Coal-fired unit collaborative scheduling method and system considering hierarchical flexible supply and demand matching

Abstract

The invention belongs to the field of coal-fired unit scheduling, and provides a coal-fired unit collaborative scheduling method and system considering hierarchical flexible supply and demand matching. The method comprises the following steps: constructing a hierarchical flexibility demand quantitative evaluation system of the power system; quantizing the hierarchical flexibility requirements of the power system in typical operation scenes of photovoltaic, wind power and load under the background of high-proportion new energy; establishing a coal-fired unit participated hierarchical flexible supply and demand matching scheduling model based on the quantified hierarchical flexible demand of the power system; under set constraint conditions, optimizing the hierarchical flexible supply and demand matching scheduling model in which the coal-fired unit participates, determining a day-ahead scheduling strategy of the coal-fired unit, and obtaining a corresponding day-ahead scheduling operation result; and analyzing a day-ahead scheduling operation result according to the hierarchical flexibility demand quantitative evaluation system of the power system, and evaluating the hierarchical flexibility adjustment capability of the coal-fired unit. The hierarchical flexible adjusting capability of the coal-fired unit can be improved.

Description

Technical Field

[0001] This invention belongs to the field of coal-fired power unit scheduling, and particularly relates to a method and system for collaborative scheduling of coal-fired power units that considers hierarchical and flexible supply and demand matching. Background Technology

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

[0003] With a high proportion of renewable energy connected to the grid, the new power system exhibits "two highs": a high proportion of power electronics increases the requirements for frequency regulation capabilities, and high volatility in source-load interaction leads to a wider peak-valley difference, threatening voltage and frequency stability. These "two highs" characteristics place higher demands on the power system's flexibility regulation capabilities, requiring not only to meet the traditional long-term peak-shaving flexibility needs but also to possess better frequency and voltage regulation flexibility. Despite the rapid development of various flexible resource types, coal-fired power units, due to their advantages such as good wide-load regulation capabilities, inertial response, long-term regulation controllability, economy, and large scale, remain the primary force for deep long-term peak-shaving, rapid frequency regulation, and voltage support for the present and for some time to come; their role in flexibility regulation is irreplaceable.

[0004] Existing research on improving system flexibility mainly focuses on long-term peak-shaving flexibility, neglecting the improvement of frequency regulation and voltage regulation flexibility, as well as the flexibility adjustment capability in emergency situations. Current assessment methods for flexibility requirements are mainly based on probabilistic statistical errors, starting only from source-load demand forecast data, without considering factors such as the physical characteristics and operating features of the power system, and without targeting specific generating units, which brings difficulties to day-ahead dispatch and in-depth exploration of the flexibility adjustment capability of coal-fired units. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method and system for coordinated scheduling of coal-fired power units that considers hierarchical and flexible supply and demand matching, which can enhance the hierarchical and flexible adjustment capabilities of coal-fired power units.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: The first aspect of the present invention provides a method for coordinated scheduling of coal-fired power units that takes into account hierarchical and flexible supply and demand matching.

[0007] In one or more embodiments, a method for coordinated scheduling of coal-fired power units considering hierarchical and flexible supply and demand matching is provided, including: Considering the flexibility of long-term peak shaving, long-term voltage regulation, short-term frequency regulation, and short-term voltage regulation, a hierarchical flexibility requirement quantitative assessment system for the power system is constructed. For each indicator in the quantitative assessment system for the hierarchical flexibility requirements of the power system, we quantify their hierarchical flexibility requirements under typical operating scenarios of photovoltaic, wind power, and load in the context of a high proportion of new energy sources. Based on the quantified hierarchical flexibility requirements of the power system, a hierarchical flexibility supply and demand matching scheduling model involving coal-fired power units is established; wherein, the hierarchical flexibility supply and demand matching scheduling model involving coal-fired power units takes minimizing daily operating costs as its objective function. Under set constraints, the hierarchical flexible supply and demand matching scheduling model involving coal-fired units is optimized to determine the day-ahead scheduling strategy of coal-fired units and obtain the corresponding day-ahead scheduling operation results. Based on the hierarchical flexibility requirement quantitative assessment system of the power system, the day-ahead dispatch operation results are analyzed to evaluate the hierarchical flexibility adjustment capability of coal-fired units.

[0008] As one implementation method, the hierarchical flexibility requirement quantitative assessment system of the power system includes two layers. The first layer is divided into active power regulation requirement and reactive power regulation requirement. In the second layer, active power regulation requirement is divided into long-term peak shaving and short-term frequency regulation, and reactive power requirement is divided into long-term voltage regulation and short-term voltage regulation.

