Power system unit commitment optimization scheduling method, device, equipment and medium

Abstract

The application belongs to the field of power system dispatching operation and control, and discloses a power system unit combination optimization dispatching method, device, equipment and medium; the method comprises the following steps: acquiring a unit set G in a power system and characteristic parameters of each unit g in the unit combination G; solving a pre-established power system unit combination model considering multi-working condition wide power regulation characteristics of coal-fired units based on the characteristic parameters of each unit g, to obtain a power system unit combination optimization dispatching result; and outputting the power system unit combination optimization dispatching result. The application enhances the support capability of the unit combination result for multi-dimensional regulation of the power system, and is suitable for the development and application of a new type of power system.

Description

Technical Field

[0001] This invention belongs to the field of power system dispatching, operation and control, and relates to a method, device, equipment and medium for optimizing the dispatching of power system unit combinations. Background Technology

[0002] With the ongoing reforms of coal-fired power plants, the regulation characteristics of generating units have changed significantly. This is especially true when facing the demands of deep peak shaving, ramp-up, and frequency regulation in the new power system, necessitating refined modifications and adjustments to the unit combination model. After the reforms, when units face special system scenarios, such as the morning and evening ramp-up of photovoltaic power and the instantaneous power ramp-up caused by peak-valley pricing, units in deep regulation mode will struggle to provide the ramp-up capabilities they would normally provide, leading to insufficient overall system ramp-up capability. Furthermore, the rotational inertia and frequency regulation capability of units in deep regulation mode decrease, resulting in insufficient overall system stability and frequency regulation capability. This presents new demands on the power system. On the one hand, the regulation capability of coal-fired power needs to be optimized collaboratively across a wide range; on the other hand, it is necessary to propose scientifically reasonable utilization levels under different renewable energy generation levels, ensuring both the balance and regulation needs of renewable energy and low-carbon operation. There is an urgent need to scientifically assess the regulation characteristics of coal-fired power and propose a day-ahead unit combination method adapted to the multi-condition, wide-power regulation characteristics of coal-fired power units, fully exploring and leveraging the system regulation role of coal-fired power in the energy transition process. Summary of the Invention

[0003] The purpose of this invention is to provide a method, device, equipment, and medium for optimizing the scheduling of power system units, in order to solve the technical problems of coal-fired power units having difficulty providing effective climbing ability under special operating conditions and the reduction of unit rotational inertia and frequency regulation capability under deep scheduling conditions.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for optimizing the scheduling of power system unit combinations, comprising: Obtain the set of generating units G in the power system, and the characteristic parameters of each generating unit g in the combination of generating units G; Based on the characteristic parameters of each unit g, the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units is solved to obtain the power system unit combination optimization scheduling results; The power system is dispatched based on the results of the optimized scheduling of power system unit combinations.

[0005] A further improvement of this invention is that: in the step of obtaining the set of generating units G in the power system, and the characteristic parameters of each generating unit g in the generating unit combination G, the characteristic parameters of each generating unit g specifically include: generating unit Startup costs ,unit Downtime costs ,unit Multi-condition wide-power segmented operation cost .

[0006] A further improvement of this invention is that: in the step of solving the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtaining the optimized scheduling results of the power system unit combination, the objective function of the power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units is: (33) in, Indicates the unit Startup costs, Indicates the unit Downtime costs Indicates the unit During the period Power-on process, Indicates the unit During the period The shutdown action, where T is the time period set; Indicates the unit Multi-condition, wide-power segmented operation cost.

[0007] A further improvement of this invention is that: in the step of solving the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtaining the power system unit combination optimization scheduling results, the constraints of the power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units include: logical constraints on the operating state of coal-fired power units, logical constraints on the peak-shaving state of coal-fired power units, output constraints of coal-fired power units, ramp-up constraints of coal-fired power units, minimum start-up and shutdown time constraints of coal-fired power units, power balance constraints, output constraints of new energy units, line power flow constraints, and grid peak-shaving, ramp-up, and frequency regulation demand constraints.

[0008] A further improvement of this invention is that the power grid peak shaving, ramping, and frequency regulation demand constraints specifically include: The power grid peak-shaving demand constraint is: (twenty two) (twenty three) Where I represents the total number of units participating in peak shaving. To increase peak demand, Let i be the operating state of unit i at time t. This represents the maximum power output of unit i during the basic peak-shaving phase. This represents the minimum power output of unit i during its basic peak-shaving phase. Let be the power of unit i at time t. Let T represent the basic peak-shaving state of unit i at time t+1, where T is the number of time periods within the scheduling cycle. To reduce peak demand, This is the minimum power output during the unit's oil injection and peak-shaving phase. This represents the state of unit i during the peak oil injection phase at time t+1. The climbing requirement constraint is: (28) (29) in, The hill-climbing capability of unit i; This refers to the downhill climbing capability of unit i. For the purpose of climbing uphill, For downhill climbing requirements; The frequency modulation requirement constraint is: (32) in, To meet the system frequency regulation requirements.

[0009] A further improvement of this invention is that the logical constraints on the operating state of the coal-fired power unit are as follows: (34) (35) in, Let g be the operating state of unit g at time t. This represents the startup state of unit g at time t+1. Unit g is in the off state at time t+1; The logic constraints for peak-shaving status of coal-fired power units are as follows: (36) in, The operating condition of unit g at time t; Characterizing the unit's operating conditions s ,on the contrary ; The output constraints of coal-fired power units are: (37) in, , They represent the generating units. g Under working conditions s The minimum and maximum output, For the unit g During the period t Actual output; The ramping constraint for coal-fired power units is: (38) (39) in, Indicates coal-fired power units Maximum climbing rate, To relax the climbing rate; The minimum start-up and shutdown time constraints for coal-fired power units are: (40) (41) (42) (43) in, and Representing the units Minimum start-up and shutdown times; The power balance constraint is: (44) Where R represents the set of new energy sources. The power output of the new energy unit r at time t. Let d be the power of load d at time t, and D be the set of loads in the system; The output constraints of new energy units are: (45) The power flow constraints of the line are: (46) in, For the line l The limit of current transmission, coal-fired power units g The node is connected to the line l The power transfer distribution factor For new energy units r The node is connected to the line l The power transfer distribution factor For load d The node is connected to the line l The power transfer distribution factor, where L represents the number of lines.

