Distribution network flexible resource real-time scheduling method and device

Abstract

The invention provides a real-time scheduling method and device for flexible resources of a distribution network, and belongs to the technical field of operation control of a power system. The method comprises the steps that a distribution network flexible resource real-time scheduling model is constructed, the distribution network flexible resource real-time scheduling model is composed of an objective function and constraint conditions, distribution network flexible resources comprise a common generator, a new energy unit, a hydropower station and stored energy, and the objective function is used for scheduling the new energy unit and the hydropower station on the basis that the adjustment capacity is met; the number of resources adjusted at the current moment is minimum, and meanwhile adjustment economy is considered; and solving the distribution network flexible resource real-time scheduling model to obtain the scheduling output of each generator in the distribution network at the current moment. According to the invention, the flexible adjustment capability of various resources in the distribution network is utilized to provide the supporting capability for the superior power grid, and the number of the adjusted resources is reduced as much as possible, so that frequent actions of the resources are avoided, and the overall operation safety and economy of the distribution network are ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of operation control of power systems, and in particular relates to a method and device for real-time dispatching of flexible resources in a distribution network. Background Art

[0002] As the penetration rate of renewable energy increases, the power grid urgently needs a lot of regulation capabilities to cope with the randomness and volatility of renewable energy. Microgrids, small-capacity units, energy storage and other resources in the distribution network are important sources of flexibility. In real-time time scales, real-time scheduling is required based on current measurement values ​​to ensure safe and economical operation of the power system.

[0003] At present, the relevant technologies for real-time scheduling are difficult to adapt to the situation where distribution network resources cannot be adjusted frequently and may respond to the regulation needs of the main network. For example, the invention patent with application number 202310736097.1 takes the minimum output adjustment as the objective function, but for the problem that there is a main network regulation demand and there is no safety limit violation, the one-norm objective function used in the patent may produce multiple solutions. If the two-norm is used as the objective function, it may cause the problem that the regulation amount tends to be evenly distributed to each resource; for example, the application number 202410256501.X does not consider the direction of the regulation capability, and may frequently adjust a certain resource in real-time scheduling, resulting in oscillation. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and propose a real-time dispatching method and device for flexible resources in a distribution network. The present invention utilizes the flexible adjustment capabilities of various resources (including generators and energy storage) in the distribution network to provide support capabilities for the upper power grid, while minimizing the number of resources that are adjusted as much as possible to avoid frequent resource actions, while ensuring the safety and economy of the overall operation of the distribution network.

[0005] The first embodiment of the present invention provides a method for real-time scheduling of flexible resources in a distribution network, comprising:

[0006] Constructing a real-time dispatching model for flexible resources in the distribution network, which is composed of an objective function and constraints, wherein the flexible resources in the distribution network include ordinary generators, new energy units, hydropower stations and energy storage, and the objective function minimizes the number of resources to be regulated at the current moment on the basis of satisfying the regulation capacity, while considering the regulation economy;

[0007] Solve the real-time dispatch model of the distribution network flexible resources to obtain the dispatch output of each generator in the distribution network at the current moment.

[0008] In a specific embodiment of the present invention, the objective function expression is as follows:

[0009]

[0010] Among them, t is the current time; S G represents the set of all generators, and is the set of common generators S T , the set S consisting of new energy units W And the hydropower station constitutes a set S H The union of the three, namely: S G =S T ∪S W ∪S H ; S ES Represents energy storage set; S G and S ES Together they form a collection of flexible resources;

[0011] is the deviation between the actual adjustment amount and the required adjustment amount at time t; is a 0-1 variable indicating whether the i-th resource is adjusted at time t. When it is 1, it means that the resource is adjusted at time t; when When it is 0, it means that the resource is not adjusted in real time at time t, and the power remains at the measured value; c R is the power abandonment cost of new energy units, is the predicted power of new energy unit i at time t, is the electricity price of generator i at time t; is the dispatch output of generator i at time t; σ is the penalty coefficient, ε represents the allowable deviation of adjustment;

[0012] is the regulation cost of energy storage, where c adj is the energy storage unit electricity regulation cost, is the planned storage capacity of energy storage i at time t, It is the storage capacity after real-time dispatch of energy storage i at time t.

