A method and system for hierarchical frequency-constrained unit commitment of fast and slow starting units

Abstract

The application discloses a kind of fast slow starting unit layered frequency constraint unit combination method and system, belong to electric power system optimization dispatching technical field.Load prediction data, conventional unit parameter, new energy output prediction data and frequency response parameter are acquired, and conventional unit is divided into slow starting unit and fast starting unit;First stage combination model of slow starting unit and second stage adjustment model of fast starting unit with the first stage commitment result as condition are constructed;According to the operation state of two kinds of units, establish system frequency support capability aggregation representation and construct frequency minimum point safety constraint;Two-stage model and frequency safety constraint are coupled to solve, and slow starting unit basic start-stop plan and fast starting unit calling scheme are obtained.The application can reduce unnecessary slow starting unit in advance online, improve fast starting unit flexibility utilization degree, and give consideration to frequency safety and operation economy.

Description

Technical Field

[0001] This invention belongs to the field of power system optimization scheduling and security constraint modeling technology, specifically relating to a frequency constraint unit combination method and system for fast and slow start-up unit groups. Background Technology

[0002] With the increasing integration of new energy sources such as wind and solar power into the power system, the power system's power structure and operating characteristics are undergoing significant changes. On the one hand, the output of new energy sources exhibits strong randomness and volatility, and deviations may exist between predicted and actual output, leading to increased fluctuations in the system's net load. On the other hand, the large-scale integration of new energy sources alters the online proportion of traditional synchronous generator units, impacting system inertia and frequency regulation capabilities. When power disturbances occur, frequency changes become more sensitive, posing higher safety requirements for unit combination and operation scheduling. Therefore, under conditions of high new energy integration, unit combination optimization not only needs to meet conventional operating constraints such as power balance, unit output range, ramp-up capability, and minimum start-up and shutdown times, but also requires further consideration of system frequency security.

[0003] Unit combination is a crucial optimization problem in power system operation and dispatching. It primarily determines the start-up and shutdown status and output plan of units within each dispatching period based on information such as load forecasting, renewable energy output forecasting, conventional unit operating parameters, and operating costs. Traditional unit combination methods typically aim to minimize system operating costs, optimizing unit operation modes while satisfying conditions such as power balance, unit output upper and lower limits, start-up and shutdown logic, minimum start-up time, minimum downtime, and ramp-up constraints. Regarding system frequency security, some existing methods indirectly ensure the system's power support capability after disturbances by setting a uniform spinning reserve capacity, reserving a certain power margin, or using empirical safety factors.

[0004] While the aforementioned approaches can improve system safety margins to some extent, reserve capacity or experience margins are typically static constraints and cannot fully reflect the differences in inertia, frequency regulation capabilities, and response characteristics among different online units. As the penetration rate of renewable energy increases and system frequency safety constraints become more stringent, simply increasing uniform reserve capacity may require pre-planning to keep more conventional units online, resulting in some units operating at low loads, increasing the number of online units and raising operating costs. Therefore, existing research has gradually incorporated frequency safety indicators into unit combination models, establishing frequency safety constraints based on the composition of online units and their frequency response capabilities to limit the rate of frequency change after disturbances, the frequency minimum, or other frequency safety indicators.

[0005] However, existing frequency-constrained unit combination methods typically treat different types of conventional units within a unified combination decision-making framework. This means each unit determines its start-up and shutdown status and output plan according to the same decision-making timescale, without fully considering the differences in start-up speed and operational flexibility among different units. In actual operation, the start-up characteristics of different conventional units vary significantly. Some units have longer start-up times, requiring their start-up and shutdown status to be determined in advance during the day-ahead period or earlier, making them suitable for undertaking relatively stable base output tasks. Other units have faster start-up speeds and can be flexibly deployed based on subsequent operating conditions, making them more suitable for handling net load changes, power deficits, and other temporary adjustment needs.

[0006] If the different starting characteristics mentioned above are not distinguished during the unit combination process, and the start-up and shutdown plans of fast-start units and slow-start units are determined uniformly in advance, the operational characteristics of fast-start units, which allow for delayed decision-making and on-demand deployment, cannot be fully utilized. Especially during operating periods with high frequency safety requirements, in order to ensure that frequency constraints are met, optimization models often tend to increase the number of slow-start units online in advance, allowing more slow-start units to bear the safety margin. Although this approach can improve the basic frequency support capacity, it will cause some units with longer start-up times to start up earlier and maintain operation for a longer period of time, resulting in a more conservative unit combination outcome.

[0007] Existing technologies also include solutions that utilize fast-start units to undertake standby or power compensation tasks. This involves calling upon fast-start units when there is a predicted increase in load, a decrease in renewable energy output, or a power deficit in the system, thereby rapidly increasing available active power to improve system power balance. However, in these methods, fast-start units are typically used primarily as power balancing or backup resources, and their flexible deployment capability lacks a direct joint decision-making relationship with frequency security constraints in the unit portfolio. In other words, frequency security constraints still mainly determine how many conventional units need to be kept online during the day-ahead phase, while fast-start units passively undertake power compensation in subsequent phases. Their roles in the optimization model are relatively separate, making it difficult to leverage the subsequent deployment capability of fast-start units to change the commitment method of slow-start units during the day-ahead phase.

[0008] Therefore, existing solutions face at least the following challenges in the actual modeling and optimization process: First, generating units with different startup characteristics have different decision-making time scales, making it difficult to reasonably represent them using a uniform unit combination approach. Slow-start units require advance planning of their start-up and shutdown states, while fast-start units can be flexibly deployed based on subsequent system operating conditions. If all units commit uniformly in the day-ahead phase, it will reduce the flexibility of fast-start units; if all units postpone their decisions, it will not meet the requirements of the actual startup process of slow-start units. Therefore, how to establish an interconnected phased decision-making mechanism based on the startup characteristics of generating units is one of the problems that existing unit combination models need to solve.

[0009] Second, there is a significant challenge in coordinating frequency security requirements with economical unit operation. When frequency constraints directly affect the traditional unified unit combination model, the most direct optimization method to improve frequency security margin is usually to increase the number of units in operation or reserve more frequency regulation capacity. This may lead to early startup of slow-start units, prolonged low-load operation, and overly conservative allocation of reserve resources. How to reduce unnecessary early startup of units without compromising frequency security is a major challenge in frequency-constrained unit combination.

[0010] Third, the flexibility of fast-start units makes it difficult to reflect their system value within frequency security constraints. Fast-start units are characterized by their ability to be put into operation in subsequent stages based on system status, but if they are only used as general reserve capacity or power compensation resources, their startup flexibility will not have a reverse impact on the day-ahead commitment decisions of slow-start units, thus failing to fully utilize fast-start units to reduce the need for base units to be online in advance.

[0011] Fourth, there are coupling difficulties between unit decisions and frequency constraints at different stages. The online status of slow-start units determines the basic operating structure of the system, while the commissioning status of fast-start units affects the subsequent available power support resources. System frequency security depends on the overall frequency support capability of the system under different operating states. Therefore, if traditional unit combinations are completed independently first, and then frequency verification or fast-start units are added to the results, it is easy to cause the optimization objectives at each stage to be disconnected, making it difficult to obtain a reasonable overall unit operation plan.

[0012] Fifth, errors in renewable energy forecasts and changes in net load further increase the conservatism required to determine the operating status of all units in advance. Day-ahead forecasts cannot fully reflect actual subsequent operating conditions. If too many slow-start units are put into operation in advance during the day-ahead phase to cover all possible renewable energy fluctuations and power deficits, unnecessary operating costs will be incurred. Conversely, if the safety margin reserved in the day-ahead phase is insufficient, power support and frequency security may be lacking in subsequent operating phases. Therefore, a reasonable division of labor needs to be established between the pre-determined basic operating mode and the flexibly available regulation resources.