[0010] In a second aspect, the present invention provides a power system unit combination optimization scheduling device, comprising: The acquisition module is used to acquire the set of generating units G in the power system, as well as the characteristic parameters of each generating unit g in the combination of generating units G; The optimization scheduling module is used to solve the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtain the power system unit combination optimization scheduling results. The scheduling module is used to schedule the power system based on the optimized scheduling results of the power system unit combination.

[0011] A further improvement of this invention is that: in the step of obtaining the set of generating units G in the power system, and the characteristic parameters of each generating unit g in the generating unit combination G, the characteristic parameters of each generating unit g specifically include: generating unit Startup costs ,unit Downtime costs ,unit Multi-condition wide-power segmented operation cost .

[0012] A further improvement of this invention is that: in the step of solving the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtaining the optimized scheduling results of the power system unit combination, the objective function of the power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units is: (33) in, Indicates the unit Startup costs, Indicates the unit Downtime costs Indicates the unit During the period Power-on process, Indicates the unit During the period The shutdown action, where T is the time period set; Indicates the unit Multi-condition, wide-power segmented operation cost.

[0013] A further improvement of this invention is that: in the step of solving the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtaining the power system unit combination optimization scheduling results, the constraints of the power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units include: logical constraints on the operating state of coal-fired power units, logical constraints on the peak-shaving state of coal-fired power units, output constraints of coal-fired power units, ramp-up constraints of coal-fired power units, minimum start-up and shutdown time constraints of coal-fired power units, power balance constraints, output constraints of new energy units, line power flow constraints, and grid peak-shaving, ramp-up, and frequency regulation demand constraints.

[0014] A further improvement of this invention is that the power grid peak shaving, ramping, and frequency regulation demand constraints specifically include: The power grid peak-shaving demand constraint is: (twenty two) (twenty three) Where I represents the total number of units participating in peak shaving. To increase peak demand, Let i be the operating state of unit i at time t. This represents the maximum power output of unit i during the basic peak-shaving phase. This represents the minimum power output of unit i during its basic peak-shaving phase. Let be the power of unit i at time t. Let T represent the basic peak-shaving state of unit i at time t+1, where T is the number of time periods within the scheduling cycle. To reduce peak demand, This is the minimum power output during the unit's oil injection and peak-shaving phase. This represents the state of unit i during the peak oil injection phase at time t+1. The climbing requirement constraint is: (28) (29) in, The hill-climbing capability of unit i; This refers to the downhill climbing capability of unit i. For the purpose of climbing uphill, For downhill climbing requirements; The frequency modulation requirement constraint is: (32) in, To meet the system frequency regulation requirements.

[0015] A further improvement of this invention is that the logical constraints on the operating state of the coal-fired power unit are as follows: (34) (35) in, Let g be the operating state of unit g at time t. This represents the startup state of unit g at time t+1. Unit g is in the off state at time t+1; The logic constraints for peak-shaving status of coal-fired power units are as follows: (36) in, The operating condition of unit g at time t; Characterizing the unit's operating conditions s ,on the contrary ; The output constraints of coal-fired power units are: (37) in, , They represent the generating units. g Under working conditions s The minimum and maximum output, For the unit g During the period t Actual output; The ramping constraint for coal-fired power units is: (38) (39) in, Indicates coal-fired power units Maximum climbing rate, To relax the climbing rate; The minimum start-up and shutdown time constraints for coal-fired power units are: (40) (41) (42) (43) in, and Representing the units Minimum start-up and shutdown times; The power balance constraint is: (44) Where R represents the set of new energy sources. The power output of the new energy unit r at time t. Let d be the power of load d at time t, and D be the set of loads in the system; The output constraints of new energy units are: (45) The power flow constraints of the line are: (46) in, For the line l The limit of current transmission, coal-fired power units g The node is connected to the line l The power transfer distribution factor For new energy units rThe node is connected to the line l The power transfer distribution factor For load d The node is connected to the line l The power transfer distribution factor, where L represents the number of lines.

[0016] Thirdly, the present invention provides an electronic device, including a processor and a memory, wherein the processor is used to execute a computer program stored in the memory to implement the power system unit combination optimization scheduling method.

[0017] Thirdly, the present invention provides a computer-readable storage medium storing at least one instruction, which, when executed by a processor, implements the power system unit combination optimization scheduling method.

[0018] Compared with the prior art, the present invention has the following beneficial effects: This invention provides a method for optimal scheduling of power system unit combination, comprising: obtaining a set G of units in the power system, and characteristic parameters of each unit g in the unit combination G; solving a pre-established power system unit combination model considering the multi-condition wide-power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, to obtain the optimal scheduling result of the power system unit combination; and scheduling the power system based on the optimal scheduling result of the power system unit combination. This invention constructs a multi-condition operating cost model for units, analyzes and models the peak-shaving, ramp-up, and frequency regulation demands of the power system, and provides the regulation capacity of coal-fired power units corresponding to the power system demand. It also constructs multi-dimensional regulation characteristic constraints for the power system, and adds relevant constraints as backup constraints to the unit combination model, enhancing the support capability of the unit combination results for multi-dimensional regulation of the power system; adapting to the development and application of new power systems.

