CN116245315A - Distributed flexible market clearing method, device, equipment and storage medium - Google Patents
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Abstract
The invention discloses a distributed flexible market clearing method, a device, equipment and a storage medium, which comprise the following steps: s1: establishing a shared power flexibility system; s2: constructing an objective function with the lowest comprehensive operation cost of a distribution system operator; s3: constructing a clearing condition of the objective function; s4: and solving an objective function based on the Gonuo equilibrium to obtain a planning scheme. The beneficial effects of the invention are as follows: the utilization efficiency of distributed new energy can be improved according to the running state of the equipment and the balance of supply and demand.
Description
Technical Field
The invention relates to the technical field of power, in particular to a distributed flexible market clearing method, a device, equipment and a storage medium.
Background
At present, as the distributed new energy has volatility, randomness and difficult accuracy predictability, the increase of the installed capacity of the distributed new energy brings challenges to the safe and stable operation of a power system, the distribution network and a transmission network are tightly coupled due to the large number of distributed new energy access, the splitting operation between the transmission network and the distribution network cannot effectively coordinate the resources between different networks, and the safety risks such as local section limit overrun and local area voltage stability problem are caused.
In the prior art, distributed new energy sources such as distributed power sources, energy storage, adjustable loads and the like in a power distribution network are numerous in quantity and distributed, the utilization efficiency of the distributed new energy sources cannot be improved to the greatest extent, and the problem that the utilization efficiency of the distributed new energy sources cannot be improved according to the running state of equipment and the supply and demand balance exists.
For example, a "a distributed new energy storage device" disclosed in chinese patent literature, its bulletin number: CN109873502a, filing date: in 12 months 2017 and 03, the invention is matched with an electric energy storage module, a control module, a voltage induction module, a new energy conversion electric energy module, a new energy distributed management module and a load energy-saving module, so that the device can partially utilize electric energy generated by new energy, further can fully utilize the electric energy generated by new energy, and provides an efficient and quick new energy storage device for a new energy distribution and utilization process of a user, but has the problem that the utilization efficiency of the distributed new energy cannot be improved according to the running state and supply and demand balance of equipment.
Disclosure of Invention
Aiming at the defect that the prior art can not improve the utilization efficiency of the distributed new energy according to the running state of the equipment and the supply and demand balance, the invention provides a distributed flexible market clearing method, a device, equipment and a storage medium, and can improve the utilization efficiency of the distributed new energy according to the running state of the equipment and the supply and demand balance.
The technical scheme of the invention is as follows, and the distributed flexible market clearing method comprises the following steps:
s1: establishing a shared power flexibility system;
s2: constructing an objective function with the lowest comprehensive operation cost of a distribution system operator;
s3: constructing a clearing condition of the objective function;
s4: and solving an objective function based on the Gonuo equilibrium to obtain a planning scheme.
In the scheme, a shared power flexibility system is established to collect information such as power consumption of a user side, power output of a distributed generator set, power allocation and regional allocation of a power grid, and the like, the lower model of a local flexibility market Gonuo equilibrium model taking the participation of distributed new energy into consideration is an clearing condition of the local flexibility market according to the minimum comprehensive operation cost of a distribution system operator as an objective function according to reduction and interruption power generation cost of the distributed generator set, charge and discharge cost of distributed energy storage, reduction cost of load and translation cost of translatable load, a model result is obtained by solving the objective function by adopting the Gonuo equilibrium model, and a planning scheme is obtained based on the model result and is used for changing the running state of the equipment, so that the utilization efficiency of the distributed new energy is improved.
Preferably, the comprehensive operation cost of the power distribution system operator is determined according to the cut-off power generation cost of the distributed generator set, the charge and discharge cost of the distributed energy storage, the cut-down cost of the reducible load and the translation cost of the translatable load.
In the scheme, the objective function with the lowest comprehensive operation cost of the distribution system operator is constructed based on the reduction of the interruption power generation cost of the distributed generator set, the charge and discharge cost of the distributed energy storage, the reduction cost of the load and the translation cost of the translatable load, and the objective function can be constructed based on the actual conditions of the distributed generator set, the distributed energy storage and other devices, so that the optimal planning scheme of the distributed generator set, the distributed energy storage and other devices is analyzed, and the utilization efficiency of distributed new energy is improved. The objective function of the operating cost of the distribution system operator is as follows:
in the above formula, P is the price,
to reduce the cost of generating power of the unit; />
Cost for shutting down the generator set; />
The cost of charging the stored energy; />
The cost of energy storage and discharge; />
Cost for cutting down load; />
Cost for moving translatable loads.
