CN112531746A - Virtual power plant operation method based on local autonomous optimization of central air conditioner - Google Patents

Virtual power plant operation method based on local autonomous optimization of central air conditioner Download PDF

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CN112531746A
CN112531746A CN202011104226.8A CN202011104226A CN112531746A CN 112531746 A CN112531746 A CN 112531746A CN 202011104226 A CN202011104226 A CN 202011104226A CN 112531746 A CN112531746 A CN 112531746A
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virtual
power
power generation
central air
virtual power
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CN112531746B (en
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高赐威
马思思
陈涛
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Nanjing Chunning Electric Power Technology Co ltd
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Nanjing Chunning Electric Power Technology Co ltd
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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
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • 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
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • 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
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • 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
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/10—The network having a local or delimited stationary reach
    • H02J2310/12—The local stationary network supplying a household or a building
    • H02J2310/14—The load or loads being home appliances
    • 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
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
    • H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
    • H02J2310/58—The condition being electrical
    • H02J2310/60—Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/222—Demand response systems, e.g. load shedding, peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/242—Home appliances
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/242—Home appliances
    • Y04S20/244—Home appliances the home appliances being or involving heating ventilating and air conditioning [HVAC] units

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  • Power Engineering (AREA)
  • Air Conditioning Control Device (AREA)

Abstract

The invention discloses a virtual power plant operation method based on local autonomous optimization of a central air conditioner, which comprises the following steps: (1) constructing a system virtual energy storage model according to the thermal inertia of the central air-conditioning system; (2) evaluating the adjustment potential of the central air conditioning system based on the virtual energy storage characteristic; (3) constructing a virtual power generation unit of the central air-conditioning system based on an internal resource coordination control mechanism; (4) carrying out normalized calling on the virtual power generation unit by adopting a local autonomous optimization method; (5) and forming a virtual power plant participating power grid peak shaving operation method based on the standardized calling of the virtual power generation unit. The method provided by the invention integrates the central air-conditioning clusters into the virtual power plant, fully utilizes the thermal inertia of the central air-conditioning system to provide adjustable capacity for the power grid, realizes the standardized modeling of the complex central air-conditioning system, and relieves the operating pressure during the peak load period of the power grid by fully exploiting the adjustment potential of resources on the demand side.

Description

Virtual power plant operation method based on local autonomous optimization of central air conditioner
Technical Field
The invention relates to a virtual power plant operation method based on local autonomous optimization of a central air conditioner, and belongs to a power system and an automation technology thereof.
Background
In recent years, with the development of social economy, the power load of China is continuously increased, the peak-valley difference is continuously increased, and the peak regulation difficulty of a power system is highlighted. In the high-temperature period in summer of 2019, the power load of the power grid in east China is as high as 2.9791 hundred million kilowatts, the year-by-year increase is 5.95%, and the innovation history is high. The urban power load is concentrated in China, and air-conditioning power consumers are numerous and large in size, so that the urban power grid summer peak load is caused mainly. Compared with a split-type air conditioner, the load electric power demand of the central air conditioner comprising a plurality of subsystems such as a refrigeration system, a water system, a wind system and the like is larger. In the Huangpu district of the sea city as an example, the peak load of a large commercial building mainly based on the load of a central air conditioner is near 500MW, and the annual power consumption is about 13 hundred million kilowatt hours, which accounts for more than 65% of the total energy consumption of the whole district.
Although the central air-conditioning load consumes significant energy, the building to which the central air-conditioning load belongs can convert electric energy into heat energy for storage within a specific time, and load transfer or reduction can be realized through reasonable regulation, so that the central air-conditioning load has power regulation potential within a comfort range which can be borne by a user. The highest power reduction of a flexible load of a certain commercial building including a central air conditioner in Nanjing West road in Huangpu district in Shanghai can reach 1069kW in peak time in summer, and the regulation potential is very huge, so that the flexible load becomes an effective substitute resource for the adjustable capacity at the side of a power grid.
The virtual power plant can aggregate distributed user side resources through an advanced coordination control technology, an intelligent metering technology and an information communication technology, external virtual power generation is realized through load demand response, the whole system is used as an intermediate unit to participate in power grid dispatching and market trading, interconnection and interaction of a plurality of user power equipment can be realized, and an effective way is provided for large-scale calling of user side resources with small quantity and scattered positions.
Therefore, the virtual power plant operation method based on the local autonomous optimization of the central air conditioner is provided, the central air conditioner cluster is aggregated into the virtual power plant, the virtual power plant participates in power grid peak shaving as an application scene, the thermal inertia of the central air conditioner system is fully utilized to provide adjustable capacity for the power grid, the whole system is packaged into a virtual power generation unit which provides continuous and stable output through comprehensive coordination control of a plurality of power devices in the system, not only is standardized modeling of the complex central air conditioner system realized, but also the operation pressure during the peak load period of the power grid is relieved through fully excavating the adjustment potential of resources on the demand side.
Disclosure of Invention
The purpose of the invention is as follows: in order to excavate the adjustment potential of user side resources, utilize load demand response to carry out power grid peak shaving, relieve power grid scheduling operation pressure and save power grid investment and construction cost, the invention provides a virtual power plant operation method based on central air conditioner local autonomous optimization, a central air conditioner cluster is aggregated into a virtual power plant, the whole system is packaged into a virtual power generation unit which provides continuous and stable output through the comprehensive coordination control of power equipment in a central air conditioner system, and the operation method of the virtual power plant participating in power grid peak shaving is formed based on the standardized calling of the virtual power generation unit.
The technical scheme is as follows: in order to achieve the purpose, the invention adopts the technical scheme that:
a virtual power plant operation method based on central air-conditioning local autonomous optimization comprises the following steps:
(1) constructing a system virtual energy storage model according to the thermal inertia of the central air-conditioning system;
(2) evaluating the adjustment potential of the central air conditioning system based on the virtual energy storage characteristic;
(3) constructing a virtual power generation unit of the central air-conditioning system based on an internal resource coordination control mechanism;
(4) carrying out normalized calling on the virtual power generation unit by adopting a local autonomous optimization method;
(5) and forming a virtual power plant participating power grid peak shaving operation method based on the standardized calling of the virtual power generation unit.