[0019] This invention studies the wide-range power regulation characteristics of coal-fired power units under multiple operating conditions, effectively addressing the problems of insufficient overall system ramping and frequency regulation capabilities under special operating conditions of coal-fired power plants. In particular, it improves the low inertia, weak frequency regulation, and limited ramping capabilities during the deep regulation phase of coal-fired power units, which will help optimize the allocation of grid regulation resources, significantly improve the grid regulation level and operating costs, while also increasing the absorption of new energy sources, enhancing the economic efficiency and resource optimization of grid operation, and contributing to the construction of a new power system.

[0020] This invention characterizes the operating costs of generating units during deep peak shaving, establishes a multi-condition, wide-power unit combination operating cost model for coal-fired power units, constructs multi-dimensional regulation characteristic constraints of the power system based on the power system's peak shaving, ramp-up, and frequency regulation requirements, and integrates the multi-condition, wide-power operating costs of coal-fired power units, system constraints, and multi-dimensional regulation characteristics of the power system to construct a day-ahead unit combination model that adapts to the multi-condition, wide-power regulation characteristics of coal-fired power transformation, fully exploring and leveraging the system regulation role of coal-fired power in the energy transition process. Attached Figure Description

[0021] The accompanying drawings, which form part of this specification, 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 undue limitation of the invention. In the drawings: Figure 1 This is a flowchart illustrating a power system unit combination optimization scheduling method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of a power system unit combination optimization dispatching device according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device according to the present invention. Detailed Implementation

[0022] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0023] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this invention is for describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0024] This invention provides a power system unit combination optimization scheduling method, comprising: First, in order to more accurately characterize the operating cost during the deep peak shaving process of the units, modeling the cost sources during the deep shaving process separately, and establishing a multi-condition wide-power unit combination operating cost model for coal-fired power units; Second, analyzing and modeling the peak shaving, ramping, and frequency regulation demands of the power system, characterizing the regulation capability of coal-fired power units corresponding to the power system demand, and constructing multi-dimensional regulation characteristic constraints of the power system; Finally, integrating the multi-condition wide-power operating cost of coal-fired power units, system constraints, and multi-dimensional regulation characteristics of the power system, constructing a day-ahead unit combination model adapted to the multi-condition wide-power regulation characteristics of coal-fired power plant reform.

[0025] This invention provides a power system unit combination optimization scheduling method, particularly a power system unit combination optimization scheduling method that takes into account the multi-condition wide power regulation characteristics of coal-fired power units, including: 1. Wide power regulation constraints for coal-fired power units under multiple operating conditions (1) Coal consumption cost Coal consumption costs exist in conventional peak shaving, deep peak shaving without oil injection, and deep peak shaving with oil injection. These coal consumption costs are considered to be expressed using a quadratic function of fuel consumption characteristics. (1) in, Indicates the output of the coal-fired power unit. Indicates the start / stop status; 1 indicates the start status and 0 indicates the stop status. The coefficients of the secondary, primary, and constant cost functions for coal-fired power units, respectively.

[0026] When coal-fired power units are in the basic peak-shaving phase, their operation is largely consistent with the conventional economic dispatch model. Their coal consumption characteristic curve can be described as a quadratic function. However, approximating the coal-fired power generation cost curve with a quadratic function would impose an unnecessary computational burden on solving the Unit Commitment (UC) problem. Therefore, the quadratic form of the coal-fired power unit generation cost curve is generally piecewise linearized. The resulting coal-fired power unit generation cost after piecewise linearization is as follows: (2) in, Represents the set of all segments; and The first two lines represent the piecewise linearized power generation cost curves of coal-fired power units. The segment outputs the upper and lower bounds, and This involves linearizing equation (1) piecewise into the cost function coefficients of equation (2). Further processing of the equations is needed to ensure they are linearly constrained and embedded into the UC model. The specific processing method is as follows: (3) Therefore, the piecewise linearized coal-fired power generation cost can approximate the quadratic function form of the coal-fired power generation cost curve. The accuracy and efficiency of the cost balance model can be adaptively determined based on the required number of linearized segments.

[0027] (2) Unit loss cost In addition to coal consumption costs, the depreciation costs of the generating unit also need to be considered under both non-oil-fuel peak shaving and oil-fuel peak shaving conditions. This is based on the Manson-Coffin formula: (4) This represents the total strain amplitude of the rotor. The fatigue strength coefficient of the material. For elastic modulus, For the number of rotor-induced cracking cycles, The fatigue strength index of the material. This is the fatigue ductility coefficient of the material. It varies depending on the unit output. The rotor's thermal stress and centrifugal tangential stress can be obtained through simulation, thus yielding the rotor's total strain amplitude. Solve for the number of rotor-induced cracking cycles. That is, to obtain the unit's output power Lower rotor cracking cycle number Then, combined with the purchase cost The output is Unit loss cost .

[0028] (5) in, For coefficients, Indicates the cost of the generating unit. Indicates output force Rotor-induced cracking cycles.

[0029] It is generally believed that as the power output increases from the oil-fueled stable combustion limit to the minimum technical output, the rotor loss will gradually decrease and tend to stabilize. This means that the rotor cracking cycle number exhibits a marginal decrease effect with increasing unit output, indicating that the second derivative of the rotor cracking cycle number function is negative, i.e. (6) At this point, based on the second derivative of the cost function for the non-oil-injection peak shaving and oil-injection peak shaving stages: (7) Clearly, the second derivative of the cost function in both the non-oil-injection peak shaving and oil-injection peak shaving stages is non-negative. Therefore, their cost functions in their respective stages are convex and can be linearized using conventional peak shaving cost function linearization methods.

[0030] (3) Oil input cost The cost of oil injection needs to be considered under peak-shaving conditions: (8) in, Indicates output force The cost of oil production, For oil prices, This refers to the amount of oil added.