[0009] As one implementation method, the evaluation indicators for long-term peak shaving flexibility are: the dispatchable power volume for long-term peak shaving of large coal-fired power units within 15 minutes, the dispatchable power volume for long-term peak shaving of large coal-fired power units within one hour, and the power curtailment of new energy units; the evaluation indicators for long-term voltage regulation flexibility are: the maximum load ratio under the static stable voltage threshold; the evaluation indicators for short-term frequency regulation flexibility are: frequency deviation amplitude and recovery time; the evaluation indicators for short-term voltage regulation flexibility are: voltage deviation amplitude and recovery time after fault recovery.

[0010] As one implementation method, the objective function of the hierarchical flexible supply and demand matching scheduling model involving coal-fired power units is:

[0011] In the formula, The penalty coefficient for curtailment of electricity generated by new energy units. and These refer to the start-up and shutdown costs of coal-fired power units, respectively. , , These refer to coal-fired power units. The power generation cost coefficient; Indicates the number of coal-fired power units; , , , These refer to the incentive coefficients for providing tiered flexibility to coal-fired power units; The power generation of a coal-fired power unit; and These refer to coal-fired power units. Start-up and shutdown variables; Indicates coal-fired power unit The amount of electricity wasted; , Indicates coal-fired power unit The long-term peak-shaving flexibility reserve requirement; positive and negative values ​​represent the upper and lower long-term peak-shaving requirements, respectively. Indicates coal-fired power unit Long-term voltage regulation flexibility backup requirements; Indicates coal-fired power unit Short-timescale frequency modulation flexibility backup requirements; Indicates coal-fired power unit Short-timescale voltage regulation flexibility backup requirements; m Indicates the number of photovoltaic power generation units; n This indicates the number of wind turbine generators.

[0012] As one implementation method, typical operating scenarios for photovoltaic, wind power and load under a high proportion of new energy are established, taking into account the temporal and spatial correlations of photovoltaic power generation, wind power generation and load demand.

[0013] As one implementation, the constraints include AC power flow constraints of the power system, power supply and demand balance constraints of coal-fired units, start-up, shutdown and ramp-up constraints of coal-fired units, and hierarchical flexibility constraints of coal-fired units.

[0014] A second aspect of the present invention provides a coal-fired power unit collaborative scheduling system that considers hierarchical and flexible supply and demand matching.

[0015] In one or more embodiments, a coal-fired power unit collaborative scheduling system considering hierarchical flexible supply and demand matching includes: The quantitative assessment system construction module is used to consider the flexibility of long-term peak shaving, long-term voltage regulation, short-term frequency regulation and short-term voltage regulation, and to construct a hierarchical quantitative assessment system for the flexibility requirements of the power system. The hierarchical flexibility requirement quantification module is used to quantify the hierarchical flexibility requirements of the power system under typical operating scenarios of photovoltaic, wind power and load in the context of high proportion of new energy. The supply and demand matching scheduling model construction module is used to establish a hierarchical flexibility supply and demand matching scheduling model involving coal-fired power units based on the quantified hierarchical flexibility requirements of the power system; wherein, the hierarchical flexibility supply and demand matching scheduling model involving coal-fired power units takes minimizing daily operating costs as the objective function. The day-ahead scheduling strategy optimization module is used to optimize the hierarchical flexible supply and demand matching scheduling model involving coal-fired units under set constraints, determine the day-ahead scheduling strategy of coal-fired units and obtain the corresponding day-ahead scheduling operation results; The hierarchical flexibility adjustment capability assessment module is used to analyze the day-ahead dispatch operation results based on the hierarchical flexibility requirement quantitative assessment system of the power system, and to evaluate the hierarchical flexibility adjustment capability of coal-fired units.

[0016] A third aspect of the present invention provides a computer-readable storage medium.

[0017] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described method for coordinated scheduling of coal-fired power units considering hierarchical flexible supply and demand matching.

[0018] A fourth aspect of the present invention provides an electronic device.

[0019] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the above-described method for coordinated scheduling of coal-fired power units that considers hierarchical flexible supply and demand matching.

[0020] A fifth aspect of the present invention provides an electronic device.

[0021] A computer program product includes a computer program / instructions that, when executed by a processor, implement the steps in the above-described method for coordinated scheduling of coal-fired power units that considers hierarchical flexible supply and demand matching.

[0022] Compared with the prior art, the beneficial effects of the present invention are: (1) This invention proposes a coal-fired power unit collaborative scheduling method that considers hierarchical flexibility supply and demand matching. It comprehensively considers the hierarchical flexibility requirements of the power system and constructs a quantitative evaluation system for the hierarchical flexibility requirements of the new power system, including four parts: long-term peak shaving, long-term voltage regulation, short-term frequency regulation, and short-term voltage regulation flexibility. It quantitatively analyzes the long-term peak shaving, long-term voltage regulation, short-term frequency regulation, and short-term voltage regulation flexibility requirements of the new power system, establishes a hierarchical flexibility supply and demand matching scheduling model involving coal-fired power units, and obtains the day-ahead scheduling operation strategy of coal-fired power units that meets the hierarchical flexibility requirements of the new power system through optimization. It also analyzes the day-ahead scheduling operation results based on the hierarchical flexibility index evaluation system. Compared with the traditional analysis that only considers the long-term peak shaving flexibility, it more comprehensively considers the operating rules and dynamic changes of the power system, can better cope with emergencies, and has a high degree of advancement.

