Power generation-standby joint optimization method and device considering AGC process

Abstract

The invention provides a power generation-standby joint optimization method and device considering an AGC process, and belongs to the field of power system operation control. The method comprises the following steps: establishing an economic dispatching stage optimization model; based on the secondary frequency modulation AGC process of each time period in the economic dispatching stage, establishing an optimization control model of the secondary frequency modulation stage; embedding the optimization control model of the secondary frequency modulation stage into the optimization model of the economic dispatching stage to obtain a power generation-standby joint optimization model considering the AGC process; and solving the joint optimization model to obtain optimization results of the power generation plan and the standby plan. According to the method, a secondary frequency modulation process with a finer time scale is considered in an economic dispatching stage, an AGC control optimization model is embedded into an economic dispatching optimization model, and a more reasonable and reliable power generation plan and a secondary frequency modulation standby plan are obtained through calculation, so that a dispatcher is guided to make a dispatching decision.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of operation control of power systems, and particularly relates to a generation-reserve joint optimization method and device considering an AGC process. BACKGROUND

[0002] Frequency control of a power system can be divided into three levels according to time scales: primary frequency regulation is a difference control in seconds, and a generator set adjusts output according to local measurement to suppress frequency deviation; secondary frequency regulation (also referred to as automatic generation control, AGC) is a difference-free control, and a control center compensates for power shortage according to regional control error, with a period of 2 to 10 seconds; tertiary frequency regulation (also referred to as economic dispatch, ED) is frequency control in a longer time scale, and a control center optimizes a generator power base point according to a daily load curve and an economic optimality principle, with a period of 5 or 15 minutes. Among them, secondary frequency regulation reserve determines the power adjustable space of AGC in a dispatch period, and is usually jointly optimized and decided by a control center according to future load prediction and generation plan, and reasonable reserve decision is crucial to power system operation. However, large-scale new energy access brings strong uncertainty and randomness to power system operation, and a traditional decision-making method without considering a load change trajectory (i.e., without considering an AGC process) cannot obtain reliable and economic secondary frequency regulation reserve scheme, resulting in coexistence of inefficiency and risk, and seriously threatening safe and economic operation of the power system. SUMMARY

[0003] The application aims to overcome the deficiencies of the prior art, and provides a generation-reserve joint optimization method and device considering an AGC process. The application considers a secondary frequency regulation process in a more fine time scale in an economic dispatch stage, embeds an AGC control optimization model into an economic dispatch optimization model, and obtains more reasonable and reliable generation plan and secondary frequency regulation reserve plan through calculation, thereby guiding a dispatcher to make dispatching decisions.

[0004] The first aspect embodiment of the application provides a generation-reserve joint optimization method considering an AGC process, including:

[0005] establishing an economic dispatch stage optimization model;

[0006] based on a secondary frequency regulation AGC process in each period in the economic dispatch stage, establishing an optimization control model of a secondary frequency regulation stage;

[0007] embedding the optimization control model of the secondary frequency regulation stage into the economic dispatch stage optimization model to obtain a generation-reserve joint optimization model considering the AGC process;

[0008] solving the joint optimization model to obtain optimization results of the generation plan and the reserve plan.

[0009] In one specific embodiment of the present application, the objective function of the economic dispatch stage optimization model is to minimize the generation and reserve cost, expressed as follows:

[0010]

[0011] wherein, are the index and set of scheduling periods, respectively; are the index and set of conventional units, respectively; are the index and set of new energy stations, respectively; are the index and set of energy storage stations, respectively; denotes the total cost of the economic dispatch stage in the scheduling period ; , denote the fuel cost and secondary frequency modulation reserve cost of the conventional unit in the scheduling period ; denotes the abandoned power cost of the new energy station in the scheduling period ; , denote the charging and discharging loss cost and secondary frequency modulation reserve cost of the energy storage station in the scheduling period ;

[0012] wherein, the expression of the conventional unit fuel cost is as follows:

[0013]

[0014] wherein, denotes the output power of the conventional unit in the scheduling period ; denote the quadratic term, linear term, and constant term coefficients of the fuel cost of the conventional unit ;

[0015] The expression of the conventional unit secondary frequency modulation reserve cost is as follows:

[0016]

[0017] wherein, denote the upward secondary frequency modulation reserve and downward secondary frequency modulation reserve of the conventional unit in the scheduling period ; denotes the secondary frequency modulation reserve cost coefficient of the conventional unit ;

[0018] The expression of the new energy station abandoned power cost is as follows:

[0019]

[0020] wherein, denotes the new energy station in the dispatch period output power; denotes the new energy station in the dispatch period predicted output; denotes the new energy station abandon electricity cost coefficient;

[0021] The energy storage station charging and discharging loss cost expression is as follows:

[0022]

[0023] wherein, denotes the energy storage station in the dispatch period charging and discharging power loss, denotes the energy storage station charging and discharging loss cost coefficient; the charging and discharging power loss is expressed as the larger value of the charging loss and the discharging loss:

[0024]

[0025] wherein, respectively denote the charging power loss and the discharging power loss of the energy storage station in the dispatch period :

[0026]

[0027]

[0028] wherein, denotes the energy storage station in the dispatch period charging and discharging power, denotes discharging, denotes charging; respectively denote the charging efficiency and the discharging efficiency of the energy storage station ;

[0029] Formula (6) is relaxed into formula (9):

[0030]

[0031] The energy storage station secondary frequency modulation standby cost expression is as follows:

[0032]

[0033] in, These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; Indicates energy storage power station The secondary frequency regulation backup cost coefficient.

[0034] In a specific embodiment of the present invention, the constraints of the economic scheduling phase optimization model include:

[0035] 1) Power balance constraints:

[0036]

[0037] in, These are the label and node set of the load node, respectively; Indicates load node During the scheduling period The load power; These represent conventional units. New energy power stations Energy storage power station During the scheduling period ; output power;

[0038] 2) Constraints of conventional units:

[0039]

[0040]

[0041]

[0042]

[0043] in, These represent conventional units. Upper and lower bounds of output power; These represent conventional units. Critical rates for climbing uphill and downhill; Indicates conventional units During the scheduling period ; output power; Indicates the length of the scheduling period;

[0044] 3) Constraints on new energy power stations:

[0045]

[0046] in, Indicates new energy power station During the scheduling period The predicted output;

[0047] 4) Constraints of energy storage power stations:

[0048]

[0049]

[0050]

[0051]

[0052]

[0053] in, Indicates energy storage power station During the scheduling period The state of charge; These represent energy storage power stations. During the scheduling period The charging and discharging power and the charging and discharging power loss; , These represent energy storage power stations. Upper and lower bounds of charging and discharging power; Indicates energy storage power station The installed capacity value; , These represent energy storage power stations. Upper and lower bounds of the state of charge;

[0054] 5) Line power constraints:

[0055]

[0056] in, Indicates the line number; Indicates the line Maximum permissible transmission power; They represent the lines respectively. Regarding conventional units New energy power stations Energy storage power station and load nodes The transmission allocation coefficient.

[0057] In a specific embodiment of the present invention, the objective function of the optimization control model in the secondary frequency regulation stage is to minimize the power system frequency deviation and the secondary frequency regulation mileage cost, as expressed below:

[0058]

[0059] in, The number representing the scheduling period. This is a label for the AGC control cycle. This represents the total number of AGC control cycles within a scheduling period. Indicates the scheduling period The sum of control costs for all AGC control cycles within the system; Indicates the scheduling period AGC control cycle The corresponding frequency deviation; The weighting coefficient representing the cost of frequency deviation; Indicates the scheduling period AGC control cycle The corresponding adjustment mileage cost is the sum of the adjustment mileage costs of all units participating in AGC control:

[0060]

[0061] in, Indicates conventional units During the scheduling period AGC control cycle The corresponding AGC control commands; Indicates energy storage power station During the scheduling period AGC control cycle The corresponding AGC control commands; Indicates conventional units The AGC adjustment mileage cost coefficient; Indicates energy storage power station The AGC adjustment mileage cost coefficient;

[0062] Equation (24) is transformed by introducing slack variables:

[0063]

[0064]

[0065]

[0066] in, They are conventional units During the scheduling period AGC control cycle The corresponding positive and negative control instructions slack variables; Energy storage power stations During the scheduling period AGC control cycle The corresponding positive and negative control command relaxation variables, all of which take non-negative values.