Specifically, in the step (1), a system virtual energy storage model is constructed according to thermal inertia of the central air-conditioning system, and specifically:
(1-1) virtual energy storage charging and discharging power of the system:
Figure BDA0002726401240000021
wherein: n is power equipment compilationNumber; n is the total number of the electrical equipment in the central air-conditioning system; pt ESVirtual energy storage power for the central air-conditioning system; pn,tReal-time power is provided for the power equipment; pn,0And (4) reference power for the electric equipment.
(1-2) virtual stored energy variation:
Figure BDA0002726401240000022
Figure BDA0002726401240000023
Figure BDA0002726401240000024
wherein:
Figure BDA0002726401240000025
change of the virtual stored energy in the t period;
Figure BDA0002726401240000026
energy is stored virtually for the current system.
(1-3) virtual energy storage state of charge:
Figure BDA0002726401240000027
Figure BDA0002726401240000028
wherein: VSOCtStoring the current state of charge for the virtual energy storage; eES,maxIs the virtual maximum stored energy.
Specifically, in the step (2), the evaluation of the adjustment potential of the central air conditioning system is performed based on the virtual energy storage characteristics, specifically:
(2-1) minimizing an electric power value of each device for a prescribed period in the future.
(a) End fan power minimization
Figure BDA0002726401240000029
S＝{fa,ra,ma,rla} (8)
Constraint conditions are as follows:
and (6) limiting the air quantity of a fan at the tail end.
Figure BDA0002726401240000031
Figure BDA0002726401240000032
Figure BDA0002726401240000033
And secondly, the cold quantity is taken by the user area for constraint. The minimum cooling capacity calculation formula actually taken by the fan coil in each user area is as follows.
Figure BDA0002726401240000034
Figure BDA0002726401240000035
Wherein: outdoor temperature Tt outConsidered a constant in a short time; indoor temperature
Figure BDA0002726401240000036
Taking the highest temperature T tolerable by users in the areal a,in,max(ii) a Because the chilled water system has thermal inertia and timely ductility, the water temperature at the inlet of the fan coil
Figure BDA0002726401240000037
The change speed is far less than the change speed of the fan power, so that the water temperature at the inlet at the current moment is taken
Figure BDA0002726401240000038
(b) Minimization of refrigerating machine power
By adjusting the outlet water temperature of the chilled water to the upper limit T of the outlet water temperature allowed by the refrigeratorw,ch,out*The minimization of the refrigerating machine power is realized as shown in the following formula.
Figure BDA0002726401240000039
Wherein: t isw,ch,in*The temperature of the outlet water of the chilled water is adjusted to Tw,ch,out*Then, the system reaches the inlet water temperature of the refrigerator at the new steady state.
In the actual regulation and control process, the chilled water outlet water temperature set value T can be set in consideration of the cold quantity requirement of a user areaw,spUp-regulated to [ Tw,ch,out0,Tw,ch,out*]A value within the range.
(2-2) the system can continuously provide the maximum adjustable capacity as the sustainable time of the adjustment potential, and the specific calculation process is as follows.
(a) Indoor temperature from Tl a,in0Up to Tl a,in,maxIn the process, the total cold energy released by the air-conditioning room is the maximum energy storage of the virtual battery in the current state of the room, and the specific expression is as follows:
Figure BDA00027264012400000310
(b) in analogy to lithium batteries, reducing the amount of cold input to a user area is equivalent to discharging a virtual battery in the user area, where the reduced amount of cold input is equivalent to the discharge power of the virtual battery, as shown in the following formula.
Figure BDA00027264012400000311
In the formula: t isl a,in'To reach the room temperature at the new steady state.
(c) Due to Tl a,in'>Tl a,in0Deviates from the actual temperature set value of the user, so the user can only set the room temperature to be Tl a ,in'The user's tolerable duration is considered as the maximum discharge duration τ' of the virtual battery. If the cold input of the user area starts to be reduced at the moment t, the cold energy stored in the area at the moment t + tau
Figure BDA00027264012400000312
When the release is completed, the energy conservation expression in the process is shown as the following formula.
Figure BDA00027264012400000313
From this, the sustainable time expression can be derived as follows:
Figure BDA0002726401240000041
specifically, in the step (3), the virtual power generation unit of the central air conditioning system is constructed based on an internal resource coordination control mechanism, which specifically includes:
and (3-1) establishing a system internal resource coordination control mechanism combining global control and local control according to the power regulation characteristic of the central air-conditioning system, regulating the temperature of a cold source and the air quantity of a tail end fan, regulating and controlling the power of the central air-conditioning system, and prolonging the sustainable time of the maximum adjustable capacity of the system.
And (3-2) calculating the adjustable electric quantity gap of the refrigerator and the maximum adjustable electric quantity provided by the tail end fan cluster.
(a) Measuring the maximum adjustable electric quantity of the fan by using the scene with the minimum cold quantity requirement of each user area, wherein the terminal wind is in the sceneThe power is
Figure BDA0002726401240000042
The sustainable time of a scene is tau*And calculating the total maximum adjustable electric quantity value of the end fans of all user areas according to the following formula:
Figure BDA0002726401240000043
(b) calculating the maximum adjustable electric quantity of the refrigerator as follows:
Figure BDA0002726401240000044
wherein: p0The power reference value of the refrigerating machine, and f (t) is a dynamic power expression of the refrigerating machine.
(c) With P0-P1As the maximum reducible power of the refrigerator, the reducible power cut in the virtual power generation unit is calculated as follows:
ΔE＝(P0-P1)T*-Ee,ch (21)
wherein: p1The minimum value of the power of the refrigerator corresponding to the maximum value of the outlet water temperature of the refrigerator is obtained.
(3-3) according to Delta E and Ee,fThe virtual power generation unit of the central air conditioner is constructed under two conditions.