[0013] In summary, while existing frequency-constrained unit combination methods can ensure system frequency security by increasing reserve capacity, increasing the number of online units, or explicitly introducing frequency security constraints, they still lack a hierarchical coordination mechanism that can fully utilize the flexibility of fast-start units for conventional units with different start-up characteristics. Especially under conditions of high renewable energy integration, how to coordinate the early commitment of slow-start units with the flexible later deployment of fast-start units, and how to directly involve system frequency security requirements in the operational division of labor between fast and slow units, while satisfying frequency security constraints and reducing unnecessary early online operation and inefficient operation of slow-start units, are problems that existing technologies still need to further address. Summary of the Invention

[0014] The technical problem this invention aims to solve is to address the shortcomings of the prior art by providing a frequency-constrained unit combination method and system with stratified fast and slow start-up units. This method stratifies the early commitment of slow start-up units and the subsequent adjustment of fast start-up units, and jointly optimizes the operating states of both types of units in relation to frequency safety constraints. This coordinates basic operational requirements, subsequent flexible adjustment requirements, and frequency safety requirements. It addresses the problem that existing frequency-constrained unit combination methods fail to adequately distinguish the differences in start-up characteristics and decision-making time scales between fast and slow start-up units, resulting in the difficulty of the fast start-up units' subsequent flexible deployment capabilities participating in unit combination decisions under frequency safety constraints, and causing the system to overly rely on the early online status of slow start-up units to meet frequency safety requirements. The present invention adopts the following technical solution: A frequency-constrained unit combination method with fast and slow start-up units includes the following steps: Obtain load forecast data, conventional unit parameters, new energy output forecast data, and frequency response parameters. Based on unit start-up time, minimum start-up time, or equivalent flexibility index, conventional units are divided into slow-start units and fast-start units. Taking slow-start units as the first-stage decision-making objects, we establish start-up state variables, start-up variables, shutdown variables and baseline output variables, and construct a first-stage unit combination model including state transition constraints, minimum start-up and shutdown time constraints, upper and lower limit output constraints, ramp-up constraints and basic power balance constraints. Based on the commitment results of the slow-start units determined in the first stage, and considering net load deviation, fluctuations in renewable energy output, or power deficit, establish the input state variables and output adjustment variables of the fast-start units, and construct the second-stage adjustment model. Based on the online status of the slow-start units and the commissioning status and output capacity of the fast-start units, an aggregated characterization of the system frequency support capacity is established, and a safety constraint for the lowest frequency point is constructed based on the aggregated characterization. The first-stage unit combination model, the second-stage regulation model, and the minimum frequency point safety constraint are coupled to form a two-stage joint optimization model. Through mixed integer optimization, the basic start-up and shutdown plan of slow-start units and the call-up scheme of fast-start units are obtained.

[0015] Furthermore, the startup time, minimum start-up time, minimum shutdown time, rated capacity, and frequency regulation characteristics of each conventional unit are obtained, and the units are classified according to their startup flexibility. Conventional units with long startup times and whose operating status should not be changed frequently are classified as slow-start units, while conventional units that can be put into operation in a short time and have flexible dispatch capabilities are classified as fast-start units.

[0016] Furthermore, the first-stage unit combination model takes the basic operating cost of slow-start units within the scheduling cycle as the optimization objective. By optimizing the start-up status variables, start-up variables, shutdown variables, and baseline output variables, it determines the slow-start units that need to be put into operation in advance for each scheduling period and their corresponding baseline output, thus forming the basic operating mode of the system.

[0017] Furthermore, in the first-stage unit combination model, the state transition constraint is used to limit the logical relationship between the start-up state, startup state, and shutdown state of the slow-start unit during adjacent scheduling periods. The minimum start-up and shutdown time constraints are used to limit the continuous start-up time and continuous shutdown time of slow-start units; The upper and lower limits of output are used to limit the reference output range of the slow-start unit according to its operating status. The ramp constraint is used to limit the output variation of slow-start units between adjacent scheduling periods; The basic power balance constraint is used to limit the power supply and demand balance relationship for each scheduling period.

[0018] Furthermore, while maintaining the basic commitment structure of the slow-start units determined in the first stage, the second-stage adjustment model optimizes the input state variables and output adjustment variables of the fast-start units based on the net load deviation, decrease in new energy output, or power deficit that occur during actual operation, so as to determine the fast-start units put into operation and their adjusted output in each scheduling period.

[0019] Furthermore, when the system net load increases, the output of new energy sources decreases, or there is a power deficit, the supplementary active power provided by the fast-start units is determined based on the commissioning status and adjustable output of the fast-start units; and the frequency support capability corresponding to the fast-start units in operation is incorporated into the aggregated representation of the system frequency support capability.

[0020] Furthermore, the aggregated characterization of the system's frequency support capability is determined based on the online unit composition and corresponding frequency response characteristics of each scheduling period. The online status of the slow-start units is used to characterize the system's basic inertia and basic frequency regulation support capability, while the commissioning status and output capability of the fast-start units are used to characterize the additional frequency support capability. The lowest point of the system frequency is determined based on the aggregated characterization of the system frequency support capability, and the lowest point of the system frequency is not lower than a preset frequency safety threshold as the safety constraint of the lowest point of the frequency.

[0021] Furthermore, in the two-stage joint optimization model, based on the relationship between the basic frequency support capacity formed by the slow-start units in the first stage and the minimum frequency safety constraint, the input status and output of the fast-start units in the second stage are optimized so that the fast-start units provide additional frequency support during scheduling periods when the basic frequency support capacity is insufficient to meet the minimum frequency safety constraint.

[0022] Furthermore, the two-stage joint optimization model takes system operating cost as the optimization objective. Under the conditions of satisfying the operating constraints of the first-stage unit combination model, the operating constraints of the second-stage regulation model, and the safety constraints of the minimum frequency point, the basic start-up and shutdown plan of the slow-start units, the benchmark output of each scheduling period, and the input status and regulation output of the fast-start units are jointly determined by the mixed integer optimization method.

[0023] Secondly, embodiments of the present invention provide a frequency-constrained unit combination system with fast and slow start-up units, comprising: The data classification module is used to acquire load forecast data, conventional unit parameters, new energy output forecast data and frequency response parameters, and classify conventional units into slow-start units and fast-start units according to the unit start-up characteristics. The first-stage combination module is used to establish the start-up status variables, start-up variables, shutdown variables and baseline output variables of the slow-start unit as the decision object, and to construct the first-stage unit combination model. The second-stage adjustment module is used to establish the input state variables and output adjustment variables of the fast-start unit based on the slow-start unit commitment results determined by the first-stage combination module, according to the net load deviation, new energy output fluctuations or power deficit, and to construct the second-stage adjustment model. The frequency constraint module is used to establish an aggregated characterization of the system frequency support capability based on the online status of the slow-start unit and the commissioning status and output capacity of the fast-start unit, and to construct a minimum frequency safety constraint based on the aggregated characterization. The joint optimization module is used to couple the first-stage unit combination model, the second-stage regulation model, and the minimum frequency point safety constraint to form a two-stage joint optimization model, and solve the two-stage joint optimization model to obtain the basic start-up and shutdown plan of the slow-start unit and the call scheme of the fast-start unit.

[0024] Thirdly, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described frequency-constrained unit combination method for fast and slow start-up unit stratification.