[0067] In a specific embodiment of the present invention, the constraints of the optimized control model in the secondary frequency modulation stage include:

[0068] State vector and control input vector constraints:

[0069]

[0070]

[0071]

[0072] in, Indicates the scheduling period AGC control cycle The original state vector; Indicates the scheduling period AGC control cycle The control input vector; Indicates the scheduling period AGC control cycle Corresponding net load change; Indicates the scheduling period AGC control cycle The corresponding frequency deviation, Indicates conventional units During the scheduling period AGC control cycle The corresponding turbine valve opening. Indicates conventional units During the scheduling period AGC control cycle The corresponding output power increment, Indicates energy storage power station During the scheduling period AGC control cycle The corresponding increase in output power; Indicates conventional units During the scheduling period AGC control cycle The corresponding AGC control commands, Indicates energy storage power station During the scheduling period AGC control cycle The corresponding AGC control commands; Represents the original state transition matrix; This represents the original input matrix corresponding to the control input vector; This represents the original input matrix corresponding to the change in net load;

[0073] State-space equation constraints;

[0074] The state vector incorporates the change in state of charge caused by the energy storage power station's participation in AGC. This change in state of charge is related to the AGC control command of the energy storage power station as follows:

[0075]

[0076]

[0077] in, This represents a vector composed of the changes in state of charge caused by all energy storage power stations participating in AGC; Indicates energy storage power station During the scheduling period AGC control cycle The corresponding change in state of charge; Indicates energy storage power station The installed capacity value; This indicates the length of the AGC control cycle and the length of the scheduling period. Satisfying the relation ;

[0078] Vector of change of state of charge Augmented to the original state vector Construct a new state vector This leads to the final state-space equation:

[0079]

[0080]

[0081]

[0082] in, Indicates the scheduling period AGC control cycle The corresponding new state vector; This represents the input matrix corresponding to the change in state of charge. Represents a diagonal matrix. Represents the zero matrix. Represents the identity matrix; This represents the augmented state transition matrix. This represents the augmented input matrix corresponding to the control input vector. This represents the input matrix corresponding to the net load change after augmentation;

[0083] Adjustable space constraints for state and control variables:

[0084]

[0085]

[0086]

[0087]

[0088]

[0089] in, Indicates the maximum permissible frequency deviation of the power system; , These represent conventional units. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; These represent conventional units. Critical rates for climbing uphill and downhill; These represent energy storage power stations. During the scheduling period AGC control cycle The upper and lower bounds of the corresponding change in state of charge are determined by the SOC value at the end of the previous scheduling period. and the charging and discharging power during the current scheduling period and power loss Decide:

[0090]

[0091]

[0092] in, These represent energy storage power stations. Upper and lower bounds of the state of charge. Indicates energy storage power station The installed capacity value.

[0093] In one specific embodiment of the present invention, it further includes:

[0094] The optimized control model for the second frequency modulation stage can be simplified to the following expression:

[0095]

[0096]

[0097]

[0098]

[0099]

[0100]

[0101] Among them, equation (43) corresponds to the objective function equations (23)-(25). Let them represent the cost coefficient matrix and cost coefficient vector respectively; Equation (44) corresponds to the state space equations (33)-(35); Equation (45) corresponds to the relaxation process equations (26)-(27) for the control vector adjustment mileage calculation. , These represent the scheduling periods. AGC control cycle The vector of relaxation variables corresponding to the positive and negative control commands; Equation (46) corresponds to the adjustable range constraints of the state variables (36), (38), and (40). Represents the state variable constraint matrix. Indicates the scheduling period The corresponding state variable constraint vector; Equation (47) corresponds to the adjustable range constraint equation (37) of the control variable. Represents the control variable constraint matrix. Indicates the scheduling period The corresponding control variable constraint vector; Equation (48) corresponds to the ramp constraint equation (39) for the state variable. This represents the state variable ramp constraint matrix. This represents the state variable climbing constraint vector.

[0102] In one specific embodiment of the present invention, it further includes:

[0103] 1) The optimized control model is embedded into the economic dispatch stage optimization model to establish a power generation-reserve joint optimization model that considers the AGC process;

[0104] Among them, after introducing the AGC process, the coupling constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period is considered:

[0105]

[0106]

[0107] Equation (49) represents the coupled ramp constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period for conventional units. This constraint is added to the joint optimization model as an additional constraint. Equation (50) represents the SOC-charge-discharge coupling constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period for energy storage power stations. This constraint replaces the original constraint equation (20).

[0108] The expression for the power generation-reserve joint optimization model considering the AGC process is as follows:

[0109]

[0110]

[0111]

[0112]

[0113] in, Indicates the scheduling period The decision variables corresponding to the economic scheduling stage; Indicates the scheduling period The decision variables corresponding to the second frequency modulation stage; Indicates the scheduling period The corresponding total cost of economic scheduling is expressed as (1)-(10); Indicates the scheduling period The corresponding total cost of secondary frequency regulation is expressed in equations (23)-(25); equation (52) represents the constraints (11)-(22) of the economic scheduling stage. Equation (53) represents the feasible region corresponding to the constraints of the economic scheduling stage; Equation (26)-(42) represents the constraints of the secondary frequency regulation stage. This represents the feasible region corresponding to the constraints in the second frequency regulation stage, which is influenced by the decision variables in the economic scheduling stage. The influence of; Equation (54) represents the coupling constraints of the economic scheduling stage and the secondary frequency regulation stage (49)-(50). , This represents the coefficient matrix under this constraint. This represents the coefficient vector under this constraint.

[0114] 2) Solve the power generation-reserve joint optimization model considering the AGC process established in step 1) to obtain the power generation plan of conventional units, the secondary frequency regulation reserve plan, the power generation plan of new energy power plants, the charging and discharging plan of energy storage power plants, and the secondary frequency regulation reserve plan, etc.

[0115]

[0116] in, Represents the set of result variables; Indicates conventional units During the scheduling period ; output power; , These represent conventional units. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; Indicates new energy power station During the scheduling period ; output power; Indicates energy storage power station During the scheduling period The charging and discharging power; , These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup.

[0117] A second aspect of the present invention provides a power generation-reserve joint optimization device considering the AGC process, comprising:

[0118] The module for constructing the optimization model for the economic scheduling phase is used to build the optimization model for the economic scheduling phase.

[0119] The optimization control model construction module for the secondary frequency regulation stage is used to establish an optimization control model for the secondary frequency regulation stage based on the secondary frequency regulation AGC process in each time period of the economic scheduling stage.

[0120] A power generation-reserve joint optimization model construction module is used to embed the optimization control model of the secondary frequency regulation stage into the optimization model of the economic dispatch stage to obtain a power generation-reserve joint optimization model considering the AGC process.

[0121] The optimization module is used to solve the joint optimization model to obtain the optimization results of the power generation plan and the reserve plan.

[0122] A third aspect of the present invention provides an electronic device comprising:

[0123] At least one processor; and a memory communicatively connected to said at least one processor;

[0124] The memory stores instructions that can be executed by the at least one processor, the instructions being configured to execute the aforementioned power generation-reserve joint optimization method considering the AGC process.

[0125] A fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions for causing the computer to execute the above-described power generation-reserve joint optimization method considering the AGC process.

[0126] The features and beneficial effects of this invention are as follows:

[0127] (1) In the economic scheduling stage, the present invention considers the secondary frequency regulation process with a shorter time scale and embeds the AGC optimization control model as a sub-optimization problem into the economic scheduling optimization model, which can realize the optimal backup decision that meets the AGC control requirements.

[0128] (2) The AGC optimization control model established in this invention takes into account the change in state of charge caused by the participation of the energy storage power station in secondary frequency regulation, and sets reasonable upper and lower bound constraints on the change to ensure the safety of the state of charge of the energy storage power station and avoid overcharging and discharging scenarios.

[0129] (3) By performing linear relaxation on the nonlinear expression, the mathematical essence of the power generation-reserve joint optimization model established by this invention is a quadratic programming problem, which can be solved quickly by calling a commercial solver to meet the real-time calculation needs of the actual operation of the power system. Attached Figure Description

[0130] Figure 1 This is an overall flowchart of a power generation-reserve joint optimization method considering the AGC process according to an embodiment of the present invention. Detailed Implementation

[0131] This invention proposes a power generation-reserve joint optimization method and apparatus that considers the AGC process. The following detailed description, in conjunction with the accompanying drawings and specific embodiments, further illustrates the proposed method.

[0132] The first aspect of this invention proposes a generation-reserve joint optimization method considering the AGC process. This method, during the economic dispatch phase, establishes a generation-reserve joint optimization model based on the load forecast curve with a shorter time scale, comprehensively considering the secondary frequency regulation process within the dispatch interval. Through calculation, it provides generation-reserve decision schemes that meet the secondary frequency regulation requirements, ensuring the reliable and economical operation of the power system. The method includes:

[0133] Establish an optimization model for the economic scheduling phase;

[0134] Based on the secondary frequency regulation AGC process in each time period of the economic scheduling phase, an optimal control model for the secondary frequency regulation phase is established.