(a) When E ise,fWhen the power is more than or equal to delta E, calculating the maximum reducible power delta PmaxThe following were used:
Figure BDA0002726401240000045
(b) when E ise,f<When delta E is reached, in order to fully compensate the electric quantity reducible gap of the refrigerator by the electric quantity reducible of the tail end fan, the water outlet temperature set value of the chilled water of the refrigerator is required to be
Figure BDA0002726401240000046
Up-regulated to [ Tw,ch,out0,Tw,ch,out*]A value within the range. To maximize the reducible power Δ P of the central air conditioning systemmaxAs a target, pair
Figure BDA0002726401240000047
The values are optimized.
Figure BDA0002726401240000048
Constraint conditions are as follows:
Figure BDA0002726401240000049
ΔE＝ΔPmaxT*-Ee,ch (25)
Ee,f≥ΔE (26)
(3-4) the sustainable time period generated by the control center of the central air-conditioning system is T*The virtual power generation unit reduces the maximum power of the system by delta Pmax(i.e., virtual generated power P)VGU) And reporting to a virtual power plant control center, and performing unified regulation and control management by the virtual power plant control center.
Specifically, in the step (4), a local autonomous optimization method is adopted to perform normalized calling on the virtual power generation unit, and specifically, the method includes:
(4-1) Global Primary optimization
(a) Cold source temperature set value optimization
The refrigerator agent takes the difference between the maximum reduction amount of the refrigerator power and the virtual power generation unit as a target, and carries out optimization decision on the outlet water temperature set value of the chilled water, and the specific process is as follows.
Figure BDA0002726401240000051
ΔPch,max＝Pch0-Pch,min (28)
Wherein: t isw,spIs a cold source temperature set value; delta Pch,maxCutting down the maximum power of the refrigerator in the whole virtual power generation period; pVGUGenerating power for the virtual power generation unit; pch0The initial power of the refrigerator; pch,minIs the minimum power of the refrigerator in the entire virtual power generation period.
Constraint conditions are as follows:
the temperature setting value of the cold source is within the range of the outlet water temperature allowed by the refrigerator.
Tw,sp,min≤Tw,sp≤Tw,sp,max (29)
In the formula: t isw,sp,minAnd Tw,sp,maxThe minimum value and the maximum value of the set value of the temperature of the cold source are respectively.
(b) Regional virtual energy storage calling
The central air-conditioning system control center regards each user area as an independent and uniformly packaged virtual battery, reduces the calling of the area virtual energy storage as far as possible on the basis of making up the whole virtual power generation power gap of the system, namely maximizes the area virtual charge state, and optimizes the virtual power generation power of each area, and the specific process is as follows.
Figure BDA0002726401240000052
Wherein:
Figure BDA0002726401240000053
generating power for the regional virtual battery; delta Pt VGUA virtual power generation unit power gap; VSOCt,lA regional virtual battery state of charge; omegaPAnd ωSThe weight coefficients of the two optimization terms are respectively.
Constraint conditions are as follows:
1) and (4) energy balance constraint. The virtual generator unit power notch is the difference between the overall virtual generator power requirement and the refrigerator power reduction.
ΔPt VGU＝PVGU-NchΔPt ch (31)
2) And (5) virtual generated power constraint. The area virtual power generation power is a positive value and does not exceed the maximum discharge power of the area virtual energy storage.
Figure BDA0002726401240000054
In the formula: pl VES,maxThe maximum discharge power of the regional virtual energy storage.
3) Virtual stored energy constraints. The regional virtual energy storage needs to satisfy the following state transition process.
Figure BDA0002726401240000061
Figure BDA0002726401240000062
Wherein:
Figure BDA0002726401240000063
the maximum energy storage capacity of the regional virtual energy storage;
Figure BDA0002726401240000064
the current stored energy is the virtual stored energy of the region; Δ t is a unit period duration.
4) Virtual state of charge constraints. The virtual state of charge is the ratio of the current virtual stored energy to the total stored energy, and is required to be within a specified range.
Figure BDA0002726401240000065
0≤VSOCt,l≤1 (36)
Wherein: VSOCt,lAnd the virtual state of charge of the regional virtual energy storage.
(4-2) local quadratic optimization
After receiving the virtual power generation power requirement, each regional agent performs virtual power generation power sharing in each regional fan through local autonomous optimization on the premise of maximizing the comfort of users to generate an optimal air volume control signal, and the specific process is as follows.
Figure BDA0002726401240000066
Figure BDA0002726401240000067
Wherein: beta is at,lFor the comfort level of regional users, the specific calculation mode is shown in section 2.2.6;
Figure BDA0002726401240000068
a decision variable vector in a local autonomous optimization problem;
Figure BDA0002726401240000069
and
Figure BDA00027264012400000610
the air supply amount, the fresh air amount, the return air amount and the exhaust air amount are respectively expressed.
Constraint conditions are as follows:
1) and (4) power balance constraint. The regional virtual power generation power is the difference between the initial value and the current value of the regional fan power.
Figure BDA00027264012400000611
2) And (5) deciding variable constraints. The decision variables have to be between their upper and lower limits.