[0025] Fourthly, embodiments of the present invention provide a computer-readable storage medium including a computer program, which, when executed by a processor, implements the steps of the above-described frequency-constrained unit combination method for fast and slow start-up unit stratification.

[0026] Compared with the prior art, the present invention has at least the following beneficial effects: A tiered frequency-constrained unit combination method with fast and slow start-up configurations is proposed. Conventional units are divided into slow-start and fast-start units based on their start-up characteristics. A first-stage slow-start unit combination model and a second-stage fast-start unit regulation model are established. The system frequency support capacity and minimum frequency safety constraints are then incorporated into the two-stage joint optimization. This ensures that units with different start-up speeds are no longer uniformly committed to the same time scale. Units with slow start-up speeds, requiring advance scheduling, primarily undertake basic operational tasks, while reserving space for fast-start units to be deployed as needed in subsequent stages. When net load, renewable energy output, or frequency support demand changes, fast-start units are used to supplement the load, avoiding the need to pre-schedule too many slow-start units online during the day-ahead phase. This balances frequency safety, unit operation rationality, and scheduling economy.

[0027] Furthermore, conventional generating units are classified using parameters such as start-up time, minimum start-up and shutdown time, rated capacity, and frequency regulation characteristics, ensuring that the division between fast and slow start-up units is based on actual operating characteristics. This determines the criteria for different units entering different optimization stages. For units whose operating states should not change frequently, combination decisions are made in advance; for units that can be put into operation relatively quickly, the ability to be called up later is retained. This reduces the neglect of the actual start-up and shutdown characteristics of units in the unified modeling, making the optimization results in the subsequent two stages more consistent with actual scheduling conditions.

[0028] Furthermore, taking slow-start units as the primary decision-making target in the first phase, the start-up and shutdown status and baseline output of these units are determined based on the system's basic operating costs. This ensures that a stable operating structure capable of undertaking basic power supply tasks is established in the first phase. Utilizing the limited start-up and shutdown flexibility of slow-start units to address basic operational issues that need to be determined in advance avoids increasing the number of slow-start units online due to excessive reserve of adjustment capacity, leaving room for optimization in the second phase when fast-start units are deployed.

[0029] Furthermore, the start-up and shutdown processes and output changes of slow-start units are constrained through state transition constraints, minimum start-up and shutdown time constraints, upper and lower output limit constraints, ramping constraints, and basic power balance constraints. This ensures that the basic start-up and shutdown plan formed in the first stage not only meets power balance requirements but also conforms to the slow-start unit's own continuous operating time, shutdown time, output range, and ramping capability, avoiding mathematically feasible but practically unexecutable operating schemes, thus improving the feasibility of the basic combination results in the first stage.

[0030] Furthermore, while maintaining the basic commitment structure of the slow-start units in the first phase, the commissioning status and regulation output of the fast-start units are optimized based on net load deviations, decreases in renewable energy output, or power deficits. This avoids frequently overturning the established slow-start unit plans after changes in system operating conditions, instead utilizing the fast-start units to undertake subsequent incremental adjustment tasks. It leverages the rapid start-up and flexible regulation characteristics of the fast-start units, reducing the frequent changes in start-stop status of the slow-start units due to short-term operational variations, thus establishing a clear division of labor between the basic plan and subsequent flexible adjustments.

[0031] Furthermore, the regulations stipulate that when net load increases, renewable energy output decreases, or a power deficit exists, fast-start units will provide supplementary active power, and the frequency support capacity corresponding to the fast-start units already in operation will be included in the aggregated representation of the system's frequency support capacity. This allows fast-start units to not only perform power balance compensation but also participate in the system's frequency support evaluation after being put into operation, thus extending their operational value beyond ordinary standby capacity. It establishes a link between the subsequent commissioning of fast-start units and system safety requirements, improving the actual utilization of flexible resources.

[0032] Furthermore, an aggregated characterization of the system's frequency support capability is established based on the online unit configuration and its frequency response characteristics, with the system's lowest frequency not falling below a preset safety threshold as a frequency safety constraint. This avoids indirectly reflecting frequency safety solely through uniform reserve capacity or empirical margins, allowing the frequency support capability corresponding to different unit operating states to directly influence unit combination decisions. Slow-start units establish basic inertia and basic frequency regulation support, while fast-start units provide additional support after being put into operation, enabling the determination of whether the operating scheme meets frequency safety requirements based on the actual unit configuration.

[0033] Furthermore, based on the relationship between the basic frequency support capacity established in the first phase and the minimum frequency safety constraints, the commissioning status and output of the fast-start units in the second phase are determined. When the basic support capacity already meets the frequency safety requirements, the number of fast-start units can be reduced; when the basic support is insufficient, fast-start units are used to supplement it. This allows frequency constraints to directly participate in the decision-making process for fast-start units, enabling safety resources to be configured according to actual needs and reducing the conservative operating mode of keeping a large number of units online in advance to cover all potential risks.

[0034] Furthermore, the first-stage operational constraints, the second-stage regulation constraints, and the minimum frequency safety constraints are all unified under the system operating cost optimization objective for mixed-integer optimization. This ensures that the basic start-up and shutdown plans and baseline output of slow-start units, as well as the operational status and regulation output of fast-start units, can be determined in a coordinated manner. This avoids inconsistencies in objectives caused by simply combining separately optimized components. It allows safety constraints, basic operational requirements, and flexible regulation requirements to interact within the same optimization framework, reducing unnecessary online capacity and inefficient operating periods while meeting unit operating conditions and frequency safety requirements.

[0035] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0036] In summary, this invention separates slow-start and fast-start units into two decision-making stages and incorporates the minimum frequency constraint into joint optimization. This allows slow-start units to undertake basic commitments while fast-start units compensate as needed, reducing the premature online status of slow-start units and improving the utilization rate of fast-start units. This improves the operational structure and economy while ensuring frequency safety.

[0037] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0038] Figure 1 This is a flowchart illustrating the frequency-constrained unit combination method for fast and slow start-up units according to the present invention. Figure 2 This is a schematic diagram of the two-stage joint optimization framework of the fast-start unit and the slow-start unit of the present invention; Figure 3 This is a schematic diagram illustrating the optimization process of the first-stage slow-start unit combination model of the present invention; Figure 4 This is a schematic diagram illustrating the optimization process of the second-stage fast-start unit regulation model of the present invention; Figure 5 This is a schematic diagram illustrating the relationship between the frequency support capability aggregation characterization of the system of the present invention, the safety constraint of the minimum frequency point, and the two-stage unit decision-making. Figure 6 This is a schematic diagram of the frequency-constrained unit combination optimization system for fast and slow start-up units of the present invention. Figure 7 A schematic diagram of a computer device provided in an embodiment of the present invention; Figure 8 This is a block diagram of an electronic device according to an embodiment of the present invention.

[0039] Among them, 60. Computer equipment; 61. Processor; 62. Memory; 63. Computer program; 600. Electronic device; 610. Processing unit; 620. Storage unit; 6201. Random access memory unit; 6202. Cache memory unit; 6203. Read-only memory unit; 6204. Program / utility; 6205. Program module; 630. Bus; 640. Display unit; 650. Input / output interface; 660. Network adapter; 700. External device. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0042] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0043] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0044] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0045] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0046] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0047] This invention provides a frequency-constrained unit combination method with tiered fast and slow start-up configurations. First, conventional units are categorized into slow-start and fast-start units based on their start-up characteristics, establishing a foundational commitment for the start-stop status and baseline output of the slow-start units in the first stage. Then, while maintaining the committed structure of the slow-start units, the operational status and adjusted output of the fast-start units are determined in the second stage based on net load deviation, renewable energy fluctuations, or power deficits. Furthermore, a minimum frequency safety constraint is set based on the system frequency support capacity corresponding to the unit states in both stages, allowing frequency safety requirements to participate in the joint combination decision-making of fast and slow units. This mechanism can transform some of the safety margin that would otherwise rely on slow-start units to provide in advance into flexible resource allocation in subsequent stages, reducing unnecessary long-term online and low-load operation of slow-start units, improving the unit operation structure and reducing operating costs while meeting frequency safety requirements.

