Compressed air energy storage system scheduling method, device and equipment considering inertia

Abstract

The application relates to the technical field of new energy, in particular to a compressed air energy storage system scheduling method and device considering inertia and equipment, and the method comprises the following steps: acquiring weather data of a target period and historical power generation load data of a new energy generating unit; predicting future output of the new energy generating unit based on the weather data of the target period, and predicting future power generation load of the new energy generating unit based on the historical power generation load data; calculating the inertia of the new energy generating unit in the target period according to the future output and the future power generation load; and scheduling the compressed air energy storage system to store energy or supply energy according to the minimum inertia of the power system and the inertia of the new energy generating unit. Therefore, the problem that the inertia and frequency modulation capability of the power system continuously decrease in the related art, resulting in the reduction of the operation safety of the power grid, is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy, in particular to a compressed air energy storage system scheduling method considering inertia, a device and equipment. BACKGROUND

[0002] In the traditional power system, the energy source is mainly synchronous generator, the inertia and primary frequency modulation capacity are sufficient, and only the power balance is concerned in the operation and scheduling, without special consideration of whether the inertia and frequency modulation power capacity of the system are sufficient. However, in recent years, with the increasing proportion of new energy access, the inertia and frequency modulation capacity of the system are continuously declining, and the uncertain fluctuation of wind power output increases the possibility of short-time high-power disturbance events. Therefore, on the one hand, the method of improving the new energy access to the power grid is improved to improve its ability to provide virtual inertia; on the other hand, the inertia support capacity of the existing elements in the new type of power system is deeply explored. SUMMARY

[0003] The present application provides a compressed air energy storage system scheduling method considering inertia, a device and equipment, to solve the problems of continuously declining inertia and frequency modulation capacity in the power system in related technologies, which reduces the safety of power grid operation.

[0004] The first aspect of the present application provides a compressed air energy storage system scheduling method considering inertia, comprising the following steps: obtaining weather data and historical power generation load data of new energy generating units in a target period; predicting the future output of the new energy generating units based on the weather data of the target period, and predicting the future power generation load of the new energy generating units based on the historical power generation load data; calculating the inertia of the new energy generating units in the target period according to the future output and the future power generation load, and scheduling the compressed air energy storage system for energy storage or energy supply according to the minimum inertia of the power system and the inertia of the new energy generating units.

[0005] Optionally, scheduling the compressed air energy storage system according to the minimum inertia of the power system and the inertia of the new energy generating units comprises: obtaining a day-ahead scheduling model of the compressed air energy storage system; inputting the minimum inertia of the power system and the inertia of the new energy generating units into the day-ahead scheduling model, and the day-ahead scheduling model scheduling the compressed air energy storage system to supply energy or store the power generation energy of the new energy generating units.

[0006] Optionally, the day-ahead scheduling model is:

[0007] ;

[0008] ;

[0009] ;

[0010] wherein, is the day-ahead scheduling cost, a start-stop cost, no-load cost vector of the unit, a start, stop, and running state variable of the unit, a constraint matrix of the unit running state, a vector corresponding to the unit running state, a matrix corresponding to the intra-day scheduling constraint, a unit output vector, a charging power of the compressed air energy storage system, a discharging power of the compressed air energy storage system, a matrix corresponding to the intra-day scheduling constraint, a vector corresponding to the intra-day scheduling constraint.

[0011] Optionally, before scheduling the compressed air energy storage system according to the minimum inertia of the power system and the inertia of the new energy generating unit, the method further comprises: obtaining a maximum frequency change rate allowed by the power system and a power imbalance value that needs to be coped with; and calculating the minimum inertia of the power system according to the maximum frequency change rate and the power imbalance value that needs to be coped with.

[0012] The second aspect embodiment of the application provides a compressed air energy storage system scheduling device considering inertia, comprising: an obtaining module configured to obtain weather data of a target period and historical power generation load data of a new energy generating unit; a prediction module configured to predict future output of the new energy generating unit based on the weather data of the target period, and predict future power generation load of the new energy generating unit based on the historical power generation load data; and a scheduling module configured to calculate inertia of the new energy generating unit in the target period according to the future output and the future power generation load, and schedule the compressed air energy storage system to store energy or supply energy according to the minimum inertia of the power system and the inertia of the new energy generating unit.