Figure BDA00027264012400000612
Specifically, in the step (5), the method for forming the virtual power plant to participate in the peak shaving operation of the power grid based on the standardized calling of the virtual power generation unit specifically includes:
(5-1) after the virtual power plant control center receives a peak clipping instruction issued by a power grid dispatching department, the virtual power plant control center performs peak clipping according to the total peak clipping duration TdurDetermining the virtual power generation time length T of each virtual power generation unit*Dividing the calling process of the virtual power generation unit into R ═ Tdur/T*Wheel to virtual generation time period T*Sending the data to each central air-conditioning system control center;
(5-2) the virtual power plant control center determines the peak clipping capacity margin gamma belongs to [0,1] according to the historical response statistics condition of each virtual power generation unit;
(5-3) the virtual power plant control center records the number of the virtual power generation unit calling wheels as r-1;
(5-4) each central air-conditioning system control center generates electricity according to the virtual electricity generation time length T*According to the requirements, local autonomous optimization is carried out, a virtual power generation unit is constructed, and a parameter set { P } of the virtual power generation unit is obtainedVGU,TidleReporting to a virtual power plant control center, wherein TidleThe idle time of the virtual power generation unit;
(5-5) the virtual power plant control center enables the virtual power generation units to be in accordance with TidleThe parameters are sorted from big to small, TidleIn the case of the same parameters, according to Δ PmaxSequencing from big to small to form a virtual power generation unit sequence;
(5-6) the virtual power plant control center selects the first N virtual power generation units from the sequence to participate in power grid peak clipping, wherein N meets the following conditions:
Figure BDA0002726401240000071
δk＝1,k＝1,2,…,N-1 (42)
Figure BDA0002726401240000072
(5-7) the virtual power plant control center issues a calling coefficient delta to each virtual power generation unit in the sequencekAnd the input timetkIf the virtual power generation unit is included in the current call sequence, δkTaking the above formula to calculate the result, tkGet
Figure BDA0002726401240000073
(indicating that the kth virtual power generation unit is put into the process of the r round calling); on the contrary, deltakAnd tkAll are taken as 0;
(5-8) the virtual power plant control center judges the size relation between R and R, if R is less than R, the R is made to be R +1, and the step returns to (5-4); otherwise, turning to (5-9);
and (5-9) the virtual power plant control center feeds back to a power grid dispatching department, issues peak clipping confirmation instructions to each virtual power generation unit, and performs peak clipping operation when a peak clipping period comes.
Drawings
FIG. 1 is a flow chart of an embodiment of the method of the present invention;
FIG. 2 is a schematic diagram of a virtual energy storage model of a central air conditioner according to the present invention;
FIG. 3 is a schematic view of a virtual power generation unit according to the present invention;
FIG. 4 is a diagram of a multi-level operation control architecture for a virtual power plant participating in peak shaving of a power grid according to the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings.
Fig. 1 shows a virtual power plant operation method based on local autonomous optimization of a central air conditioner, and the whole implementation process is specifically described below.
The method comprises the following steps: and constructing a system virtual energy storage model according to the thermal inertia of the central air-conditioning system.
(1-1) virtual energy storage charging and discharging power of the system:
Figure BDA0002726401240000074
wherein: n is the number of the power equipment; n is the total number of the electrical equipment in the central air-conditioning system; pt ESVirtual energy storage power for the central air-conditioning system; pn,tReal-time power is provided for the power equipment; pn,0And (4) reference power for the electric equipment.
(1-2) virtual stored energy variation:
Figure BDA0002726401240000075
Figure BDA0002726401240000076
Figure BDA0002726401240000081
wherein:
Figure BDA0002726401240000082
change of the virtual stored energy in the t period;
Figure BDA0002726401240000083
energy is stored virtually for the current system.
(1-3) virtual energy storage state of charge:
Figure BDA0002726401240000084
Figure BDA0002726401240000085
wherein: VSOCtStoring the current state of charge for the virtual energy storage; eES,maxIs the virtual maximum stored energy.
Step two: and evaluating the adjustment potential of the central air conditioning system based on the virtual energy storage characteristics.
(2-1) minimizing an electric power value of each device for a prescribed period in the future.
(a) End fan power minimization
Figure BDA0002726401240000086
S＝{fa,ra,ma,rla} (8)
Constraint conditions are as follows:
and (6) limiting the air quantity of a fan at the tail end.
Figure BDA0002726401240000087
Figure BDA0002726401240000088
Figure BDA0002726401240000089
And secondly, the cold quantity is taken by the user area for constraint. The minimum cooling capacity calculation formula actually taken by the fan coil in each user area is as follows.
Figure BDA00027264012400000810
Figure BDA00027264012400000811
Wherein: outdoor temperature Tt outConsidered a constant in a short time; indoor temperature
Figure BDA00027264012400000812
Taking the highest temperature T tolerable by users in the areal a,in,max(ii) a Because the chilled water system has thermal inertia and timely ductility, the water temperature at the inlet of the fan coil
Figure BDA00027264012400000813
The change speed is far less than the change speed of the fan power, so that the water temperature at the inlet at the current moment is taken
Figure BDA00027264012400000814
(b) Minimization of refrigerating machine power
By adjusting the outlet water temperature of the chilled water to the upper limit T of the outlet water temperature allowed by the refrigeratorw,ch,out*The minimization of the refrigerating machine power is realized as shown in the following formula.
Figure BDA00027264012400000815
Wherein: t isw,ch,in*The temperature of the outlet water of the chilled water is adjusted to Tw,ch,out*Then, the system reaches the inlet water temperature of the refrigerator at the new steady state.
In the actual regulation and control process, the chilled water outlet water temperature set value T can be set in consideration of the cold quantity requirement of a user areaw,spUp-regulated to [ Tw,ch,out0,Tw,ch,out*]A value within the range.
(2-2) the system can continuously provide the maximum adjustable capacity as the sustainable time of the adjustment potential, and the specific calculation process is as follows.
(a) Indoor temperature from Tl a,in0Up to Tl a,in,maxIn the process, the total cold energy released by the air-conditioning room is the maximum energy storage of the virtual battery in the current state of the room, and the specific expression is as follows:
Figure BDA0002726401240000091
(b) in analogy to lithium batteries, reducing the amount of cold input to a user area is equivalent to discharging a virtual battery in the user area, where the reduced amount of cold input is equivalent to the discharge power of the virtual battery, as shown in the following formula.
Figure BDA0002726401240000092
In the formula: t isl a,in'To achieveRoom temperature at new steady state.
(c) Due to Tl a,in'>Tl a,in0Deviates from the actual temperature set value of the user, so the user can only set the room temperature to be Tl a ,in'The user's tolerable duration is considered as the maximum discharge duration τ' of the virtual battery. If the cold input of the user area starts to be reduced at the moment t, the cold energy stored in the area at the moment t + tau
Figure BDA0002726401240000093
When the release is completed, the energy conservation expression in the process is shown as the following formula.