[0048] This invention addresses the problem that traditional frequency-constrained unit combination methods, under conditions of high-proportion renewable energy access, do not adequately distinguish the operating characteristics of fast-start units and slow-start units. This results in the difficulty for fast-start units to participate in unit combination decisions under frequency security constraints, and the problem of scheduling a large number of slow-start units online in advance to meet frequency security requirements. The invention places slow-start units and fast-start units in different decision-making stages for coordinated optimization.

[0049] The first phase primarily addresses which slow-start units need to be pre-arranged for online operation and how to allocate the baseline output of each slow-start unit. Because slow-start units have a longer startup process and a slower adjustment speed in their operating status, failing to determine their start-up and shutdown status in advance may make it difficult to meet subsequent system operation requirements. Therefore, the combination and arrangement of slow-start units are mainly completed during the day-ahead phase or the corresponding advance decision-making phase.

[0050] The second stage primarily addresses the question of which fast-start units should be activated and how much regulating output each unit should provide when the system's operating state changes, under the basic operating mode established in the first stage. Compared to slow-start units, fast-start units can be put into operation in a shorter time, and their main role is to provide supplementary power and additional frequency support when needed. Therefore, this invention, through two-stage modeling, assigns basic support tasks to slow-start units and subsequent flexible reinforcement tasks to fast-start units, thereby enabling units with different starting characteristics to participate in unit combination optimization according to their respective operating features.

[0051] Please see Figure 1 The present invention provides a frequency-constrained unit combination method with fast and slow start-up units, comprising the following steps: S1. Read system basic data and complete unit classification. Different types of conventional generating units are assigned to different decision-making stages by making combined decisions on a unified time scale, which provides a foundation for the subsequent construction of a two-stage unit combination model with fast and slow start-up units.

[0052] S2. Construct the first-stage slow-start unit combination model. After classifying the generating units, the slow-starting units were taken as the main decision-making objects in the first stage. Based on load forecast data, new energy output forecast data, and operating parameters of the slow-starting units, the start-up status variables, start-up variables, shutdown variables, and baseline output variables of the slow-starting units were established for each scheduling period.

[0053] Among them, the start-up status variable is used to characterize whether the corresponding slow-start unit is in operation during the corresponding scheduling period; the start-up variable and the shutdown variable are used to characterize the start-up or shutdown status changes of the slow-start unit between adjacent scheduling periods; and the baseline output variable is used to characterize the basic active power output undertaken by the slow-start unit under the corresponding operating state.

[0054] The first phase focuses on arranging the basic start-up and shutdown schedule and baseline output of slow-start units, with the optimization objective of minimizing the basic operating cost of the system, and constructs a day-ahead combination optimization model for slow-start units.

[0055] The first-stage slow-start unit combination model includes at least the following constraints: (1) State transition constraints of slow start units Establish corresponding logical relationships based on the start-up, startup, and shutdown status of slow-start units in adjacent scheduling periods, so that the start-up, startup, and shutdown decisions of the units are consistent, thereby ensuring that the unit start-up and shutdown plans obtained in the first stage meet the actual operating state transition relationships.

[0056] (2) Minimum start-up time and minimum downtime constraints Based on the minimum start-up and minimum shutdown times corresponding to each slow-start unit, constraints are imposed on the continuous running time and continuous shutdown time of the unit to prevent the slow-start unit from frequently changing its operating state when it does not meet its own start-stop characteristics, so that the obtained start-stop plan conforms to the actual operating characteristics of the slow-start unit.

[0057] (3) Output upper and lower limit constraints Based on the operating status and output capacity of the slow-start units, the baseline output for each scheduling period is limited so that the baseline output of the slow-start units in operation is within their allowable output range.

[0058] (4) Climbing constraint Based on the output regulation capability of the slow-start unit, the output variation between adjacent scheduling periods is restricted so that the baseline output variation of the slow-start unit conforms to its actual climbing capability.

[0059] (5) Basic power balance constraints Based on the load forecast results, new energy output forecast results, and unit output arrangements for each scheduling period, a basic power balance relationship is established so that the operating mode formed in the first phase can meet the basic power supply needs of the system.

[0060] By coordinating the start-up and shutdown status and baseline output of the slow-start unit through the above constraints, the slow-start unit is mainly responsible for the basic operating tasks that need to be determined in advance.

[0061] Through the first stage of optimization, the basic operating mode of the slow-start units throughout the entire scheduling cycle is obtained, including the slow-start units that need to be put into operation in advance and the benchmark output corresponding to each scheduling period, thus forming the basic support layer of the system.

[0062] Unlike the approach of allocating all safety margins to slow-start units in advance, the first stage of this invention mainly determines the basic operating structure required by the system. It does not require increasing the number of online slow-start units in the first stage to pre-handle all subsequent regulation and frequency safety requirements. Instead, it reserves decision-making space for flexible compensation using fast-start units in the second stage.

[0063] S3. Construct the second-stage fast-start unit regulation model. After obtaining the basic commitment results of the slow-start units in the first stage, the commitment results of the slow-start units are used as the basis for the second stage optimization. A supplementary adjustment model for the fast-start units is established to address the net load deviation, new energy output fluctuations, or power deficits that may occur during the subsequent operation of the system.

[0064] The second-stage adjustment model includes the input status variables, output adjustment variables, and corresponding variables required for system balance correction of the fast-start units during each scheduling period.

[0065] Among them, the input state variable is used to characterize whether the corresponding fast-start unit is put into operation during the corresponding scheduling period; the output adjustment variable is used to characterize the supplementary active power provided by the fast-start unit after it is put into operation.

[0066] The second phase does not change the basic commitment structure of the slow-start units already determined in the first phase. Instead, it utilizes the flexibility of the fast-start units to compensate for any support deficiencies that may occur during system operation, building upon the aforementioned basic operating mode. Therefore, unlike the slow-start units, the fast-start units do not require a unified prior commitment in the first phase; instead, their activation and corresponding adjustment levels can be determined based on the system operating status corresponding to the second phase.

[0067] Specifically, when the net load of the system increases relative to the basic operating state, the available output of new energy sources in actual or corresponding operating states decreases, or there is insufficient power support during the corresponding scheduling period, one or more fast-start units can be put into operation to provide additional active power to compensate for the corresponding power deficit and reduce the pressure on slow-start units to bear the immediate power adjustment.

[0068] In addition to power compensation, the second phase also utilizes the commissioned fast-start units to increase the frequency support resources available to the system. When the system faces frequency security constraints, the commissioning status and corresponding output capacity of the fast-start units, together with the available frequency support capacity of the system, participate in the subsequent frequency security assessment.

[0069] Therefore, this step is not a simple adjustment of the output results of the first stage, but rather, while maintaining the basic commitment structure of the slow-start units, it transforms the fast-start units from ordinary units that require prior unified commitment into flexible resources that can be called up later according to system needs, so that their rapid deployment and flexible adjustment characteristics can participate in the unit combination optimization.