[0013] In a specific embodiment of the present invention, the constraint conditions include:

[0014] Generator constraints;

[0015]

[0016] Among them, P i min With P i max are the minimum startup power and maximum startup power of generator i respectively; is a binary variable representing the start / stop status of generator i; is the real-time power measurement value of generator i at time t;

[0017] Hydropower plant constraints;

[0018]

[0019] in, is the set of all small hydropower units in hydropower station i, is the start and stop status of small and medium-sized hydropower unit k in hydropower station i, is a binary variable representing the start / stop status of hydropower station i at time t, P i k is the capacity of small and medium-sized hydropower unit k in hydropower station i; Representing a collection The number of elements in ;

[0020] Constraints on renewable energy generation;

[0021]

[0022] Energy storage constraints;

[0023]

[0024] in, are the discharge power and charging power of energy storage i at time t respectively; are the maximum discharge power and maximum charging power of energy storage i respectively; is the real-time power measurement value of energy storage i at time t; is the storage capacity of energy storage i at time t, and Δt is the time interval of real-time scheduling; are the maximum and minimum storage capacity of energy storage i at time t respectively;

[0025] Flexible adjustment of demand constraints;

[0026]

[0027] in, is the regulation demand of the upper power grid at time t.

[0028] In a specific embodiment of the present invention, it also includes:

[0029] When the upper power grid issues a positive reserve demand at time t, The flexible adjustment demand constraint adopts equation (13) and equation (15); when the upper power grid issues a negative reserve demand at time t, The flexible adjustment demand constraint adopts equation (14) and equation (15).

[0030] The second embodiment of the present invention provides a real-time scheduling device for flexible resources in a distribution network, comprising:

[0031] The model building module is used to build a real-time dispatch model for distribution network flexible resources. The real-time dispatch model for distribution network flexible resources is composed of an objective function and constraints. The distribution network flexible resources include: ordinary generators, new energy units, hydropower stations and energy storage. The objective function minimizes the number of resources to be regulated at the current moment on the basis of satisfying the regulation capacity, while considering the regulation economy.

[0032] The scheduling optimization module is used to solve the real-time scheduling model of the distribution network flexible resources and obtain the scheduling output of each generator in the distribution network at the current moment.

[0033] In a specific embodiment of the present invention, the objective function expression is as follows:

[0034]

[0035] Among them, t is the current time; S G represents the set of all generators, and is the set of common generators S T , the set S consisting of new energy units W And the hydropower station constitutes a set S H The union of the three, namely: S G =S T ∪S W ∪S H ; S ES Represents energy storage set; S G and S ES Together they form a collection of flexible resources;

[0036] is the deviation between the actual adjustment amount and the required adjustment amount at time t; is a 0-1 variable indicating whether the i-th resource is adjusted at time t. When it is 1, it means that the resource is adjusted at time t; when When it is 0, it means that the resource is not adjusted in real time at time t, and the power remains at the measured value; c R is the power abandonment cost of new energy units, is the predicted power of new energy unit i at time t, is the electricity price of generator i at time t; is the dispatch output of generator i at time t; σ is the penalty coefficient, ε represents the allowable deviation of adjustment;

[0037] is the regulation cost of energy storage, where c adj is the energy storage unit electricity regulation cost, is the planned storage capacity of energy storage i at time t, It is the storage capacity after real-time dispatch of energy storage i at time t.

[0038] In a specific embodiment of the present invention, the constraint conditions include:

[0039] Generator constraints;

[0040]

[0041] Among them, P i min With P i max are the minimum startup power and maximum startup power of generator i respectively; is a binary variable representing the start / stop status of generator i; is the real-time power measurement value of generator i at time t;

[0042] Hydropower plant constraints;

[0043]

[0044] in, is the set of all small hydropower units in hydropower station i, is the start and stop status of small and medium-sized hydropower unit k in hydropower station i, is a binary variable representing the start / stop status of hydropower station i at time t, P i k is the capacity of small and medium-sized hydropower unit k in hydropower station i; Representing a collection The number of elements in ;

[0045] Constraints on renewable energy generation;

[0046]

[0047] Energy storage constraints;

[0048]

[0049] in, are the discharge power and charging power of energy storage i at time t respectively; are the maximum discharge power and maximum charging power of energy storage i respectively; is the real-time power measurement value of energy storage i at time t; is the storage capacity of energy storage i at time t, and Δt is the time interval of real-time scheduling; are the maximum and minimum storage capacity of energy storage i at time t respectively;

[0050] Flexible adjustment of demand constraints;

[0051]

[0052] in, is the regulation demand of the upper power grid at time t.

[0053] In a specific embodiment of the present invention, it also includes:

[0054] When the upper power grid issues a positive reserve demand at time t, The flexible adjustment demand constraint adopts equation (13) and equation (15); when the upper power grid issues a negative reserve demand at time t, The flexible adjustment demand constraint adopts equation (14) and equation (15).