Figure BDA0002726401240000094
From this, the sustainable time expression can be derived as follows:
Figure BDA0002726401240000095
step three: and constructing a virtual power generation unit of the central air-conditioning system based on an internal resource coordination control mechanism.
And (3-1) establishing a system internal resource coordination control mechanism combining global control and local control according to the power regulation characteristic of the central air-conditioning system, regulating the temperature of a cold source and the air quantity of a tail end fan, regulating and controlling the power of the central air-conditioning system, and prolonging the sustainable time of the maximum adjustable capacity of the system.
And (3-2) calculating the adjustable electric quantity gap of the refrigerator and the maximum adjustable electric quantity provided by the tail end fan cluster.
(a) The maximum adjustable electric quantity of the fan is measured by the scene with the minimum requirement on the cold quantity of each user area, and the power of the tail end fan is
Figure BDA0002726401240000096
The sustainable time of a scene is tau*From which all are calculatedThe maximum adjustable electric quantity total value of the fan at the tail end of the user area is as follows:
Figure BDA0002726401240000097
(b) calculating the maximum adjustable electric quantity of the refrigerator as follows:
Figure BDA0002726401240000098
wherein: p0The power reference value of the refrigerating machine, and f (t) is a dynamic power expression of the refrigerating machine.
(c) With P0-P1As the maximum reducible power of the refrigerator, the reducible power cut in the virtual power generation unit is calculated as follows:
ΔE＝(P0-P1)T*-Ee,ch (21)
wherein: p1The minimum value of the power of the refrigerator corresponding to the maximum value of the outlet water temperature of the refrigerator is obtained.
(3-3) according to Delta E and Ee,fThe virtual power generation unit of the central air conditioner is constructed under two conditions.
(a) When E ise,fWhen the power is more than or equal to delta E, calculating the maximum reducible power delta PmaxThe following were used:
Figure BDA0002726401240000101
(b) when E ise,f<When delta E is reached, in order to fully compensate the electric quantity reducible gap of the refrigerator by the electric quantity reducible of the tail end fan, the water outlet temperature set value of the chilled water of the refrigerator is required to be
Figure BDA0002726401240000102
Up-regulated to [ Tw,ch,out0,Tw,ch,out*]A value within the range. To maximize the reducible power Δ P of the central air conditioning systemmaxAs a target, pair
Figure BDA0002726401240000103
The values are optimized.
Figure BDA0002726401240000104
Constraint conditions are as follows:
Figure BDA0002726401240000105
ΔE＝ΔPmaxT*-Ee,ch (25)
Ee,f≥ΔE (26)
(3-4) the sustainable time period generated by the control center of the central air-conditioning system is T*The virtual power generation unit reduces the maximum power of the system by delta Pmax(i.e., virtual generated power P)VGU) And reporting to a virtual power plant control center, and performing unified regulation and control management by the virtual power plant control center.
Step four: and carrying out normalized calling on the virtual power generation unit by adopting a local autonomous optimization method.
(4-1) Global Primary optimization
(a) Cold source temperature set value optimization
The refrigerator agent takes the difference between the maximum reduction amount of the refrigerator power and the virtual power generation unit as a target, and carries out optimization decision on the outlet water temperature set value of the chilled water, and the specific process is as follows.
Figure BDA0002726401240000106
ΔPch,max＝Pch0-Pch,min (28)
Wherein: t isw,spIs a cold source temperature set value; delta Pch,maxCutting down the maximum power of the refrigerator in the whole virtual power generation period; pVGUGenerating power for the virtual power generation unit; pch0The initial power of the refrigerator; pch,minIs the minimum power of the refrigerator in the entire virtual power generation period.
Constraint conditions are as follows:
the temperature setting value of the cold source is within the range of the outlet water temperature allowed by the refrigerator.
Tw,sp,min≤Tw,sp≤Tw,sp,max (29)
In the formula: t isw,sp,minAnd Tw,sp,maxThe minimum value and the maximum value of the set value of the temperature of the cold source are respectively.
(b) Regional virtual energy storage calling
The central air-conditioning system control center regards each user area as an independent and uniformly packaged virtual battery, reduces the calling of the area virtual energy storage as far as possible on the basis of making up the whole virtual power generation power gap of the system, namely maximizes the area virtual charge state, and optimizes the virtual power generation power of each area, and the specific process is as follows.
Figure BDA0002726401240000111
Wherein:
Figure BDA0002726401240000112
generating power for the regional virtual battery; delta Pt VGUA virtual power generation unit power gap; VSOCt,lA regional virtual battery state of charge; omegaPAnd ωSThe weight coefficients of the two optimization terms are respectively.
Constraint conditions are as follows:
1) and (4) energy balance constraint. The virtual generator unit power notch is the difference between the overall virtual generator power requirement and the refrigerator power reduction.
ΔPt VGU＝PVGU-NchΔPt ch (31)
2) And (5) virtual generated power constraint. The area virtual power generation power is a positive value and does not exceed the maximum discharge power of the area virtual energy storage.
Figure BDA0002726401240000113
In the formula: pl VES,maxThe maximum discharge power of the regional virtual energy storage.
3) Virtual stored energy constraints. The regional virtual energy storage needs to satisfy the following state transition process.
Figure BDA0002726401240000114
Figure BDA0002726401240000115
Wherein:
Figure BDA0002726401240000116
the maximum energy storage capacity of the regional virtual energy storage;
Figure BDA0002726401240000117
the current stored energy is the virtual stored energy of the region; Δ t is a unit period duration.
4) Virtual state of charge constraints. The virtual state of charge is the ratio of the current virtual stored energy to the total stored energy, and is required to be within a specified range.
Figure BDA0002726401240000118
0≤VSOCt,l≤1 (36)
Wherein: VSOCt,lAnd the virtual state of charge of the regional virtual energy storage.
(4-2) local quadratic optimization
After receiving the virtual power generation power requirement, each regional agent performs virtual power generation power sharing in each regional fan through local autonomous optimization on the premise of maximizing the comfort of users to generate an optimal air volume control signal, and the specific process is as follows.