[0031] (4) Comprehensive peak-shaving cost function Based on the cost models of each stage mentioned above, a piecewise function is constructed to combine the multi-condition operating cost models of coal-fired power units under conventional peak shaving, peak shaving without oil injection, and peak shaving with oil injection, and establishes a mixed-integer form multi-condition wide-power piecewise operating cost model: (9) In this context, subscripts 1, 2, and 3 represent the basic peak-shaving stage, the peak-shaving stage without oil injection, and the peak-shaving stage with oil injection, respectively. The operating cost during the basic peak-shaving phase, and These are the lower and upper limits of unit output during the basic peak-shaving phase, respectively. To reduce operating costs during peak-shaving periods without oil injection, and These are the lower and upper limits of unit output during peak shaving without oil injection, respectively. To cover the operating costs during the peak oil release phase, and These are the lower and upper limits of unit output during peak-shaving periods without oil injection; (10) Using disjunctive programming, the segmented operating costs are constructed into a mixed-integer operating cost model as follows: (11) And it needs to meet the following requirements: (12) (13) The cost function at this point exhibits nonlinear costs, thus requiring further linearization: (14) (15) (16) (17) At this point, the cost model is fully linearized and can be solved by a linear solver.

[0032] 2. Constructing multi-dimensional regulation characteristic constraints for the power system To improve the optimization results' support for the multi-dimensional regulation characteristics requirements of the power system, relevant constraints on the multi-dimensional regulation characteristics requirements of the power system are added.

[0033] (1) Construction of peak-shaving constraints Peak shaving is the service capability provided by generator sets to adjust their output in a planned manner and at a certain adjustment rate to track load peak-valley changes. In systems with high renewable energy penetration, in addition to load peak-valley changes, the volatility of renewable energy output also has a significant impact. Therefore, grid-connected power sources that are controllable on the generation side need to adjust their output or even change their operating status to track load or equivalent load peak-valley changes. Peak shaving can be divided into upward peak shaving and downward peak shaving, that is, the power source output must be able to rise during peak load or equivalent load periods and the power source output must be able to fall during off-peak load periods.

[0034] (18) (19) in, To increase peak demand, To reduce peak demand, B represents the total system bus load, and b represents the bus load index. Let J be the predicted power of bus load b at time t+1, and J be the total number of renewable energy plants. Let be the predicted power of bus load b at time t. Let j be the predicted power of the new energy power plant at time t+1. Let t be the predicted power of the new energy power plant j at time t, and T be the number of time periods within the scheduling cycle.

[0035] Peak-shaving demand refers to the demand during a given time period. t+1 Due to changes in load and renewable energy output, the output of coal-fired power units should also change accordingly to meet power balance requirements. This includes adjusting peak-shaving demand. Calculated by formula (18), if the time period t+1 If the increase in renewable energy output is smaller than the increase in load, then the peak-shaving demand will be increased. In other words, there is a demand for upward peak shaving; and a demand for downward peak shaving. According to formula (19), if the increase in new energy output is greater than the increase in load in the next period, then the peak-shaving demand will be reduced. This means there is a need to reduce peak loads.

[0036] (20) (twenty one) Where I represents the total number of units participating in peak shaving; This represents the operating status of unit i at time t, where 1 indicates startup and 0 indicates shutdown. Let be the power of unit i at time t; This represents the basic peak-shaving state of unit i at time t+1, where 1 represents basic peak-shaving and 0 represents non-basic peak-shaving. This refers to the maximum power output of unit i during its basic peak-shaving phase, which is generally the unit's maximum technical output. This represents the minimum power output of unit i during its basic peak-shaving phase. This is the minimum power output during the unit's oil injection and peak-shaving phase. This represents the state of unit i during the oil injection peak shaving phase at time t+1, where 1 indicates oil injection peak shaving and 0 indicates no oil injection peak shaving.

[0037] Peak-shaving capacity refers to the ability of a coal-fired power unit to change its overall output power by increasing or decreasing its output, or by starting or stopping the unit. Peak-shaving capacity is calculated using formula (20), which is the ratio of the current output of all online units to the maximum output limit under normal peak-shaving conditions during the period, assuming the coal-fired power units remain operational. The upward peak-shaving range. The downward peak-shaving capacity is calculated by formula (21), which is the minimum output limit of all online units from the current output to the oil injection depth peak-shaving condition. The lower peak-shaving range. Additional peak-shaving capacity can be obtained by starting and stopping the units, and additional upper peak-shaving capacity is added when the units are running. When the unit is shut down, its peak-shaving capacity during that period is: .

[0038] Based on peak-shaving demand and capacity, in order to ensure that the unit combination results in the peak-shaving capacity of coal-fired power units meets the peak-shaving demand of the power system, the peak-shaving demand constraint of the power system can be constructed as follows: (twenty two) (twenty three) (2) Construction of climbing constraints Ramp-up refers to the service provided by grid-connected entities with strong load regulation capabilities to adjust their output according to dispatch instructions in order to maintain system power balance in response to short-term and significant changes in system net load caused by uncertainties such as fluctuations in renewable energy generation. When the system's ramp-up capacity is insufficient, there is a risk of power curtailment due to insufficient supply; when the system's ramp-up capacity is insufficient, there is a risk of power curtailment due to oversupply. Ramp-up demand refers to the increase or decrease in output required by coal-fired power units between two periods in order to track peak and valley load changes and fluctuations in renewable energy output.

[0039] (twenty four) (25) in To meet the uphill climbing demand, representing the time period t arrive t+1 The power system requires increased output from coal-fired power units due to load changes and fluctuations in new energy output. For downhill climbing demand, representing the time period t arrivet+1 Due to load changes and fluctuations in new energy output, the power system requires coal-fired power units to reduce their output.

[0040] (26) (27) in, The hill-climbing capability of unit i; This refers to the downhill climbing capability of unit i.

