CN113162054B - Step aggregation method and system of comprehensive service station based on large-scale controllable load - Google Patents

Step aggregation method and system of comprehensive service station based on large-scale controllable load Download PDF

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CN113162054B
CN113162054B CN202110452763.XA CN202110452763A CN113162054B CN 113162054 B CN113162054 B CN 113162054B CN 202110452763 A CN202110452763 A CN 202110452763A CN 113162054 B CN113162054 B CN 113162054B
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load
controllable
energy storage
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temperature
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CN113162054A (en
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冯亮
鉴庆之
李文升
赵龙
郑志杰
孙东磊
刘冬
刘蕊
孙毅
王宪
邓海珊
李勃
朱毅
冯旭
曹璞佳
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State Grid Corp of China SGCC
Economic and Technological Research Institute of State Grid Shandong Electric Power Co Ltd
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State Grid Corp of China SGCC
Economic and Technological Research Institute of State Grid Shandong Electric Power 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
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • H02J3/144—Demand-response operation of the power transmission or distribution network
    • 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
    • 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
    • H02J3/322—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means the battery being on-board an electric or hybrid vehicle, e.g. vehicle to grid arrangements [V2G], power aggregation, use of the battery for network load balancing, coordinated or cooperative battery charging
    • 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]
    • 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

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Abstract

The application discloses a large-scale controllable load-based step aggregation method and a system for a comprehensive service station, wherein the method comprises the following steps: according to the controllable load, carrying out homogeneous aggregation modeling of the comprehensive service station, wherein the controllable load comprises: temperature control load and energy storage load; normalizing the energy state of the controllable load; and carrying out heterogeneous aggregation modeling on the comprehensive service station according to the normalization processing result and the homogeneous aggregation model. The system comprises: the device comprises a homogenization polymerization module, a normalization processing module and a heterogeneous polymerization module. Through the application, the accuracy and the flexibility of energy control can be improved.