[0055] A third aspect of the present invention provides an electronic device, including:

[0056] at least one processor; and a memory communicatively coupled to the at least one processor;

[0057] The memory stores instructions executable by the at least one processor, and the instructions are configured to execute the above-mentioned method for real-time scheduling of flexible resources in a distribution network.

[0058] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the above-mentioned method for real-time scheduling of flexible resources in a distribution network.

[0059] Features and beneficial effects of the present invention:

[0060] The present invention aims at the fact that the current objective function design for real-time scheduling is usually difficult to adapt to the actual situation that the distribution network resources cannot be adjusted frequently and may respond to the main network regulation requirements. For example, the one-norm objective function used may produce multiple solutions, and the use of the two-norm as the objective function may produce the problem that the regulation amount tends to be evenly distributed to each resource. A real-time scheduling method and device for flexible resources in the distribution network are proposed. The present invention adopts a weighted combination of the number and economy of the resources that are regulated as the objective function. The present invention uses the flexible regulation capability of various resources (including generator sets and energy storage) in the distribution network to provide support capabilities for the upper power grid, while minimizing the number of resources that are regulated as much as possible to avoid frequent resource actions, while ensuring the safety and economy of the overall operation of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is an overall flow chart of a method for real-time scheduling of flexible resources in a distribution network according to an embodiment of the present invention. DETAILED DESCRIPTION

[0062] The present invention provides a method and device for real-time scheduling of flexible resources in a distribution network, which is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0063] The first embodiment of the present invention provides a method for real-time scheduling of flexible resources in a distribution network, comprising:

[0064] Constructing a real-time dispatching model for flexible resources in the distribution network, which is composed of an objective function and constraints, wherein the flexible resources in the distribution network include ordinary generators, new energy units, hydropower stations and energy storage, and the objective function minimizes the number of resources to be regulated at the current moment on the basis of satisfying the regulation capacity, while considering the regulation economy;

[0065] Solve the real-time dispatch model of the distribution network flexible resources to obtain the dispatch output of each generator in the distribution network at the current moment.

[0066] In a specific embodiment of the present invention, the overall process of a real-time scheduling method for flexible resources in a distribution network is as follows: Figure 1 As shown, the method comprises the following steps:

[0067] 1) Construct the objective function of the real-time scheduling model of distribution network flexible resources.

[0068] In this embodiment, the objective function minimizes the number of resources to be adjusted at the current moment on the basis of satisfying the adjustment capacity as much as possible, while considering the adjustment economy:

[0069]

[0070] Among them, t is the current time; S G represents the set of all generators, and is the set of common generators S T , a collection of new energy units (wind turbines, photovoltaics) S W And the hydropower station constitutes a set S H The union of the three, namely: S G =S T ∪S W ∪S H ; S ES Represents energy storage set; S G and S ES Together they form a collection of flexible resources.

[0071] σ is the penalty coefficient, and its value should be greater than the electricity price of all units at all times, and greater than the product of the regulation allowable deviation ε and the sum of the number of all resources, that is, is the deviation between the actual adjustment amount and the required adjustment amount at time t; is a 0-1 variable indicating whether the i-th resource is adjusted at time t. When it is 1, it means that the resource is adjusted at time t; when When it is 0, it means that the resource is not adjusted in real time at time t, that is, the power remains at the measured value; c R is the power abandonment cost of new energy units, is the predicted power of new energy unit i at time t, is the electricity price of generator i at time t, which can be reported by each hydropower station. For ordinary generators, it can be calculated by combining their consumption curves and fuel prices. For renewable energy power generation, it is usually taken as 0, considering only the cost of abandoned electricity; is the dispatch output of generator i at time t.

[0072] The last term in the objective function is the regulation cost of energy storage, where c adj is the unit electricity regulation cost of energy storage, which can be calculated from the peak-valley electricity price difference. is the planned storage capacity of energy storage i at time t, which is usually obtained by day-ahead scheduling or intraday scheduling; It is the storage capacity after real-time dispatch of energy storage i at time t.

[0073] 2) The constraints for constructing the real-time dispatch model of distribution network flexible resources include:

[0074] 2-1) Generator constraints;

[0075]

[0076] Among them, P i min With P i max are the minimum and maximum startup power of generator i, respectively. For a hydropower station, P i max The maximum allowable active output of the generator must be taken. is a binary variable representing the start / stop status of generator i; is the real-time power measurement value of generator i at time t, which can be obtained from the configured active power measurement value; The value is usually determined by the result of day-ahead / day-intraday scheduling; Formula (2) is the generator power constraint, and Formula (3) describes whether the current generator is adjusted.