[0135] The optimization control model of the secondary frequency regulation stage is embedded into the optimization model of the economic dispatch stage to obtain a joint optimization model of power generation and reserve considering the AGC process.

[0136] Solve the joint optimization model to obtain the optimization results of the power generation plan and the reserve plan.

[0137] In a specific embodiment of the present invention, the overall process of the power generation-reserve joint optimization method considering the AGC process is shown in Figure 1, including the following steps:

[0138] 1) Establish an optimization model for the economic scheduling stage. The specific steps are as follows:

[0139] 1-1) Establish the objective function of the optimization model for the economic scheduling stage:

[0140] In this embodiment, economic dispatch is typically initiated by the power system control center every 5 or 15 minutes. Based on load and predicted power from new energy sources, it calculates and provides generation plans for various types of generating units and secondary frequency regulation reserve plans for AGC units. The objective function expression of the optimization model for the economic dispatch phase is as follows:

[0141]

[0142] In this embodiment, the objective of the economic dispatch phase is to minimize power generation and reserve costs. These are the scheduling period number and the period set, respectively; These are the designations and unit groups for conventional generating units, respectively. These are the designations and collections of new energy power stations, respectively. These are the designation of the energy storage power station and the group of power stations, respectively. This indicates the economic scheduling phase during the scheduling period. Total cost; , These represent conventional units. During the scheduling period Fuel costs and secondary frequency regulation backup costs; Indicates new energy power station During the scheduling period The cost of abandoning electricity; , These represent energy storage power stations. During the scheduling period The cost of charging and discharging losses and the cost of secondary frequency regulation backup.

[0143] The fuel cost expression for conventional generating units is as follows:

[0144]

[0145] in, Indicates conventional units During the scheduling period Output power (power generation base point). These represent conventional units. The coefficients of the quadratic, linear, and constant terms of fuel cost.

[0146] The formula for the reserve cost of secondary frequency regulation of conventional generating units is as follows:

[0147]

[0148] in, These represent conventional units. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; Indicates conventional units The secondary frequency regulation backup cost coefficient;

[0149] The expression for the cost of curtailment at renewable energy power plants is as follows:

[0150]

[0151] in, Indicates new energy power station During the scheduling period ; output power; Indicates new energy power station During the scheduling period The predicted power output can be obtained from the ultra-short-term power prediction of new energy sources; Indicates new energy power station The cost coefficient of abandoned electricity.

[0152] The expression for the charging and discharging loss cost of an energy storage power station is as follows:

[0153]

[0154] in, Indicates energy storage power station During the scheduling period The charging and discharging power loss, Indicates energy storage power station The charging and discharging loss cost coefficient. Charging and discharging power loss can be expressed as the larger of the charging loss and the discharging loss:

[0155]

[0156] in, These represent energy storage power stations. During the scheduling period The charging power loss and discharging power loss are expressed as follows:

[0157]

[0158]

[0159] in, Indicates energy storage power station During the scheduling period The charging and discharging power, Indicates discharge. Indicates charging; These represent energy storage power stations. The charging efficiency and discharging efficiency.

[0160] Furthermore, equation (6) contains a maximum value term, causing the optimization problem to be non-convex. Therefore, equation (6) can be relaxed and transformed into equation (9):

[0161]

[0162] The expression for the backup cost of secondary frequency regulation in an energy storage power station is as follows:

[0163]

[0164] in, These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup. Indicates energy storage power station The secondary frequency regulation backup cost coefficient.

[0165] 1-2) Establish the constraints for the optimization model in the economic scheduling stage, including:

[0166] 1-2-1) Power balance constraints:

[0167]

[0168] in, These are the label and node set of the load node, respectively; Indicates load node During the scheduling period The load power can be obtained from ultra-short-term load power prediction. , , These represent conventional units. New energy power stations Energy storage power station During the scheduling period . output power.

[0169] 1-2-2) Conventional unit constraints:

[0170]

[0171]

[0172]

[0173]

[0174] Conventional unit constraints include power upper and lower bound constraints (12), secondary frequency regulation reserve constraints (13)-(14), and ramping constraints (15). These represent conventional units. Upper and lower bounds of output power; These represent conventional units. Critical rates for climbing uphill and downhill. Indicates conventional units During the scheduling period . output power. This indicates the length of the scheduling period, typically 5 or 15 minutes.

[0175] 1-2-3) Constraints on new energy power stations:

[0176]

[0177] The constraint on renewable energy power plants requires that their output power not exceed the predicted power for the specified dispatch period. Specifically, Indicates new energy power station During the scheduling period The predicted power output can be obtained from the ultra-short-term power prediction of new energy sources.

[0178] 1-2-4) Constraints of energy storage power stations:

[0179]

[0180]

[0181]

[0182]

[0183]

[0184] In this embodiment, the constraints of the energy storage power station include charge and discharge power constraints (17), secondary frequency regulation reserve constraints (18)-(19), state of charge-charge and discharge coupling constraints (20), and state of charge constraints (21). Indicates energy storage power station During the scheduling period The state of charge (also known as SOC); These represent energy storage power stations. During the scheduling period The charging and discharging power and the charging and discharging power loss; , These represent energy storage power stations. Upper and lower bounds of charging and discharging power; Indicates energy storage power station The installed capacity value; , These represent energy storage power stations. Upper and lower bounds of the charged state.

[0185] 1-2-5) Line power constraints:

[0186]

[0187] Line power constraints require that the bidirectional power flow of the line does not exceed its upper limit. Among these constraints, Indicates the line number; Indicates the line Maximum permissible transmission power. They represent the lines respectively. Regarding conventional units New energy power stations Energy storage power station and load nodes The transmission allocation coefficient is calculated using a DC power flow model.

[0188] 2) Establish an optimized control model for the secondary frequency modulation stage.

[0189] Economic dispatch optimizes the power base point of various generators to meet long-term load demands with the goal of achieving optimal economic efficiency. For power imbalance within a dispatch period (5 or 15 minutes), secondary frequency regulation (AGC) is used for control and compensation. Secondary frequency regulation is typically initiated by the control center every 2-10 seconds, calculating the secondary frequency regulation command for AGC resources based on the frequency deviation obtained from measurements and the secondary frequency regulation reserve capacity of AGC resources.

[0190] 2-1) Establish the objective function of the optimized control model for the secondary frequency modulation stage.

[0191] In this embodiment, an optimized control model is used in the secondary frequency regulation (AGC) stage, with the objective of minimizing the power system frequency deviation and the cost of secondary frequency regulation mileage.

[0192]

[0193] in, The number representing the scheduling period. This is a label for the AGC control cycle. This represents the total number of AGC control cycles within a scheduling period. Indicates the scheduling period The sum of control costs for all AGC control cycles within the system. Indicates the scheduling period AGC control cycle The corresponding frequency deviation; The weighting coefficient represents the cost of frequency deviation. Indicates the scheduling period AGC control cycle The corresponding adjustment mileage cost is the sum of the adjustment mileage costs of all units participating in AGC control (including conventional units and energy storage power stations):

[0194]

[0195] in, These are the designations and unit groups for conventional generating units, respectively. These are the designation of the energy storage power station and the group of power stations, respectively. Indicates conventional units During the scheduling period AGC control cycle The corresponding AGC control commands; Indicates energy storage power station During the scheduling period AGC control cycle The corresponding AGC control commands; Indicates conventional units The AGC adjustment mileage cost coefficient; Indicates energy storage power station The AGC adjustment mileage cost coefficient.

[0196] Furthermore, the adjustment mileage cost expression (24) contains an absolute value term, causing the optimization problem to be non-convex. A slack variable can be introduced for an equivalent transformation:

[0197]

[0198]

[0199]

[0200] in, They are conventional units During the scheduling period AGC control cycle The corresponding positive and negative control instructions slack variables; Energy storage power stations During the scheduling period AGC control cycle The corresponding positive and negative control instruction slack variables. All of the above slack variables take non-negative values ​​and satisfy the relationship (26)-(27) with the original variables.

[0201] 2-2) Establish the constraints of the optimized control model for the secondary frequency modulation stage.

[0202] In this embodiment, the constraints of the secondary frequency regulation optimization control model include the state-space equation of AGC and the upper and lower bound constraints of each variable. The state variables in the state vector include the system frequency deviation and the output power increment of each generator, while the input vector includes the AGC control commands for each generator set.