[0041] Climbing capacity refers to the maximum power change that a coal-fired power unit can make within a given time period while ensuring physical safety constraints. Without considering unit start-up and shutdown, the climbing capacity of a coal-fired power unit is the maximum climbing power of all online units. The sum of these values ​​indicates that the downhill climbing capacity of the coal-fired power units is equal to the maximum downhill climbing power of all online units. sum.

[0042] Based on ramping requirements and ramping capabilities, in order to ensure that the unit combination results make the ramping capabilities of coal-fired power units meet the ramping requirements of the power system, power system ramping requirement constraints can be constructed: (28) (29) As we can see, peak shaving and ramping are corresponding at the demand level, both requiring the difference in output between two adjacent periods. However, they are complementary in terms of capacity. Peak shaving capacity ensures that there is a margin for increasing or decreasing the total output of the units, while ramping capacity ensures that increasing or decreasing the output of the units is feasible at the physical level (heat and stress).

[0043] (3) Construction of frequency modulation demand constraints To ensure frequency regulation requirements and frequency stability, the larger the sum of the online unit capacities, the greater the corresponding moment of inertia, resulting in less frequency variation due to interference and a larger frequency regulation range and capability. Frequency regulation requirements are represented by the total installed online capacity necessary to guarantee frequency regulation. (30) in, To meet the system frequency regulation requirements; Correspondingly, the frequency regulation capability of coal-fired power units is: (31) Based on frequency regulation requirements and capabilities, to ensure that the unit combination results in a situation where the ramp-up capability of coal-fired power units meets the frequency regulation requirements of the power system, the following power system frequency regulation requirement constraints can be constructed: (32) 3. Power system unit combination model considering the multi-condition and wide-power regulation characteristics of coal-fired power units The day-ahead unit combination model, which adapts to the multi-condition and wide-power regulation characteristics of coal-fired power plants, arranges the start-up, shutdown, operating conditions and output of the units based on the energy consumption and other characteristics of the units, while meeting the system load demand and unit operation constraints. This maximizes the deep peak-shaving capacity of coal-fired power units and minimizes the total power generation cost of the system, achieving optimal operating economy.

[0044] (1) Model Objective The objective function of the day-ahead unit combination model adapted to the multi-operating-condition and wide-power regulation characteristics of coal-fired power plant transformation is to minimize the operating cost of the power system, which includes the cost of multi-operating-condition and wide-power segmented operation of the units. Unit start-up and shutdown costs. The start-up and shutdown costs of thermal power units include start-up costs and shutdown costs. Start-up costs represent the expenses incurred when a thermal power unit transitions from a shutdown state to an start-up state, and are constant. Shutdown costs represent the expenses incurred when a thermal power unit transitions from an start-up state to a shutdown state, and are constant.

[0045] set up For the unit At any moment The operating status; if the unit is powered on, then ;otherwise, .set up Indicates the unit At any moment The start-up signal, if the unit is in Always in the off state, If the device is switched to the power-on state at any time, then ;otherwise, .set up Indicates the unit At any moment The shutdown signal, if the unit is in Always powered on. If the device is switched to a power-off state at any time, then ;otherwise, By defining the above three types of integer variables, the unit's start-up state can be accurately described. Considering both start-up and shutdown costs and the cost of operating across multiple power conditions, the objective function is constructed as follows: (33) in, Indicates the unit Startup costs, Indicates the unit Downtime costs Indicates the unit During the period Power-on process, Indicates the unit During the period The shutdown action; G represents the unit set, and T represents the time period set; Indicates the unit Multi-condition, wide-power segmented operation cost.

[0046] (2) Model constraints Model constraints include coal-fired power unit constraints, system constraints, and regulation characteristic constraints: 1) Logical constraints on the operating status of coal-fired power units The unit operating state logic constraints characterize the operating state of generator g in the system. With startup and shutdown status ( , The relationship between ) . If generator g starts at time t, i.e. and Then there is ;otherwise, Similarly, if generator g is turned off at time t, i.e. and Then there is ;otherwise The above logic can be further described as follows: (34) (35) 2) Logic constraints for peak-shaving status of coal-fired power units To describe the different operating conditions of the generating unit during peak-shaving operation, three sets of 0-1 variables are introduced. , Characterizing the operating conditions of coal-fired power units s ,on the contrary At any given time, a coal-fired power unit can only operate in one operating condition at most, and operating in any one of these conditions indicates that the coal-fired power unit is online. ,on the contrary Specifically, operating condition 's' includes the basic peak-shaving phase, the peak-shaving phase without oil injection, and the peak-shaving phase with oil injection. The above logic can be further described as follows: (36) 3) Output constraints of coal-fired power units The unit must meet the corresponding upper and lower limits of output and cannot operate outside the output range. Furthermore, the upper and lower limits of the unit's output differ under different operating conditions, which can be expressed as: (37) in, , They represent the generating units. g Under working conditions sThe minimum and maximum output, For the unit g During the period t The actual output. The maximum output limit depends on the rated capacity designed and manufactured by the unit, which is the maximum capacity that can be continuously output during the entire specified normal service life. The minimum output limit, also known as the technical minimum output, refers to the minimum output required for the boiler to burn stably and the generator set to operate continuously and stably under technical constraints. The minimum stable output of a thermal power generating unit is an important performance indicator. Units with a small stable output have a large output adjustment range and can meet the peak-shaving needs of the power system. This value is affected by differences in coal quality, boiler operating conditions, and power plant unit equipment, and should be determined based on test data and operating experience.

[0047] In multi-condition operation, the output limits under different conditions are the unit's normal maximum output, the fuel-stable limit without oil injection, and the fuel-stable limit with oil injection. These are defined by three 0-1 variables describing the unit's operating condition. Separate and corresponding working conditions s The output limits are multiplied and superimposed to ensure that the unit's output is limited to the upper and lower limits of the unit's operating conditions.