Preferably, the clearing condition is determined according to equipment operation state constraint and flexible supply-demand balance constraint, wherein the equipment operation state constraint comprises operation state constraint of a distributed generator set, operation state constraint of energy storage, operation state constraint capable of reducing load and operation state constraint capable of translating load.
Preferably, the objective function is solved based on the Gonuo equilibrium, comprising the following steps:
s41: obtaining a first model based on the clearing condition and the upper layer optimization model;
s42: solving the first model to obtain KKT conditions of market members;
s43: obtaining a second model based on the KKT conditions of all market members;
s44: and solving the second model based on CPLEX and obtaining a model result.
In this scheme, the model of the objective function is similar to the gulo equalization model, and the solution to the objective function includes: substituting the clearing conditions of the local flexible market into the upper-layer optimization model to obtain a single-layer optimization model; on the basis, the first order KKT (Karush Kuhn Tucker) optimal conditions of each market member single-layer optimization model are obtained through sequential solving. Finally, the KKT conditions of all market members are considered simultaneously, so that a new unified single-layer optimization model is obtained. The new model after transformation belongs to the mixed integer quadratic programming problem. And finally, solving the mixed integer quadratic programming problem by using optimization software CPLEX to obtain a model result, and further obtaining a programming scheme.
Preferably, the running state constraint of the distributed generator set comprises a reducible unit running state constraint and an interruptible unit running state constraint, the running state constraint of the energy storage comprises a charge and discharge amount constraint, an electric quantity state constraint, a power constraint and a continuity constraint, the running state constraint of the reducible load comprises a state constraint, a state continuity constraint, a cutting-off frequency constraint, a minimum interval time constraint between two times of cutting off of the load and a maximum cutting-off time constraint, and the running state constraint of the translatable load comprises a starting moment constraint, and a same constraint and a running constraint of the power consumption curves before and after translation.
In the scheme, the running state constraint of the distributed generator set comprises a reducible unit running state constraint and an interruptible unit running state constraint.
The unit operation state constraint can be reduced as follows:
the operational state constraint of the interruptible unit is as follows:
in the method, in the process of the invention,
the generating capacity of the generator set g can be reduced at the moment t; />
The normal power generation amount of the generator set g at the moment t; />
Shutting down the reduced power generation amount of the generator set g at the moment t; />
If the variable is 0-1, the generator set is turned off and then is 1, otherwise, the variable is 0; />
The normal power generation amount of the generator set g at the moment t.
The operation state constraint of the energy storage comprises charge and discharge amount constraint, electric quantity state constraint, power constraint and continuity constraint:
the charge and discharge amount constraint is as follows:
the state of charge constraints are as follows:
the power constraints are as follows:
the continuity constraint is as follows:
in the method, in the process of the invention,
the charge amount of the energy storage b at the time t; />
A maximum charge amount for the stored energy b; />
The discharge capacity of the energy storage b at the moment t; />
Is the maximum discharge of the stored energy b; />
The residual electric quantity of the energy storage b at the moment t; />
Is the minimum capacity of the stored energy b; />
Is the maximum capacity of the stored energy b; />
The charge and discharge power of the energy storage b at the moment t; />
Is the minimum power of the stored energy b; />
Is the maximum power of the stored energy b.
The operating state constraints that can cut down the load include a state constraint, a state continuity constraint, a cut-off number constraint, a minimum interval time constraint between two cuts of the load, and a maximum cut-off time constraint.
The state constraints are as follows:
the state continuity constraints are as follows:
the number of cuts is constrained as follows:
the minimum interval time constraint between load cuts off is as follows:
the maximum off time constraint is as follows:
in the method, in the process of the invention,
a variable of 0-1, wherein the cut-off possible load k is 1 when the cut-off is started at the time t, and otherwise, the cut-off possible load k is 0; />
A variable of 0-1, wherein at the moment t, the load k which can be cut down is 1 when being disconnected, otherwise, the load k is 0; />
A variable of 0-1, wherein the cut-off load k is 1 when the cut-off is finished at the time t, and otherwise, the cut-off load k is 0; />
The maximum cutting frequency of the load k can be reduced; />
To reduce the minimum interval time between two cuts of the load k; />
To reduce the maximum cut-off duration of the load k.
