the cold reserve capacity and the hot reserve capacity of each week according to the unit start-stop state, the unit maintenance state and the unit output.

2. The method of claim 1, wherein, The objective function of the annual operation model is: min(C1+αC2+βC3); wherein C1 represents the system operation cost; C2 represents the total load loss; C3 represents the total new energy curtailment; α represents the system load loss penalty coefficient; β represents the system new energy curtailment penalty coefficient; and gs represents the gth thermal power plant; g' ∈ gs represents the g'th thermal power unit belonging to gs; b represents the b'th load segment; B represents the total number of load segments in this week; t represents the t'th week; T represents the number of weeks in a year; f g (·) represents the generation cost function of the thermal power unit; p g,t,b represents the output of the g'th thermal power unit in the t'th week and the b'th load segment; D t,b represents the duration of the b'th load segment in the t'th week; LC t,b represents the lost load power of the bth load segment in the tth week; RC t,b represents the new energy curtailed power of the bth load segment in the tth week.

3. The method of claim 1, wherein, The construction process of the new energy power operation constraint comprises: obtaining new energy time series output data; for each load segment, clustering the new energy time series output data corresponding to the load segment into a preset number of scenario clusters; and calculating the scenario occurrence probability of each scenario cluster according to the number of new energy time series output data corresponding to each scenario cluster and the number of new energy time series output data corresponding to the load segment; constructing a new energy power operation constraint according to the duration and the scenario occurrence probability; wherein the new energy power operation constraint is: In the formula, RE t,b Pb,t,s represents the new energy scene probability output of the bth load segment in the tth week; s represents the s th scene, that is, the s th scene cluster class; π s Pb,t,s represents the scene occurrence probability of the s th scene cluster class. Pb,t represents the new energy output of the bth load segment in the tth week. Pb,t represents the upper limit of the new energy output of the bth load segment in the tth week. Pb,t represents the lower limit of the new energy output of the bth load segment in the tth week. t,b D represents the duration of the bth load segment in the tth week. t,b LC represents the loss of load power of the bth load segment in the tth week. t,b RC represents the new energy curtailment of the bth load segment in the tth week.

4. The method of claim 1, wherein, The unit maintenance constraint comprises a unit maintenance frequency constraint, a unit maintenance time constraint, a unit maintenance capacity constraint, a unit maintenance continuity constraint and a unit maintenance time interval constraint; The unit maintenance frequency constraint is: In the formula, g represents the gth thermal power generating unit; h represents the hth hydroelectric power generating unit; p represents the pth pumped storage power generating unit; z g,t represents a 0-1 variable indicating that the gth thermal power generating unit starts maintenance in the tth week, and z g,t takes the value of 1 when the gth thermal power generating unit starts maintenance in the tth week, otherwise z g,t takes the value of 0; z h,t represents a 0-1 variable indicating that the hth hydroelectric power generating unit starts maintenance in the tth week, and z h,t takes the value of 1 when the hth hydroelectric power generating unit starts maintenance in the tth week, otherwise z h,t takes the value of 0; z p,t represents a 0-1 variable indicating that the pth pumped storage power generating unit starts maintenance in the tth week, and z p,t takes the value of 1 when the pth pumped storage power generating unit starts maintenance in the tth week, otherwise z p,t takes the value of 0; MN g represents the number of maintenance required for the thermal power generating units in the total research period; MN h represents the number of maintenance required for the hydroelectric power generating units in the total research period; MN p represents the number of maintenance required for the pumped storage power generating units in the total research period; The unit maintenance time constraint is: In the formula, x g,t is a 0-1 variable representing whether the gth thermal power unit is in a maintenance state in the tth week, and when the gth thermal power unit is in a maintenance state in the tth week, x g,t takes a value of 1, otherwise x g,t takes a value of 0; x h,t is a 0-1 variable representing whether the hth hydropower unit is in a maintenance state in the tth week, and when the hth hydropower unit is in a maintenance state in the tth week, x h,t takes a value of 1, otherwise x h,t takes a value of 0; x p,t is a 0-1 variable representing whether the pth pumped storage unit is in a maintenance state in the tth week, and when the pth pumped storage unit is in a maintenance state in the tth week, x p,t takes a value of 1, otherwise x p,t takes a value of 0; MN g represents the duration of each maintenance of the gth thermal power unit; MN h represents the duration of each maintenance of the hth hydropower unit; MN p represents the duration of each maintenance of the pth pumped storage unit; The unit maintenance capacity constraint is: In the formula, gs represents the gs-th thermal power station; g' ∈ gs represents the g'-th thermal power unit belonging to gs; hs represents the hs-th hydropower station; h' ∈ hs represents the h'-th hydropower unit belonging to hs; ps represents the ps-th pumped storage power station; p' ∈ ps represents the p'-th pumped storage unit belonging to ps; MC gs represents the number of units that can be simultaneously overhauled in the gs-th thermal power station; MC hs represents the number of units that can be simultaneously overhauled in the hs-th hydropower station; MC ps represents the number of units that can be simultaneously overhauled in the ps-th pumped storage power station; The unit maintenance continuity constraint is: The unit maintenance time interval constraint is: In the formula, MG g represents the minimum time interval between two consecutive overhauls of the gth thermal power unit; MG h represents the minimum time interval between two consecutive overhauls of the hth hydroelectric power unit; MG p represents the minimum time interval between two consecutive overhauls of the pth pumped storage power unit.