[0013] Optionally, the scheduling module is further configured to: obtain a day-ahead scheduling model of the compressed air energy storage system; and input the minimum inertia of the power system and the inertia of the new energy generating unit into the day-ahead scheduling model, so that the day-ahead scheduling model schedules the compressed air energy storage system to supply energy or store power generation energy of the new energy generating unit.

[0014] Optionally, the day-ahead scheduling model is:

[0015] ;

[0016] ;

[0017] ;

[0018] wherein, a day-ahead scheduling cost, a start-stop cost, no-load cost vector of the unit, respectively are state variables of starting, stopping and running of the unit, is a constraint matrix of the operation state of the unit, is a vector corresponding to the operation state of the unit, is a matrix corresponding to the intra-day scheduling constraint, is a unit output vector, is a charging power of the compressed air energy storage system, is a discharging power of the compressed air energy storage system, is a matrix corresponding to the intra-day scheduling constraint, is a vector corresponding to the intra-day scheduling constraint.

[0019] Optionally, the compressed air energy storage system scheduling device considering inertia further comprises a calculation module configured to, before scheduling the compressed air energy storage system according to the minimum inertia of the power system and the inertia of the new energy generating unit, acquire a maximum value of a frequency change rate allowed by the power system and a power imbalance value to be coped with, and calculate the minimum inertia of the power system according to the maximum value of the frequency change rate and the power imbalance value to be coped with.

[0020] The third aspect of the present application provides an electronic device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor executes the program to implement the compressed air energy storage system scheduling method considering inertia as described in the above embodiments.

[0021] The fourth aspect of the present application provides a computer readable storage medium having a computer program or instructions stored thereon, and the computer program or instructions are executed by a processor to implement the compressed air energy storage system scheduling method considering inertia as described in the above embodiments.

[0022] The fifth aspect of the present application provides a computer program product having a computer program or instructions stored thereon, and the computer program or instructions are executed to implement the compressed air energy storage system scheduling method considering inertia as described in the above embodiments.

[0023] Therefore, the present application has at least the following beneficial effects:

[0024] The embodiments of the present application can consider the influence of the inertia of the power system and the inertia of the new energy generating unit on the safe operation of the power grid, schedule the compressed air energy storage system for energy storage or energy supply based on the minimum inertia of the power system and the inertia of the new energy generating unit, enhance the frequency modulation capability of the new energy, effectively guarantee the safe operation of the new power system, and further improve the economic benefit of the compressed air energy storage station. Therefore, the technical problems such as the continuous decline of the inertia and the frequency modulation capability in the power system in the related art, which leads to the reduction of the safety of the power grid operation, are solved.

[0025] Additional aspects and advantages of the present application will be made apparent by the following description and the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0026] The above and / or additional aspects and advantages of the present application will become apparent and be made clear to the reader after a review of the following description and the accompanying drawings.

[0027] Figure 1 A flowchart of a compressed air energy storage system scheduling method considering inertia provided according to an embodiment of the present application;

[0028] Figure 2 A schematic diagram of a new power system model provided according to an embodiment of the present application;

[0029] Figure 3 An example diagram of a compressed air energy storage system scheduling device considering inertia provided according to an embodiment of the present application;

[0030] Figure 4 A structural schematic diagram of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] The embodiments of the present application are described in detail below with reference to the accompanying drawings, in which the same or similar components have the same or similar designations and functions throughout. The embodiments described below are exemplary and are intended to explain the present application, and are not to be understood as limiting the present application.

[0032] The compressed air energy storage system scheduling method, device and equipment considering inertia of the embodiments of the present application are described below with reference to the accompanying drawings. In view of the problem that the inertia and frequency modulation capability of the system continuously decrease and the uncertain fluctuations of wind and light increase the possibility of short-time high-power disturbance events in the related art mentioned in the above background art, the present application provides a compressed air energy storage system scheduling method considering inertia, in which the minimum inertia of the power system and the inertia of the new energy generator unit are considered to affect the power system, and the compressed air energy storage system is scheduled for energy storage or energy supply based on the minimum inertia of the power system and the inertia of the new energy generator unit. Thus, the problem that the inertia and frequency modulation capability of the power system continuously decrease in the related art, resulting in reduced grid operation safety, etc. is solved.