[0077] 2-2) Hydropower station constraints;

[0078]

[0079] in, is the set of all small hydropower units in hydropower station i, is the start and stop status of small and medium-sized hydropower unit k in hydropower station i, is a binary variable representing the start / stop status of hydropower station i at time t, P ik is the capacity of small hydropower unit k in hydropower station i; the above parameters can be obtained from the factory manual of the hydropower unit and the topological relationship between the hydropower station and the small hydropower unit.

[0080] Formula (4) is the power balance constraint considering the general discontinuous regulation of small hydropower units; for units with some associated startup states (some small hydropower units need to be started at the same time due to geographical location), the two units are combined as one equivalent unit and included in constraint formula (4); Formula (5) is the relationship between the startup and shutdown states of the units and the startup and shutdown states of the hydropower station; Representing a collection The number of elements in .

[0081] 2-3) Constraints on renewable energy generation;

[0082]

[0083] That is, in addition to meeting its own active output limits, the active output of renewable energy power generation must be less than the predicted power to meet the restrictions of meteorological conditions.

[0084] 2-4) Energy storage constraints;

[0085]

[0086] in, are the discharge power and charging power of energy storage i at time t respectively; are the maximum discharge power and maximum charging power of energy storage i respectively; is the real-time power measurement value of energy storage i at time t; is the storage capacity of energy storage i at time t, Δt is the time interval of real-time scheduling, usually 5 minutes; They are respectively the maximum and minimum storage capacity of energy storage i at time t.

[0087] Formula (7) describes the relationship between energy storage power and charging and discharging power. Formula (8) establishes whether the energy storage describes the relevant constraints. Formulas (9) and (10) are energy storage power constraints. Formula (11) is the relationship between energy storage energy and power. Formula (12) is the energy storage capacity constraint.

[0088] 2-5) Flexibly adjust demand constraints;

[0089]

[0090] in, is the regulation demand of the upper power grid at time t.

[0091] When the upper power grid issues a positive reserve demand at time t, The flexible adjustment demand constraint adopts equation (13) and equation (15); when the upper power grid issues a negative reserve demand at time t, The flexible adjustment demand constraint adopts formula (14) and formula (15). Among them, formula (15) is the auxiliary variable The lower bound constraint of is set to avoid the infeasibility of the dual optimization problem.

[0092] 3) Use the branch and bound method to solve the distribution network flexible resource real-time scheduling model composed of the objective function of step 1) and the constraints of step 2). The model is a mixed integer linear stochastic programming model. The solution is That is the real-time dispatch output of generator i at time t.

[0093] To implement the above embodiment, a second aspect of the present invention provides a real-time scheduling device for flexible resources in a distribution network, including:

[0094] A model building module is used to build a real-time dispatching model for distribution network flexible resources. The real-time dispatching model for distribution network flexible resources is composed of an objective function and constraints. The distribution network flexible resources include: ordinary generators, new energy units, hydropower stations and energy storage. The objective function minimizes the number of resources to be regulated at the current moment on the basis of satisfying the regulation capacity, while considering the regulation economy.

[0095] The scheduling optimization module is used to solve the real-time scheduling model of the distribution network flexible resources and obtain the scheduling output of each generator in the distribution network at the current moment.

[0096] In a specific implementation of the present invention, the objective function expression is as follows:

[0097]

[0098] Among them, t is the current time; S G represents the set of all generators, and is the set of common generators S T , the set S consisting of new energy units W And the hydropower station constitutes a set S H The union of the three, namely: S G =S T ∪S W ∪S H ; S ES Represents energy storage set; S G and S ES Together they form a collection of flexible resources;

[0099] is the deviation between the actual adjustment amount and the required adjustment amount at time t; is a 0-1 variable indicating whether the i-th resource is adjusted at time t. When it is 1, it means that the resource is adjusted at time t; when When it is 0, it means that the resource is not adjusted in real time at time t, and the power remains at the measured value; c R is the power abandonment cost of new energy units, is the predicted power of new energy unit i at time t, is the electricity price of generator i at time t; is the dispatch output of generator i at time t; σ is the penalty coefficient, ε represents the allowable deviation of adjustment;

[0100] is the regulation cost of energy storage, where c adj is the energy storage unit electricity regulation cost, is the planned storage capacity of energy storage i at time t, It is the storage capacity after real-time dispatch of energy storage i at time t.