[0023] (2) The hierarchical flexibility assessment system constructed by this invention covers dispatchable power indicators, renewable energy curtailment indicators, load ratio indicators under static stable voltage threshold, transient frequency offset amplitude and time indicators, and transient voltage offset amplitude and recovery time indicators of large coal-fired units at different time scales. It is relatively comprehensive and can be located for each large coal-fired unit for assessment. It can comprehensively reflect the hierarchical flexibility adjustment capability of the unit and has high practical engineering application value.

[0024] (3) This invention can be used to improve the hierarchical flexibility adjustment capability of large coal-fired power units, and can also be applied to other flexibility resources. There are no special application conditions, it is highly versatile, and it is suitable for evaluating the hierarchical flexibility adjustment capability of various flexibility resources. It has promotional value and significance. Attached Figure Description

[0025] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0026] Figure 1 This is a flowchart illustrating the collaborative scheduling method for coal-fired power units that considers hierarchical and flexible supply and demand matching, according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of a coal-fired power unit collaborative scheduling system that considers hierarchical and flexible supply and demand matching according to an embodiment of the present invention; Figure 3 This is a schematic diagram of an electronic device according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the hierarchical flexibility requirements assessment system of the present invention; Figure 5 This is a schematic diagram of typical operating scenario results generated by the present invention; Figure 6 This is a schematic diagram of the improved IEEE 39-node system used in the simulation of this invention; Figure 7 This is a schematic diagram of the quantitative evaluation results of the hierarchical flexibility requirements of the present invention; Figure 8 This is a schematic diagram of the daily operating curve results of large coal-fired power units and new energy power units under typical operating scenarios of this invention; Figure 9 This is a schematic diagram showing the comparison results of the hierarchical flexibility index of the present invention. Detailed Implementation

[0027] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0028] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0029] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0030] Figure 1 This is a flowchart illustrating a method for coordinated scheduling of coal-fired power units that considers hierarchical and flexible supply and demand matching, as described in an embodiment of the present invention. Figure 1 As shown, the coal-fired power unit collaborative scheduling method considering hierarchical flexible supply and demand matching in this embodiment may include: S101, considering the flexibility of long-term peak shaving, long-term voltage regulation, short-term frequency regulation and short-term voltage regulation, constructs a hierarchical flexibility requirement quantitative assessment system for the power system.

[0031] like Figure 4 As shown, the hierarchical flexibility demand quantitative assessment system of the power system consists of two layers. The first layer is divided into active power regulation demand and reactive power regulation demand. In the second layer, active power regulation demand is divided into long-term peak shaving and short-term frequency regulation, and reactive power demand is divided into long-term voltage regulation and short-term voltage regulation.

[0032] To address the significant peak-valley differences caused by intraday fluctuations in renewable energy and load, it is necessary to adjust the output of large coal-fired power units to achieve power supply and demand balance at every moment, considering long-term peak-shaving flexibility. To ensure that the voltage at each node of the power system remains within the allowable limits of steady-state operation under a high proportion of renewable energy, avoiding static voltage collapse due to source-load fluctuations, consider long-term voltage regulation flexibility. To reduce system frequency fluctuations when the power system experiences dynamic disturbances and power deficits, and to restore stable operation in a short time, consider transient long-term peak-shaving flexibility. To adjust reactive power to suppress node voltage changes when the power system experiences large disturbances, and to reduce node voltage fluctuations after the fault disappears, enabling the system to quickly restore stable operation, consider short-term voltage regulation flexibility.

[0033] The evaluation indicators for long-term peak shaving flexibility are: the dispatchable power volume for long-term peak shaving of large coal-fired power units within 15 minutes, the dispatchable power volume for long-term peak shaving of large coal-fired power units within one hour, and the power curtailment of new energy units; the evaluation indicators for long-term voltage regulation flexibility are: the maximum load ratio under the static stable voltage threshold; the evaluation indicators for short-term frequency regulation flexibility are: frequency deviation amplitude and recovery time; the evaluation indicators for short-term voltage regulation flexibility are: voltage deviation amplitude and recovery time after fault recovery.

[0034] S102 quantifies the hierarchical flexibility requirements of the power system for each indicator in the quantitative assessment system for the hierarchical flexibility requirements of the power system under typical operating scenarios of photovoltaic, wind power and load in the context of high proportion of new energy.