[0203]

[0204]

[0205]

[0206] in, Indicates the scheduling period AGC control cycle The original state vector; Indicates the scheduling period AGC control cycle The control input vector; Indicates the scheduling period AGC control cycle The corresponding net load change can be obtained from ultra-short-term load forecasting. Among the elements of the original state vector, Indicates the scheduling period AGC control cycle The corresponding frequency deviation, Indicates conventional units During the scheduling period AGC control cycle The corresponding turbine valve opening. Indicates conventional units During the scheduling period AGC control cycle The corresponding output power increment, Indicates energy storage power station During the scheduling period AGC control cycle The corresponding output power increment. In the elements constituting the control input vector, Indicates conventional units During the scheduling period AGC control cycle The corresponding AGC control commands, Indicates energy storage power station During the scheduling period AGC control cycle The corresponding AGC control instructions. The original state transition matrix can be calculated based on the frequency regulation model and parameters of each generator. This represents the original input matrix corresponding to the control input vector, which can also be calculated based on the frequency regulation model and parameters of each generator. The original input matrix representing the net load change can be calculated based on power system parameters.

[0207] Furthermore, the method described in this embodiment introduces the change in state of charge of the energy storage power station caused by its participation in AGC into the state vector. This change in state of charge is related to the AGC control command of the energy storage power station as follows:

[0208]

[0209]

[0210] in, This represents a vector consisting of the changes in state of charge caused by all energy storage power stations participating in AGC. Indicates energy storage power station During the scheduling period AGC control cycle The corresponding change in state of charge. Indicates energy storage power station The installed capacity value. This indicates the length of the AGC control cycle, typically 2-10 seconds, and is related to the length of the scheduling period. Satisfying the relation .

[0211] Vector of change of state of charge Augmented to the original state vector New state vectors can be constructed. This leads to the final state-space equation:

[0212]

[0213]

[0214]

[0215] in, Indicates the scheduling period AGC control cycle The corresponding new state vector (hereinafter referred to as state vector). The input matrix corresponding to the change in state of charge can be calculated using equation (35). Represents a diagonal matrix. Represents the zero matrix. Represents the identity matrix. This represents the augmented state transition matrix. This represents the augmented input matrix corresponding to the control input vector. This represents the input matrix corresponding to the change in net load after augmentation.

[0216] In addition to the state-space equations, the constraints of this optimal control model also include the adjustable space of state variables (frequency deviation, generator output increment, and energy storage SOC) and control variables (AGC commands), specifically including:

[0217]

[0218]

[0219]

[0220]

[0221]

[0222] Among them, Equation (36) is the frequency deviation constraint, Equation (37) is the adjustable range constraint of AGC control command, Equation (38) is the adjustable range constraint of output power increment, Equation (39) is the ramp constraint of conventional unit, and Equation (40) is the SOC constraint of energy storage power station. This indicates the maximum permissible frequency deviation of the power system, specified by the dispatch center. These represent conventional units. During the scheduling period The upward and downward secondary frequency regulation reserves are decision variables in the economic dispatch phase, and in the AGC phase, they serve as the adjustable range for conventional units to participate in secondary frequency regulation. These represent energy storage power stations. During the scheduling period The upward and downward secondary frequency regulation reserves are also decision variables in the economic dispatch phase, and in the AGC phase, they serve as the adjustable range for energy storage power stations to participate in secondary frequency regulation. These represent conventional units. Critical rates for climbing uphill and downhill. These represent energy storage power stations. During the scheduling period AGC control cycle The corresponding upper and lower bounds of the change in state of charge are determined by the SOC value at the end of the previous scheduling period. and the charging and discharging power during the current scheduling period and power loss Decide:

[0223]

[0224]

[0225] in, These represent energy storage power stations. Upper and lower bounds of the state of charge. Indicates energy storage power station The installed capacity value.

[0226] 2-3) Based on the results of steps 2-1) and 2-2), the optimized control model can be simplified to the following expression:

[0227]

[0228]

[0229]

[0230]

[0231]

[0232]

[0233] Among them, equation (43) corresponds to the objective functions (23)-(25). Let represent the cost coefficient matrix and cost coefficient vector, respectively. Equation (44) corresponds to the state-space equations (33)-(35). Equation (45) corresponds to the relaxation process equations (26)-(27) for calculating the control vector adjustment mileage. , These represent the scheduling periods. AGC control cycle The vector consists of the corresponding positive and negative control command relaxation variables. Equation (46) corresponds to the adjustable range constraints of state variables (36), (38), and (40). Represents the state variable constraint matrix. Indicates the scheduling period The corresponding state variable constraint vector. Equation (47) corresponds to the adjustable range constraint equation (37) for the control variable. Represents the control variable constraint matrix. Indicates the scheduling period The corresponding control variable constraint vector. Equation (48) corresponds to the ramp constraint equation (39) for the state variables. This represents the state variable ramp constraint matrix. This represents the state variable climbing constraint vector.

[0234] 3) Based on the results of steps 1) and 2), construct and solve a joint optimization model for power generation and reserve considering the AGC process to obtain the optimization results for the power generation plan and reserve plan; the specific steps are as follows:

[0235] 2-1) Based on the results of steps 1) and 2), construct a joint optimization model for power generation and standby considering the AGC process.

[0236] This embodiment embeds the optimized control model established in step 2) into the economic dispatch stage optimization model established in step 1), creating a joint optimization model for generation and reserve that considers the AGC process. Compared with traditional methods, the joint optimization model established by the method described in this embodiment considers the AGC process with a more refined time scale in the economic dispatch stage, thus the calculated generation and reserve decision scheme is more reasonable and reliable.

[0237] Since economic scheduling is a multi-time-period optimization decision problem, after introducing the AGC process, it is necessary to consider the coupling constraint between the end time of the AGC process of the previous scheduling period and the start time of the next scheduling period:

[0238]

[0239]

[0240] Equation (49) represents the coupled ramp constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period for conventional units. This constraint is added to the joint optimization model as an additional constraint. Equation (50) represents the SOC-charge-discharge coupling constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period for energy storage power stations. This constraint replaces the original constraint Equation (20).

[0241] Finally, the established power generation-reserve joint optimization model considering the AGC process can be simplified to the following expression:

[0242]

[0243]

[0244]

[0245]

[0246] in, Indicates the scheduling period The decision variables corresponding to the economic scheduling stage; Indicates the scheduling period The decision variables corresponding to the second frequency modulation stage; Indicates the scheduling period The corresponding total cost of economic scheduling is expressed as (1)-(10); Indicates the scheduling period The corresponding total cost of secondary frequency regulation is expressed as equations (23)-(25); equation (52) represents the constraint conditions (11)-(22) of the economic scheduling stage. Equation (53) represents the feasible region corresponding to the constraints of the economic scheduling stage; Equation (26)-(42) represents the constraints of the secondary frequency regulation stage. This represents the feasible region corresponding to the constraints in the second frequency regulation stage, which is influenced by the decision variables in the economic scheduling stage. The influence of; Equation (54) represents the coupling constraints of the economic scheduling stage and the secondary frequency regulation stage (49)-(50). , This represents the coefficient matrix under this constraint. This represents the coefficient vector under this constraint.

[0247] 3-2) Solve the combined optimization model of power generation and standby considering the AGC process established in step 3-1).

[0248] The power generation-reserve joint optimization model considering the AGC process established in this embodiment is mathematically a quadratic programming problem, which can be solved quickly using commercial solvers (such as Gurobi, Cplex, etc.). It should be noted that this embodiment embeds the AGC process into the economic dispatch stage optimization model to obtain a reliable and economical power generation plan and secondary frequency regulation reserve decision scheme. The AGC control commands calculated in the AGC stage will not be applied to actual operation; they only serve as auxiliary decision-making tools for the economic dispatch stage. In practical applications, the AGC stage needs to perform control calculations based on real-time measurement data to eliminate frequency deviations.

[0249] By solving the established power generation-reserve joint optimization model that considers the AGC process, we can obtain the power generation plan for conventional units, the secondary frequency regulation reserve plan, the power generation plan for new energy power plants, the charging and discharging plan for energy storage power plants, and the secondary frequency regulation reserve plan, etc.

[0250]

[0251] in, Represents the set of result variables; Indicates conventional units During the scheduling period ; output power; These represent conventional units. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; Indicates new energy power station During the scheduling period ; output power; Indicates energy storage power station During the scheduling period The charging and discharging power; These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup.

[0252] To achieve the above embodiments, a second aspect of the present invention proposes a power generation-reserve joint optimization device considering the AGC process, comprising:

[0253] The module for constructing the optimization model for the economic scheduling phase is used to build the optimization model for the economic scheduling phase.