5. The method of claim 1, wherein, The unit operation constraint comprises a unit start constraint, a thermal power unit constraint, a hydropower unit constraint and a pumped storage unit constraint; The unit start constraint is: x g,t +u g,t,b ≤1; x h,t +u h,t,b ≤1; In the formula, g represents the gth thermal power unit; h represents the hth hydropower unit; p represents the pth pumped storage unit; t represents the tth week; b represents the bth load segment; x g,t is a 0-1 variable representing whether the gth thermal power unit in the tth week is in a maintenance state, and x g,t is valued at 1 when the gth thermal power unit is in the maintenance state in the tth week, otherwise x g,t is valued at 0; x h,t is a 0-1 variable representing whether the hth hydropower unit in the tth week is in a maintenance state, and x h,t is valued at 1 when the hth hydropower unit is in the maintenance state in the tth week, otherwise x h,t is valued at 0; x p,t is a 0-1 variable representing whether the pth pumped storage unit in the tth week is in a maintenance state, and x p,t is valued at 1 when the pth pumped storage unit is in the maintenance state in the tth week, otherwise x p,t is valued at 0; u g,t,b is a 0-1 variable representing whether the gth thermal power unit in the bth load segment in the tth week is in an on-off state, and u g,t,b is valued at 1 when the gth thermal power unit in the bth load segment in the tth week is in the on state, otherwise u g,t,b is valued at 0; u h,t,b is a 0-1 variable representing whether the hth hydropower unit in the bth load segment in the tth week is in an on-off state, and u h,t,b is valued at 1 when the hth hydropower unit in the bth load segment in the tth week is in the on state, otherwise u h,t,b is valued at 0; is a 0-1 variable representing whether the pth pumped storage unit in the bth load segment in the tth week is in a power generation state, and x is valued at 1 when the pth pumped storage unit in the bth load segment in the tth week is in the power generation state, otherwise x h,t is valued at 0; is a 0-1 variable representing whether the pth pumped storage unit in the bth load segment in the tth week is in a water pumping state, and x is valued at 1 when the pth pumped storage unit in the bth load segment in the tth week is in the water pumping state, otherwise is valued at 0; The thermal power unit constraint is: p g,t,b -pdr g,t,b ≥p g,min u g,t,b ; p g,t,b +pur g,t,b ≤p g,max u g,t,b ; 0 < pdr g,t,b ≤ p g,max u g,t,b ; 0 < pur g,t,b ≤ p g,max u g,t,b ; In the formula, p g,t,b represents the output of the tth week, bth load segment, gth thermal power unit; pdr g,t,b represents the downward reserve that the tth week, bth load segment, gth thermal power unit can provide; pur g,t,b represents the upward reserve that the tth week, bth load segment, gth thermal power unit can provide; p g,min represents the lower limit of the output of the gth thermal power unit; p g,max represents the upper limit of the output of the gth thermal power unit; The hydropower unit constraint is: p h,t,b -pdr h,t,b ≥p h,min u h,t,b ; p h,t,b +pdr h,t,b ≥p h,max u h,t,b ; 0 < pdr h,t,b ≤ p h,max u h,t,b ; 0 < pur h,t,b ≤ p h,max u h,t,b ; ∑ h′∈hs (p h′,t,b -pdr h′,t,b )≥HP hs,t,min ; ∑ h′∈hs (p h′,t,b +pur h′,t,b )≤HP hs,t,max ; 0 < pdr h,t,b ≤ p h,max u h,t,b ; 0 < pdr h,t,b ≤ p h,max u h,t,b ; HE hs,t,min ≤HE hs,t +HC hs,t ≤HE hs,t,max ; where hs represents the hth hydroelectric power station; h' ∈ hs represents the h' th hydroelectric unit belonging to hs; B represents the total number of load segments in this week; T represents the number of weeks in a year; p h,t,b represents the output of the hth hydroelectric unit in the bth load segment of the tth week; pdr h,t,b represents the downward reserve that the hth hydroelectric unit can provide in the bth load segment of the tth week; pur h,t,b represents the upward reserve that the hth hydroelectric unit can provide in the bth load segment of the tth week; p h,min represents the lower limit of the output of the hth hydroelectric unit; p h,max represents the upper limit of the output of the hth hydroelectric unit; HP hs,t,min represents the forced output of the hth hydroelectric power station in the tth week; HP hs,t,max represents the expected output of the hth hydroelectric power station in the tth week; HP hs,t represents the power generation of the hth hydroelectric power station in the tth week; HE hs,t,min represents the lower limit of the power generation of the hth hydroelectric power station in the tth week; HE hs,t,max represents the upper limit of the power generation of the hth hydroelectric power station in the tth week; HE hs represents the total power generation of the hth hydroelectric power station in a year; The pumped storage unit constraint is: where ps represents the pth pumped storage power station; p' ∈ ps represents the p'th pumped storage unit belonging to ps; represents the generation power of the pth pumped storage unit in the bth load segment in the tth week; represents the pumping power of the pth pumped storage unit in the bth load segment in the tth week; pdr p,t,b represents the downward reserve that the pth pumped storage unit in the bth load segment in the tth week can provide; pur p,t,b represents the upward reserve that the pth pumped storage unit in the bth load segment in the tth week can provide; represents the minimum generation power of the pth pumped storage unit; represents the upper limit of the output of the pth pumped storage unit; represents the rated pumping power of the pth pumped storage unit; represents a 0-1 variable indicating whether the pth pumped storage unit in the bth load segment in the tth week is in the generation state, and when the pth pumped storage unit in the bth load segment in the tth week is in the generation state, takes the value 1, otherwise x h,t takes the value 0; represents a 0-1 variable indicating whether the pth pumped storage unit in the bth load segment in the tth week is in the pumping state, and when the pth pumped storage unit in the bth load segment in the tth week is in the pumping state, takes the value 1, otherwise takes the value 0; represents the generation efficiency of the pth pumped storage unit; represents the pumping efficiency of the pth pumped storage unit.