[0048] 4) Climbing constraints of coal-fired power units The maximum ramp rate boundary refers to the threshold at which the output change between two consecutive adjacent time periods cannot exceed a certain threshold during continuous operation of the unit. It is modeled as follows: (38) (39) in, Indicates coal-fired power units To avoid the inability to start and stop normally due to the maximum ramp rate limitation, the ramp rate during start-up and shutdown is relaxed. Specifically, when a coal-fired power unit changes from a shutdown state to a startup state, the maximum ramp rate constraint is relaxed to... , This is achieved by expanding using a custom or preset relaxation factor. When changing from a powered-on state to a powered-off state, the maximum downhill gradient should also be relaxed to... .

[0049] 5) Minimum start-up and shutdown time constraints for coal-fired power units Thermal power units require a certain amount of time to start up or shut down from a shutdown state. Therefore, considering the unit's start-up and shutdown state logic variables, the minimum start-up and shutdown time constraint is: (40) (41) (42) (43) in and Representing the units The minimum start-up and shutdown time is crucial. This is because the start-up and shutdown of thermal power units are achieved through the start-up and shutdown of the boiler and turbine. Frequent start-up and shutdown of the boiler can lead to damage to the boiler tube joints, and frequent start-up and shutdown of the turbine can cause the turbine shaft to bend, which will greatly reduce the lifespan of the thermal power unit. In order to reduce the wear and tear of parts and mechanical fatigue, thermal power units cannot be continuously started and stopped in a short period of time.

[0050] 6) Power balance constraints Power balance in a power system refers to the balance between power supply and demand, requiring that the total power generation and total load of the power system be kept in balance at all times. The research objects in this model include thermal power units, hydropower units, photovoltaic power generation systems, wind power units, and loads, neglecting transmission losses. The scheduling planning period is... The time interval is divided into The power balance constraint can be written as the sum of the output power of all types of generator sets equals the power of all types of loads, which can be expressed as: (44) Where R represents the set of new energy sources. The power output of the new energy unit r at time t. Let d be the power of load d at time t, and D be the set of loads in the system.

[0051] 7) Output constraints of new energy units (45) 8) Power flow constraints of the line The power transmission network has its physical boundary defined by the maximum transmission capacity of the lines. The main impact on renewable energy absorption lies in insufficient maximum transmission capacity, leading to line congestion. The maximum transmission capacity boundary is typically modeled using DC power flow, as shown below. The maximum transmission capacity boundary refers to the power flowing through the line not exceeding a certain threshold, usually modeled using DC power flow as follows: (46) in, For the line l The limit of current transmission, coal-fired power units g The node is connected to the line l The power transfer distribution factor For new energy units r The node is connected to the line l The power transfer distribution factor For loadd The node is connected to the line l The power transfer distribution factor, where L represents the number of lines.

[0052] 9) Constraints on power grid peak shaving, ramping, and frequency regulation requirements: Specifically, as described in formulas (22), (23), (28), (29), and (32).

[0053] Please see Figure 1 As shown, this embodiment of the invention provides a power system unit combination optimization scheduling method, including: S1. Obtain the set of generating units G in the power system, and the characteristic parameters of each generating unit g in the combination of generating units G; In one specific embodiment, the step of obtaining the set of generating units G in the power system, and the characteristic parameters of each generating unit g in the unit combination G, specifically includes: the characteristic parameters of each generating unit g. Startup costs ,unit Downtime costs ,unit Multi-condition wide-power segmented operation cost ; S2. Solve the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtain the power system unit combination optimization scheduling results. S3. Dispatch the power system based on the optimized scheduling results of the power system unit combination.

[0054] In one specific embodiment, the step of obtaining the set of generating units G in the power system, and the characteristic parameters of each generating unit g in the unit combination G, specifically includes: the characteristic parameters of each generating unit g. Startup costs ,unit Downtime costs ,unit Multi-condition wide-power segmented operation cost .

[0055] In one specific implementation, in the step of solving a pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtaining the optimized scheduling results of the power system unit combination, the objective function of the power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units is: (33) in, Indicates the unit Startup costs, Indicates the unit Downtime costs Indicates the unit During the period Power-on process, Indicates the unit During the period The shutdown action, where T is the time period set; Indicates the unit During the period Multi-condition wide-power segmented operation cost.

[0056] In one specific implementation, the cost model for multi-condition wide-power segmented operation is as follows: (9) In this context, subscripts 1, 2, and 3 represent the basic peak-shaving stage, the peak-shaving stage without oil injection, and the peak-shaving stage with oil injection, respectively. The operating cost during the basic peak-shaving phase, and These are the lower and upper limits of unit output during the basic peak-shaving phase, respectively. To reduce operating costs during peak-shaving periods without oil injection, and These are the lower and upper limits of unit output during peak shaving without oil injection, respectively. To cover the operating costs during the peak oil release phase, and These are the lower and upper limits of unit output during peak-shaving periods without oil injection; (10); Using disjunctive programming, the segmented operating costs are constructed into a mixed-integer operating cost model as follows: (11) And it needs to meet the following requirements: (12) (13) The cost function at this point exhibits nonlinear costs, thus requiring further linearization: (14) (15) (16) (17) At this point, the cost model is fully linearized and can be solved by a linear solver.

[0057] In one specific implementation, the step of solving the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtaining the power system unit combination optimization scheduling results, includes the following constraints on the power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units: coal-fired power unit operating state logic constraints, coal-fired power unit peak shaving state logic constraints, coal-fired power unit output constraints, coal-fired power unit ramping constraints, coal-fired power unit minimum start-stop time constraints, power balance constraints, new energy unit output constraints, line power flow constraints, and grid peak shaving, ramping, and frequency regulation demand constraints.