[0101] In a specific implementation of the present invention, the constraints include:

[0102] Generator constraints;

[0103]

[0104] Among them, P i min With P i max are the minimum startup power and maximum startup power of generator i respectively; is a binary variable representing the start / stop status of generator i; is the real-time power measurement value of generator i at time t;

[0105] Hydropower plant constraints;

[0106]

[0107] in, is the set of all small hydropower units in hydropower station i, is the start and stop status of small and medium-sized hydropower unit k in hydropower station i, is a binary variable representing the start / stop status of hydropower station i at time t, P i k is the capacity of small and medium-sized hydropower unit k in hydropower station i; Representing a collection The number of elements in ;

[0108] Constraints on renewable energy generation;

[0109]

[0110] Energy storage constraints;

[0111]

[0112]

[0113] in, are the discharge power and charging power of energy storage i at time t respectively; are the maximum discharge power and maximum charging power of energy storage i respectively; is the real-time power measurement value of energy storage i at time t; is the storage capacity of energy storage i at time t, and Δt is the time interval of real-time scheduling; are the maximum and minimum storage capacity of energy storage i at time t respectively;

[0114] Flexible adjustment of demand constraints;

[0115]

[0116] in, is the regulation demand of the upper power grid at time t.

[0117] In a specific implementation of the present invention, it also includes:

[0118] When the upper power grid issues a positive reserve demand at time t, The flexible adjustment demand constraint adopts equation (13) and equation (15); when the upper power grid issues a negative reserve demand at time t, The flexible adjustment demand constraint adopts equation (14) and equation (15).

[0119] This can achieve the goal of using the flexible adjustment capabilities of various resources within the distribution network (including generators and energy storage) to provide support for the upper-level power grid, while minimizing the number of resources that need to be adjusted to avoid frequent resource movements, while ensuring the safety and economy of the overall operation of the distribution network.

[0120] To implement the above embodiment, a third aspect of the present invention provides an electronic device, including:

[0121] at least one processor; and a memory communicatively coupled to the at least one processor;

[0122] The memory stores instructions executable by the at least one processor, and the instructions are configured to execute the above-mentioned method for real-time scheduling of flexible resources in a distribution network.

[0123] To implement the above-mentioned embodiment, the fourth aspect of the present invention proposes a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the above-mentioned method for real-time scheduling of flexible resources in a distribution network.

[0124] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0125] The computer-readable medium may be included in the electronic device, or may exist independently without being installed in the electronic device. The computer-readable medium carries one or more programs, and when the one or more programs are executed by the electronic device, the electronic device executes a method for real-time scheduling of flexible resources in a distribution network according to the above embodiment.

[0126] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate 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 a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0127] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0128] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0129] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0130] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.

[0131] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0132] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0133] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0134] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A real-time scheduling method for flexible resources in a distribution network, characterized in that: include: Constructing a real-time dispatching model for flexible resources in the distribution network, which is composed of an objective function and constraints, wherein the flexible resources in the distribution network include ordinary generators, new energy units, hydropower stations and energy storage, and the objective function minimizes the number of resources to be regulated at the current moment on the basis of satisfying the regulation capacity, while considering the regulation economy; Solve the real-time dispatch model of the distribution network flexible resources to obtain the dispatch output of each generator in the distribution network at the current moment.

2. The method according to claim 1, characterized in that The objective function expression is as follows: Among them, t is the current time; S G represents the set of all generators, and is the set of common generators S T , the set S consisting of new energy units W And the hydropower station constitutes a set S H The union of the three, namely: S G =S T ∪S W ∪S H ; S ES Represents energy storage set; S G and S ES Together they form a collection of flexible resources; is the deviation between the actual adjustment amount and the required adjustment amount at time t; is a 0-1 variable indicating whether the i-th resource is adjusted at time t. When it is 1, it means that the resource is adjusted at time t; when When it is 0, it means that the resource is not adjusted in real time at time t, and the power remains at the measured value; c R is the power abandonment cost of new energy units, is the predicted power of new energy unit i at time t, is the electricity price of generator i at time t; is the dispatch output of generator i at time t; σ is the penalty coefficient, ε represents the allowable deviation of adjustment; is the regulation cost of energy storage, where c adj is the energy storage unit electricity regulation cost, is the planned storage capacity of energy storage i at time t, It is the storage capacity after real-time dispatch of energy storage i at time t.