[0033] Specifically, Figure 1 A flowchart of a compressed air energy storage system scheduling method considering inertia provided according to an embodiment of the present application.

[0034] Before the method for scheduling the compressed air energy storage system considering inertia is described, it should be noted that the compressed air energy storage, as a form of large-scale energy storage, can form a combined system with a new energy system to enhance the frequency modulation capability of the new energy; at the same time, as a form of energy storage with rotating devices, when the power generation side of the compressed air energy storage system is connected to the power grid, it can provide synchronous inertia for the power grid.

[0035] As shown in Figure 1 the method for scheduling the compressed air energy storage system considering inertia includes the following steps:

[0036] In step S101, weather data of a target period and historical power generation load data of a new energy generating unit are obtained.

[0037] The power generation load data refers to the power supply load (i.e. the load delivered to the line, referred to as "on-grid load") borne by the power grid, plus the auxiliary power load of the power plant at the same time, to form the total power production load of the power grid; the weather conditions include temperature, humidity, sunny day, rainy day, etc.

[0038] It can be understood that the embodiments of the present application can obtain the weather data of the target period and the historical power generation load data of the new energy generating unit, so as to predict the future power generation load in the subsequent step.

[0039] In step S102, the future output of the new energy generating unit is predicted based on the weather data of the target period, and the future power generation load of the new energy generating unit is predicted based on the historical power generation load data.

[0040] It can be understood that the embodiments of the present application can predict the future output of the new energy generating unit according to the weather data of the target period, and predict the future load of the system according to the historical load data.

[0041] For example, the future output of the new energy generating unit can be predicted according to the wind power, and the future load prediction can be obtained by curve extension or machine learning based on historical data.

[0042] In step S103, the inertia of the new energy generating unit in the target period is calculated according to the future output and the future power generation load, and the compressed air energy storage system is scheduled for energy storage or energy supply according to the minimum inertia of the power system and the inertia of the new energy generating unit.

[0043] It is understood that the embodiments of this application can calculate the inertia of the new energy generating units for the target period based on the future output and future power generation load, and further schedule the compressed air energy storage system for energy storage or function based on the minimum inertia of the power system and the inertia of the new energy generating units. Thus, taking into account the impact of the system's inertia on the safe operation of the power grid, the compressed air energy storage system can provide synchronous inertia for the power grid and enhance the frequency regulation capability of new energy, effectively ensuring the safe operation of the new power system and further improving the economic benefits of the compressed air energy storage power station.

[0044] In this embodiment of the application, the compressed air energy storage system is scheduled according to the minimum inertia of the power system and the inertia of the new energy generating units, including: obtaining the day-ahead scheduling model of the compressed air energy storage system; inputting the minimum inertia of the power system and the inertia of the new energy generating units into the day-ahead scheduling model, and the day-ahead scheduling model scheduling the compressed air energy storage system to supply energy or store the generated electrical energy of the new energy generating units.

[0045] It is understood that the embodiments of this application can construct a day-ahead dispatch model for a compressed air energy storage system. The minimum inertia of the power system and the inertia of the new energy generating units are input into the day-ahead dispatch model. The day-ahead dispatch model dispatches the compressed air energy storage system to supply energy or store the generated electricity of the new energy generating units. This realizes a day-ahead dispatch model that takes inertia into account, which dispatches the compressed air energy storage system to supply energy or store the generated electricity of the new energy generating units, effectively ensuring the safe operation of the new power system.

[0046] In this embodiment of the application, the day-ahead scheduling model is as follows:

[0047] ;

[0048] ;

[0049] ;

[0050] in, For day-to-day scheduling costs, This is a vector representing the start-up and shutdown costs and no-load costs of the generating unit. These are the state variables for the unit's startup, shutdown, and operation, respectively. This is the constraint matrix for the unit's operating status. This is a vector corresponding to the unit's operating status. This is the matrix corresponding to the intraday scheduling constraints. This is the unit's output vector. The charging power for the compressed air energy storage system, This refers to the discharge power of the compressed air energy storage system. This is the matrix corresponding to the intraday scheduling constraints. This is the vector corresponding to the intraday scheduling constraints.