6. The method of claim 1, wherein, The system operation constraint comprises a power balance constraint, an electricity balance constraint and a reserve constraint; The power balance constraint is: In the formula, g represents the gth thermal power unit; h represents the hth hydroelectric power unit; p represents the pth pumped storage unit; t represents the tth week; b represents the bth load segment; p g,t,b represents the output of the gth thermal power unit in the bth load segment of the tth week; p h,t,b represents the output of the hth hydroelectric power unit in the bth load segment of the tth week; p r,t,b represents the output level of the rth new energy unit in the bth load segment of the tth week; represents the power generation of the pth pumped storage unit in the bth load segment of the tth week; represents the pumping power of the pth pumped storage unit in the bth load segment of the tth week; L t,b represents the segment load level of the bth load segment of the tth week; The electricity balance constraint is: In the formula, D t,b denotes the duration of the bth load segment in the tth week; RE t,b denotes the new energy scene probability output of the bth load segment in the tth week; RC t,b denotes the new energy curtailment of the bth load segment in the tth week; LC t,b denotes the loss of load of the bth load segment in the tth week; L t,b denotes the load level of the bth load segment in the tth week; The reserve constraint is: where r represents the rth new energy unit; pur g,t,b represents the upward reserve that the gth thermal power unit can provide in the bth load segment of the tth week; pdr g,t,b represents the downward reserve that the gth thermal power unit can provide in the bth load segment of the tth week; pur h,t,b represents the upward reserve that the hth hydropower unit can provide in the bth load segment of the tth week; pdr h,t,b represents the downward reserve that the hth hydropower unit can provide in the bth load segment of the tth week; pur p,t,b represents the upward reserve that the pth pumped storage unit can provide in the bth load segment of the tth week; pdr p,t,b represents the downward reserve that the pth pumped storage unit can provide in the bth load segment of the tth week; represents the lower limit of the output of the rth new energy unit in the bth load segment of the tth week; represents the upper limit of the output of the rth new energy unit in the bth load segment of the tth week; represents the output of the rth new energy unit in the bth load segment of the tth week at a confidence level of a; p g,max represents the upper limit of the output of the gth thermal power unit; u g,t,b represents a 0-1 variable of the start-stop state of the gth thermal power unit in the bth load segment of the tth week, and when the gth thermal power unit in the bth load segment of the tth week is in the start state, u g,t,b takes the value of 1, otherwise u g,t,b takes the value of 0; p represents the reserve coefficient.