[0254] The optimization control model construction module for the secondary frequency regulation stage is used to establish an optimization control model for the secondary frequency regulation stage based on the secondary frequency regulation AGC process in each time period of the economic scheduling stage.

[0255] A power generation-reserve joint optimization model construction module is used to embed the optimization control model of the secondary frequency regulation stage into the optimization model of the economic dispatch stage to obtain a power generation-reserve joint optimization model considering the AGC process.

[0256] The optimization module is used to solve the joint optimization model to obtain the optimization results of the power generation plan and the reserve plan.

[0257] In a specific embodiment of the present invention, the objective function of the economic dispatch phase optimization model is to minimize the generation and reserve costs, as expressed below:

[0258]

[0259] in, These are the scheduling period number and the period set, respectively; These are the designations and unit groups for conventional generating units, respectively. These are the designations and collections of new energy power stations, respectively. These are the designation of the energy storage power station and the group of power stations, respectively. This indicates the economic scheduling phase during the scheduling period. Total cost; , These represent conventional units. During the scheduling period Fuel costs and secondary frequency regulation backup costs; Indicates new energy power station During the scheduling period The cost of abandoning electricity; , These represent energy storage power stations. During the scheduling period The cost of charging and discharging losses and the cost of secondary frequency modulation backup;

[0260] The fuel cost expression for conventional generating units is as follows:

[0261]

[0262] in, Indicates conventional units During the scheduling period ; output power; These represent conventional units. Coefficients of the quadratic, linear, and constant terms of fuel cost;

[0263] The formula for the reserve cost of secondary frequency regulation of conventional generating units is as follows:

[0264]

[0265] in, These represent conventional units. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; Indicates conventional units The secondary frequency regulation backup cost coefficient;

[0266] The expression for the cost of curtailment at renewable energy power plants is as follows:

[0267]

[0268] in, Indicates new energy power station During the scheduling period ; output power; Indicates new energy power station During the scheduling period The predicted output; Indicates new energy power station The cost coefficient of abandoned electricity;

[0269] The expression for the charging and discharging loss cost of an energy storage power station is as follows:

[0270]

[0271] in, Indicates energy storage power station During the scheduling period The charging and discharging power loss, Indicates energy storage power station The charging and discharging loss cost coefficient; the charging and discharging power loss is expressed as the larger of the charging loss and the discharging loss:

[0272]

[0273] in, These represent energy storage power stations. During the scheduling period Charging power loss and discharging power loss:

[0274]

[0275]

[0276] in, Indicates energy storage power station During the scheduling period The charging and discharging power, Indicates discharge. Indicates charging; These represent energy storage power stations. The charging efficiency and discharging efficiency;

[0277] Relax equation (6) to transform it into equation (9):

[0278]

[0279] The expression for the backup cost of secondary frequency regulation in an energy storage power station is as follows:

[0280]

[0281] in, These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; Indicates energy storage power station The secondary frequency regulation backup cost coefficient.

[0282] In a specific embodiment of the present invention, the constraints of the economic scheduling phase optimization model include:

[0283] 1) Power balance constraints:

[0284]

[0285] in, These are the label and node set of the load node, respectively; Indicates load node During the scheduling period The load power; These represent conventional units. New energy power stations Energy storage power station During the scheduling period ; output power;

[0286] 2) Constraints of conventional units:

[0287]

[0288]

[0289]

[0290]

[0291] in, These represent conventional units. Upper and lower bounds of output power; These represent conventional units. Critical rates for climbing uphill and downhill; Indicates conventional units During the scheduling period ; output power; Indicates the length of the scheduling period;

[0292] 3) Constraints on new energy power stations:

[0293]

[0294] in, Indicates new energy power station During the scheduling period The predicted output;

[0295] 4) Constraints of energy storage power stations:

[0296]

[0297]

[0298]

[0299]

[0300]

[0301] in, Indicates energy storage power station During the scheduling period The state of charge; These represent energy storage power stations. During the scheduling period The charging and discharging power and the charging and discharging power loss; , These represent energy storage power stations. Upper and lower bounds of charging and discharging power; Indicates energy storage power station The installed capacity value; , These represent energy storage power stations. Upper and lower bounds of the state of charge;

[0302] 5) Line power constraints:

[0303]

[0304] in, Indicates the line number; Indicates the line Maximum permissible transmission power; They represent the lines respectively. Regarding conventional units New energy power stations Energy storage power station and load nodes The transmission allocation coefficient.

[0305] In a specific embodiment of the present invention, the objective function of the optimization control model in the secondary frequency regulation stage is to minimize the power system frequency deviation and the secondary frequency regulation mileage cost, as expressed below:

[0306]

[0307] in, The number representing the scheduling period. This is a label for the AGC control cycle. This represents the total number of AGC control cycles within a scheduling period. Indicates the scheduling period The sum of control costs for all AGC control cycles within the system; Indicates the scheduling period AGC control cycle The corresponding frequency deviation; The weighting coefficient representing the cost of frequency deviation; Indicates the scheduling period AGC control cycle The corresponding adjustment mileage cost is the sum of the adjustment mileage costs of all units participating in AGC control:

[0308]

[0309] in, Indicates conventional units During the scheduling period AGC control cycle The corresponding AGC control commands; Indicates energy storage power station During the scheduling period AGC control cycle The corresponding AGC control commands; Indicates conventional units The AGC adjustment mileage cost coefficient; Indicates energy storage power station The AGC adjustment mileage cost coefficient;

[0310] Equation (24) is transformed by introducing slack variables:

[0311]

[0312]

[0313]

[0314] in, They are conventional units During the scheduling period AGC control cycle The corresponding positive and negative control instructions slack variables; Energy storage power stations During the scheduling period AGC control cycle The corresponding positive and negative control command relaxation variables, all of which take non-negative values.

[0315] In a specific embodiment of the present invention, the constraints of the optimized control model in the secondary frequency modulation stage include:

[0316] State vector and control input vector constraints:

[0317]

[0318]

[0319]

[0320] in, Indicates the scheduling period AGC control cycle The original state vector; Indicates the scheduling period AGC control cycle The control input vector; Indicates the scheduling period AGC control cycle Corresponding net load change; Indicates the scheduling period AGC control cycle The corresponding frequency deviation, Indicates conventional units During the scheduling period AGC control cycle The corresponding turbine valve opening. Indicates conventional units During the scheduling period AGC control cycle The corresponding output power increment, Indicates energy storage power station During the scheduling period AGC control cycle The corresponding increase in output power; Indicates conventional units During the scheduling period AGC control cycle The corresponding AGC control commands, Indicates energy storage power station During the scheduling period AGC control cycle The corresponding AGC control commands; Represents the original state transition matrix; This represents the original input matrix corresponding to the control input vector; This represents the original input matrix corresponding to the change in net load;

[0321] State-space equation constraints;

[0322] The state vector incorporates the change in state of charge caused by the energy storage power station's participation in AGC. This change in state of charge is related to the AGC control command of the energy storage power station as follows:

[0323]

[0324]

[0325] in, This represents a vector composed of the changes in state of charge caused by all energy storage power stations participating in AGC; Indicates energy storage power station During the scheduling period AGC control cycle The corresponding change in state of charge; Indicates energy storage power station The installed capacity value; This indicates the length of the AGC control cycle and the length of the scheduling period. Satisfying the relation ;

[0326] Vector of change of state of charge Augmented to the original state vector Construct a new state vector This leads to the final state-space equation:

[0327]

[0328]

[0329]

[0330] in, Indicates the scheduling period AGC control cycle The corresponding new state vector; This represents the input matrix corresponding to the change in state of charge. Represents a diagonal matrix. Represents the zero matrix. Represents the identity matrix; This represents the augmented state transition matrix. This represents the augmented input matrix corresponding to the control input vector. This represents the input matrix corresponding to the net load change after augmentation;

[0331] Adjustable space constraints for state and control variables:

[0332]

[0333]

[0334]

[0335]

[0336]

[0337] in, Indicates the maximum permissible frequency deviation of the power system; , These represent conventional units. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; These represent conventional units. Critical rates for climbing uphill and downhill; These represent energy storage power stations. During the scheduling period AGC control cycle The upper and lower bounds of the corresponding change in state of charge are determined by the SOC value at the end of the previous scheduling period. and the charging and discharging power during the current scheduling period and power loss Decide:

[0338]

[0339]

[0340] in, These represent energy storage power stations. Upper and lower bounds of the state of charge. Indicates energy storage power station The installed capacity value.

