CN116976601A - Virtual power plant flexible adjustable resource optimal scheduling method and system - Google Patents
Virtual power plant flexible adjustable resource optimal scheduling method and system Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
- H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
Abstract
The application provides a flexible adjustable resource optimization scheduling method for a virtual power plant, which comprises the following steps: calculating the building adjustable load and the charging pile adjustable value load in a preset area through a flexible adjustable resource model to obtain the building total load power and the charging pile total load power; generating virtual power consumption demand instructions for a plurality of subareas according to the total load power of the building and the total load power of the charging piles based on real-time demands and system constraints; judging whether the difference value between the virtual power consumption demand instruction and the corresponding actual power consumption demand value exceeds a threshold value or not; and when the threshold value is exceeded, rescheduling and distributing power resources formed by building adjustable loads and charging pile adjustable value loads of all subareas in the area by using a preset optimization algorithm. The optimal scheduling method provided by the application can realize the generation of virtual power consumption demand instructions based on real-time demands and system constraints of the virtual power plant, and then rescheduling and distributing the virtual power consumption demand instructions, thereby improving the power consumption efficiency.
Description
Technical Field
The application relates to the technical field of power regulation, in particular to a flexible adjustable resource optimization scheduling method and system for a virtual power plant.
Background
With the progress of technology, the power consumption of a power plant obtained by computer virtual operation has become a mainstream, and the virtual power plant technology can be applied in a wide range to realize the optimal scheduling of distributed power sources and integrate a large number of distributed power sources and flexible adjustable resource loads.
Disclosure of Invention
In view of the above problems, the application provides a flexible and adjustable resource optimization scheduling method and system for a virtual power plant, so as to solve the technical problem that the current virtual power plant has no function of self-updating and distributing power better for resource optimization scheduling.
In order to achieve the above purpose, the present application adopts the following technical scheme:
in a first aspect, the present application provides a flexible and adjustable resource optimization scheduling method for a virtual power plant, where the optimization scheduling method includes:
calculating building adjustable load and charging pile adjustable value load in a preset area through a flexible adjustable resource model of the virtual power plant by a central processing unit to obtain building total load power and charging pile total load power;
generating virtual power consumption demand instructions corresponding to a plurality of subareas in the preset area respectively by the central processing unit based on real-time demands and system constraints of the virtual power plant according to the total building load power and the total charging pile load power;
judging whether the difference value between the virtual power consumption demand instruction and the corresponding actual power consumption demand value exceeds a threshold value or not by the central processing unit;
and when the threshold value is exceeded, rescheduling and distributing power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area by the central processing unit through a preset optimizing algorithm using the flexible adjustable resource model.
As an alternative embodiment, in calculating, by a central processor, the building adjustable load and the charging pile adjustable value load in the preset area through the flexible adjustable resource model of the virtual power plant, the optimal scheduling method includes:
calculating, by a central processing unit, the building adjustable load of a building area within the preset area through a flexible adjustable resource model of the virtual power plant;
and calculating the adjustable value load of the charging piles in the charging pile area in a preset area through the flexible adjustable resource model of the virtual power plant by the central processing unit.
As an optional implementation manner, in generating, by the central processing unit, virtual power consumption demand instructions corresponding to a plurality of sub-regions in the preset region, the optimal scheduling method includes:
and generating virtual power consumption demand instructions corresponding to the time energy consumption, the daily energy consumption, the Zhou Haoneng amount, the month energy consumption and the season energy consumption of the sub-areas in the preset area respectively by an addition logic circuit of the central processing unit.
As an optional implementation manner, in the determining, by the central processing unit, whether the difference value between the virtual power consumption demand instruction and the corresponding actual power consumption demand value exceeds a threshold, the optimal scheduling method includes:
and judging whether the difference value between the virtual power consumption demand instruction and the corresponding actual power consumption demand value exceeds a threshold value by the central processing unit according to the lookup table in the memory of the central processing unit, and returning to the central processing unit to calculate the building adjustable load and the charging pile adjustable value load in the preset area through the flexible adjustable resource model of the virtual power plant under the condition that the difference value does not exceed the threshold value.