The operation state constraint of the translatable load comprises a start time constraint, a same constraint of the power consumption curve before and after translation and an operation constraint:
the start-up time constraints are as follows:
the same constraint of the power consumption curve before and after the translation is as follows:
the operational constraints are as follows:
in the method, in the process of the invention,
the latest possible end time for translatable load k within translatable period c; />
Is the earliest possible start time (++) of the translatable load k within translatable period c>
And->
The middle is the translatable period c); />
A normal end time for translatable load k within translatable period c; />
A normal start time for the translatable load k within translatable period c; omega k , t The electricity consumption of the translatable load k at the time t after translation; />
The normal electricity consumption of the translatable load k at the moment t; gamma ray k,t A variable of 0-1, 1 if the translatable load k is translated to time t, or 0 if gamma k,t ＝1，ρ k ,c ＝t；ρ k ,c Representing a translatable load k translated to ρ during translatable period c k ,c Time of day.
Preferably, the flexible supply-demand balance constraint includes an up-regulation flexible supply-demand balance constraint and a down-regulation flexible supply-demand balance constraint.
In the scheme, the flexible supply and demand balance constraint comprises an up-regulation flexible supply and demand balance constraint and a down-regulation flexible supply and demand balance constraint. The up-regulation flexibility supply-demand balance constraint is as follows:
the down-regulation flexibility supply-demand balance constraint is as follows:
in the method, in the process of the invention,
the charge amount of the energy storage b at the time t; />
The discharge capacity of the energy storage b at the moment t; />
The generating capacity of the generator set g can be reduced at the moment t; />
Shutting down the reduced power generation amount of the generator set g at the moment t; omega k,t The electricity consumption of the translatable load k at the time t after translation; />
The normal electricity consumption of the translatable load k at the moment t; />
The normal electricity consumption of the load k can be reduced for the moment t; />
A variable of 0-1, wherein the cut-off possible load k is 1 when the cut-off is started at the time t, and otherwise, the cut-off possible load k is 0; />
A variable of 0-1, wherein at the moment t, the load k which can be cut down is 1 when being disconnected, otherwise, the load k is 0; />
Is a flexible requirement for power distribution system operators.
A distributed flexible market clearing device, comprising:
the flexibility acquisition module is used for acquiring and counting flexibility supply of different users;
the dispatching cost acquisition module is used for acquiring and counting comprehensive operation cost of the power distribution system operators;
the clearing module is used for determining equipment running state constraint and flexible supply-demand balance constraint;
the analysis module is used for analyzing and calculating to obtain a planning scheme;
and the execution module is used for adjusting the distributed new energy according to the planning scheme.
In the scheme, the flexibility acquisition module acquires and counts the flexibility supply of different users, the scheduling cost acquisition module acquires and counts the comprehensive operation cost of the power distribution system operators, the clearing module determines the equipment operation state constraint and the flexibility supply and demand balance constraint, the analysis module analyzes and calculates to obtain a planning scheme, the execution module adjusts the distributed new energy according to the planning scheme, and the utilization efficiency of the distributed new energy can be improved according to the equipment operation state and the supply and demand balance.
A distributed flexible market clearing device comprising: the system memory is connected with the processing unit through the network adapter, and the processing unit is connected with the external equipment and the display through the I/O interface.
Preferably, the system memory is one or more of RAM, cache and storage systems, the system memory having program means stored therein.
A storage medium storing a computer program which when executed by a processor implements a distributed flexible marketing method.
The beneficial effects of the invention are as follows: the utilization efficiency of distributed new energy can be improved according to the running state of the equipment and the balance of supply and demand.
Drawings
FIG. 1 is a schematic diagram of a distributed flexible market clearing device of the present invention.
FIG. 2 is a flow chart of a distributed flexible market clearing method of the present invention.
FIG. 3 is a schematic diagram of a distributed flexible market clearing apparatus of the present invention.
In the figure 1, a flexibility acquisition module; 2. a scheduling cost acquisition module; 3. a clearing module; 4. an analysis module; 5. an execution module; 12. an apparatus; 14. an external device; 16. a processing unit; 18. a bus; 20. a network adapter; 22. an I/O interface; 24. a display; 28. a system memory; 30. a RAM; 32. a cache; 34. a storage system; 40. a program tool; 42. program modules.