[0341] In one specific embodiment of the present invention, it further includes:

[0342] The optimized control model for the second frequency modulation stage can be simplified to the following expression:

[0343]

[0344]

[0345]

[0346]

[0347]

[0348]

[0349] Among them, equation (43) corresponds to the objective function equations (23)-(25). Let them represent the cost coefficient matrix and cost coefficient vector respectively; Equation (44) corresponds to the state space equations (33)-(35); Equation (45) corresponds to the relaxation process equations (26)-(27) for the control vector adjustment mileage calculation. , These represent the scheduling periods. AGC control cycle The vector of relaxation variables corresponding to the positive and negative control commands; Equation (46) corresponds to the adjustable range constraints of the state variables (36), (38), and (40). Represents the state variable constraint matrix. Indicates the scheduling period The corresponding state variable constraint vector; Equation (47) corresponds to the adjustable range constraint equation (37) of the control variable. Represents the control variable constraint matrix. Indicates the scheduling period The corresponding control variable constraint vector; Equation (48) corresponds to the ramp constraint equation (39) for the state variable. This represents the state variable ramp constraint matrix. This represents the state variable climbing constraint vector.

[0350] In one specific embodiment of the present invention, it further includes:

[0351] 1) The optimized control model is embedded into the economic dispatch stage optimization model to establish a power generation-reserve joint optimization model that considers the AGC process;

[0352] Among them, after introducing the AGC process, the coupling constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period is considered:

[0353]

[0354]

[0355] Equation (49) represents the coupled ramp constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period for conventional units. This constraint is added to the joint optimization model as an additional constraint. Equation (50) represents the SOC-charge-discharge coupling constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period for energy storage power stations. This constraint replaces the original constraint equation (20).

[0356] The expression for the power generation-reserve joint optimization model considering the AGC process is as follows:

[0357]

[0358]

[0359]

[0360]

[0361] in, Indicates the scheduling period The decision variables corresponding to the economic scheduling stage; Indicates the scheduling period The decision variables corresponding to the second frequency modulation stage; Indicates the scheduling period The corresponding total cost of economic scheduling is expressed as (1)-(10); Indicates the scheduling period The corresponding total cost of secondary frequency regulation is expressed in equations (23)-(25); equation (52) represents the constraints (11)-(22) of the economic scheduling stage. Equation (53) represents the feasible region corresponding to the constraints of the economic scheduling stage; Equation (26)-(42) represents the constraints of the secondary frequency regulation stage. This represents the feasible region corresponding to the constraints in the second frequency regulation stage, which is influenced by the decision variables in the economic scheduling stage. The influence of; Equation (54) represents the coupling constraints of the economic scheduling stage and the secondary frequency regulation stage (49)-(50). , This represents the coefficient matrix under this constraint. This represents the coefficient vector under this constraint.

[0362] 2) Solve the power generation-reserve joint optimization model considering the AGC process established in step 1) to obtain the power generation plan of conventional units, the secondary frequency regulation reserve plan, the power generation plan of new energy power plants, the charging and discharging plan of energy storage power plants, and the secondary frequency regulation reserve plan, etc.

[0363]

[0364] in, Represents the set of result variables; Indicates conventional units During the scheduling period ; output power; , These represent conventional units. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; Indicates new energy power station During the scheduling period ; output power; Indicates energy storage power station During the scheduling period The charging and discharging power; , These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup.

[0365] This allows for a more refined secondary frequency regulation process that considers the time scale during the economic dispatch phase. By embedding the AGC control optimization model into the economic dispatch optimization model, a more reasonable and reliable power generation plan and secondary frequency regulation reserve plan can be obtained through calculation, thereby guiding dispatchers in making dispatch decisions.

[0366] To implement the above embodiments, a third aspect of the present invention provides an electronic device, comprising:

[0367] At least one processor; and a memory communicatively connected to said at least one processor;

[0368] The memory stores instructions that can be executed by the at least one processor, the instructions being configured to execute the aforementioned power generation-reserve joint optimization method considering the AGC process.

[0369] To implement the above embodiments, a fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions for causing the computer to execute the above-described power generation-reserve joint optimization method considering the AGC process.

[0370] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0371] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to perform a power generation-reserve joint optimization method considering the AGC process according to the above embodiments.

[0372] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0373] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0374] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0375] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the function involved, as will be understood by those skilled in the art to which embodiments of this application pertain.

[0376] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0377] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0378] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0379] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0380] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A joint optimization method for power generation and reserve considering the AGC process, characterized in that, include: Establish an optimization model for the economic scheduling phase; Based on the secondary frequency regulation AGC process in each time period of the economic scheduling phase, an optimal control model for the secondary frequency regulation phase is established. The optimization control model of the secondary frequency regulation stage is embedded into the optimization model of the economic dispatch stage to obtain a joint optimization model of power generation and reserve considering the AGC process. Solve the joint optimization model to obtain the optimization results of the power generation plan and the reserve plan.

2. The method according to claim 1, characterized in that, The objective function of the optimization model in the economic dispatch phase is to minimize the generation and reserve costs, as expressed below: in, These are the label and set of time periods, respectively; These are the designations and unit groups for conventional generating units, respectively. These are the designations and collections of new energy power stations, respectively. These are the designation of the energy storage power station and the group of power stations, respectively. This indicates the economic scheduling phase during the scheduling period. Total cost; , These represent conventional units. During the scheduling period Fuel costs and secondary frequency regulation backup costs; Indicates new energy power station During the scheduling period The cost of abandoning electricity; , These represent energy storage power stations. During the scheduling period The cost of charging and discharging losses and the cost of secondary frequency modulation backup; The fuel cost expression for conventional generating units is as follows: in, Indicates conventional units During the scheduling period ; output power; These represent conventional units. Coefficients of the quadratic, linear, and constant terms of fuel cost; The formula for the reserve cost of secondary frequency regulation of conventional generating units is as follows: in, These represent conventional units. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; Indicates conventional units The secondary frequency regulation backup cost coefficient; The expression for the cost of curtailment at renewable energy power plants is as follows: in, Indicates new energy power station During the scheduling period ; output power; Indicates new energy power station During the scheduling period The predicted output; Indicates new energy power station The cost coefficient of abandoned electricity; The expression for the charging and discharging loss cost of an energy storage power station is as follows: in, Indicates energy storage power station During the scheduling period The charging and discharging power loss, Indicates energy storage power station The charging and discharging loss cost coefficient; the charging and discharging power loss is expressed as the larger of the charging loss and the discharging loss: in, These represent energy storage power stations. During the scheduling period Charging power loss and discharging power loss: in, Indicates energy storage power station During the scheduling period The charging and discharging power, Indicates discharge. Indicates charging; These represent energy storage power stations. The charging efficiency and discharging efficiency; Relax equation (6) to transform it into equation (9): The expression for the backup cost of secondary frequency regulation in an energy storage power station is as follows: in, These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; Indicates energy storage power station The secondary frequency regulation backup cost coefficient.

3. The method according to claim 2, characterized in that, The constraints of the optimization model for the economic scheduling phase include: 1) Power balance constraints: in, These are the label and node set of the load node, respectively; Indicates load node During the scheduling period The load power; These represent conventional units. New energy power stations Energy storage power station During the scheduling period ; output power; 2) Constraints of conventional units: in, These represent conventional units. Upper and lower bounds of output power; These represent conventional units. Critical rates for climbing uphill and downhill; Indicates conventional units During the scheduling period ; output power; Indicates the length of the scheduling period; 3) Constraints on new energy power stations: in, Indicates new energy power station During the scheduling period The predicted output; 4) Constraints of energy storage power stations: in, Indicates energy storage power station During the scheduling period The state of charge; These represent energy storage power stations. During the scheduling period The charging and discharging power and charging and discharging power loss; , These represent energy storage power stations. Upper and lower bounds of charging and discharging power; Indicates energy storage power station The installed capacity value; , These represent energy storage power stations. Upper and lower bounds of the state of charge; 5) Line power constraints: in, Indicates the line number; Indicates the line Maximum permissible transmission power; They represent the lines respectively. Regarding conventional units New energy power stations Energy storage power station and load nodes The transmission allocation coefficient.

4. The method according to claim 3, characterized in that, The objective function of the optimization control model in the secondary frequency regulation stage is to minimize the power system frequency deviation and the cost of secondary frequency regulation mileage, as expressed below: in, The number representing the scheduling period. This is a label for the AGC control cycle. This represents the total number of AGC control cycles within a scheduling period. Indicates the scheduling period The sum of control costs for all AGC control cycles within the system; Indicates the scheduling period AGC control cycle The corresponding frequency deviation; The weighting coefficient representing the cost of frequency deviation; Indicates the scheduling period AGC control cycle The corresponding adjustment mileage cost is the sum of the adjustment mileage costs of all units participating in AGC control: in, Indicates conventional units During the scheduling period AGC control cycle The corresponding AGC control commands; Indicates energy storage power station During the scheduling period AGC control cycle The corresponding AGC control commands; Indicates conventional units The AGC adjustment mileage cost coefficient; Indicates energy storage power station The AGC adjustment mileage cost coefficient; Equation (24) is transformed by introducing slack variables: in, They are conventional units During the scheduling period AGC control cycle The corresponding positive and negative control instructions slack variables; Energy storage power stations During the scheduling period AGC control cycle The corresponding positive and negative control command relaxation variables, all of which take non-negative values.