[0058] In one specific implementation, the power grid peak shaving, ramping, and frequency regulation demand constraints specifically include: The power grid peak-shaving demand constraint is: (twenty two) (twenty three) Where I represents the total number of units participating in peak shaving. To increase peak demand, Let i be the operating state of unit i at time t. This represents the maximum power output of unit i during the basic peak-shaving phase. This represents the minimum power output of unit i during its basic peak-shaving phase. Let be the power of unit i at time t. Let T represent the basic peak-shaving state of unit i at time t+1, where T is the number of time periods within the scheduling cycle. To reduce peak demand, This is the minimum power output during the unit's oil injection and peak-shaving phase. This represents the state of unit i during the peak oil injection phase at time t+1. The climbing requirement constraint is: (28) (29) in, The hill-climbing capability of unit i; This refers to the downhill climbing capability of unit i. For the purpose of climbing uphill, For downhill climbing requirements; The frequency modulation requirement constraint is: (32) in, To meet the system frequency regulation requirements.

[0059] In one specific implementation, the logical constraints of the coal-fired power unit's operating state are as follows: (34) (35) in, Let g be the operating state of unit g at time t. This represents the startup state of unit g at time t+1. Unit g is in the off state at time t+1; The logic constraints for peak-shaving status of coal-fired power units are as follows: (36) in, The operating condition of unit g at time t; Characterizing the unit's operating conditions s ,on the contrary ; The output constraints of coal-fired power units are: (37) in, , They represent the generating units. g Under working conditions s The minimum and maximum output, For the unit g During the period t Actual output; The ramping constraint for coal-fired power units is: (38) (39) in, Indicates coal-fired power units Maximum climbing rate, To relax the climbing rate; The minimum start-up and shutdown time constraints for coal-fired power units are: (40) (41) (42) (43) in, and Representing the units Minimum start-up and shutdown times; The power balance constraint is: (44) Where R represents the set of new energy sources. The power output of the new energy unit r at time t. Let d be the power of load d at time t, and D be the set of loads in the system; The output constraints of new energy units are: (45) The power flow constraints of the line are: (46) in, For the line l The limit of current transmission, coal-fired power units g The node is connected to the line l The power transfer distribution factor For new energy units r The node is connected to the line l The power transfer distribution factor For load d The node is connected to the line l The power transfer distribution factor, where L represents the number of lines.

[0060] Please see Figure 2 As shown, the present invention provides a power system unit combination optimization scheduling device, comprising: The acquisition module is used to acquire the set of generating units G in the power system, as well as the characteristic parameters of each generating unit g in the combination of generating units G; The optimization scheduling module is used to solve the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtain the power system unit combination optimization scheduling results. The scheduling module is used to schedule the power system based on the optimized scheduling results of the power system unit combination.

[0061] Please see Figure 3 As shown, the present invention also provides an electronic device 100 for implementing a power system unit combination optimization scheduling method; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104.

[0062] The memory 101 can be used to store the computer program 103. The processor 102 implements the steps of the power system unit combination optimization scheduling method described above by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device 100 (such as audio data), etc. In addition, the memory 101 may include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0063] The at least one processor 102 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 may be a microprocessor or any conventional processor. The processor 102 is the control center of the electronic device 100, connecting various parts of the electronic device 100 via various interfaces and lines.

[0064] The memory 101 in the electronic device 100 stores multiple instructions to implement a power system unit combination optimization scheduling method, and the processor 102 can execute the multiple instructions to achieve the following: Obtain the set of generating units G in the power system, and the characteristic parameters of each generating unit g in the combination of generating units G; Based on the characteristic parameters of each unit g, the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units is solved to obtain the power system unit combination optimization scheduling results; The power system is dispatched based on the results of the optimized scheduling of power system unit combinations.

[0065] If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0066] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0067] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0068] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0069] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0070] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for optimizing the scheduling of power system unit combinations, characterized in that, include: Obtain the set of generating units G in the power system, and the characteristic parameters of each generating unit g in the set of generating units G; Based on the characteristic parameters of each unit g, the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units is solved to obtain the power system unit combination optimization scheduling results; The power system is dispatched based on the results of the optimized scheduling of power system unit combinations; In the step of obtaining the set of generating units G in the power system, and the characteristic parameters of each generating unit g in the set of generating units G, the characteristic parameters of each generating unit g specifically include: the generating unit Startup costs ,unit Downtime costs ,unit Multi-condition wide-power segmented operation cost ; In the step of solving the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtaining the optimized scheduling results of the power system unit combination, the objective function of the power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units is: （33） in, Indicates the unit Startup costs, Indicates the unit Downtime costs Indicates the unit During the period Power-on process, Indicates the unit During the period The shutdown action, where T is the time period set; Indicates the unit During the period Multi-condition wide-power segmented operation cost; In the step of solving the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtaining the power system unit combination optimization scheduling results, the constraints of the power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units include: coal-fired power unit operating state logic constraints, coal-fired power unit peak shaving state logic constraints, coal-fired power unit output constraints, coal-fired power unit ramping constraints, coal-fired power unit minimum start-stop time constraints, power balance constraints, new energy unit output constraints, line power flow constraints, and grid peak shaving, ramping, and frequency regulation demand constraints. The specific constraints on power grid peak shaving, ramping, and frequency regulation requirements include: The power grid peak-shaving demand constraint is: （22） （23） Where I represents the total number of units participating in peak shaving. To increase peak demand, Let i be the operating state of unit i at time t. This represents the maximum power output of unit i during the basic peak-shaving phase. This represents the minimum power output of unit i during its basic peak-shaving phase. Let be the power of unit i at time t. Let T represent the basic peak-shaving state of unit i at time t+1, where T is the number of time periods within the scheduling cycle. To reduce peak demand, This is the minimum power output during the unit's oil injection and peak-shaving phase. This represents the state of unit i during the peak oil injection phase at time t+1. The climbing requirement constraint is: （28） （29） in, The hill-climbing capability of unit i; This refers to the downhill climbing capability of unit i. For the need to climb uphill, For downhill climbing requirements; The frequency modulation requirement constraint is: （32） in, To meet the system frequency regulation requirements.