[0051] In the embodiment of the present application, before the compressed air energy storage system is dispatched according to the minimum inertia of the power system and the inertia of the new energy generator unit, the maximum frequency change rate allowed by the power system and the power imbalance value that needs to be coped with are obtained; and the minimum inertia of the power system is calculated according to the maximum frequency change rate and the power imbalance value that needs to be coped with.

[0052] It can be understood that the minimum inertia required by the system can be calculated according to the maximum frequency change rate allowed by the power system and the power imbalance value that needs to be coped with, and the minimum inertia of the power system is further calculated according to the maximum frequency change rate and the power imbalance value that needs to be coped with, so that when the system is disturbed by power and causes power imbalance, the frequency changes sharply, and the system should ensure that the initial frequency change rate meets the constraint, thereby enhancing the frequency modulation capability of the new energy.

[0053] It should be noted that the day-ahead scheduling model of the embodiment of the present application is a mixed integer linear programming problem, which can be efficiently solved by using the traditional Benders decomposition method, so as to obtain the scheduling method of the compressed air energy storage system, thereby effectively ensuring the safe operation of the new power system.

[0054] Specifically, the process of the compressed air energy storage system scheduling method considering inertia in the embodiment of the present application is as follows:

[0055] Step 1: establish a new power system model, as shown in Figure 2

[0056] A new power system model including traditional thermal power units, new energy generator units, compressed air energy storage systems and transmission lines is established, so as to clearly determine the energy flow relationship and further determine the expression of energy conservation. Further, the new energy output and the load are predicted to obtain the data required for day-ahead scheduling (i.e. the power consumption data (load) and the predicted value of the new energy output) and establish a unit commitment model. The new energy output is obtained by predicting the weather of the next day, and the load prediction is obtained by learning from historical data. The new energy output can directly supply the load, or can be stored in the compressed air energy storage system, and the remaining part can be discarded. The compressed air energy storage system can be charged by new energy, or can supply power to the load; the charging and discharging power and the state of charge of the compressed air energy storage system cannot exceed its upper and lower limits. Considering the above constraints, the minimum system operation cost or equivalent standard coal consumption is taken as the objective function, and the system operation cost is taken as the objective function in the present application, and a traditional unit commitment model is established.

[0057] (0a);

[0058] (0b); ​

[0059] (0c);

[0060] (0d);

[0061] (0e);

[0062] (0f);

[0063] (0g);

[0064] The objective function (0a) is the operating cost of the system (including coal consumption, no-load, start-up and shutdown costs of traditional units, etc.). These are the linear coal consumption cost of the unit, the no-load cost of the unit, the start-up cost of the unit, and the shutdown cost of the unit (starting up, shutting down, and running the unit will cause damage to the rotor, which can be converted into a certain cost (standard coal consumption). The unit output requires coal consumption, which causes costs (standard coal consumption)). These represent the unit's online status, unit startup actions, unit shutdown actions, and unit... During the period The output power of the unit. Constraint (0b) limits the unit's single-period output to between the upper and lower limits of the unit's allowable output. Constraints (0c), (0d), and (0e) impose restrictions on the unit's start-up and shutdown logic. Constraint (0f) imposes restrictions on the system's power balance; Time periods The output of internal new energy sources, the discharge power and charging power of compressed air energy storage systems; For time period The load within the system. Constraint (0g) limits the system to having a certain amount of reserve capacity.

[0065] Step 2: Consider the minimum inertia constraint.

[0066] By incorporating minimum inertia constraints and frequency regulation reserve constraints into the unit combination model, a day-ahead dispatch model for the compressed energy storage system considering inertia is formed. First, the minimum inertia required by the system is calculated based on the maximum allowable rate of frequency change and the power imbalance that needs to be addressed. When a power disturbance occurs in the system, leading to a power imbalance, the frequency changes drastically; the system must ensure that the initial rate of frequency change meets the constraints.

[0067] (1a);

[0068] The rate of change of the system's frequency is determined by the power deficit and the system's total inertia, i.e.

[0069] (1b);

[0070] The power shortage value of the system in the time period is determined by the demand of the system; The total inertia of the system is provided by the thermal power units in the system and the compressed air energy storage system. The constraint (1a) can be expanded as follows:

[0071] (1c);

[0072] wherein, The inertia of the unit , The operating state of the unit at the time , 1 represents that the unit is running, and 0 represents that the unit is not running, The inertia provided by the compressed air energy storage system, The working state of the compressed air energy storage system, 0 represents that the system is charging, and 1 represents that the system is releasing energy, The reference frequency of the power grid is 50 Hz in China.