Detailed Description
The technical scheme of the invention is further specifically described below through examples and with reference to the accompanying drawings.
Embodiment one: as shown in fig. 1, a distributed flexible market clearing device is implemented in a software and/or hardware manner, and the device can be configured in a terminal device. The device comprises:
the flexibility acquisition module 1 is used for acquiring and counting flexibility supplies of different users;
the dispatching cost acquisition module 2 is used for acquiring and counting comprehensive operation cost of the power distribution system operators;
the clearing module 3 is used for determining equipment running state constraint and flexible supply-demand balance constraint;
the analysis module 4 is used for analyzing and calculating to obtain a planning scheme;
and the execution module 5 is used for adjusting the distributed new energy according to the planning scheme.
In the embodiment of the device, each unit and module included are only divided according to the functional logic, but are not limited to the above division, so long as the corresponding functions can be realized; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.
Embodiment two: as shown in fig. 2, a distributed flexible market clearing method includes the steps of:
s1: establishing a shared power flexibility system;
s2: constructing an objective function with the lowest comprehensive operation cost of a distribution system operator;
s3: constructing a clearing condition of the objective function;
s4: and solving an objective function based on the Gonuo equilibrium to obtain a planning scheme.
Step S1, a shared power flexible system is established. Participants in the shared power flexibility system include: users, grids, energy storage investors, and distributed generator sets. And acquiring and counting flexibility supplies of different users through a flexibility acquisition module. And further, based on the power data of the power flexibility system, predicting the power output and consumption in a future period of time through machine learning.
And S2, determining that the comprehensive operation cost of the power distribution system operator is the lowest as an objective function according to the reduction and interruption power generation cost, the charge and discharge cost of the distributed energy storage, the reduction cost of the reducible load and the translation cost of the translatable load of the distributed generator set. And acquiring and counting comprehensive operation cost of the power distribution system operators through a dispatching cost acquisition module. The objective function of the operating cost of the distribution system operator is as follows:
in the above formula, P is the price,
to reduce the cost of generating power of the unit; />
Cost for shutting down the generator set; />
The cost of charging the stored energy; />
The cost of energy storage and discharge; />
Cost for cutting down load; />
Cost for moving translatable loads.
And step S3, determining the clearing conditions of the local flexible market and the like according to the equipment running state constraint and the flexible supply and demand balance constraint. The lower model of the local flexibility market Gonuo equilibrium model taking into consideration the participation of distributed new energy is the clearing condition of the local flexibility market, and the clearing condition is determined according to the equipment running state constraint and the flexibility supply and demand equilibrium constraint. And determining equipment running state constraint and flexible supply and demand balance constraint through a clearing module.
The equipment operation state constraint comprises an operation state constraint of a distributed generator set, an operation state constraint of energy storage, an operation state constraint capable of reducing load and an operation state constraint capable of translating load.
The running state constraint of the distributed generator set comprises a reducible unit running state constraint and an interruptible unit running state constraint.
The unit operation state constraint can be reduced as follows:
the operational state constraint of the interruptible unit is as follows:
in the method, in the process of the invention,
the generating capacity of the generator set g can be reduced at the moment t; />
The normal power generation amount of the generator set g at the moment t; />
Shutting down the reduced power generation amount of the generator set g at the moment t; />
If the variable is 0-1, the generator set is turned off and then is 1, otherwise, the variable is 0; />
The normal power generation amount of the generator set g at the moment t.
The operation state constraint of the energy storage comprises charge and discharge amount constraint, electric quantity state constraint, power constraint and continuity constraint:
the charge and discharge amount constraint is as follows:
the state of charge constraints are as follows:
the power constraints are as follows:
the continuity constraint is as follows:
in the method, in the process of the invention,
the charge amount of the energy storage b at the time t; />
A maximum charge amount for the stored energy b; />
The discharge capacity of the energy storage b at the moment t; />
Is the maximum discharge of the stored energy b; />
The residual electric quantity of the energy storage b at the moment t; />
Is the minimum capacity of the stored energy b; />
Is the maximum capacity of the stored energy b; />
The charge and discharge power of the energy storage b at the moment t; />
Is the minimum power of the stored energy b;
is the maximum power of the stored energy b.