As an alternative embodiment, in the case when the threshold value is exceeded, the central processing unit reschedules and allocates the power resource formed by the building adjustable load and the charging pile adjustable value load of each sub-area within the preset area by using a preset optimization algorithm of the flexible adjustable resource model, the optimal scheduling method includes:
when the first threshold value is exceeded, rescheduling and distributing the power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area in a system constraint mode through a preset optimization algorithm using the flexible adjustable resource model by the central processing unit; or (b)
And when the second threshold value is exceeded, rescheduling and distributing the power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area by the central processing unit through a preset optimization algorithm using the flexible adjustable resource model.
In a second aspect, the present application provides a flexible and adjustable resource optimization scheduling system for a virtual power plant, where the optimization scheduling system is applicable to a flexible and adjustable resource optimization scheduling method for a virtual power plant, and the optimization scheduling system includes:
the first calculation module is used for controlling the central processing unit to calculate the building adjustable load and the charging pile adjustable value load in a preset area through the flexible adjustable resource model of the virtual power plant, and obtaining the building total load power and the charging pile total load power;
the first generation module is used for controlling the central processing unit to generate virtual power consumption demand instructions corresponding to a plurality of subareas in the preset area respectively according to the total building load power and the total charging pile load power based on real-time demands and system constraints of the virtual power plant;
the first judging module is used for controlling the central processing unit to judge whether the difference value between the virtual power consumption demand instruction and the corresponding actual power consumption demand value exceeds a threshold value or not;
and the first scheduling module controls the central processing unit to reschedule and allocate power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area through a preset optimization algorithm using the flexible adjustable resource model under the condition that the threshold value is exceeded.
As an alternative embodiment, the optimal scheduling system includes:
the second calculation module is used for controlling the central processing unit to calculate the building adjustable load of the building area in the preset area through the flexible adjustable resource model of the virtual power plant;
and the third calculation module is used for controlling the central processing unit to calculate the adjustable value load of the charging pile in the charging pile area in the preset area through the flexible adjustable resource model of the virtual power plant.
As an alternative embodiment, the optimal scheduling system includes:
the second generation module controls the addition logic circuit of the central processing unit to generate virtual power consumption demand instructions corresponding to the time energy consumption, the daily energy consumption, the Zhou Haoneng energy consumption, the month energy consumption and the season energy consumption of the sub-areas in the preset area respectively.
As an alternative embodiment, the optimal scheduling system includes:
and the second judging module is used for controlling the central processing unit to judge whether the difference value between the virtual power consumption demand instruction and the corresponding actual power consumption demand value exceeds a threshold value according to the lookup table in the memory of the central processing unit, and when the difference value does not exceed the threshold value, the first calculating module is used for controlling the central processing unit to calculate the building adjustable load and the charging pile adjustable value load in a preset area through the flexible adjustable resource model of the virtual power plant.
As an optional implementation manner, the optimal scheduling method includes:
the second scheduling module controls the central processing unit to reschedule and allocate power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area in a system constraint way by using a preset optimization algorithm of the flexible adjustable resource model under the condition that the first threshold value is exceeded;
and the third scheduling module controls the central processing unit to carry out external system constraint on power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area through a preset optimization algorithm using the flexible adjustable resource model under the condition that the second threshold value is exceeded.
In a third aspect, the present application provides an electronic device, the electronic device including a memory for storing a computer program and a processor that runs the computer program to cause the electronic device to execute the above-described optimal scheduling method.
In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program for implementing an electronic device used in the above-described optimal scheduling method.
The application provides a flexible adjustable resource optimization scheduling method for a virtual power plant, which comprises the following steps: calculating the building adjustable load and the charging pile adjustable value load in a preset area through a flexible adjustable resource model to obtain the building total load power and the charging pile total load power; generating virtual power consumption demand instructions for a plurality of subareas according to the total load power of the building and the total load power of the charging piles based on real-time demands and system constraints; judging whether the difference value between the virtual power consumption demand instruction and the corresponding actual power consumption demand value exceeds a threshold value or not; and when the threshold value is exceeded, rescheduling and distributing power resources formed by building adjustable loads and charging pile adjustable value loads of all subareas in the set area by using a preset optimization algorithm. The optimal scheduling method provided by the application can realize the generation of virtual power consumption demand instructions based on real-time demands and system constraints of the virtual power plant, and then rescheduling and distributing the virtual power consumption demand instructions, thereby improving the power consumption efficiency. Furthermore, the preset optimization algorithm for judging the flexible adjustable resource model through different conditions of multiple threshold allocation respectively reschedules and allocates the internal or external constraints of the system to each subarea in the preset area, so that the flexible resource model has more flexibility.