[0035] In the specific implementation process, typical operating scenarios under the background of high-proportion photovoltaic and wind power grid connection are constructed, and the optimal model of spatiotemporal correlation is fitted. Typical operating scenarios are established considering the temporal and spatial correlations of photovoltaic power generation, wind power generation, and load demand. The temporal correlation part is based on the optimal Copula method, and the spatial correlation part is based on the optimal Vine Copula method. Specifically, the Copula function types considered for temporal correlation include four types: Gaussian, T, Frank, Gumbel, and Clayton Copula; the Vine Copula types considered for spatial correlation include three types: C, D, and R Vine Copula.

[0036] like Figure 5 As shown, considering spatiotemporal correlation, a schematic diagram is established to represent a typical operating scenario under a high proportion of renewable energy grid connection. Figure 5 (a)-(d) in the figure represent the structures of four typical operating scenarios. The results in each typical operating scenario refer to the 24-hour change ratio of photovoltaic generator sets, wind turbine generator sets, and load demand. The installed capacity of each unit needs to be considered in the simulation.

[0037] Typical operating scenarios under the background of high-proportion photovoltaic and wind power grid connection are constructed. A massive number of scenarios are generated based on Latin Hypercube Sampling (LHS), and typical operating scenarios are selected using the K-means++ method. The LHS method divides the value range of each variable into... N Divide the intervals into equal-width intervals and randomly select a sample point within each interval:

[0038]

[0039] In the formula, Indicates the first i The first variablej A range; u Indicates a uniform distribution; Indicates the interval The random variable follows a uniform distribution. N Let be the number of intervals.

[0040] The K-means++ method uses minimizing the sum of distances from all data points to the center of their respective clusters as its objective function.

[0041] In the formula, TAE is the total absolute error, which is measured in Euclidean distance; k The number of typical operating scenarios is determined by the elbow rule; C i For the first i Data payload of each cluster; x As a variable; m i For the first i The center point of each cluster; T This represents the total number of moments.

[0042] like Figure 6 As shown, a simulation was performed using an improved IEEE 39-node system. This system has 39 nodes, a rated frequency of 60 Hz, and includes ten large coal-fired power units, two photovoltaic power units connected inside the system, and three wind turbines distributed on the periphery of the system.

[0043] To ensure a uniform time scale, such as Figure 7 The demand shown is measured on an hourly timescale, and is evaluated using a hierarchical and flexible quantitative assessment system. Figure 7 (a) in the text represents the active power flexibility requirement; Figure 7 (b) in the text represents the reactive power flexibility requirement.

[0044] The first part addresses the long-term peak-shaving flexibility requirements of the power system:

[0045] In the formula, and They refer to large coal-fired power units i The peak shaving flexibility requirements on the 15-minute and 1-hour long-term scales, with positive and negative values ​​representing the peak shaving requirements on the upper and lower long-term scales, respectively. and Large coal-fired power units i exist and Efforts made over time; , and , They refer to large coal-fired power units i The power available for peak shaving on upper and lower time scales of 15 minutes and 1 hour; and These are large coal-fired power units i Maximum uphill and downhill climbing rates; and These are large coal-fired power units i The upper and lower limits of active power output; It refers to a time scale, with two options: fifteen minutes and one hour. , and These refer to new energy power units. j The amount of abandoned electricity, actual power generation, and power grid connection.

[0046] The second part addresses the long-term voltage regulation flexibility requirements of the power system, calculating the long-term voltage regulation flexibility reserve requirements for each large coal-fired unit. :

[0047] In the formula, For large coal-fired power units i In t The need for flexible backup voltage regulation at any given time; S c Refers to maximum load power. P c This refers to the maximum active power load. Q c This refers to the maximum reactive power load. λ This refers to the critical load ratio; P 0 and Q 0 refers to the initial active and reactive load power, respectively; V ( t )refer to t The node voltage value at time; V min and V max These refer to the minimum and maximum values ​​of the node voltage, respectively. F 1() is a function that describes the long-term voltage regulation process of the power system; Large coal-fired power units i exist t Reactive power generation at time t; Z1 refers to the matrix of other variables; u 1( t (referring to the system) t The static stable voltage threshold at time t.

[0048] The third part addresses the short-timescale frequency regulation flexibility requirements of the power system, calculating the short-timescale frequency regulation flexibility reserve requirements for each large coal-fired unit. :

[0049] In the formula, For large coal-fired power units i exist t Short-timescale frequency modulation flexibility backup requirements; F 2() is a function that describes the short-time-scale frequency regulation process of the power system; Large coal-fired power units i exist t Active power generation at time t; Z2 refers to the matrix of other variables; Refers to the system t Frequency offset value at time; This refers to the maximum frequency offset value allowed by the system. , and These refer to the frequency recovery time, the time after frequency recovery, and the time before the fault occurred, respectively.