Figure BDA0002726401240000119
Figure BDA00027264012400001110
Wherein: beta is at,lFor the comfort level of regional users, the specific calculation mode is shown in section 2.2.6;
Figure BDA00027264012400001111
a decision variable vector in a local autonomous optimization problem;
Figure BDA00027264012400001112
and
Figure BDA00027264012400001113
the air supply amount, the fresh air amount, the return air amount and the exhaust air amount are respectively expressed.
Constraint conditions are as follows:
1) and (4) power balance constraint. The regional virtual power generation power is the difference between the initial value and the current value of the regional fan power.
Figure BDA00027264012400001114
2) And (5) deciding variable constraints. The decision variables have to be between their upper and lower limits.
Figure BDA00027264012400001115
Step five: and forming a virtual power plant participating power grid peak shaving operation method based on the standardized calling of the virtual power generation unit.
(5-1) after the virtual power plant control center receives a peak clipping instruction issued by a power grid dispatching department, the virtual power plant control center performs peak clipping according to the total peak clipping duration TdurDetermining the virtual power generation time length T of each virtual power generation unit*Calling of the virtual power generation unitThe equation is R ═ Tdur/T*Wheel to virtual generation time period T*Sending the data to each central air-conditioning system control center;
(5-2) the virtual power plant control center determines the peak clipping capacity margin gamma belongs to [0,1] according to the historical response statistics condition of each virtual power generation unit;
(5-3) the virtual power plant control center records the number of the virtual power generation unit calling wheels as r-1;
(5-4) each central air-conditioning system control center generates electricity according to the virtual electricity generation time length T*According to the requirements, local autonomous optimization is carried out, a virtual power generation unit is constructed, and a parameter set { P } of the virtual power generation unit is obtainedVGU,TidleReporting to a virtual power plant control center, wherein TidleThe idle time of the virtual power generation unit;
(5-5) the virtual power plant control center enables the virtual power generation units to be in accordance with TidleThe parameters are sorted from big to small, TidleIn the case of the same parameters, according to Δ PmaxSequencing from big to small to form a virtual power generation unit sequence;
(5-6) the virtual power plant control center selects the first N virtual power generation units from the sequence to participate in power grid peak clipping, wherein N meets the following conditions:
Figure BDA0002726401240000121
δk＝1,k＝1,2,…,N-1 (42)
Figure BDA0002726401240000122
(5-7) the virtual power plant control center issues a calling coefficient delta to each virtual power generation unit in the sequencekAnd a throw-in time tkIf the virtual power generation unit is included in the current call sequence, δkTaking the above formula to calculate the result, tkGet
Figure BDA0002726401240000123
(denotes the k-thThe virtual power generation unit is put into the r-th round of calling process); on the contrary, deltakAnd tkAll are taken as 0;
(5-8) the virtual power plant control center judges the size relation between R and R, if R is less than R, the R is made to be R +1, and the step returns to (5-4); otherwise, turning to (5-9);
and (5-9) the virtual power plant control center feeds back to a power grid dispatching department, issues peak clipping confirmation instructions to each virtual power generation unit, and performs peak clipping operation when a peak clipping period comes.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.

Claims (6)

1. A virtual power plant operation method based on central air-conditioning local autonomous optimization is characterized in that: the method comprises the following steps:
(1) constructing a system virtual energy storage model according to the thermal inertia of the central air-conditioning system;
(2) evaluating the adjustment potential of the central air conditioning system based on the virtual energy storage characteristic;
(3) constructing a virtual power generation unit of the central air-conditioning system based on an internal resource coordination control mechanism;
(4) carrying out normalized calling on the virtual power generation unit by adopting a local autonomous optimization method;
(5) and forming a virtual power plant participating power grid peak shaving operation method based on the standardized calling of the virtual power generation unit.
2. The virtual power plant operation method based on the local autonomous optimization of the central air-conditioning system according to claim 1, characterized in that: in the step (1), a system virtual energy storage model is constructed according to the thermal inertia of the central air-conditioning system, and the method specifically comprises the following steps:
(1-1) virtual energy storage charging and discharging power of the system:
Figure FDA0002726401230000011
wherein: n is the number of the power equipment; n is the total number of the electrical equipment in the central air-conditioning system; pt ESVirtual energy storage power for the central air-conditioning system; pn,tReal-time power is provided for the power equipment; pn,0Reference power for the electrical equipment;
(1-2) virtual stored energy variation:
Figure FDA0002726401230000012
Figure FDA0002726401230000013
Figure FDA0002726401230000014
wherein:
Figure FDA0002726401230000015
change of the virtual stored energy in the t period; et ESVirtually storing energy for the current system;
(1-3) virtual energy storage state of charge:
Figure FDA0002726401230000016
Figure FDA0002726401230000017
wherein: VSOCtStoring the current state of charge for the virtual energy storage; eES,maxIs the virtual maximum stored energy.