In order to make the above objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope of the present application.
FIG. 1 is a flow chart of a method for optimizing and dispatching flexible and adjustable resources of a virtual power plant.
FIG. 2 is a block diagram of a flexible and adjustable resource optimization scheduling system for a virtual power plant.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments.
The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
The terms "comprises," "comprising," "including," or any other variation thereof, are intended to cover a specific feature, number, step, operation, element, component, or combination of the foregoing, which may be used in various embodiments of the present application, and are not intended to first exclude the presence of or increase the likelihood of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Referring to fig. 1, fig. 1 is a flowchart of a method for optimizing and scheduling flexible and adjustable resources of a virtual power plant. The optimal scheduling method for the flexible adjustable resource of the virtual power plant comprises the following steps:
s1, calculating the building adjustable load and the charging pile adjustable value load in a preset area through the flexible adjustable resource model of the virtual power plant by a central processing unit, and obtaining the building total load power and the charging pile total load power.
In one embodiment, the central processing unit calculates the building adjustable load and the charging pile adjustable value load in the preset area through a flexible adjustable resource model of the virtual power plant (Virtual Power Plant, VPP), and obtains the building total load power and the charging pile total load power obtained under the operation of the virtual power plant. In this embodiment, only the building adjustable load and the charging pile adjustable value load are calculated, and because the two power consumption amounts belong to a higher energy consumption proportion in the virtual power plant, in other embodiments, the adjustable loads such as street lamps, advertisement screen signboards, traffic lights and the like can be calculated, and the application is not limited by this. For example, the virtual power plant can organically combine a distributed generator set, controllable loads and distributed energy storage facilities, realizes a carrier for integrated regulation and control of various distributed energy sources through a matched regulation and control technology and a communication technology, can be used as a special virtual power plant to participate in a coordination management system for electric power market and power grid operation, can also be used as a positive power plant to supply power to a system for peak shaving, and can also be used as a negative power plant to increase load absorption and match with the system for filling the valley. For example, under the concept of regional division of a preset region, a central processing unit can calculate building adjustable loads (such as air conditioning energy consumption, photovoltaic motor sets and wind power sets of a building) of a building region in the preset region through a flexible adjustable resource model of a virtual power plant, and in addition, the photovoltaic motor sets and the wind power sets can generate solar energy and wind power energy for counteracting power consumption loads such as air conditioning, running motor sets and the like in the building. The central processing unit calculates the adjustable load of the charging piles in the charging pile area in the preset area (for example, the power consumption of the charging pile base station in a specific time range) through the flexible adjustable resource model of the virtual power plant, and a general driving family or level bicycle user can charge the electric energy automobile by using the charging piles in the charging pile area in the normal use area at night, so that the virtual power plant can calculate the power consumption of the charging pile area in the night time range larger than the power consumption in the daytime time range through the flexible adjustable resource model so as to strengthen the power supply of the charging pile area, and the power distribution flexibility is improved.
S2, generating virtual power consumption demand instructions corresponding to a plurality of subareas in the preset area respectively by the central processing unit based on real-time demands and system constraints of the virtual power plant according to the total load power of the building and the total load power of the charging pile.