2. The power system unit combination optimization scheduling method according to claim 1, characterized in that, The logical constraints for the operating status of the coal-fired power units are as follows: （34） （35） in, Let g be the operating state of unit g at time t. This represents the startup state of unit g at time t+1. Unit g is in the off state at time t+1; The logic constraints for peak-shaving status of coal-fired power units are as follows: （36） in, The operating condition of unit g at time t; Characterizing the unit's operating conditions s ,on the contrary ; The output constraints of coal-fired power units are: （37） in, , They represent the generating units. g Under working conditions s The minimum and maximum output, For the unit g During the period t Actual output; The ramping constraint for coal-fired power units is: （38） （39） in, Indicates coal-fired power units Maximum climbing rate, To relax the climbing rate; The minimum start-up and shutdown time constraints for coal-fired power units are: （40） （41） （42） （43） in, and Representing the units Minimum start-up and shutdown times; The power balance constraint is: （44） Where R represents the set of new energy sources. The power output of the new energy unit r at time t. Let d be the power of load d at time t, and D be the set of loads in the system; The output constraints of new energy units are: （45） The power flow constraints of the line are: （46） in, For the line l The limit of current transmission, coal-fired power units g The node is connected to the line l The power transfer distribution factor For new energy units r The node is connected to the line l The power transfer distribution factor For load d The node is connected to the line l The power transfer distribution factor, where L represents the number of lines.

3. A power system unit combination optimization and dispatching device, characterized in that, include: The acquisition module is used to acquire the set of generating units G in the power system, and the characteristic parameters of each generating unit g in the set of generating units G; The optimization scheduling module is used to solve the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtain the power system unit combination optimization scheduling results. The scheduling module is used to schedule the power system based on the optimized scheduling results of the power system unit combination; In the step of obtaining the set of generating units G in the power system, and the characteristic parameters of each generating unit g in the set of generating units G, the characteristic parameters of each generating unit g specifically include: the generating unit Startup costs ,unit Downtime costs ,unit Multi-condition wide-power segmented operation cost ; In the step of solving the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtaining the optimized scheduling results of the power system unit combination, the objective function of the power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units is: （33） in, Indicates the unit Startup costs, Indicates the unit Downtime costs Indicates the unit During the period Power-on process, Indicates the unit During the period The shutdown action, where T is the time period set; Indicates the unit Multi-condition, wide-power segmented operation cost; In the step of solving the pre-established power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units based on the characteristic parameters of each unit g, and obtaining the power system unit combination optimization scheduling results, the constraints of the power system unit combination model that takes into account the multi-condition wide power regulation characteristics of coal-fired power units include: coal-fired power unit operating state logic constraints, coal-fired power unit peak shaving state logic constraints, coal-fired power unit output constraints, coal-fired power unit ramping constraints, coal-fired power unit minimum start-stop time constraints, power balance constraints, new energy unit output constraints, line power flow constraints, and grid peak shaving, ramping, and frequency regulation demand constraints. The specific constraints on power grid peak shaving, ramping, and frequency regulation requirements include: The power grid peak-shaving demand constraint is: （22） （23） Where I represents the total number of units participating in peak shaving. To increase peak demand, Let i be the operating state of unit i at time t. This represents the maximum power output of unit i during the basic peak-shaving phase. This represents the minimum power output of unit i during its basic peak-shaving phase. Let be the power of unit i at time t. Let T represent the basic peak-shaving state of unit i at time t+1, where T is the number of time periods within the scheduling cycle. To reduce peak demand, This is the minimum power output during the unit's oil injection and peak-shaving phase. This represents the state of unit i during the peak oil injection phase at time t+1. The climbing requirement constraint is: （28） （29） in, The hill-climbing capability of unit i; This refers to the downhill climbing capability of unit i. For the need to climb uphill, For downhill climbing requirements; The frequency modulation requirement constraint is: （32） in, To meet the system frequency regulation requirements.

4. The power system unit combination optimization dispatching device according to claim 3, characterized in that, The logical constraints for the operating status of the coal-fired power units are as follows: （34） （35） in, Let g be the operating state of unit g at time t. This represents the startup state of unit g at time t+1. Unit g is in the off state at time t+1; The logic constraints for peak-shaving status of coal-fired power units are as follows: （36） in, The operating condition of unit g at time t; Characterizing the unit's operating conditions s ,on the contrary ; The output constraints of coal-fired power units are: （37） in, , They represent the generating units. g Under working conditions s The minimum and maximum output, For the unit g During the period t Actual output; The ramping constraint for coal-fired power units is: （38） （39） in, Indicates coal-fired power units Maximum climbing rate, To relax the climbing rate; The minimum start-up and shutdown time constraints for coal-fired power units are: （40） （41） （42） （43） in, and Representing the units Minimum start-up and shutdown times; The power balance constraint is: （44） Where R represents the set of new energy sources. The power output of the new energy unit r at time t. Let d be the power of load d at time t, and D be the set of loads in the system; The output constraints of new energy units are: （45） The power flow constraints of the line are: （46） in, For the line l The limit of current transmission, coal-fired power units g The node is connected to the line l The power transfer distribution factor For new energy units r The node is connected to the line l The power transfer distribution factor For load d The node is connected to the line l The power transfer distribution factor, where L represents the number of lines.

5. An electronic device, characterized in that, It includes a processor and a memory, the processor being used to execute a computer program stored in the memory to implement the power system unit combination optimization scheduling method as described in any one of claims 1 to 2.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, which, when executed by a processor, implements the power system unit combination optimization scheduling method as described in any one of claims 1 to 2.

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