3. The virtual power plant operation method based on the local autonomous optimization of the central air-conditioning system according to claim 1, characterized in that: in the step (2), the adjustment potential evaluation of the central air conditioning system is performed based on the virtual energy storage characteristics, and specifically comprises the following steps:
(2-1) minimizing an electric power value of each device for a prescribed period in the future;
(a) end fan power minimization
Figure FDA0002726401230000018
S＝{fa,ra,ma,rla} (8)
Constraint conditions are as follows:
firstly, restraining the air quantity of a tail end fan:
Figure FDA0002726401230000021
Figure FDA0002726401230000022
Figure FDA0002726401230000023
secondly, the cold quantity taken by the user area is restricted, and the minimum cold quantity actually taken by the fan coil of each user area is calculated according to the formula as follows:
Figure FDA0002726401230000024
Figure FDA0002726401230000025
wherein: outdoor temperature Tt outConsidered a constant in a short time; indoor temperature
Figure FDA0002726401230000026
Taking the highest temperature T tolerable by users in the areal a,in,max(ii) a Because the chilled water system has thermal inertia and timely ductility, the water temperature at the inlet of the fan coil
Figure FDA0002726401230000027
The change speed is far less than the change speed of the fan power, so that the water temperature at the inlet at the current moment is taken
Figure FDA0002726401230000028
(b) Minimization of refrigerating machine power
By adjusting the outlet water temperature of the chilled water to the upper limit T of the outlet water temperature allowed by the refrigeratorw,ch,out*The minimization of the power of the refrigerating machine is realized as shown in the following formula:
Figure FDA0002726401230000029
wherein: t isw,ch,in*The temperature of the outlet water of the chilled water is adjusted to Tw,ch,out*Then, the system reaches the inlet water temperature of the refrigerator when in a new steady state;
in the actual regulation and control process, the chilled water outlet water temperature set value T can be set in consideration of the cold quantity requirement of a user areaw,spUp-regulated to [ Tw,ch,out0,Tw,ch,out*]A value within a range;
(2-2) the system can continuously provide the maximum adjustable capacity as the sustainable time of the adjustment potential, and the specific calculation process is as follows:
(a) indoor temperature from Tl a,in0Up to Tl a,in,maxIn the process, the total cold energy released by the air-conditioning room is the maximum energy storage of the virtual battery in the current state of the room, and the specific expression is as follows:
Figure FDA00027264012300000210
(b) similar to a lithium battery, reducing the amount of cold input into the user area is equivalent to discharging a virtual battery in the user area, wherein the reduced amount of cold input is equivalent to the discharge power of the virtual battery, as shown in the following formula:
Figure FDA00027264012300000211
in the formula: t isl a,in'To reach the indoor temperature at the new steady state;
(c) due to Tl a,in'>Tl a,in0Deviates from the actual temperature set value of the user, so the user can only set the room temperature to be Tl a,in'The state of (1) is endured for a certain time, the endurable time of the user is considered as the maximum discharge time tau 'of the virtual battery, if the cold input of the user area starts to be reduced at the moment of t, the cold energy stored in the area at the moment of t + tau' is used for cooling the virtual battery
Figure FDA00027264012300000212
When the release is completed, the energy conservation expression in the process is shown as the following formula:
Figure FDA00027264012300000213
the sustainable time expression is derived as follows:
Figure FDA0002726401230000031
4. the virtual power plant operation method based on the local autonomous optimization of the central air-conditioning system according to claim 1, characterized in that: in the step (3), the virtual power generation unit of the central air conditioning system is constructed based on an internal resource coordination control mechanism, which specifically comprises the following steps:
(3-1) establishing a system internal resource coordination control mechanism combining global control and local control according to the power regulation characteristic of the central air-conditioning system, regulating the temperature of a cold source and the air quantity of a tail end fan, regulating and controlling the power of the central air-conditioning system, and prolonging the sustainable time of the maximum adjustable capacity of the system;
(3-2) calculating the adjustable electric quantity gap of the refrigerator and the maximum adjustable electric quantity which can be provided by the tail end fan cluster;
(a) the maximum adjustable electric quantity of the fan is measured by the scene with the minimum requirement on the cold quantity of each user area, and the power of the tail end fan is
Figure FDA0002726401230000032
The sustainable time of a scene is tau*And calculating the total maximum adjustable electric quantity value of the end fans of all user areas according to the following formula:
Figure FDA0002726401230000033
(b) calculating the maximum adjustable electric quantity of the refrigerator as follows:
Figure FDA0002726401230000034
wherein: p0Is the power reference value of the refrigerator, and f (t) is the dynamic power expression of the refrigerator;
(c) with P0-P1As the maximum reducible power of the refrigerator, the reducible power cut in the virtual power generation unit is calculated as follows:
ΔE＝(P0-P1)T*-Ee,ch (21)
wherein: p1The corresponding refrigerator power minimum value when the refrigerator outlet water temperature is adjusted up to the maximum value;
(3-3) according to Delta E and Ee,fThe virtual power generation unit structure of the central air conditioner is carried out under two conditionsBuilding;
(a) when E ise,fWhen the power is more than or equal to delta E, calculating the maximum reducible power delta PmaxThe following were used:
Figure FDA0002726401230000035
(b) when E ise,f<When delta E is reached, in order to fully compensate the electric quantity reducible gap of the refrigerator by the electric quantity reducible of the tail end fan, the water outlet temperature set value of the chilled water of the refrigerator is required to be
Figure FDA0002726401230000036
Up-regulated to [ Tw,ch,out0,Tw,ch,out*]A value within the range to maximize the curtailable power Δ P of the central air conditioning systemmaxAs a target, pair
Figure FDA0002726401230000037
Optimizing the value:
Figure FDA0002726401230000038
constraint conditions are as follows:
Figure FDA0002726401230000039
ΔE＝ΔPmaxT*-Ee,ch (25)
Ee,f≥ΔE (26)
(3-4) the sustainable time period generated by the control center of the central air-conditioning system is T*The virtual power generation unit reduces the maximum power of the system by delta Pmax(i.e., virtual generated power P)VGU) And reporting to a virtual power plant control center, and performing unified regulation and control management by the virtual power plant control center.