In an embodiment, real-time demand based on virtual power plants can be regarded as a business scenario of demand side response, frequency modulation service, electric auxiliary service, electric market transaction, deviation assessment compensation service, energy efficiency management and the like as an influence factor. In the application, the real-time demand of the virtual power plant can achieve the necessary trend and requirement that the response of the minute level and the second level is the future development, the real-time performance, the reliability and the trafficability of the control of the virtual power plant are effectively enhanced, in other words, the virtual power consumption demand instructions corresponding to the time energy consumption, the daily energy consumption, the Zhou Haoneng amount, the month energy consumption and the season energy of a plurality of subareas in a preset area can be generated by the addition logic circuit of the central processing unit. The system constraints of a virtual power plant may be considered as operating conditions of the power system, referring to various technical and economic requirements that the system needs to meet during normal operation. The system constraints of a virtual power plant may be defined, but are not limited, in terms of: stability: when the power system normally operates, the electrical parameters should be kept stable, and the stable state can be quickly recovered when an emergency occurs; reliability: the power system has enough toughness and redundancy to cope with different fault conditions, and the continuity and safety of power supply are ensured; load supply: the power system should be able to meet a variety of load requirements, including base load, peak load, and special power requirements; energy efficiency: the power system should improve energy utilization efficiency as much as possible while meeting load demands, reduce line loss, transformer loss, etc. The energy efficiency can be measured by indexes such as line loss rate, equipment efficiency and the like; flexibility: the power system has good scheduling and control capability so as to cope with emergency situations such as load change, equipment failure and the like, so that the application is embodied, real-time requirements and system constraints are fully considered to specifically explain how the virtual power plant perfects the fine operation of electric energy consumption and distribution.
And S3, judging whether the difference value between the virtual power consumption demand instruction and the corresponding actual power consumption demand value exceeds a threshold value or not by the central processing unit.
In one embodiment, the central processing unit judges whether the difference value between the virtual power consumption demand instruction and the corresponding actual power consumption demand value exceeds a threshold value according to the lookup table in the memory of the central processing unit, and returns to S1 when the difference value does not exceed the threshold value, the central processing unit calculates the building adjustable load and the charging pile adjustable value load in the preset area through the flexible adjustable resource model of the virtual power plant, and the process goes to S4 when the difference value exceeds the threshold value. It should be noted that, the lookup table in the cpu memory may be a historical power consumption lookup table stored according to the historical power consumption, or the lookup table in the cpu may be a real-time updated power consumption lookup table stored in a preset area and a place other than the preset area according to the current power consumption, so as to compare whether the difference between the virtual power consumption demand command and the corresponding actual power consumption demand value exceeds the threshold, for example, the difference is a minor error between 1% and 5%, the difference is a medium error between 5% and 10%, and the difference is an off-average error between 10% and 20%.
And S4, when the threshold value is exceeded, rescheduling and distributing power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area by the central processing unit through a preset optimization algorithm using the flexible adjustable resource model.
In an embodiment, when the first threshold value is exceeded (for example, the difference value is a small error between 1% and 5%), the central processor performs rescheduling and allocation of the intra-system constraint on the power resources formed by the building adjustable load and the charging pile adjustable value load of each sub-area in the preset area through a preset optimization algorithm using the flexible adjustable resource model, so that when the difference value is small, the optimal scheduling method performs rescheduling and allocation of the intra-system constraint on the power resources formed by the adjustable load and the charging pile adjustable value load, in other words, the intra-system constraint can perform central scheduling and allocation of electric energy conveniently and rapidly, and flexibility is improved. On the other hand, when the second threshold value is exceeded (for example, the difference value is 10% -20% of the mean value error), the central processing unit performs rescheduling and allocation of system external constraints on the power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area through a preset optimization algorithm using the flexible adjustable resource model (for example, the central processing unit performs power support scheduling through a channel communication connection utility power bureau or a power saving bureau which is generated in advance by a communication circuit), in other words, the application judges that the preset optimization algorithm of the flexible adjustable resource model performs rescheduling and allocation of system internal or external constraints on each subarea in the preset area respectively through different situations of multiple threshold value allocation, and the virtual power plant of the application can also perform rescheduling and allocation of system internal and external constraints simultaneously so as to prevent inconvenience caused by system faults and has flexibility and accuracy.
Referring to fig. 2, fig. 2 is a schematic block diagram of a flexible adjustable resource optimization scheduling system for a virtual power plant. The application provides a flexible adjustable resource optimal scheduling system of a virtual power plant, which is suitable for a flexible adjustable resource optimal scheduling method of the virtual power plant, wherein the optimal scheduling system 200 comprises the following components:
the first calculation module 210 is used for controlling the central processing unit to calculate the building adjustable load and the charging pile adjustable value load in a preset area through the flexible adjustable resource model of the virtual power plant, so as to obtain the building total load power and the charging pile total load power;
the first generating module 220 controls the central processing unit to generate virtual power consumption demand instructions corresponding to a plurality of subareas in the preset area according to the total building load power and the total charging pile load power based on real-time demands and system constraints of the virtual power plant;
a first judging module 230, configured to control the central processing unit to judge whether a difference value between the virtual power consumption demand instruction and an actual power consumption demand value corresponding to the virtual power consumption demand instruction exceeds a threshold value;
the first scheduling module 240 controls the central processing unit to reschedule and allocate power resources formed by the building adjustable load and the charging pile adjustable value load of each sub-region within the preset region by using a preset optimization algorithm of the flexible adjustable resource model when a threshold value is exceeded.