[0070] Through the above methods, a relatively stable basic operating structure is formed in the first stage, and the second stage is used to strengthen the power regulation and frequency support requirements not covered by the basic operating structure, thus forming a layered operation mode of fast and slow start-up units with "basic support + flexible compensation".

[0071] S4. Establish a frequency constraint model Based on the completion of the first-stage slow-start unit combination model and the second-stage fast-start unit regulation model, the system frequency safety requirements are explicitly introduced into the unit combination optimization process.

[0072] Specifically, based on the online unit composition and frequency response characteristics of the corresponding units in each scheduling period, aggregate parameters are established to characterize the system's frequency support capability. Based on these aggregate parameters, a frequency nadir safety constraint is constructed to ensure that the optimized unit operation mode meets the preset frequency safety threshold requirements.

[0073] In this system, the online status determined in the first stage of the slow-start units forms the basic operational structure of the system, and the inertia and frequency regulation capabilities of the online units constitute the basic frequency support capability of the system. The fast-start units provide additional support resources based on the commissioning status and output capability determined in the second stage. Therefore, under the tiered decision-making of fast and slow start units, the system frequency support capability is jointly determined by the basic support formed in the first stage and the flexible support that can be provided in the second stage.

[0074] The lowest frequency point under the corresponding operating state is determined based on the aggregated characterization of the system's frequency support capability, and the lowest frequency point being no lower than a preset frequency safety threshold is taken as the frequency safety condition that the unit combination optimization needs to meet.

[0075] During the optimization process, the minimum frequency safety constraint is not independently verified after all unit combination calculations are completed, but rather participates in determining the operating mode of fast and slow start units. When the basic frequency support capacity formed by the slow start units in the first stage is sufficient to meet the frequency safety requirements of the corresponding scheduling period, the use of fast start units can be reduced or eliminated. When the frequency support capacity corresponding to the basic operating mode is insufficient to meet the frequency safety requirements, the available support capacity is increased by adjusting the input status and output level of the fast start units in the second stage to supplement the frequency safety requirements of the corresponding period.

[0076] Therefore, frequency security requirements can affect the way fast-start units are deployed in the second phase, so that fast-start units are not configured according to fixed standby capacity, but rather the need to be put into operation and the level of operation is determined according to the system support status of the corresponding scheduling period.

[0077] Through the above processing, system frequency security no longer relies solely on increasing the number of slow-start units online in advance or reserving a uniform static safety margin. Instead, it utilizes the basic support capabilities of slow-start units and the post-regulation capabilities of fast-start units to jointly meet frequency security requirements.

[0078] S5. Formulate and solve the two-stage joint optimization model. The first-stage slow-start unit combination model established in step S2, the second-stage fast-start unit regulation model established in step S3, and the frequency minimum point safety constraint established in step S4 are coupled to form a two-stage unit combination joint optimization model that considers the hierarchical decision-making of fast and slow start units and frequency safety constraints.

[0079] In the two-stage joint optimization model, the first stage is used to determine the basic start-up and shutdown plan and baseline output of the slow-start units, forming the basic support framework required for system operation; the second stage, based on the slow-start unit commitment results formed in the first stage, determines the input status and regulation output of the fast-start units according to power regulation requirements and frequency security requirements.

[0080] The first and second stages are not independent: the online status and baseline output of the slow-start units determined in the first stage affect the system's basic power and frequency support capabilities; the system's basic support capabilities further affect the number and output level of the fast-start units that need to be called up in the second stage; the fast-start units put into operation in the second stage participate in system power balance and frequency safety constraints by providing supplementary active power and corresponding support capabilities. Therefore, the coordinated operation between slow-start and fast-start units is achieved through the aforementioned two-stage joint optimization model.

[0081] With system operating cost as the optimization objective, and under the conditions of satisfying the state transition constraints of slow start-up units, minimum start-up and shutdown time constraints, upper and lower output limits constraints, ramping constraints, power balance constraints, fast start-up unit regulation requirements, and minimum frequency safety constraints, the two-stage joint optimization model is solved using a mixed integer optimization method.

[0082] The optimization results obtained by solving the problem include the basic start-up and shutdown plan of slow-start units, the basic operating mode corresponding to each scheduling period, the flexible dispatching scheme of fast-start units, and the total system operating cost.

[0083] According to the above two-stage joint optimization approach, during scheduling periods with strong system infrastructure support, the second stage can reduce the deployment of fast-start units; while during scheduling periods with insufficient infrastructure support or additional power support requirements, the second stage can selectively deploy fast-start units for compensation. Therefore, the start-up schedule of slow-start units is mainly determined by basic power supply needs, without needing to add a large number of slow-start units to the system in advance to cover all the flexible safety margins; fast-start units are mainly deployed during scheduling periods with actual compensation needs.

[0084] Compared to a uniform unit combination approach that does not distinguish between fast-start and slow-start units, this invention achieves a more compact overall online unit structure by configuring the two types of units at different decision-making stages. Slow-start units do not need to maintain too many units online in advance to cover all subsequent changes, and fast-start units do not need to run continuously throughout the entire scheduling cycle. Instead, they are flexibly deployed according to system needs, thereby reducing unnecessary starts and stops and inefficient online operation.

[0085] Furthermore, this invention does not merely add fast-start units as supplementary units to the traditional unit combination model, but rather utilizes a two-stage mechanism to change the operational division of labor between fast and slow-start units under frequency constraints. Slow-start units undertake basic operational tasks that need to be determined in advance, while fast-start units undertake subsequent flexible compensation tasks. Frequency security constraints participate in the resource allocation between the two types of units, transforming the system from a conservative operation mode that primarily relies on adding slow-start units to be online in advance to an operation mode that coordinates basic support with flexible compensation.

[0086] Therefore, this invention coordinates the early commitment of slow-start units, the later call-up of fast-start units, and system frequency security requirements within the same two-stage optimization framework through hierarchical decision-making of fast-start units and slow-start units. While ensuring power balance and frequency security requirements, it helps reduce unnecessary early online and long-term low-load operation of slow-start units, reduces start-up and operation costs, improves the utilization of flexible resources of fast-start units, and improves the rationality and economy of unit combination operation under high proportion of renewable energy access.

[0087] After completing steps S1 to S5, hierarchical decision-making is implemented for slow-start and fast-start units, and the two-stage unit combination process is jointly optimized with frequency safety constraints. This allows units with different start-up characteristics to undertake corresponding system functions according to their respective operating characteristics. Slow-start units primarily undertake the pre-determined basic start-up and shutdown and baseline output tasks, forming the system's basic operating structure. Fast-start units, based on the system's operating status in the second stage, are flexibly deployed when there are net load deviations, new energy output fluctuations, power deficits, or frequency support requirements, forming a basic support + flexible compensation operating mode.

[0088] By adopting the above-mentioned hierarchical decision-making approach, the start-up and shutdown status of slow-start units, which have longer start-up times and slower status adjustment speeds, can be pre-arranged in the first stage based on basic operational needs. For fast-start units with greater start-up flexibility, their activation can be determined in the second stage based on actual support requirements. This reduces the need for standardized decisions that ignore the start-up characteristics of different units, making the unit combination results more consistent with the actual operating patterns of fast and slow-start units.

[0089] Furthermore, this invention utilizes fast-start units as flexible adjustment resources in the second stage, enabling them not only to provide supplementary active power when net load increases, renewable energy output decreases, or power deficits exist, but also to participate in subsequent adjustments when frequency security constraints require further enhancement of system support capabilities. Therefore, fast-start units can be retroactively called upon based on system operating status and frequency security requirements, allowing their rapid start-up and flexible adjustment characteristics to directly contribute to the formation of unit combination results.