[0073] The constraint (1c) is added to the unit combination model constructed above to form the following day-ahead scheduling model of the compressed air energy storage system considering inertia:

[0074] (1d);

[0075] (1e);

[0076] (1f);

[0077] wherein, The objective function of the problem is to minimize the total operating cost of the system, The coefficient vector of the unit cost, The coal consumption cost coefficient of the unit. The coefficient matrix corresponding to the constraints (0b) (0c) (0d) (0e) (0g), The vector corresponding to the constraints (0b) (0c) (0d) (0e) (0g). The coefficient matrix corresponding to the constraints (0f) (1c), The vector corresponding to the constraints (0f) (1c).

[0078] Step 3: Solve the compressed air energy storage system scheduling model considering inertia.

[0079] The method is solved by using a method for solving an integer linear programming problem such as a traditional Benders decomposition method, so as to improve the safe and stable operation ability of the system and the economic benefit of the pressure storage power station. The above-mentioned scheduling model of the inertia-considered compressed air energy storage system is a mixed integer linear programming problem, which can be efficiently solved by using the traditional Benders decomposition method, so as to obtain the scheduling method of the compressed air energy storage system, and effectively guarantee the safe operation of the new type of power system.

[0080] The original problem is decomposed into a master problem and a sub-problem as follows:

[0081]

[0082]

[0083] (3a)

[0084]

[0085] (3b)

[0086] wherein, is a relaxation variable introduced, representing a lower bound of the optimal value of the master problem, is a coefficient matrix representing the objective function of the master problem, is the minimum, is the total operation cost of the system (i.e., the start-up, no-load and shutdown cost of the unit), are state variables of the start-up, shutdown and operation of the unit, respectively, is a constraint matrix of the operation state of the unit, is a vector corresponding to the constraints (0b), (0c), (0d), (0e) and (0g), is a coefficient matrix corresponding to the constraints (0f) and (1c), is a vector corresponding to the constraints (0f) and (1c), is the optimal solution of the master problem, is a dual variable introduced.

[0087] Algorithm 1 Benders decomposition method for solving a mixed integer linear programming problem;

[0088] Initialization: solve the master problem to obtain the initial and ;

[0089] 1. Solve the sub-problem, if the problem has a solution, set , if the upper and lower bounds converge, the problem is successfully solved; if they do not converge, add the constraint to the master problem. If the sub-problem is unbounded, add the constraint .

[0090] 2, solve the main problem, update , if convergence, then jump out of the loop, if not convergence, return 1.

[0091] The compressed air energy storage system scheduling method considering inertia provided in the embodiments of the present application can consider the influence of the inertia of the power system and the inertia of the new energy generating unit on the safe operation of the power grid, and schedule the compressed air energy storage system for energy storage or energy supply based on the minimum inertia of the power system and the inertia of the new energy generating unit, thereby enhancing the frequency modulation capability of the new energy, effectively ensuring the safe operation of the new power system, and further improving the economic benefit of the compressed air energy storage station.

[0092] Secondly, the compressed air energy storage system scheduling device considering inertia provided in the embodiments of the present application is described with reference to the accompanying drawings.

[0093] Figure 3 is a block schematic diagram of the compressed air energy storage system scheduling device considering inertia in the embodiments of the present application.

[0094] As shown in Figure 3 , the compressed air energy storage system scheduling device 10 considering inertia includes an acquisition module 100, a prediction module 200, and a scheduling module 300.

[0095] The acquisition module 100 is configured to acquire weather data and historical power generation load data of the new energy generating unit in a target period; the prediction module 200 is configured to predict future output of the new energy generating unit based on the weather data in the target period, and predict future power generation load of the new energy generating unit based on the historical power generation load data; and the scheduling module 300 is configured to calculate inertia of the new energy generating unit in the target period according to the future output and the future power generation load, and schedule the compressed air energy storage system for energy storage or energy supply according to the minimum inertia of the power system and the inertia of the new energy generating unit.