5. The method according to claim 4, characterized in that, The constraints of the optimized control model in the secondary frequency modulation stage include: State vector and control input vector constraints: in, Indicates the scheduling period AGC control cycle The original state vector; Indicates the scheduling period AGC control cycle The control input vector; Indicates the scheduling period AGC control cycle Corresponding net load change; Indicates the scheduling period AGC control cycle The corresponding frequency deviation, Indicates conventional units During the scheduling period AGC control cycle The corresponding turbine valve opening, Indicates conventional units During the scheduling period AGC control cycle The corresponding output power increment, Indicates energy storage power station During the scheduling period AGC control cycle The corresponding output power increment; Indicates conventional units During the scheduling period AGC control cycle The corresponding AGC control commands, Indicates energy storage power station During the scheduling period AGC control cycle The corresponding AGC control commands; Represents the original state transition matrix; This represents the original input matrix corresponding to the control input vector; This represents the original input matrix corresponding to the change in net load; State-space equation constraints; The state vector incorporates the change in state of charge caused by the energy storage power station's participation in AGC. This change in state of charge is related to the AGC control command of the energy storage power station as follows: in, This represents a vector composed of the changes in state of charge caused by all energy storage power stations participating in AGC; Indicates energy storage power station During the scheduling period AGC control cycle The corresponding change in state of charge; Indicates energy storage power station The installed capacity value; This indicates the length of the AGC control cycle and the length of the scheduling period. Satisfying the relation ; Vector of change of state of charge Augmented to the original state vector Construct a new state vector This leads to the final state-space equation: in, Indicates the scheduling period AGC control cycle The corresponding new state vector; This represents the input matrix corresponding to the change in state of charge. Represents a diagonal matrix. Represents the zero matrix. Represents the identity matrix; This represents the augmented state transition matrix. This represents the augmented input matrix corresponding to the control input vector. This represents the input matrix corresponding to the net load change after augmentation; Adjustable space constraints for state and control variables: in, Indicates the maximum permissible frequency deviation of the power system; , These represent conventional units. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; These represent conventional units. Critical rates for climbing uphill and downhill; These represent energy storage power stations. During the scheduling period AGC control cycle The upper and lower bounds of the corresponding change in state of charge are determined by the SOC value at the end of the previous scheduling period. and the charging and discharging power during the current scheduling period and power loss Decide: in, These represent energy storage power stations. Upper and lower bounds of the state of charge. Indicates energy storage power station The installed capacity value.

6. The method according to claim 5, characterized in that, Also includes: The optimized control model for the second frequency modulation stage can be simplified to the following expression: Among them, equation (43) corresponds to the objective function equations (23)-(25). Let them represent the cost coefficient matrix and cost coefficient vector respectively; Equation (44) corresponds to the state space equations (33)-(35); Equation (45) corresponds to the relaxation process equations (26)-(27) for the control vector adjustment mileage calculation. , These represent the scheduling periods. AGC control cycle The vector composed of the corresponding positive and negative control command relaxation variables; Equation (46) corresponds to the adjustable range constraints of the state variables (36), (38), and (40). Represents the state variable constraint matrix. Indicates the scheduling period The corresponding state variable constraint vector; Equation (47) corresponds to the adjustable range constraint equation (37) of the control variable. Represents the control variable constraint matrix. Indicates the scheduling period The corresponding control variable constraint vector; Equation (48) corresponds to the ramp constraint equation (39) for the state variable. This represents the state variable ramp constraint matrix. This represents the state variable, the hill-climbing constraint vector.

7. The method according to claim 6, characterized in that, Also includes: 1) The optimized control model is embedded into the economic dispatch stage optimization model to establish a power generation-reserve joint optimization model that considers the AGC process; Among them, after introducing the AGC process, the coupling constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period is considered: Equation (49) represents the coupled ramp constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period for conventional units. This constraint is added to the joint optimization model as an additional constraint. Equation (50) represents the SOC-charge-discharge coupling constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period for energy storage power stations. This constraint replaces the original constraint equation (20). The expression for the power generation-reserve joint optimization model considering the AGC process is as follows: in, Indicates the scheduling period The decision variables corresponding to the economic scheduling stage; Indicates the scheduling period The decision variables corresponding to the second frequency modulation stage; Indicates the scheduling period The corresponding total cost of economic scheduling is expressed as (1)-(10); Indicates the scheduling period The corresponding total cost of secondary frequency regulation is expressed in equations (23)-(25); equation (52) represents the constraints (11)-(22) of the economic scheduling stage. Equation (53) represents the feasible region corresponding to the constraints of the economic scheduling stage; Equation (26)-(42) represents the constraints of the secondary frequency regulation stage. This represents the feasible region corresponding to the constraints in the second frequency regulation stage, which is influenced by the decision variables in the economic scheduling stage. The influence of; Equation (54) represents the coupling constraints of the economic scheduling stage and the secondary frequency regulation stage (49)-(50). , This represents the coefficient matrix under this constraint. This represents the coefficient vector under this constraint. 2) Solve the power generation-reserve joint optimization model considering the AGC process established in step 1) to obtain the power generation plan of conventional units, the secondary frequency regulation reserve plan, the power generation plan of new energy power plants, the charging and discharging plan of energy storage power plants, and the secondary frequency regulation reserve plan, etc. in, Represents the set of result variables; Indicates conventional units During the scheduling period ; output power; , These represent conventional units. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; Indicates new energy power station During the scheduling period ; output power; Indicates energy storage power station During the scheduling period The charging and discharging power; , These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup.

8. A power generation-reserve joint optimization device considering the AGC process, characterized in that, include: The module for constructing the optimization model for the economic scheduling phase is used to build the optimization model for the economic scheduling phase. The optimization control model construction module for the secondary frequency regulation stage is used to establish an optimization control model for the secondary frequency regulation stage based on the secondary frequency regulation AGC process in each time period of the economic scheduling stage. A power generation-reserve joint optimization model construction module is used to embed the optimization control model of the secondary frequency regulation stage into the optimization model of the economic dispatch stage to obtain a power generation-reserve joint optimization model considering the AGC process. The optimization module is used to solve the joint optimization model to obtain the optimization results of the power generation plan and the reserve plan.

9. The apparatus according to claim 8, characterized in that, The objective function of the optimization model in the economic dispatch phase is to minimize the generation and reserve costs, as expressed below: in, These are the label and set of time periods, respectively; These are the designations and unit groups for conventional generating units, respectively. These are the designations and collections of new energy power stations, respectively. These are the designation of the energy storage power station and the group of power stations, respectively. This indicates the economic scheduling phase during the scheduling period. Total cost; , These represent conventional units. During the scheduling period Fuel costs and secondary frequency regulation backup costs; Indicates new energy power station During the scheduling period The cost of abandoning electricity; , These represent energy storage power stations. During the scheduling period The cost of charging and discharging losses and the cost of secondary frequency modulation backup; The fuel cost expression for conventional generating units is as follows: in, Indicates conventional units During the scheduling period ; output power; These represent conventional units. Coefficients of the quadratic, linear, and constant terms of fuel cost; The formula for the reserve cost of secondary frequency regulation of conventional generating units is as follows: in, These represent conventional units. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; Indicates conventional units The secondary frequency regulation backup cost coefficient; The expression for the cost of curtailment at renewable energy power plants is as follows: in, Indicates new energy power station During the scheduling period ; output power; Indicates new energy power station During the scheduling period The predicted output; Indicates new energy power station The cost coefficient of abandoned electricity; The expression for the charging and discharging loss cost of an energy storage power station is as follows: in, Indicates energy storage power station During the scheduling period The charging and discharging power loss, Indicates energy storage power station The charging and discharging loss cost coefficient; the charging and discharging power loss is expressed as the larger of the charging loss and the discharging loss: in, These represent energy storage power stations. During the scheduling period Charging power loss and discharging power loss: in, Indicates energy storage power station During the scheduling period The charging and discharging power, Indicates discharge. Indicates charging; These represent energy storage power stations. The charging efficiency and discharging efficiency; Relax equation (6) to transform it into equation (9): The expression for the backup cost of secondary frequency regulation in an energy storage power station is as follows: in, These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; Indicates energy storage power station The secondary frequency regulation backup cost coefficient.