7. The method of claim 1, wherein, The calculation of the cold reserve capacity and the hot reserve capacity of each week according to the unit start-stop state, the unit maintenance state and the unit output comprises: According to the unit start-stop state and the unit output, calculate the hot reserve capacity of each week; According to the unit start-stop state and the unit maintenance state, calculate the cold reserve capacity of each week; The calculation formula of the hot reserve capacity is: RH t,b =∑ g u g,t,b (p g,max -p g,t,b )+∑ h u h,t,b (p h,max -p h,t,b )+∑ p u p,t,b (p p,max - p p,t,b )； where RH t,b represents the thermal reserve capacity of the bth load section in the tth week; g represents the gth thermal power unit; h represents the hth hydroelectric power unit; p represents the pth pumped storage power unit; t represents the tth week; u g,t,b represents the start-stop state of the gth thermal power unit in the bth load section in the tth week; u h,t,b represents the start-stop state of the hth hydroelectric power unit in the bth load section in the tth week; u p,t,b represents the start-stop state of the pth pumped storage power unit in the bth load section in the tth week; p g,t,b represents the power generation of the gth thermal power unit in the bth load section in the tth week; p g,max represents the upper limit of the power output of the gth thermal power unit; p h,t,b represents the power generation of the hth hydroelectric power unit in the bth load section in the tth week; p h,max represents the upper limit of the power output of the hth hydroelectric power unit; p p,t,b represents the power generation of the pth pumped storage power unit in the bth load section in the tth week; p p,max represents the upper limit of the power output of the pth pumped storage power unit; The calculation formula of the cold reserve capacity is: RC t,b =∑ g (1-u g,t,b )(1-x g,t,b )p g,max +∑ h (1-u h,t,b )(1-x h,t,b )p h,max + ∑ p (1-u p,t,b )(1-x p,t,b )p p,max ; In the formula, RC t,b represents the cold reserve capacity of the bth load section in the tth week; x g,t,b represents a 0-1 variable indicating whether the gth thermal power unit in the bth load section in the tth week is in a maintenance state, x g,t,b takes a value of 1, otherwise x g,t,b takes a value of 0; x h,t,b represents a 0-1 variable indicating whether the hth hydropower unit in the bth load section in the tth week is in a maintenance state, x h,t,b takes a value of 1, otherwise x h,t,b takes a value of 0; x p,t,b represents a 0-1 variable indicating whether the pth pumped storage unit in the bth load section in the tth week is in a maintenance state, x p,t,b takes a value of 1, otherwise x p,t,b takes a value of 0.

8. A device for distributing annual cold and hot reserve of a multi-power system containing new energy, characterized in that, It comprises: A data acquisition module and a continuous load curve generation module; A model construction and solution module and a cold and hot reserve calculation module; The data acquisition module is configured to acquire a first annual load curve of a power system. The continuous load curve generation module is configured to divide the first annual load curve into a plurality of weekly load curves; for each weekly load curve, arrange the load data of the weekly load curve in descending order to obtain an accurate weekly continuous load curve; generate an approximate weekly continuous load curve with an amount of electricity equal to that of the accurate weekly continuous load curve according to a plurality of preset segmented load levels; wherein the approximate weekly continuous load curve comprises a plurality of load segments, and the load of each load segment corresponds to a segmented load level. The model construction and solution module is configured to obtain the duration of each load segment in each week according to all the approximate weekly continuous load curves. According to the duration, construct an annual operation model with the minimum system operation cost, the minimum loss of load, and the minimum new energy curtailment as the target; solve the annual operation model under the constraints of unit maintenance, unit operation, new energy power operation, and system operation to obtain the unit start-stop state, the unit maintenance state, and the unit output of each week. The cold and hot reserve calculation module is configured to calculate the cold reserve capacity and the hot reserve capacity of each week according to the unit start-stop state, the unit maintenance state, and the unit output.

9. A terminal device, comprising: It comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the computer program is executed by the processor, the method for allocating annual cold and hot reserves of a multi-source power system containing new energy is realized.

10. A computer-readable storage medium, characterized in that, It comprises: A stored computer program, wherein when the computer program is running, the device where the computer readable storage medium is located is controlled to execute the method for allocating annual cold and hot reserves of a multi-source power system containing new energy.

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