5. The virtual power plant operation method based on the local autonomous optimization of the central air-conditioning system according to claim 1, characterized in that: in the step (4), a local autonomous optimization method is adopted to carry out standardized calling on the virtual power generation unit, and the method specifically comprises the following steps:
(4-1) Global Primary optimization
(a) Cold source temperature set value optimization
The refrigerator agent takes the difference between the maximum reduction amount of the refrigerator power and the virtual power generation unit as a target, and carries out optimization decision on the outlet water temperature set value of the chilled water, and the specific process is as follows:
Figure FDA0002726401230000041
ΔPch,max＝Pch0-Pch,min (28)
wherein: t isw,spIs a cold source temperature set value; delta Pch,maxCutting down the maximum power of the refrigerator in the whole virtual power generation period; pVGUGenerating power for the virtual power generation unit; pch0The initial power of the refrigerator; pch,minThe minimum power of the refrigerator in the whole virtual power generation period;
constraint conditions are as follows:
the temperature setting value of the cold source is within the range of the outlet water temperature allowed by the refrigerator,
Tw,sp,min≤Tw,sp≤Tw,sp,max (29)
in the formula: t isw,sp,minAnd Tw,sp,maxRespectively the minimum value and the maximum value of the cold source temperature set value;
(b) regional virtual energy storage calling
The central air-conditioning system control center regards each user area as an independent and uniformly packaged virtual battery, reduces the calling of the area virtual energy storage as far as possible on the basis of making up the whole virtual power generation power gap of the system, namely maximizes the area virtual charge state, and optimizes the virtual power generation power of each area, and the specific process is as follows:
Figure FDA0002726401230000042
wherein:
Figure FDA0002726401230000043
generating power for the regional virtual battery; delta Pt VGUA virtual power generation unit power gap; VSOCt,lA regional virtual battery state of charge; omegaPAnd ωSThe weight coefficients of the two optimization terms are respectively;
constraint conditions are as follows:
1) and (3) energy balance constraint, wherein a virtual power generation unit power notch is the difference between the overall virtual power generation power requirement and the power reduction amount of the refrigerator:
ΔPt VGU＝PVGU-NchΔPt ch (31)
2) and (3) virtual generated power constraint, wherein the regional virtual generated power is a positive value and does not exceed the maximum discharge power of regional virtual energy storage:
Figure FDA0002726401230000044
in the formula: pl VES,maxMaximum discharge power for regional virtual energy storage;
3) and (4) virtual energy storage constraint, wherein the regional virtual energy storage needs to meet the following state transfer process:
Figure FDA0002726401230000051
Figure FDA0002726401230000052
wherein: el VES,maxThe maximum energy storage capacity of the regional virtual energy storage;
Figure FDA0002726401230000053
the current stored energy is the virtual stored energy of the region; Δ t is a unit time period duration;
4) and (3) virtual state of charge constraint, wherein the virtual state of charge is the proportion of the current virtual stored energy to the total stored energy and needs to be within a specified range:
Figure FDA0002726401230000054
0≤VSOCt,l≤1 (36)
wherein: VSOCt,lVirtual state of charge for regional virtual energy storage;
(4-2) local quadratic optimization
After each regional agent receives the virtual power generation power requirement, the regional agents perform virtual power generation power sharing in each fan in the region through local autonomous optimization on the premise of maximizing the comfort degree of a user to generate an optimal air volume control signal, and the specific process is as follows:
Figure FDA0002726401230000055
Figure FDA0002726401230000056
wherein: beta is at,lFor the comfort level of regional users, the specific calculation mode is shown in section 2.2.6;
Figure FDA0002726401230000057
a decision variable vector in a local autonomous optimization problem;
Figure FDA0002726401230000058
and
Figure FDA0002726401230000059
respectively showing the air supply quantity, the fresh air quantity, the air return quantity and the air exhaust quantity,
constraint conditions are as follows:
1) and (3) power balance constraint, wherein the regional virtual generated power is the difference between the initial value and the current value of the regional fan power:
Figure FDA00027264012300000510
2) constraint of decision variables, decision variables must be between their upper and lower limits:
Figure FDA00027264012300000511
6. the virtual power plant operation method based on the local autonomous optimization of the central air-conditioning system according to claim 1, characterized in that: in the step (5), the method for participating in the peak shaving operation of the power grid by the virtual power plant is formed based on the standardized calling of the virtual power generation unit, and specifically comprises the following steps:
(5-1) after the virtual power plant control center receives a peak clipping instruction issued by a power grid dispatching department, the virtual power plant control center performs peak clipping according to the total peak clipping duration TdurDetermining the virtual power generation time length T of each virtual power generation unit*Dividing the calling process of the virtual power generation unit into R ═ Tdur/T*Wheel to virtual generation time period T*Sending the data to each central air-conditioning system control center;
(5-2) the virtual power plant control center determines the peak clipping capacity margin gamma belongs to [0,1] according to the historical response statistics condition of each virtual power generation unit;
(5-3) the virtual power plant control center records the number of the virtual power generation unit calling wheels as r-1;
(5-4) each central air-conditioning system control center generates electricity according to the virtual electricity generation time length T*According to the requirements, local autonomous optimization is carried out, a virtual power generation unit is constructed, and a parameter set { P } of the virtual power generation unit is obtainedVGU,TidleReporting to a virtual power plant control center, wherein TidleFor idling of the virtual power generating unitA duration;
(5-5) the virtual power plant control center enables the virtual power generation units to be in accordance with TidleThe parameters are sorted from big to small, TidleIn the case of the same parameters, according to Δ PmaxSequencing from big to small to form a virtual power generation unit sequence;
(5-6) the virtual power plant control center selects the first N virtual power generation units from the sequence to participate in power grid peak clipping, wherein N meets the following conditions:
Figure FDA0002726401230000061
δk＝1,k＝1,2,…,N-1 (42)
Figure FDA0002726401230000062
(5-7) the virtual power plant control center issues a calling coefficient delta to each virtual power generation unit in the sequencekAnd a throw-in time tkIf the virtual power generation unit is included in the current call sequence, δkTaking the above formula to calculate the result, tkGet
Figure FDA0002726401230000063
(indicating that the kth virtual power generation unit is put into the process of the r round calling); on the contrary, deltakAnd tkAll are taken as 0;
(5-8) the virtual power plant control center judges the size relation between R and R, if R is less than R, the R is made to be R +1, and the step returns to (5-4); otherwise, turning to (5-9);
and (5-9) the virtual power plant control center feeds back to a power grid dispatching department, issues peak clipping confirmation instructions to each virtual power generation unit, and performs peak clipping operation when a peak clipping period comes.
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CN115639789A (en) * 2022-09-09 2023-01-24 南方电网科学研究院有限责任公司 Virtual power plant regulation and control method, device, system, equipment and readable storage medium
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CN117439276B (en) * 2023-12-21 2024-04-16 深圳前海中碳综合能源科技有限公司 Virtual power plant demand side management and control system

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