[0090] In traditional unified unit configuration methods, when system frequency security requirements increase, it is usually necessary to improve system support capacity by increasing the number of online units or reserving more operational margin. This can easily lead to some slow-start units being put into operation ahead of schedule and kept running for extended periods. This invention, after establishing the basic operational structure of slow-start units in the first stage, retains flexible deployment space for fast-start units in the second stage. This allows some subsequent support needs to be met by fast-start units when needed, rather than covering everything by adding slow-start units to the network in advance.

[0091] Therefore, while meeting the corresponding power balance and frequency safety constraints, the unnecessary early online requirements of some slow-start units can be reduced, allowing the operation schedule of slow-start units to be determined more around the basic power supply demand, while fast-start units are mainly put into operation during periods with actual compensation needs. This reduces the long-term low-load operation of some units and redundant online capacity, making the overall online unit structure more compact and the unit start-up, shutdown, and output arrangements more reasonable.

[0092] Meanwhile, since fast-start units can be deployed according to the actual needs of the second phase, there is no need to reserve all subsequent adjustment and safety support capabilities in advance through slow-start units in the first phase. Therefore, it can reduce unnecessary start-ups and shutdowns and inefficient online periods of some slow-start units, and reduce the additional operational burden caused by idle operation and excessive standby. Fast-start units are called upon according to the support needs of specific time periods, which also allows adjustment resources to be more concentrated on the actual operating segments, which helps to reduce the overall system operating cost and comprehensive scheduling cost.

[0093] Furthermore, this invention directly incorporates frequency safety constraints into the two-stage joint optimization process of fast and slow start units. The basic support capacity provided by the slow start units in the first stage and the additional support capacity provided by the fast start units in the second stage both participate in the frequency safety constraints. When the basic support capacity can meet the frequency safety requirements, the use of fast start units is reduced; when the basic support capacity is insufficient, it is supplemented by adjusting the operation status and output level of the fast start units in the second stage, so that the frequency safety requirements can participate in the operational division of labor between the fast and slow start units.

[0094] Therefore, this invention coordinates the advance commitment of slow-start units, the subsequent call of fast-start units, and system frequency security requirements through a layered and two-stage joint optimization mechanism for fast and slow start units. This transforms the system operation mode from a conservative configuration that mainly relies on increasing the online status of slow-start units in advance to an operation mode in which the basic operating structure and flexible support resources work together. This improves the rationality of unit combination results while meeting system frequency security requirements and taking into account the economic efficiency of system operation.

[0095] In another embodiment of the present invention, a frequency-constrained unit combination system with fast and slow start-up mechanisms is provided. This system can be used to implement the above-mentioned frequency-constrained unit combination method with fast and slow start-up mechanisms. Specifically, the frequency-constrained unit combination system with fast and slow start-up mechanisms includes a data classification module, a first-stage combination module, a second-stage adjustment module, a frequency constraint module, and a joint optimization module.

[0096] The data classification module is used to acquire load forecast data, conventional unit parameters, new energy output forecast data and frequency response parameters, and classify conventional units into slow-start units and fast-start units according to the unit start-up characteristics. The first-stage combination module is used to establish the start-up status variables, start-up variables, shutdown variables and baseline output variables of the slow-start unit as the decision object, and to construct the first-stage unit combination model. The second-stage adjustment module is used to establish the input state variables and output adjustment variables of the fast-start unit based on the slow-start unit commitment results determined by the first-stage combination module, according to the net load deviation, new energy output fluctuations or power deficit, and to construct the second-stage adjustment model. The frequency constraint module is used to establish an aggregated characterization of the system frequency support capability based on the online status of the slow-start unit and the commissioning status and output capacity of the fast-start unit, and to construct a safety constraint for the lowest frequency point based on the aggregated characterization. The joint optimization module is used to couple the first-stage unit combination model, the second-stage regulation model, and the minimum frequency point safety constraint to form a two-stage joint optimization model, and solve the two-stage joint optimization model to obtain the basic start-up and shutdown plan of the slow-start unit and the call scheme of the fast-start unit.

[0097] This invention provides a terminal device comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, graphics processing units (GPUs), tensor processing units (TPUs), 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. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve a corresponding method flow or function. The processor described in this embodiment can be used in the operation of a frequency-constrained unit combination method with fast and slow start-up units, including: Obtain load forecast data, conventional unit parameters, renewable energy output forecast data, and frequency response parameters. Based on unit start-up time, minimum start-up time, or equivalent flexibility indicators, conventional units are classified into slow-start units and fast-start units. Taking slow-start units as the first-stage decision-making object, establish start-up state variables, start-up variables, shutdown variables, and baseline output variables. Construct a first-stage unit combination model including state transition constraints, minimum start-up and shutdown time constraints, output upper and lower limit constraints, ramp-up constraints, and base power balance constraints. Using the slow-start unit commitment results determined in the first stage as conditions, for net... For load deviations, fluctuations in renewable energy output, or power deficits, establish input state variables and output adjustment variables for fast-start units, and construct a second-stage adjustment model. Based on the online status of slow-start units and the input status and output capacity of fast-start units, establish an aggregated representation of the system frequency support capacity, and construct a minimum frequency safety constraint based on the aggregated representation. Couple the first-stage unit combination model, the second-stage adjustment model, and the minimum frequency safety constraint to form a two-stage joint optimization model. Solve the model using mixed integer optimization to obtain the basic start-up and shutdown plan for slow-start units and the dispatch scheme for fast-start units.

[0098] Please see Figure 7 The terminal device is a computer device. In this embodiment, the computer device 60 includes a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When executed by the processor 61, the computer program 63 implements the frequency-constrained unit combination method of the fast-start unit layer in this embodiment. To avoid repetition, these details are not elaborated here. Alternatively, when executed by the processor 61, the computer program 63 implements the functions of each model / unit in the frequency-constrained unit combination system of the fast-start unit layer in this embodiment. To avoid repetition, these details are not elaborated here.

[0099] Computer device 60 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. Computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will understand that... Figure 7 This is merely an example of computer device 60 and does not constitute a limitation on computer device 60. It may include more or fewer components than shown, or combine certain components, or different components. For example, computer device may also include input / output devices, network access devices, buses, etc.

[0100] The processor 61 may be a Central Processing Unit (CPU), or other general-purpose processors, graphics processing units (GPUs), tensor processing units (TPUs), 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 may be a microprocessor or any conventional processor.

[0101] The memory 62 can be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 can also be an external storage device of the computer device 60, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on the computer device 60.

[0102] Furthermore, the memory 62 may include both internal storage units of the computer device 60 and external storage devices. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 can also be used to temporarily store data that has been output or will be output.

[0103] Please see Figure 8 The terminal device is an electronic device 600, which is manifested in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including storage unit 620 and processing unit 610), a display unit 640, etc.

[0104] The storage unit stores program code, which can be executed by the processing unit 610 to perform the steps described in the method section of this specification according to various exemplary embodiments of the present invention. For example, the processing unit 610 can perform actions such as... Figure 1 The steps are shown in the figure.

[0105] Storage unit 620 may include readable media in the form of volatile storage units, such as random access memory (RAM) 6201 and / or cache memory 6202, and may further include read-only memory (ROM) 6203.

[0106] Storage unit 620 may also include a program / utility 6204 having a set (at least one) program module 6205, such program module 6205 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0107] Bus 630 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the multiple bus structures.