In one embodiment, the optimal scheduling system 200 includes:
a second calculation module (not shown) for controlling the central processing unit to calculate the building adjustable load of the building area in the preset area through the flexible adjustable resource model of the virtual power plant;
and a third calculation module (not shown) for controlling the central processing unit to calculate the adjustable value load of the charging piles in the charging pile area in a preset area through the flexible adjustable resource model of the virtual power plant.
In one embodiment, the optimal scheduling system 200 includes:
the second generation module (not shown) controls the addition logic circuit of the central processing unit to generate virtual power consumption demand instructions corresponding to the time energy consumption, the daily energy consumption, the Zhou Haoneng energy consumption, the month energy consumption and the season energy consumption of the sub-areas in the preset area respectively.
In one embodiment, the optimal scheduling system 200 includes:
a second scheduling module (not shown), when the first threshold is exceeded, the second scheduling module controls the central processing unit to reschedule and allocate the power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area in a system constraint way through a preset optimization algorithm using the flexible adjustable resource model;
and a third scheduling module (not shown) which controls the central processor to carry out system external constraint on power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area through a preset optimization algorithm using the flexible adjustable resource model when a second threshold value is exceeded.
In addition, the application also provides an electronic device (which can be called a terminal device), comprising a memory and a processor, wherein the memory is used for storing a computer program, and the processor runs the computer program to enable the electronic device to execute the optimal scheduling method, and the terminal device can comprise a smart phone, a tablet computer, a desktop computer, a portable computer and the like. The terminal device comprises a memory for storing a computer program and a processor for causing the terminal device to perform the functions of the above-described modules applied in the optimal scheduling method or in the above-described optimal scheduling system by running the computer program.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the terminal device, and the like. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device.
The present embodiment also provides a computer-readable storage medium storing a computer program for implementing the electronic device used in the above-described optimal scheduling method.
In the several embodiments provided in the present application, it should be understood that the disclosed system and method may be implemented in other manners as well. The system embodiments described above are merely illustrative, for example, of the flowcharts and block diagrams in the figures that illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules or units in various embodiments of the application may be integrated together to form a single part, or the modules may exist alone, or two or more modules may be integrated to form a single part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a smart phone, a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application.
Claims (10)
1. The flexible adjustable resource optimal scheduling method for the virtual power plant is characterized by comprising the following steps of:
calculating building adjustable load and charging pile adjustable value load in a preset area through a flexible adjustable resource model of the virtual power plant by a central processing unit to obtain building total load power and charging pile total load power;
generating virtual power consumption demand instructions corresponding to a plurality of subareas in the preset area respectively by the central processing unit based on real-time demands and system constraints of the virtual power plant according to the total building load power and the total charging pile load power;
judging whether the difference value between the virtual power consumption demand instruction and the corresponding actual power consumption demand value exceeds a threshold value or not by the central processing unit;
and when the threshold value is exceeded, rescheduling and distributing power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area by the central processing unit through a preset optimizing algorithm using the flexible adjustable resource model.
2. The optimal scheduling method according to claim 1, wherein in calculating, by a central processor, building adjustable loads and charging pile adjustable value loads in a preset area through a flexible adjustable resource model of the virtual power plant, the optimal scheduling method comprises:
calculating, by a central processing unit, the building adjustable load of a building area within the preset area through a flexible adjustable resource model of the virtual power plant;
and calculating the adjustable value load of the charging piles in the charging pile area in a preset area through the flexible adjustable resource model of the virtual power plant by the central processing unit.
3. The optimal scheduling method according to claim 1, wherein in generating virtual power consumption demand instructions respectively corresponding to a plurality of sub-areas within the preset area by the central processing unit, the optimal scheduling method comprises:
and generating virtual power consumption demand instructions corresponding to the time energy consumption, the daily energy consumption, the Zhou Haoneng amount, the month energy consumption and the season energy consumption of the sub-areas in the preset area respectively by an addition logic circuit of the central processing unit.