10. The apparatus according to claim 9, characterized in that, The constraints of the optimization model for the economic scheduling phase include: 1) Power balance constraints: in, These are the label and node set of the load node, respectively; Indicates load node During the scheduling period The load power; These represent conventional units. New energy power stations Energy storage power station During the scheduling period ; output power; 2) Constraints of conventional units: in, These represent conventional units. Upper and lower bounds of output power; These represent conventional units. Critical rates for climbing uphill and downhill; Indicates conventional units During the scheduling period ; output power; Indicates the length of the scheduling period; 3) Constraints on new energy power stations: in, Indicates new energy power station During the scheduling period The predicted output; 4) Constraints of energy storage power stations: in, Indicates energy storage power station During the scheduling period The state of charge; These represent energy storage power stations. During the scheduling period The charging and discharging power and charging and discharging power loss; , These represent energy storage power stations. Upper and lower bounds of charging and discharging power; Indicates energy storage power station The installed capacity value; , These represent energy storage power stations. Upper and lower bounds of the state of charge; 5) Line power constraints: in, Indicates the line number; Indicates the line Maximum permissible transmission power; They represent the lines respectively. Regarding conventional units New energy power stations Energy storage power station and load nodes The transmission allocation coefficient.

11. The apparatus according to claim 10, characterized in that, The objective function of the optimization control model in the secondary frequency regulation stage is to minimize the power system frequency deviation and the cost of secondary frequency regulation mileage, as expressed below: in, The number representing the scheduling period. This is a label for the AGC control cycle. This represents the total number of AGC control cycles within a scheduling period. Indicates the scheduling period The sum of control costs for all AGC control cycles within the system; Indicates the scheduling period AGC control cycle The corresponding frequency deviation; The weighting coefficient representing the cost of frequency deviation; Indicates the scheduling period AGC control cycle The corresponding adjustment mileage cost is the sum of the adjustment mileage costs of all units participating in AGC control: in, Indicates conventional units During the scheduling period AGC control cycle The corresponding AGC control commands; Indicates energy storage power station During the scheduling period AGC control cycle The corresponding AGC control commands; Indicates conventional units The AGC adjustment mileage cost coefficient; Indicates energy storage power station The AGC adjustment mileage cost coefficient; Equation (24) is transformed by introducing slack variables: in, They are conventional units During the scheduling period AGC control cycle The corresponding positive and negative control instructions slack variables; Energy storage power stations During the scheduling period AGC control cycle The corresponding positive and negative control command relaxation variables, all of which take non-negative values.

12. The apparatus according to claim 11, characterized in that, The constraints of the optimized control model in the secondary frequency modulation stage include: State vector and control input vector constraints: in, Indicates the scheduling period AGC control cycle The original state vector; Indicates the scheduling period AGC control cycle The control input vector; Indicates the scheduling period AGC control cycle Corresponding net load change; Indicates the scheduling period AGC control cycle The corresponding frequency deviation, Indicates conventional units During the scheduling period AGC control cycle The corresponding turbine valve opening, Indicates conventional units During the scheduling period AGC control cycle The corresponding output power increment, Indicates energy storage power station During the scheduling period AGC control cycle The corresponding output power increment; Indicates conventional units During the scheduling period AGC control cycle The corresponding AGC control commands, Indicates energy storage power station During the scheduling period AGC control cycle The corresponding AGC control commands; Represents the original state transition matrix; This represents the original input matrix corresponding to the control input vector; This represents the original input matrix corresponding to the change in net load; State-space equation constraints; The state vector incorporates the change in state of charge caused by the energy storage power station's participation in AGC. This change in state of charge is related to the AGC control command of the energy storage power station as follows: in, This represents a vector composed of the changes in state of charge caused by all energy storage power stations participating in AGC; Indicates energy storage power station During the scheduling period AGC control cycle The corresponding change in state of charge; Indicates energy storage power station The installed capacity value; This indicates the length of the AGC control cycle and the length of the scheduling period. Satisfying the relation ; Vector of change of state of charge Augmented to the original state vector Construct a new state vector This leads to the final state-space equation: in, Indicates the scheduling period AGC control cycle The corresponding new state vector; This represents the input matrix corresponding to the change in state of charge. Represents a diagonal matrix. Represents the zero matrix. Represents the identity matrix; This represents the augmented state transition matrix. This represents the augmented input matrix corresponding to the control input vector. This represents the input matrix corresponding to the net load change after augmentation; Adjustable space constraints for state and control variables: in, Indicates the maximum permissible frequency deviation of the power system; , These represent conventional units. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; These represent conventional units. Critical rates for climbing uphill and downhill; These represent energy storage power stations. During the scheduling period AGC control cycle The upper and lower bounds of the corresponding change in state of charge are determined by the SOC value at the end of the previous scheduling period. and the charging and discharging power during the current scheduling period and power loss Decide: in, These represent energy storage power stations. Upper and lower bounds of the state of charge. Indicates energy storage power station The installed capacity value.

13. The apparatus according to claim 12, characterized in that, Also includes: The optimized control model for the second frequency modulation stage can be simplified to the following expression: Among them, equation (43) corresponds to the objective function equations (23)-(25). Let them represent the cost coefficient matrix and cost coefficient vector respectively; Equation (44) corresponds to the state space equations (33)-(35); Equation (45) corresponds to the relaxation process equations (26)-(27) for the control vector adjustment mileage calculation. , These represent the scheduling periods. AGC control cycle The vector composed of the corresponding positive and negative control command relaxation variables; Equation (46) corresponds to the adjustable range constraints of the state variables (36), (38), and (40). Represents the state variable constraint matrix. Indicates the scheduling period The corresponding state variable constraint vector; Equation (47) corresponds to the adjustable range constraint equation (37) of the control variable. Represents the control variable constraint matrix. Indicates the scheduling period The corresponding control variable constraint vector; Equation (48) corresponds to the ramp constraint equation (39) for the state variable. This represents the state variable ramp constraint matrix. This represents the state variable, the hill-climbing constraint vector.

14. The apparatus according to claim 13, characterized in that, Also includes: 1) The optimized control model is embedded into the economic dispatch stage optimization model to establish a power generation-reserve joint optimization model that considers the AGC process; Among them, after introducing the AGC process, the coupling constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period is considered: Equation (49) represents the coupled ramp constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period for conventional units. This constraint is added to the joint optimization model as an additional constraint. Equation (50) represents the SOC-charge-discharge coupling constraint between the end time of the AGC process in the previous scheduling period and the start time of the next scheduling period for energy storage power stations. This constraint replaces the original constraint equation (20). The expression for the power generation-reserve joint optimization model considering the AGC process is as follows: in, Indicates the scheduling period The decision variables corresponding to the economic scheduling stage; Indicates the scheduling period The decision variables corresponding to the second frequency modulation stage; Indicates the scheduling period The corresponding total cost of economic scheduling is expressed as (1)-(10); Indicates the scheduling period The corresponding total cost of secondary frequency regulation is expressed in equations (23)-(25); equation (52) represents the constraints (11)-(22) of the economic scheduling stage. Equation (53) represents the feasible region corresponding to the constraints of the economic scheduling stage; Equation (26)-(42) represents the constraints of the secondary frequency regulation stage. This represents the feasible region corresponding to the constraints in the second frequency regulation stage, which is influenced by the decision variables in the economic scheduling stage. The influence of; Equation (54) represents the coupling constraints of the economic scheduling stage and the secondary frequency regulation stage (49)-(50). , This represents the coefficient matrix under this constraint. This represents the coefficient vector under this constraint. 2) Solve the power generation-reserve joint optimization model considering the AGC process established in step 1) to obtain the power generation plan of conventional units, the secondary frequency regulation reserve plan, the power generation plan of new energy power plants, the charging and discharging plan of energy storage power plants, and the secondary frequency regulation reserve plan, etc. in, Represents the set of result variables; Indicates conventional units During the scheduling period ; output power; , These represent conventional units. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup; Indicates new energy power station During the scheduling period ; output power; Indicates energy storage power station During the scheduling period The charging and discharging power; , These represent energy storage power stations. During the scheduling period Upward secondary frequency modulation backup and downward secondary frequency modulation backup.

15. An electronic device, characterized in that, include: At least one processor; And, a memory communicatively connected to the at least one processor; The memory stores instructions executable by the at least one processor, the instructions being configured to perform the method described in any one of claims 1-7.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the method according to any one of claims 1-7.

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