[0050] Part Four addresses the short-timescale voltage regulation flexibility requirements of the power system, calculating the short-timescale voltage regulation flexibility reserve requirements for each large coal-fired unit. :

[0051] In the formula, For large coal-fired power units i exist t Short-term voltage regulation flexibility and backup requirements at any given time; F 3() is a function that describes the short-time-scale voltage regulation process of the power system; Large coal-fired power units i exist t Reactive power generation at time t; Z3 refers to the matrix of other variables; Refers to the first i Nodes t The node voltage offset value at time; This refers to the maximum allowable node voltage offset value of the system; , and These refer to the voltage recovery time, the time after voltage recovery, and the time before the fault occurred, respectively.

[0052] S103. Based on the quantified hierarchical flexibility requirements of the power system, a hierarchical flexibility supply and demand matching scheduling model involving coal-fired power units is established; wherein, the hierarchical flexibility supply and demand matching scheduling model involving coal-fired power units takes minimizing daily operating costs as its objective function.

[0053] The objective function of the hierarchical flexible supply and demand matching scheduling model involving coal-fired power units is:

[0054] In the formula, The penalty coefficient for curtailment of electricity generated by new energy units. and These refer to the start-up and shutdown costs of coal-fired power units, respectively. , , These refer to coal-fired power units. The power generation cost coefficient; Indicates the number of coal-fired power units; , , , These refer to the incentive coefficients for providing tiered flexibility to coal-fired power units; The active power generation of a coal-fired power unit; and These refer to coal-fired power units. Start-up and shutdown variables; Indicates coal-fired power unit The amount of electricity wasted; , Indicates coal-fired power unit The long-term peak-shaving flexibility reserve requirement; positive and negative values ​​represent the upper and lower long-term peak-shaving requirements, respectively. Indicates coal-fired power unit Long-term voltage regulation flexibility backup requirements; Indicates coal-fired power unit Short-timescale frequency modulation flexibility backup requirements; Indicates coal-fired power unit Short-timescale voltage regulation flexibility backup requirements; m Indicates the number of photovoltaic power generation units; n This indicates the number of wind turbine generators.

[0055] The constraints include AC power flow constraints of the power system, power supply and demand balance constraints of coal-fired units, start-up, shutdown and ramp-up constraints of coal-fired units, and hierarchical flexibility constraints of coal-fired units.

[0056] Considering AC power flow constraints in the power system:

[0057] In the formula, and Large coal-fired power units i exist t Active and reactive power generation at any given moment; and They are nodes b exist t The active and reactive power injected at all times; and Refers to the line parameters, with the two ends being... b and b '; B 1 represents the number of nodes in the power system; θ b min and θ b max They are nodes b The minimum and maximum values ​​of the voltage phase angle; and Each refers to a node b and nodes b 'exist t Voltage phase angle at any given moment; and They are nodes b and b 'exist t Voltage amplitude at any given moment; , Line In t Power and maximum capacity values ​​at any given time.

[0058] The power supply and demand balance constraints for large coal-fired power units are:

[0059] The start-up, shutdown, and ramp-up constraints for large coal-fired power units are as follows:

[0060] In the formula, Large coal-fired power units i The amount of active power generated in the previous moment; and Large coal-fired power units i The start / stop state variables at this moment and the previous moment are zero-one variables; and They refer to the first j The coefficient of change in the installed capacity and 24-hour power generation of each new energy unit (in [the context of the data]) t (At present) and These are large coal-fired power unitsi The upper and lower limits of reactive power output.

[0061] The hierarchical flexibility constraints of large-scale coal-fired units are as follows:

[0062] In the formula, 、 、 respectively refer to t The hierarchical flexibility demand of the system at time , where the long-term scale peak shaving demand includes two directions, positive and negative, which are and .

[0063] S104. Under the set constraint conditions, optimize the hierarchical flexibility supply-demand matching scheduling model participated by coal-fired units, determine the day-ahead scheduling strategy of coal-fired units and obtain the corresponding day-ahead scheduling operation results.

[0064] S105. Analyze the day-ahead scheduling operation results according to the hierarchical flexibility demand quantification evaluation system of the power system, and evaluate the hierarchical flexibility regulation ability of coal-fired units.

[0065] To evaluate the hierarchical flexibility improvement ability of large-scale coal-fired units, it is necessary to compare and consider the long-term scale peak shaving, long-term scale voltage regulation, short-term scale frequency modulation and short-term scale voltage regulation flexibility indexes in two scenarios: considering hierarchical flexibility demand and not considering hierarchical flexibility demand.

[0066] This invention takes 2 photovoltaic power plants, 3 wind power plants, the total regional load demand in a certain province and the improved IEEE 39-node system as an example for analysis.