[0108] Electronic device 600 can also communicate with one or more external devices 700 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 600, and / or with any device that enables electronic device 600 to communicate with one or more other computing devices (e.g., router, modem). This communication can be performed via input / output interface 650. Furthermore, electronic device 600 can also communicate with one or more networks (e.g., local area network, wide area network, and / or public network, such as the Internet) via network adapter 660. Network adapter 660 can communicate with other modules of electronic device 600 via bus 630. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0109] This invention also provides a storage medium, specifically a computer-readable storage medium, which is a memory device in a terminal device for storing programs and data. It is understood that the computer-readable storage medium here can include both built-in storage media in the terminal device and extended storage media supported by the terminal device; it can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor, which can be one or more computer programs (including program code). More specific examples of the computer-readable storage medium include: an electrical connection with one or more wires, a portable disk, a hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical fiber, portable compact disk read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0110] Computer-readable storage media also include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable storage medium can also be any readable medium other than a readable storage medium that can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium can be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, radio frequency, etc., or any suitable combination thereof.

[0111] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0112] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the frequency-constrained unit combination method related to the fast and slow start-up unit stratification in the above embodiments; one or more instructions in the computer-readable storage medium are loaded by the processor and executed as follows: Obtain load forecast data, conventional unit parameters, renewable energy output forecast data, and frequency response parameters. Based on unit start-up time, minimum start-up time, or equivalent flexibility indicators, conventional units are classified into slow-start units and fast-start units. Taking slow-start units as the first-stage decision-making object, establish start-up state variables, start-up variables, shutdown variables, and baseline output variables. Construct a first-stage unit combination model including state transition constraints, minimum start-up and shutdown time constraints, output upper and lower limit constraints, ramp-up constraints, and base power balance constraints. Using the slow-start unit commitment results determined in the first stage as conditions, for net... For load deviations, fluctuations in renewable energy output, or power deficits, establish input state variables and output adjustment variables for fast-start units, and construct a second-stage adjustment model. Based on the online status of slow-start units and the input status and output capacity of fast-start units, establish an aggregated representation of the system frequency support capacity, and construct a minimum frequency safety constraint based on the aggregated representation. Couple the first-stage unit combination model, the second-stage adjustment model, and the minimum frequency safety constraint to form a two-stage joint optimization model. Solve the model using mixed integer optimization to obtain the basic start-up and shutdown plan for slow-start units and the dispatch scheme for fast-start units.

[0113] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0114] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0115] To further illustrate the implementation process and function of the frequency-constrained unit combination method with fast and slow start-up described in this invention, a power system including conventional units, renewable energy sources, and system loads can be selected as the simulation object for unit combination calculation. The load forecast data, renewable energy output forecast data, and the start-up time, minimum start-up time, minimum downtime, rated capacity, ramp-up capability, and frequency response parameters of each conventional unit can all be obtained from the actual operating data of the power system to be dispatched.

[0116] First, based on the start-up time and operational flexibility of each conventional unit, the conventional units are divided into slow-start units and fast-start units. Units whose operating status needs to be determined in advance are classified as slow-start units, while units that can be quickly put into operation according to system needs during subsequent operation phases are classified as fast-start units.

[0117] During the day-ahead dispatch phase, a first-stage slow-start unit combination model is established according to step S2. Based on load forecasting and renewable energy output forecasting, the basic start-up and shutdown plan and baseline output of the slow-start units are determined. The first stage mainly forms a unit operation structure that meets the basic power supply requirements.

[0118] Subsequently, operational scenarios are set up to accommodate changes in the actual output of renewable energy relative to the forecast, increases in system net load, or additional power support requirements. While maintaining the basic commitment structure of the slow-start units in the first phase, step S3 determines the fast-start units to be deployed in the second phase and their regulating output. When the basic operating mode can meet the system power and balance requirements, the deployment of fast-start units is reduced; when there is a net load deviation, reduced renewable energy output, or power deficit, supplementary active power is provided by deploying the corresponding fast-start units.

[0119] Furthermore, based on the frequency response characteristics of the online slow-start units in the first phase and the fast-start units put into operation in the second phase, an aggregated characterization of the system's frequency support capability is established. Then, according to step S4, it is calculated or determined whether the minimum frequency point under the corresponding operating state meets the preset frequency safety threshold. When the basic operating mode of the first phase can already meet the frequency safety requirements, no unnecessary fast-start units are added. When the basic frequency support capability is insufficient, additional support is formed by adjusting the operation status and output level of the fast-start units in the second phase, and the frequency safety constraints are met again.

[0120] To evaluate the effectiveness of the method of the present invention, the two-stage optimization method of fast and slow start units described in the present invention is compared with the unified unit combination method that does not distinguish between fast and slow start units, and the following indicators are statistically analyzed respectively: the number of online slow start units and the online time period, the number of start-stop times of slow start units, the call time period and call level of fast start units, the unit output allocation in each time period, the system operating cost, and whether the minimum frequency point meets the set safety threshold.

[0121] The above comparison reveals the differences in operational structures resulting from the two unit combination methods under frequency security constraints. For a unified unit combination method, to proactively cover changes in renewable energy output, power deficits, and frequency security requirements, it is necessary to simultaneously determine the operating status of a number of conventional units during the day-ahead phase. The optimization results may gain significant foundational support by increasing the number of slow-start units that are brought online in advance.

[0122] When using the method of this invention, the first stage mainly determines the start-up and shutdown status and baseline output of the slow-start units based on basic operational requirements, while reserving some subsequent adjustment capacity for the fast-start units in the second stage. When no significant power or frequency support demand arises in subsequent operating conditions, there is no need to add corresponding slow-start units in advance to cover potential changes; only when the system does experience insufficient support are the fast-start units called in to supplement it. Therefore, by comparing the number of slow-start units online, low-load operating periods, and start-up and shutdown situations, it can be verified whether this invention reduces the conservative operational arrangements caused by pre-reserving safety margins.

[0123] Meanwhile, by comparing the minimum frequency points under various operating scenarios, it is verified that the above-mentioned operational structure adjustment does not come at the cost of reducing frequency safety levels. When the unit combination scheme obtained by adopting this invention still meets the preset minimum frequency safety constraint, it can be shown that the tiered decision-making of fast and slow start units, while maintaining frequency safety requirements, provides scheduling space to reduce the excessive early online status of slow start units.

[0124] Further comparison of the system operating costs corresponding to the two methods is conducted to evaluate the impact of post-calling of fast-start units on operational economy. Since this invention transfers some of the flexible safety margin that would otherwise be borne by slow-start units to the second stage, and only calls up fast-start units during periods of actual adjustment demand, its economic improvement does not stem from simply reducing safety reserves, but rather from changing the allocation of safety support resources across different units and decision-making stages.

[0125] In practical applications, this invention can be applied to optimize the day-ahead and subsequent operation modes of power systems with a high proportion of new energy sources such as wind power and photovoltaics. The dispatching system first determines the basic operation plan for slow-start units based on new energy and load forecasts. After obtaining updated new energy output, net load, or system operating status, it then utilizes fast-start units for flexible compensation and adjusts the corresponding dispatching scheme in conjunction with frequency security constraints. This allows for the absorption of some subsequent operational uncertainties by using fast-start units without altering the basic commitment structure of slow-start units, transforming unit dispatching from pre-configuration of all resources to pre-determining basic resources and on-demand dispatching of flexible resources.