4. The optimal scheduling method according to claim 1, wherein in determining by the central processing unit whether or not a difference between the virtual power consumption demand instruction and its corresponding actual power consumption demand value exceeds a threshold value, the optimal scheduling method comprises:
and judging whether the difference value between the virtual power consumption demand instruction and the corresponding actual power consumption demand value exceeds a threshold value by the central processing unit according to the lookup table in the memory of the central processing unit, and returning to the central processing unit to calculate the building adjustable load and the charging pile adjustable value load in the preset area through the flexible adjustable resource model of the virtual power plant under the condition that the difference value does not exceed the threshold value.
5. The optimal scheduling method according to claim 1, wherein in rescheduling and allocating, by the central processor, power resources formed by the building adjustable load and the charging pile adjustable value load of each sub-region within the preset region by a preset optimization algorithm using the flexible adjustable resource model when a threshold is exceeded, the optimal scheduling method comprises:
when the first threshold value is exceeded, rescheduling and distributing the power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area in a system constraint mode through a preset optimization algorithm using the flexible adjustable resource model by the central processing unit; or (b)
And when the second threshold value is exceeded, rescheduling and distributing the power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area by the central processing unit through a preset optimization algorithm using the flexible adjustable resource model.
6. The utility model provides a flexible adjustable resource optimization scheduling system of virtual power plant, characterized in that, the optimization scheduling system is applicable to flexible adjustable resource optimization scheduling method of virtual power plant, and the optimization scheduling system includes:
the first calculation module is used for controlling the central processing unit to calculate the building adjustable load and the charging pile adjustable value load in a preset area through the flexible adjustable resource model of the virtual power plant, and obtaining the building total load power and the charging pile total load power;
the first generation module is used for controlling the central processing unit to generate virtual power consumption demand instructions corresponding to a plurality of subareas in the preset area respectively according to the total building load power and the total charging pile load power based on real-time demands and system constraints of the virtual power plant;
the first judging module is used for controlling the central processing unit to judge whether the difference value between the virtual power consumption demand instruction and the corresponding actual power consumption demand value exceeds a threshold value or not;
and the first scheduling module controls the central processing unit to reschedule and allocate power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area through a preset optimization algorithm using the flexible adjustable resource model under the condition that the threshold value is exceeded.
7. The optimal scheduling system of claim 6, wherein the optimal scheduling system comprises:
the second calculation module is used for controlling the central processing unit to calculate the building adjustable load of the building area in the preset area through the flexible adjustable resource model of the virtual power plant;
and the third calculation module is used for controlling the central processing unit to calculate the adjustable value load of the charging pile in the charging pile area in the preset area through the flexible adjustable resource model of the virtual power plant.
8. The optimal scheduling system of claim 6, wherein the optimal scheduling system comprises:
the second generation module controls the addition logic circuit of the central processing unit to generate virtual power consumption demand instructions corresponding to the time energy consumption, the daily energy consumption, the Zhou Haoneng energy consumption, the month energy consumption and the season energy consumption of the sub-areas in the preset area respectively.
9. The optimal scheduling system of claim 6, wherein the optimal scheduling system comprises:
and the second judging module is used for controlling the central processing unit to judge whether the difference value between the virtual power consumption demand instruction and the corresponding actual power consumption demand value exceeds a threshold value according to the lookup table in the memory of the central processing unit, and when the difference value does not exceed the threshold value, the first calculating module is used for controlling the central processing unit to calculate the building adjustable load and the charging pile adjustable value load in a preset area through the flexible adjustable resource model of the virtual power plant.
10. The optimal scheduling system of claim 6, wherein the optimal scheduling method comprises:
the second scheduling module controls the central processing unit to reschedule and allocate power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area in a system constraint way by using a preset optimization algorithm of the flexible adjustable resource model under the condition that the first threshold value is exceeded;
and the third scheduling module controls the central processing unit to reschedule and allocate power resources formed by the building adjustable load and the charging pile adjustable value load of each subarea in the preset area in a system external constraint mode through a preset optimization algorithm using the flexible adjustable resource model under the condition that the second threshold value is exceeded.
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