[0067] First, it is necessary to consider the spatio-temporal correlation to generate typical operation scenarios. The time correlation fitting results are shown in Table 1 (where 'none' is because photovoltaic power generation does not generate electricity at night and no fitting is performed; Gaussian, Gumbel, t, Frank and Clayton respectively represent that the fitting results are Gaussian Copula, Gumbel Copula, t Copula, Frank Copula and Clayton Copula), and the space correlation fitting results are shown in Table 2 (where C and D respectively represent that the fitting results are C-tree Copula and D-tree Copula).

[0068] Table 1 Time correlation fitting results

[0069] Table 2 Space correlation fitting results

[0070] Four typical operating scenarios were generated based on the K-means++ method, and one typical operating scenario was randomly selected for subsequent analysis.

[0071] Then, based on typical operating scenarios, the hierarchical flexibility requirements of the power system are calculated, such as... Figure 7 As shown, active power flexibility requirements include two parts: long-time scale peak shaving flexibility and short-time scale frequency regulation flexibility. Reactive power flexibility requirements include two parts: long-time scale voltage regulation flexibility and short-time scale voltage regulation flexibility. Long-time scale peak shaving flexibility is divided into upward and downward directions, while other flexibility requirements are mainly upward regulation flexibility.

[0072] A day-ahead scheduling model for large coal-fired power units is established based on hierarchical flexibility requirements to match supply and demand. The daily operating curves of large coal-fired power units and new energy units are as follows: Figure 8 As shown in (a) and (b) in the figure, large coal-fired power units provide hierarchical flexibility to the power system through strategies such as start-up and shutdown, ramping, and providing backup, thereby improving the system's flexibility, stability, and security.

[0073] The simulation results are analyzed based on a hierarchical flexibility requirement assessment system to evaluate the flexibility of the power system in four aspects: long-term peak shaving, long-term voltage regulation, short-term frequency regulation, and short-term voltage regulation. The amount of renewable energy curtailment is shown in Table 3, with random selections of time points for illustration. Negative values ​​indicate a decrease in curtailment, signifying an optimization effect.

[0074] Table 3. Amount of abandoned renewable energy

[0075] The comparison results of the long-time scale voltage regulation flexibility, short-time scale frequency regulation flexibility, and short-time scale voltage regulation flexibility indices are attached. Figure 9 As shown in (a), (b), and (c), each exhibits varying degrees of improvement. Comparative analysis of flexibility indicators demonstrates that this invention can comprehensively enhance the hierarchical flexibility of the power system, enabling the development of a strategy that considers hierarchical flexibility for the day-ahead dispatching of large coal-fired units.

[0076] like Figure 9 As shown, the hierarchical flexibility enhancement effect of the present invention is evaluated. Figure 9 (a) shows the simulation results of voltage regulation flexibility over a long time scale. This invention can improve the load ratio under static limit operation at all times, thereby improving the stability and security of the power system. Figure 9 (b) shows the simulation results of frequency modulation flexibility on a short time scale. By setting up a machine switching fault for electromechanical transient simulation, the present invention can reduce the frequency offset of most moments and nodes, and local nodes can avoid the frequency from dropping to the normal frequency range red line. Figure 9(c) in the figure represents the simulation results of short-timescale voltage regulation flexibility. The present invention can reduce the voltage deviation of most nodes and facilitate voltage recovery after fault clearance.

[0077] like Figure 2 As shown, the coal-fired power unit collaborative scheduling system considering hierarchical flexible supply and demand matching provided in this embodiment of the invention can be implemented in software. The coal-fired power unit collaborative scheduling system considering hierarchical flexible supply and demand matching includes the following software modules: Module 201 for constructing a quantitative assessment system is used to consider the flexibility of long-term peak shaving, long-term voltage regulation, short-term frequency regulation and short-term voltage regulation, and to construct a hierarchical quantitative assessment system for the flexibility requirements of the power system. The hierarchical flexibility requirement quantification module 202 is used to quantify the hierarchical flexibility requirements of the power system under typical operating scenarios of photovoltaic, wind power and load in the context of high proportion of new energy. The supply and demand matching scheduling model construction module 203 is used to establish a hierarchical flexibility supply and demand matching scheduling model involving coal-fired power units based on the quantified hierarchical flexibility requirements of the power system; wherein, the hierarchical flexibility supply and demand matching scheduling model involving coal-fired power units takes minimizing daily operating costs as the objective function. The day-ahead scheduling strategy optimization module 204 is used to optimize the hierarchical flexible supply and demand matching scheduling model involving coal-fired units under set constraints, determine the day-ahead scheduling strategy of coal-fired units and obtain the corresponding day-ahead scheduling operation results. The hierarchical flexibility adjustment capability assessment module 205 is used to analyze the day-ahead dispatch operation results based on the hierarchical flexibility requirement quantitative assessment system of the power system, and to assess the hierarchical flexibility adjustment capability of coal-fired units.