[0126] Therefore, the above simulation or actual operation comparisons can verify the technical effects of the present invention from four aspects: unit operation structure, fast start-up resource utilization, frequency security, and operational economy. Specifically, the unit online structure and start-up / shutdown status are used to evaluate whether conservative operation arrangements are reduced; the fast start-up unit call results are used to evaluate whether its flexibility truly participates in subsequent adjustments; the lowest frequency point is used to evaluate whether the adjusted unit operation mode still meets frequency security requirements; and the system operating cost is used to evaluate the economic differences arising from different resource allocation methods. All of these indicators collectively reflect the technical effect of the present invention in achieving a balance between frequency security and operational economy through layered and two-stage joint optimization of fast and slow start-up units.

[0127] In summary, this invention provides a tiered frequency-constrained unit combination method and system for fast and slow start-up units, placing slow-start and fast-start units in two separate decision-making stages. The first stage determines the basic start-up and shutdown plan and baseline output of the slow-start units based on load and renewable energy forecasts. The second stage, without altering the basic commitment structure of the slow-start units, calls upon fast-start units based on net load deviation, renewable energy output fluctuations, power deficits, and frequency support requirements. By establishing a system frequency support capability aggregation representation and a minimum frequency point safety constraint, frequency safety requirements directly participate in the operational division of labor between the two types of units. This invention reduces the need to prematurely deploy slow-start units to cover subsequent uncertainties, allows fast-start units to provide power compensation and additional support on demand, reduces low-load operation and redundant online operation, improves unit start-up and shutdown scheduling, and balances frequency safety and operational economy.

[0128] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A method for combining frequency-constrained units with tiered fast and slow start-up configurations, characterized in that, Includes the following steps: Obtain load forecast data, conventional unit parameters, new energy output forecast data, and frequency response parameters. Based on unit start-up time, minimum start-up time, or equivalent flexibility index, conventional units are divided into slow-start units and fast-start units. Taking slow-start units as the first-stage decision-making objects, we establish start-up state variables, start-up variables, shutdown variables and baseline output variables, and construct a first-stage unit combination model including state transition constraints, minimum start-up and shutdown time constraints, upper and lower limit output constraints, ramp-up constraints and basic power balance constraints. Based on the commitment results of the slow-start units determined in the first stage, and considering net load deviation, fluctuations in renewable energy output, or power deficit, establish the input state variables and output adjustment variables of the fast-start units, and construct the second-stage adjustment model. Based on the online status of the slow-start units and the commissioning status and output capacity of the fast-start units, an aggregated characterization of the system frequency support capacity is established, and a safety constraint for the lowest frequency point is constructed based on the aggregated characterization. The first-stage unit combination model, the second-stage regulation model, and the minimum frequency point safety constraint are coupled to form a two-stage joint optimization model. Through mixed integer optimization, the basic start-up and shutdown plan of slow-start units and the call-up scheme of fast-start units are obtained.

2. The frequency-constrained unit combination method with fast and slow start-up units according to claim 1, characterized in that, The startup time, minimum start-up time, minimum shutdown time, rated capacity, and frequency regulation characteristics of each conventional unit are obtained. The units are classified according to their startup flexibility. Conventional units with long startup times and whose operating status should not be changed frequently are classified as slow-start units, while conventional units that can be put into operation in a short time and have flexible dispatch capabilities are classified as fast-start units.

3. The frequency-constrained unit combination method with fast and slow start-up units according to claim 1, characterized in that, The first-stage unit combination model takes the basic operating cost of slow-start units within the scheduling cycle as the optimization objective. By optimizing the start-up status variables, start-up variables, shutdown variables, and baseline output variables, it determines the slow-start units that need to be put into operation in advance for each scheduling period and their corresponding baseline output, thus forming the basic operating mode of the system.

4. The frequency-constrained unit combination method with fast and slow start-up units according to claim 1, characterized in that, In the first-stage unit combination model, the state transition constraint is used to limit the logical relationship between the start-up state, startup state, and shutdown state of the slow-start unit during adjacent scheduling periods; The minimum start-up and shutdown time constraints are used to limit the continuous start-up time and continuous shutdown time of slow-start units; The upper and lower limits of output are used to limit the reference output range of the slow-start unit according to its operating status. The ramp constraint is used to limit the output variation of slow-start units between adjacent scheduling periods; The basic power balance constraint is used to limit the power supply and demand balance relationship for each scheduling period.

5. The frequency-constrained unit combination method with fast and slow start-up units according to claim 1, characterized in that, The second-stage adjustment model, while maintaining the basic commitment structure of the slow-start units determined in the first stage, optimizes the input state variables and output adjustment variables of the fast-start units based on the net load deviation, decrease in new energy output, or power deficit that occur during actual operation, so as to determine the fast-start units put into operation and their adjusted output in each scheduling period.

6. The frequency-constrained unit combination method with fast and slow start-up units according to claim 5, characterized in that, When the system net load increases, the output of new energy sources decreases, or there is a power deficit, the supplementary active power provided by the fast-start units is determined based on the commissioning status and adjustable output of the fast-start units; and the frequency support capability corresponding to the fast-start units in operation is included in the aggregated representation of the system frequency support capability.

7. The frequency-constrained unit combination method with fast and slow start-up units according to claim 1, characterized in that, The aggregated characterization of the system's frequency support capability is determined based on the online unit composition and corresponding frequency response characteristics of each scheduling period. The online status of the slow-start units is used to characterize the system's basic inertia and basic frequency regulation support capability, while the commissioning status and output capability of the fast-start units are used to characterize the additional frequency support capability. The lowest point of the system frequency is determined based on the aggregated characterization of the system frequency support capability, and the lowest point of the system frequency is not lower than a preset frequency safety threshold as the safety constraint of the lowest point of the frequency.

8. The frequency-constrained unit combination method with fast and slow start-up units according to claim 7, characterized in that, In the two-stage joint optimization model, the input status and output of the fast-start units in the second stage are optimized based on the relationship between the basic frequency support capacity formed by the slow-start units in the first stage and the minimum frequency safety constraint, so that the fast-start units can provide additional frequency support during the scheduling period when the basic frequency support capacity is insufficient to meet the minimum frequency safety constraint.

9. The frequency-constrained unit combination method with fast and slow start-up units according to claim 1, characterized in that, The two-stage joint optimization model takes system operating cost as the optimization objective. Under the conditions of satisfying the operating constraints of the first-stage unit combination model, the operating constraints of the second-stage regulation model, and the safety constraints of the minimum frequency point, the basic start-up and shutdown plan of the slow-start units, the benchmark output of each scheduling period, and the input status and regulation output of the fast-start units are jointly determined by the mixed integer optimization method.

10. A frequency-constrained unit combination system with tiered fast and slow start-up units, characterized in that, include: The data classification module is used to acquire load forecast data, conventional unit parameters, new energy output forecast data and frequency response parameters, and classify conventional units into slow-start units and fast-start units according to the unit start-up characteristics. The first-stage combination module is used to establish the start-up status variables, start-up variables, shutdown variables and baseline output variables of the slow-start unit as the decision object, and to construct the first-stage unit combination model. The second-stage adjustment module is used to establish the input state variables and output adjustment variables of the fast-start unit based on the slow-start unit commitment results determined by the first-stage combination module, according to the net load deviation, new energy output fluctuations or power deficit, and to construct the second-stage adjustment model. The frequency constraint module is used to establish an aggregated characterization of the system frequency support capability based on the online status of the slow-start unit and the commissioning status and output capacity of the fast-start unit, and to construct a safety constraint for the lowest frequency point based on the aggregated characterization. The joint optimization module is used to couple the first-stage unit combination model, the second-stage regulation model, and the minimum frequency point safety constraint to form a two-stage joint optimization model, and solve the two-stage joint optimization model to obtain the basic start-up and shutdown plan of the slow-start unit and the call scheme of the fast-start unit.

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