[0096] In the embodiments of the present application, the scheduling module 200 is further configured to: acquire a day-ahead scheduling model of the compressed air energy storage system; input the minimum inertia of the power system and the inertia of the new energy generating unit into the day-ahead scheduling model, and the day-ahead scheduling model schedules the compressed air energy storage system for energy supply or stores power generation energy of the new energy generating unit.

[0097] In the embodiments of the present application, the day-ahead scheduling model is:

[0098] ;

[0099] ;

[0100] ;

[0101] wherein, a day-ahead scheduling cost, a start-stop cost and no-load cost vector of the unit, a state variable of start, stop and operation of the unit respectively, a constraint matrix of the operation state of the unit, a vector corresponding to the operation state of the unit, a matrix corresponding to the intra-day scheduling constraint, a unit output vector, a charging power of the compressed air energy storage system, a discharging power of the compressed air energy storage system, a matrix corresponding to the intra-day scheduling constraint, a vector corresponding to the intra-day scheduling constraint.

[0102] In the embodiments of the present application, the device 10 of the present application further comprises a calculation module.

[0103] The calculation module is configured to, before scheduling the compressed air energy storage system according to the minimum inertia of the power system and the inertia of the new energy generating unit, obtain a maximum frequency change rate allowed by the power system and a power imbalance value that needs to be coped with; and calculate the minimum inertia of the power system according to the maximum frequency change rate and the power imbalance value that needs to be coped with.

[0104] It should be noted that the foregoing description of the embodiment of the compressed air energy storage system scheduling method considering inertia is also applicable to the embodiment of the compressed air energy storage system scheduling device considering inertia, which will not be described here again.

[0105] The compressed air energy storage system scheduling device considering inertia according to the embodiments of the present application can consider the influence of the inertia of the power system and the inertia of the new energy generating unit on the safe operation of the power grid, schedule the compressed air energy storage system for energy storage or energy supply based on the minimum inertia of the power system and the inertia of the new energy generating unit, enhance the frequency modulation capability of the new energy, effectively guarantee the safe operation of the new power system, and further improve the economic benefit of the compressed air energy storage station.

[0106] Figure 4 The electronic device provided in the embodiments of the present application is shown in a structural schematic diagram. The electronic device can include:

[0107] The memory 401, the processor 402, and the computer program stored in the memory 401 and executable on the processor 402.

[0108] The processor 402 executes the program to implement the compressed air energy storage system scheduling considering inertia provided in the above embodiments.

[0109] Further, the electronic device further includes:

[0110] The communication interface 403 is configured to communicate between the memory 401 and the processor 402.

[0111] The memory 401 is configured to store a computer program executable on the processor 402.

[0112] The memory 401 can include a high-speed RAM (Random Access Memory) memory, and can further include a non-volatile memory, for example, at least one disk memory.

[0113] If the memory 401, the processor 402 and the communication interface 403 are independently implemented, the communication interface 403, the memory 401 and the processor 402 can be connected to each other through a bus and complete communication between each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 4 In the figure, only one thick line is used to represent, but it does not mean that there is only one bus or one type of bus.

[0114] Optionally, in a specific implementation, if the memory 401, the processor 402 and the communication interface 403 are integrated on a chip, the memory 401, the processor 402 and the communication interface 403 can complete communication between each other through an internal interface.

[0115] The processor 402 can be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement one or more embodiments of the present application.

[0116] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program or instructions, and the computer program or instructions are executed by the processor to implement the above-mentioned compressed air energy storage system scheduling method considering inertia.

[0117] The embodiment of the present application further provides a computer program product, which stores a computer program or instructions, and the computer program or instructions are executed to implement the above-mentioned compressed air energy storage system scheduling method considering inertia.

[0118] In the description of the application, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the application. In the description of the application, the illustrative description of the above terms is not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or N embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the description and the features of the different embodiments or examples, without contradiction.

[0119] In addition, the terms "first", "second" are only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the application, the meaning of "N" is at least two, for example, two, three, etc., unless otherwise specifically limited.

[0120] Any process or method descriptions in flow charts or described elsewhere herein can be understood as representing code modules, segments, or portions of code that include one or more executable instructions for implementing specific logic functions (or steps) in the process, and the various embodiments of the application can include additional or fewer steps performing the same or equivalent functions in the same or equivalent order as those described herein, as appropriate, without departing from the spirit and scope of the application.