The operating state constraints that can cut down the load include a state constraint, a state continuity constraint, a cut-off number constraint, a minimum interval time constraint between two cuts of the load, and a maximum cut-off time constraint.
The state constraints are as follows:
the state continuity constraints are as follows:
the number of cuts is constrained as follows:
the minimum interval time constraint between load cuts off is as follows:
the maximum off time constraint is as follows:
in the method, in the process of the invention,
a variable of 0-1, wherein the cut-off possible load k is 1 when the cut-off is started at the time t, and otherwise, the cut-off possible load k is 0; />
A variable of 0-1, wherein at the moment t, the load k which can be cut down is 1 when being disconnected, otherwise, the load k is 0; />
A variable of 0-1, wherein the cut-off load k is 1 when the cut-off is finished at the time t, and otherwise, the cut-off load k is 0; />
The maximum cutting frequency of the load k can be reduced; />
To reduce the minimum interval time between two cuts of the load k; />
To reduce the maximum cut-off duration of the load k.
The operation state constraint of the translatable load comprises a start time constraint, a same constraint of the power consumption curve before and after translation and an operation constraint:
the start-up time constraints are as follows:
the same constraint of the power consumption curve before and after the translation is as follows:
the operational constraints are as follows:
in the method, in the process of the invention,
the latest possible end time for translatable load k within translatable period c; />
Is the earliest possible start time (++) of the translatable load k within translatable period c>
And->
The middle is the translatable period c); />
A normal end time for translatable load k within translatable period c; />
A normal start time for the translatable load k within translatable period c; omega k , t The electricity consumption of the translatable load k at the time t after translation; />
The normal electricity consumption of the translatable load k at the moment t; gamma ray k,t A variable of 0-1, 1 if the translatable load k is translated to time t, or 0 if gamma k,t ＝1，ρ k ,c ＝t；ρ k ,c Representative ofTranslating the translatable load k to ρ during translatable period c k ,c Time of day.
The flexible supply-demand balance constraint comprises an up-regulation flexible supply-demand balance constraint and a down-regulation flexible supply-demand balance constraint.
The up-regulation flexibility supply-demand balance constraint is as follows:
the down-regulation flexibility supply-demand balance constraint is as follows:
in the method, in the process of the invention,
the charge amount of the energy storage b at the time t; />
The discharge capacity of the energy storage b at the moment t; />
The generating capacity of the generator set g can be reduced at the moment t; />
Shutting down the reduced power generation amount of the generator set g at the moment t; omega k,t The electricity consumption of the translatable load k at the time t after translation; />
The normal electricity consumption of the translatable load k at the moment t; />
The normal electricity consumption of the load k can be reduced for the moment t; />
A variable of 0-1, wherein the cut-off possible load k is 1 when the cut-off is started at the time t, and otherwise, the cut-off possible load k is 0; />
A variable of 0-1, wherein at the moment t, the load k which can be cut down is 1 when being disconnected, otherwise, the load k is 0; />
Is a flexible requirement for power distribution system operators.
Step S4, the model of the objective function is similar to a Gonuo equilibrium model, and the method for solving the objective function comprises the following steps: substituting the clearing conditions of the local flexible market into the upper-layer optimization model to obtain a single-layer optimization model; on the basis, the first order KKT (Karush Kuhn Tucker) optimal conditions of each market member single-layer optimization model are obtained through sequential solving. Finally, the KKT conditions of all market members are considered simultaneously, so that a new unified single-layer optimization model is obtained. The new model after transformation belongs to the mixed integer quadratic programming problem. And finally, solving the mixed integer quadratic programming problem by using optimization software CPLEX to obtain a model result, and further obtaining a programming scheme. And analyzing and calculating by an analysis module to obtain a planning scheme.
Embodiment III: a distributed flexible market clearing device provides services for realizing a distributed flexible market clearing method in a second embodiment, and a distributed flexible market clearing device in a first embodiment can be configured. Fig. 3 illustrates a block diagram of an exemplary device 12 suitable for use in implementing embodiments of the present invention. The device 12 shown in fig. 3 is merely an example and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.
As shown in fig. 3, device 12 is in the form of a general purpose computing device. Components of device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects the various system components including the system memory 28 and the processing units 16.
The I/O interface 22 connects the external device 14, the display 24, and the processing unit 16 connects the system memory 28 through the network adapter 20.