[0078] It should be noted here that, Figure 2 The various modules in the hierarchical and flexible supply and demand matching coal-fired power unit collaborative scheduling system are considered in conjunction with... Figure 1 Each step in the hierarchical and flexible supply and demand matching coal-fired unit collaborative scheduling method corresponds to the previous one, and their specific implementation process is the same, so it will not be repeated here.

[0079] The structure of the electronic device according to an embodiment of the present invention will be described in detail below. Figure 3 This is a schematic diagram of the composition structure of an electronic device provided in an embodiment of the present invention. It can be understood that... Figure 3 The diagram shows only an exemplary structure of the electronic device, not the entire structure. Some or all of the structures shown may be implemented as needed.

[0080] The electronic device provided in this embodiment of the invention includes: at least one processor 301, a memory 302, a user interface 303, and at least one network interface 304. The various components in a hierarchical, flexible supply-demand matching coal-fired power unit collaborative scheduling system are coupled together via a bus system 305. It can be understood that the bus system 305 is used to realize the connection and communication between these components. In addition to a data bus, the bus system 305 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 3 The general designated all buses as Bus System 305.

[0081] The user interface 303 may include a monitor, keyboard, mouse, trackball, click wheel, buttons, touchpad, or touch screen.

[0082] It is understood that memory 302 can be volatile memory or non-volatile memory, or both. In this embodiment of the invention, memory 302 is capable of storing data to support the operation of the terminal. Examples of this data include any computer programs used to operate on the terminal, such as operating systems and applications. The operating system includes various system programs, such as framework layers, core library layers, driver layers, etc., used to implement various basic services and handle hardware-based tasks. Applications can include various applications.

[0083] In some embodiments, the coal-fired power unit collaborative scheduling system considering hierarchical flexible supply and demand matching provided in this invention can be implemented using a combination of hardware and software. As an example, the coal-fired power unit collaborative scheduling system considering hierarchical flexible supply and demand matching provided in this invention can be a processor in the form of a hardware decoding processor, programmed to execute the coal-fired power unit collaborative scheduling method considering hierarchical flexible supply and demand matching provided in this invention. For example, the processor in the form of a hardware decoding processor can employ one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components.

[0084] As an example, processor 301 can be an integrated circuit chip with signal processing capabilities, such as a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., wherein the general-purpose processor can be a microprocessor or any conventional processor, etc.

[0085] As an example of the hardware implementation of the coal-fired power unit collaborative scheduling system considering hierarchical flexible supply and demand matching provided in the embodiments of the present invention, the device provided in the embodiments of the present invention can be directly executed by a processor 301 in the form of a hardware decoding processor. For example, it can be executed by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components to implement the coal-fired power unit collaborative scheduling method considering hierarchical flexible supply and demand matching provided in the embodiments of the present invention.

[0086] The memory 302 in this embodiment of the invention is used to store various types of data to support the operation of a coal-fired unit collaborative scheduling system that considers hierarchical and flexible supply and demand matching, or to store data for execution. Figure 1 The program code for the method shown. Examples of this data include: any executable instructions for operating on a coal-fired unit collaborative scheduling system that takes into account hierarchical flexible supply and demand matching, such as executable instructions, and programs implementing the coal-fired unit collaborative scheduling method that takes into account hierarchical flexible supply and demand matching of embodiments of the present invention may be contained in executable instructions.

[0087] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including functions for executing... Figure 1 The program code for the method shown. In such an embodiment, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by the central processing unit, it performs the various functions defined in the apparatus of this application.

[0088] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0089] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for coordinated scheduling of coal-fired power units considering hierarchical and flexible supply and demand matching, characterized in that, include: Considering the flexibility of long-term peak shaving, long-term voltage regulation, short-term frequency regulation, and short-term voltage regulation, a hierarchical flexibility requirement quantitative assessment system for the power system is constructed. For each indicator in the quantitative assessment system for the hierarchical flexibility requirements of the power system, we quantify their hierarchical flexibility requirements under typical operating scenarios of photovoltaic, wind power, and load in the context of a high proportion of new energy sources. Based on the quantified hierarchical flexibility requirements of the power system, a hierarchical flexibility supply and demand matching scheduling model involving coal-fired power units is established; wherein, the hierarchical flexibility supply and demand matching scheduling model involving coal-fired power units takes minimizing daily operating costs as its objective function. Under set constraints, the hierarchical flexible supply and demand matching scheduling model involving coal-fired units is optimized to determine the day-ahead scheduling strategy of coal-fired units and obtain the corresponding day-ahead scheduling operation results. Based on the hierarchical flexibility requirement quantitative assessment system of the power system, the day-ahead dispatch operation results are analyzed to evaluate the hierarchical flexibility adjustment capability of coal-fired units.