[0121] It should be understood that parts of the application can be implemented in hardware, software, firmware or a combination thereof. In the above-described embodiments, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. As in another embodiment, if implemented in hardware, any of the following technologies known in the art or their combinations can be used: discrete logic circuit with logic gate circuit for implementing logic functions on data signals, application specific integrated circuit with suitable combination logic gate circuit, programmable gate array, field programmable gate array, etc.

[0122] Those skilled in the art of the present technology can understand that all or part of the steps carried out by the above-mentioned embodiment method can be completed by a program instructing the relevant hardware, and the program can be stored in a computer readable storage medium. The program, when executed, includes one or a combination of steps of the method embodiments.

Claims

1. A scheduling method for compressed air energy storage system considering inertia, characterized in that, The method comprises the following steps: acquiring weather data of a target period and historical power generation load data of a new energy generating unit; predicting future output of the new energy generating unit based on the weather data of the target period and predicting future power generation load of the new energy generating unit based on the historical power generation load data; calculating inertia of the new energy generating unit in the target period according to the future output and the future power generation load, and scheduling the compressed air energy storage system to store energy or supply energy according to minimum inertia of a power system and the inertia of the new energy generating unit; the scheduling of the compressed air energy storage system according to the minimum inertia of the power system and the inertia of the new energy generating unit comprises: acquiring a day-ahead scheduling model of the compressed air energy storage system; inputting the minimum inertia of the power system and the inertia of the new energy generating unit into the day-ahead scheduling model, and the day-ahead scheduling model scheduling the compressed air energy storage system to supply energy or store power generation energy of the new energy generating unit, wherein the day-ahead scheduling model is constructed based on adding a target constraint in a unit combination model, and the target constraint comprises: The single-period output constraint of the unit is: ; wherein, is an online state of the unit, is a unit is an output power of the unit at a time period ; The start-stop logic constraints of the unit are that: ; ； ； wherein, is the on action of the unit is the on action of the unit at time period is the on-line status of the unit g at time t, is the off action of the unit; The power balance constraint of the power system is: ; in, For the unit number, For the unit During the period 'output power' For time period The output of the internal new energy units, For time period The discharge power of the internal compressed air energy storage system For time period The charging power of the internal compressed air energy storage system For time period Internal load; Capacity constraints of the power system are given by: ; wherein, is a unit number, is an on-line state of the unit, is a time period a load within; The rate of change of frequency constraint for power systems is given by: ; wherein, Jtotal is the total inertia of the power system, Junit is the inertia of the unit, Junit is the inertia of the unit, Junit is the inertia of the unit, Junit is the inertia of the unit, Junit is the inertia of the unit, 1 represents that the unit is running, and 0 represents that the unit is not running, JCAES is the inertia provided by the compressed air energy storage system, JCAES is the working state of the compressed air energy storage system, 0 represents that the compressed air energy storage system is charging, and 1 represents that the compressed air energy storage system is releasing energy, fgrid is the reference frequency of the power grid; the day-ahead scheduling model is: ； ； ； in, For day-to-day scheduling costs, This is a vector representing the start-up and shutdown costs and no-load costs of the generating unit. These are the state variables for the unit's startup, shutdown, and operation, respectively. This is the coal consumption cost coefficient of the unit. This is the coefficient matrix corresponding to the unit's single-period output constraints, the unit's start-stop logic constraints, and the power system's capacity constraints. This is a vector corresponding to the unit's single-period output constraints, the unit's start-up and shutdown logic constraints, and the power system's capacity constraints. This is the coefficient matrix corresponding to the power balance constraints of the power system. This is the unit's output vector. The charging power for the compressed air energy storage system, This refers to the discharge power of the compressed air energy storage system. This is the coefficient matrix corresponding to the frequency change rate constraint of the power system. This is the vector corresponding to the power balance constraint and the frequency change rate constraint of the power system.

2. The method of claim 1, wherein, before the scheduling of the compressed air energy storage system according to the minimum inertia of the power system and the inertia of the new energy generating unit, the method further comprises: acquiring a maximum value of a frequency change rate allowed by the power system and a power imbalance value to be coped with; calculating the minimum inertia of the power system according to the maximum value of the frequency change rate and the power imbalance value to be coped with.