3. The method according to claim 2, characterized in that The constraints include: Generator constraints; Among them, P i min With P i max are the minimum startup power and maximum startup power of generator i respectively; is a binary variable representing the start / stop status of generator i; is the real-time measured power value of generator i at time t; Hydropower plant constraints; in, is the set of all small hydropower units in hydropower station i, is the start and stop status of small and medium-sized hydropower unit k in hydropower station i, is a binary variable representing the start / stop status of hydropower station i at time t, P i k is the capacity of small and medium-sized hydropower unit k in hydropower station i; Representing a collection The number of elements in ; Constraints on renewable energy generation; Energy storage constraints; in, are the discharge power and charging power of energy storage i at time t respectively; are the maximum discharge power and maximum charging power of energy storage i respectively; is the real-time power measurement value of energy storage i at time t; is the storage capacity of energy storage i at time t, and Δt is the time interval of real-time scheduling; are the maximum and minimum storage capacity of energy storage i at time t respectively; Flexible adjustment of demand constraints; in, is the regulation demand of the upper power grid at time t.

4. The method according to claim 3, characterized in that Also includes: When the upper power grid issues a positive reserve demand at time t, The flexible adjustment demand constraint adopts equation (13) and equation (15); when the upper power grid issues a negative reserve demand at time t, The flexible adjustment demand constraint adopts equation (14) and equation (15).

5. A real-time dispatching device for flexible resources in a distribution network, characterized in that: include: The model building module is used to build a real-time dispatch model for distribution network flexible resources. The real-time dispatch model for distribution network flexible resources is composed of an objective function and constraints. The distribution network flexible resources include: ordinary generators, new energy units, hydropower stations and energy storage. The objective function minimizes the number of resources to be regulated at the current moment on the basis of satisfying the regulation capacity, while considering the regulation economy. The scheduling optimization module is used to solve the real-time scheduling model of the distribution network flexible resources and obtain the scheduling output of each generator in the distribution network at the current moment.

6. The device according to claim 5, characterized in that The objective function expression is as follows: Among them, t is the current time; S G represents the set of all generators, and is the set of common generators S T , the set S consisting of new energy units W And the hydropower station constitutes a set S H The union of the three, namely: S G =S T ∪S W ∪S H ; S ES Represents energy storage set; S G and S ES Together they form a collection of flexible resources; is the deviation between the actual adjustment amount and the required adjustment amount at time t; is a 0-1 variable indicating whether the i-th resource is adjusted at time t. When it is 1, it means that the resource is adjusted at time t; when When it is 0, it means that the resource is not adjusted in real time at time t, and the power remains at the measured value; c R is the power abandonment cost of new energy units, is the predicted power of new energy unit i at time t, is the electricity price of generator i at time t; is the dispatch output of generator i at time t; σ is the penalty coefficient, ε represents the allowable deviation of adjustment; is the regulation cost of energy storage, where c adj is the energy storage unit electricity regulation cost, is the planned storage capacity of energy storage i at time t, It is the storage capacity after real-time dispatch of energy storage i at time t.

7. The device according to claim 6, characterized in that The constraints include: Generator constraints; Among them, P i min With P i max are the minimum startup power and maximum startup power of generator i respectively; is a binary variable representing the start / stop status of generator i; is the real-time measured power value of generator i at time t; Hydropower plant constraints; in, is the set of all small hydropower units in hydropower station i, is the start and stop status of small and medium-sized hydropower unit k in hydropower station i, is a binary variable representing the start / stop status of hydropower station i at time t, P i k is the capacity of small and medium-sized hydropower unit k in hydropower station i; Representing a collection The number of elements in ; Constraints on renewable energy generation; Energy storage constraints; in, are the discharge power and charging power of energy storage i at time t respectively; are the maximum discharge power and maximum charging power of energy storage i respectively; is the real-time power measurement value of energy storage i at time t; is the storage capacity of energy storage i at time t, and Δt is the time interval of real-time scheduling; are the maximum and minimum storage capacity of energy storage i at time t respectively; Flexible adjustment of demand constraints; in, is the regulation demand of the upper power grid at time t.

8. The device according to claim 7, characterized in that Also includes: When the upper power grid issues a positive reserve demand at time t, The flexible adjustment demand constraint adopts equation (13) and equation (15); when the upper power grid issues a negative reserve demand at time t, The flexible adjustment demand constraint adopts equation (14) and equation (15).

9. An electronic device, characterized in that: include: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions executable by the at least one processor, and the instructions are configured to execute the method according to any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method according to any one of claims 1 to 4.

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