2. The coal-fired power unit collaborative scheduling method considering hierarchical flexible supply and demand matching as described in claim 1, characterized in that, The hierarchical flexibility requirement quantitative assessment system for the power system consists of two layers. The first layer is divided into active power regulation requirement and reactive power regulation requirement. In the second layer, active power regulation requirement is divided into long-term peak shaving and short-term frequency regulation, and reactive power requirement is divided into long-term voltage regulation and short-term voltage regulation.

3. The coal-fired power unit collaborative scheduling method considering hierarchical flexible supply and demand matching as described in claim 1, characterized in that, The evaluation indicators for long-term peak shaving flexibility are: the dispatchable power volume for long-term peak shaving of large coal-fired power units within 15 minutes, the dispatchable power volume for long-term peak shaving of large coal-fired power units within one hour, and the power curtailment of new energy units; the evaluation indicators for long-term voltage regulation flexibility are: the maximum load ratio under the static stable voltage threshold; the evaluation indicators for short-term frequency regulation flexibility are: frequency deviation amplitude and recovery time; the evaluation indicators for short-term voltage regulation flexibility are: voltage deviation amplitude and recovery time after fault recovery.

4. The coal-fired power unit collaborative scheduling method considering hierarchical flexible supply and demand matching as described in claim 1, characterized in that, The objective function of the hierarchical flexible supply and demand matching scheduling model involving coal-fired power units is: In the formula, The penalty coefficient for curtailment of electricity generated by new energy units. and These refer to the start-up and shutdown costs of coal-fired power units, respectively. , , These refer to coal-fired power units. The power generation cost coefficient; Indicates the number of coal-fired power units; , , , These refer to the incentive coefficients for providing tiered flexibility to coal-fired power units; The power generation of a coal-fired power unit; and These refer to coal-fired power units. Start-up and shutdown variables; Indicates coal-fired power unit The amount of electricity wasted; , Indicates coal-fired power unit The long-term peak-shaving flexibility reserve requirement; positive and negative values ​​represent the upper and lower long-term peak-shaving requirements, respectively. Indicates coal-fired power unit Long-term voltage regulation flexibility backup requirements; Indicates coal-fired power unit Short-timescale frequency modulation flexibility backup requirements; Indicates coal-fired power unit Short-timescale voltage regulation flexibility backup requirements; m Indicates the number of photovoltaic power generation units; n This indicates the number of wind turbine generators.

5. The method for coordinated scheduling of coal-fired power units considering hierarchical and flexible supply and demand matching as described in claim 1, characterized in that, Considering the temporal and spatial correlations of photovoltaic power generation, wind power generation, and load demand, typical operating scenarios for photovoltaic, wind power, and load under a high proportion of new energy sources are established.

6. The coal-fired power unit collaborative scheduling method considering hierarchical flexible supply and demand matching as described in claim 1, characterized in that, The constraints include AC power flow constraints of the power system, power supply and demand balance constraints of coal-fired units, start-up, shutdown and ramp-up constraints of coal-fired units, and hierarchical flexibility constraints of coal-fired units.

7. A coal-fired power unit collaborative scheduling system considering hierarchical and flexible supply and demand matching, characterized in that, include: The quantitative assessment system construction module is used to consider the flexibility of long-term peak shaving, long-term voltage regulation, short-term frequency regulation and short-term voltage regulation, and to construct a hierarchical quantitative assessment system for the flexibility requirements of the power system. The hierarchical flexibility requirement quantification module is used to quantify the hierarchical flexibility requirements of the power system under typical operating scenarios of photovoltaic, wind power and load in the context of high proportion of new energy. The supply and demand matching scheduling model construction module is used to establish a hierarchical flexibility supply and demand matching scheduling model involving coal-fired power units based on the quantified hierarchical flexibility requirements of the power system; wherein, the hierarchical flexibility supply and demand matching scheduling model involving coal-fired power units takes minimizing daily operating costs as the objective function. The day-ahead scheduling strategy optimization module is used to optimize the hierarchical flexible supply and demand matching scheduling model involving coal-fired units under set constraints, determine the day-ahead scheduling strategy of coal-fired units and obtain the corresponding day-ahead scheduling operation results; The hierarchical flexibility adjustment capability assessment module is used to analyze the day-ahead dispatch operation results based on the hierarchical flexibility requirement quantitative assessment system of the power system, and to evaluate the hierarchical flexibility adjustment capability of coal-fired units.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the coal-fired unit collaborative scheduling method considering hierarchical flexible supply and demand matching as described in any one of claims 1-6.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the coal-fired unit collaborative scheduling method considering hierarchical flexible supply and demand matching as described in any one of claims 1-6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the steps in the coal-fired unit collaborative scheduling method considering hierarchical flexible supply and demand matching as described in any one of claims 1-6.

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