3. An inertia-considered compressed air energy storage system scheduling device, characterized in that, comprise: an acquisition module, configured to acquire weather data of a target period and historical power generation load data of a new energy generating unit; a prediction module, configured to predict future output of the new energy generating unit based on the weather data of the target period and predict future power generation load of the new energy generating unit based on the historical power generation load data; The scheduling module is configured to calculate inertia of the new energy generator unit in the target period according to the future output and the future power generation load, and schedule the compressed air energy storage system to store energy or supply energy according to the minimum inertia of the power system and the inertia of the new energy generator unit; the scheduling module is further configured to: obtain a day-ahead scheduling model of the compressed air energy storage system; input the minimum inertia of the power system and the inertia of the new energy generator unit into the day-ahead scheduling model, and the day-ahead scheduling model schedules the compressed air energy storage system to supply energy or store power generation energy of the new energy generator unit, wherein the day-ahead scheduling model is constructed based on adding a target constraint in a unit commitment model, and a single-period output constraint of a unit is: ​ wherein, is an online state of the unit, is a unit is an output power of the unit at a time period ; The start-stop logic constraints of the unit are that: ; ； ； wherein, is the on action of the unit is the on action of the unit g at time t, is the on action of the unit g at time t, is the on-line status of the unit g at time t, is the off action of the unit g; The power balance constraint of the power system is: ; wherein, is a unit number, is a unit is an output power of the unit in the time period, is an output power of the unit in the time period, is an output power of the unit in the time period, is an output power of the unit in the time period, is an output power of the unit in the time period, is an output power of the unit in the time period, is an output power of the unit in the time period, is an output power of the unit in the time period, is an output power of the unit in the time period, is an output power of the unit in the time period, Capacity constraints of the power system are given by: ; wherein, is a unit number, is an on-line state of the unit, is a time period a load within; The rate of change of frequency constraint for power systems is given by: ; wherein, Jtotal is the total inertia of the power system, Junit is the inertia of the unit, Junit is the inertia of the unit, Junit is the inertia of the unit, Junit is the inertia of the unit, Junit is the inertia of the unit, 1 represents that the unit is running, and 0 represents that the unit is not running, JCAES is the inertia provided by the compressed air energy storage system, JCAES is the working state of the compressed air energy storage system, 0 represents that the compressed air energy storage system is charging, and 1 represents that the compressed air energy storage system is releasing energy, fref is the reference frequency of the power grid; the day-ahead scheduling model is: ； ； ； wherein, is a day-ahead dispatch cost, is a start-up and shut-down cost vector of the units, are state variables of start-up, shut-down and operation of the units, respectively, is a coal consumption cost coefficient of the units, is a coefficient matrix corresponding to the single-period output constraint of the units, the start-up and shut-down logic constraint of the units, and the capacity constraint of the power system, is a vector corresponding to the single-period output constraint of the units, the start-up and shut-down logic constraint of the units, and the capacity constraint of the power system, is a coefficient matrix corresponding to the power balance constraint of the power system, is a unit output vector, is a charging power of the compressed air energy storage system, is a discharging power of the compressed air energy storage system, is a coefficient matrix corresponding to the frequency rate of change constraint of the power system, is a vector corresponding to the power balance constraint of the power system and the frequency rate of change constraint of the power system.

4. The device for scheduling an inertial compressed air energy storage system according to claim 3, characterized in that, The compressed air energy storage system scheduling device considering inertia further comprises a calculation module, configured to, before the scheduling of the compressed air energy storage system according to the minimum inertia of the power system and the inertia of the new energy generating unit, acquire a maximum value of a frequency change rate allowed by the power system and a power imbalance value to be coped with; and calculate the minimum inertia of the power system according to the maximum value of the frequency change rate and the power imbalance value to be coped with.

5. An electronic device, comprising: comprise: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the program to implement the compressed air energy storage system scheduling method considering inertia according to any one of claims 1-2.

6. A computer readable storage medium having stored thereon a computer program or instructions, characterized in that, The computer program or instructions are executed by the processor to implement the compressed air energy storage system scheduling method considering inertia according to any one of claims 1-2.

7. A computer program product having stored thereon a computer program or instructions, characterized in that, The computer program or instructions are executed to implement the compressed air energy storage system scheduling method considering inertia according to any one of claims 1-2.

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