The system memory 28 may include computer system readable media in the form of volatile memory, such as RAM30 and/or cache 32, which is random access memory. Device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from or write to non-removable, nonvolatile magnetic media (not shown in FIG. 3, commonly referred to as a "hard disk drive"). Although not shown in fig. 3, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of embodiments of the invention.
A program tool 40 having a set (at least one) of program modules 42 may be stored in, for example, memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods of the embodiments described herein.
The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, for example, implementing a distributed flexible marketing method provided by the second embodiment of the present invention.
Embodiment four: a storage medium, computer-executable instructions, when executed by a computer processor, for performing a distributed flexible marketing method of the second embodiment.
The storage media of embodiments of the present invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present invention may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
Of course, a storage medium containing computer-executable instructions provided by embodiments of the present invention is not limited to the method operations described above.
The above disclosure is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention, which is defined by the appended claims.
Claims (10)
1. A distributed flexible marketing method, comprising the steps of:
s1: establishing a shared power flexibility system;
s2: constructing an objective function with the lowest comprehensive operation cost of a distribution system operator;
s3: constructing a clearing condition of the objective function;
s4: and solving an objective function based on the Gonuo equilibrium to obtain a planning scheme.
2. The distributed flexible market clearing method according to claim 1, wherein the comprehensive operation cost of the power distribution system operator is determined according to cut-off power generation cost of the distributed generator set, charge and discharge cost of the distributed energy storage, cut-down cost of the reducible load and translation cost of the translatable load.
3. The distributed flexible market clearing method of claim 1, wherein the clearing condition is determined based on equipment operating state constraints and flexible supply-demand balance constraints, the equipment operating state constraints comprising operating state constraints of the distributed generator set, operating state constraints of the stored energy, operating state constraints of the load that can be cut down, and operating state constraints of the load that can be translated.
4. The distributed flexible market clearing method according to claim 1, wherein the objective function is solved based on the gulo-equilibrium, comprising the steps of:
s41: obtaining a first model based on the clearing condition and the upper layer optimization model;
s42: solving the first model to obtain KKT conditions of market members;
s43: obtaining a second model based on the KKT conditions of all market members;
s44: and solving the second model based on CPLEX and obtaining a model result.
5. A distributed flexible market clearing method according to claim 1 or 3, wherein the running state constraints of the distributed generator set include a reducible set running state constraint and an interruptible set running state constraint, the running state constraints of the stored energy include a charge and discharge amount constraint, an electric quantity state constraint, a power constraint and a continuity constraint, the running state constraints of the reducible load include a state constraint, a state continuity constraint, a cut-off number constraint, a minimum interval time constraint between two cuts of the load and a maximum cut-off time constraint, and the running state constraints of the translatable load include a start-time constraint, a same constraint of power curves before and after translation and a running constraint.
6. A distributed flexible market clearing method according to claim 1 or 3 wherein the flexible supply and demand balance constraints comprise an up-regulation flexible supply and demand balance constraint and a down-regulation flexible supply and demand balance constraint.
7. A distributed flexible market clearing device adapted for use in a distributed flexible market clearing method according to any one of claims 1-6, comprising:
the flexibility acquisition module is used for acquiring and counting flexibility supply of different users;
the dispatching cost acquisition module is used for acquiring and counting comprehensive operation cost of the power distribution system operators;
the clearing module is used for determining equipment running state constraint and flexible supply-demand balance constraint;
the analysis module is used for analyzing and calculating to obtain a planning scheme;
and the execution module is used for adjusting the distributed new energy according to the planning scheme.
8. A distributed flexible market clearing device, comprising: the system memory is connected with the processing unit through the network adapter, and the processing unit is connected with the external equipment and the display through the I/O interface.
9. The distributed flexible marketing apparatus of claim 8, wherein the system memory is one or more of RAM, cache and storage systems, and wherein the system memory has program means stored therein.
10. A storage medium storing a computer program, wherein the computer program when executed by a processor implements a distributed flexible marketing method as claimed in any one of claims 1-6.
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| CN202310054588.8A CN116245315A (en) | 2023-02-03 | 2023-02-03 | Distributed flexible market clearing method, device, equipment and storage medium |
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| CN202310054588.8A CN116245315A (en) | 2023-02-03 | 2023-02-03 | Distributed flexible market clearing method, device, equipment and storage medium |
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