Description

Step aggregation method and system of comprehensive service station based on large-scale controllable load
Technical Field
The application relates to the technical field of comprehensive service station energy aggregation, in particular to a large-scale controllable load-based comprehensive service station step aggregation method and system.
Background
With the development of economy, realization of clean and efficient use of energy has become an important research topic in energy environment in recent years. The comprehensive energy system integrates the production, transportation, conversion and consumption of various energy sources, can fully play the complementary characteristics and synergistic effect of different energy sources, and is an important means for realizing the efficient utilization of the energy sources.
Wherein, the energy internet comprehensive service station based on the 'multi-station-in-one' mainly comprises: resource facilities such as transformer substations, energy storage stations, data center stations, distributed photovoltaic, distributed wind power and charging stations. The resource aggregation method of the comprehensive service station is a key for improving the comprehensive efficiency of the system.
At present, a resource aggregation method of a comprehensive service station mainly focuses on an optimization model of a distributed cogeneration system, a solar photovoltaic and miniature combined cooling heating and power system set model and a distributed energy network model. Modeling is carried out from the angles, so that the comprehensive efficiency of the system is improved.
However, in the current resource aggregation method for the integrated service station, although the modeling objects include a cogeneration system, a solar photovoltaic system, a combined cooling heating and power system and a distributed energy system, the modeling can only be performed in the systems, and the integrated service station composed of different systems is not modeled, so that the current modeling method is not deep enough in matching on the space-time scale of the physical characteristics of the resources in the system, and the accuracy and flexibility of the unified control on the integrated service station of the energy internet are not high enough.
Disclosure of Invention
The application provides a large-scale controllable load-based step aggregation method and system for an integrated service station, and aims to solve the problem that the unified control accuracy and flexibility of a modeling method in the prior art on an energy Internet integrated service station are not high enough.
In order to solve the technical problem, the embodiment of the application discloses the following technical scheme:
a large-scale controllable load-based integrated service station step aggregation method comprises the following steps:
according to the controllable load, carrying out homogeneous aggregation modeling of the comprehensive service station, wherein the controllable load comprises: temperature control load and energy storage load;
normalizing the energy state of the controllable load;
and carrying out heterogeneous aggregation modeling on the comprehensive service station according to the normalization processing result and the homogeneous aggregation model.
Optionally, when the controllable load is a temperature-controlled load, the method for performing homogeneous aggregation modeling of the integrated service station according to the controllable load includes:
dividing the equipment group of the temperature control load into an opening group and a closing group according to the on-off state, and describing the opening state and the closing state of any temperature control load equipment by using a state variable;
respectively determining controlled groups in an opening group and a closing group according to a set controllable temperature range threshold;
using a formula based on the determined controlled population
Figure BDA0003039454500000021
Calculating the homogeneous aggregate power of the temperature-controlled load equipment group under the uncontrolled condition, wherein P T1 (t) homogeneous polymerization power when the temperature-controlled load device performs natural state update at time t, w k For the switching state of the kth temperature-controlled load device,
Figure BDA0003039454500000022
for temperature-controlled load apparatusRated power, N is the number of temperature control load devices;
using a formula based on the determined controlled population
Figure BDA0003039454500000023
Calculating the homogeneous aggregate power of the temperature-controlled load equipment group under the controlled condition, wherein P T2 (t) is the output response of the controllable load according to the load control signal, Δ P 1 And (t) is the adjustment amount borne by the temperature-controlled load equipment.
Optionally, when the controllable load is an energy storage load, the method for performing homogeneous aggregation modeling of the integrated service station according to the controllable load includes:
using a formula
Figure BDA0003039454500000024
Calculating the homogeneous aggregate power of the energy storage load equipment in a natural charging state, wherein P N (t) natural charging power of the energy storage load device at time t, N t Number of energy-storage load devices to be networked at time t, s k For the state of the kth energy storage load device at time t, when the energy storage load device is in an idle state s k 0, when the energy storage load device is in a charging state k ＝1；
Judging whether the time interval between the current time and the last state switching time of the energy storage load equipment is greater than a set time interval or not;
if so, judging that the energy storage load equipment is controllable energy storage load equipment;
if not, judging that the energy storage load equipment is uncontrollable energy storage load equipment;
controllable energy storage load equipment in large-scale controllable loads is collected, and a controllable energy storage load equipment group is established;
dividing the controllable energy storage load equipment group into a controllable charging group, a controllable discharging group and a controllable idle group;
using a formula based on the obtained response control signal
Figure BDA0003039454500000031
Calculating respective charge and discharge powers of the controllable charge group, the controllable discharge group and the controllable idle group at the current moment, wherein,
Figure BDA0003039454500000032
Figure BDA0003039454500000033
Figure BDA0003039454500000034
C t for a controllable charging group, D t Is a controllable discharge group, S t Is a controllable group of the idle objects,
Figure BDA0003039454500000035
respectively the number of the energy storage load devices in the respective energy storage load device group at the time t, and
Figure BDA0003039454500000036
respectively the numbers of the energy storage load devices in the respective energy storage load device groups,
Figure BDA0003039454500000037
for the time interval between the current time and the last state switching time of the energy storage load device,
Figure BDA0003039454500000038
is a set time interval;
and determining the adjusting direction of the energy storage load equipment group according to the obtained tracking target of the controllable energy storage load equipment group.
Optionally, the determining an adjustment direction of the energy storage load device group according to the obtained tracking target of the controllable energy storage load device group includes:
according to the tracking target of the controllable energy storage load equipment group obtained at the time t, a formula delta P is utilized 2 (t)＝P target (t)-P N (t) calculating the power to be regulated of the controllable energy storage load equipment group, wherein P target (t) obtained at time tTracking target, Δ P, for a group of controllable energy storage load devices 2 (t) the power to be regulated of the controllable energy storage load equipment group;
when Δ P 2 (t) when less than 0, reducing the charging power of the controllable energy storage load equipment group;
when Δ P 2 When the t is 0, the controllable energy storage load equipment group has no charging power;
when Δ P is 2 And when the (t) > 0, increasing the charging power of the controllable energy storage load equipment group.
Optionally, when the controllable load is a temperature-controlled load, normalizing the energy state of the controllable load includes:
using formulas
Figure BDA0003039454500000039
Determining a temperature extension margin of the temperature-controlled load device at the current moment, wherein O t And B t The number of the temperature control load devices corresponding to the opening group and the closing group is n 1 And n 2 The total number of the temperature control load equipment is n ═ n 1 +n 2 ，T i，t ，
Figure BDA00030394545000000310
And
Figure BDA00030394545000000311
the operating temperature and the upper limit and the lower limit of the operating temperature at the time t of the ith temperature-controlled load device,
Figure BDA00030394545000000312
the temperature of the temperature control load equipment at the current moment is extended by a margin;
using formulas
Figure BDA00030394545000000313
Determining T corresponding to equipment group of temperature control load EM Gathering;
using formulas
Figure BDA00030394545000000314
T corresponding to temperature-controlled load equipment group EM And performing normalization processing on the set to obtain a normalized temperature extension margin, wherein,
Figure BDA00030394545000000315
extend margin for normalized temperature, and
Figure BDA00030394545000000316
δ i，t for controlling the operating temperature of the load device at time t, and
Figure BDA0003039454500000041
using a formula based on the normalized temperature extension margin
Figure BDA0003039454500000042
Determining NT corresponding to temperature-controlled load equipment group EM A collection of, among other things,
Figure BDA0003039454500000043
NT for temperature-controlled load group EM And (4) collecting.
Optionally, when the controllable load is an energy storage load, normalizing the energy state of the controllable load includes:
using a formula
Figure BDA0003039454500000044
Calculating to obtain the normalized electric quantity adjustable margin of the energy storage load equipment, wherein,
Figure BDA0003039454500000045
for normalizing the electric quantity adjustable margin, and
Figure BDA0003039454500000046
D t and C t Energy storage load equipment discharge group and energy storage load equipment charge group at time t, respectively, corresponding to energy storage load equipment discharge group and energy storage load equipment charge groupThe number of the energy storage load devices is n respectively 1 And n 2 The total number of the energy storage load equipment is n ═ n 1 +n 2 ，E i，t ，
Figure BDA0003039454500000047
And
Figure BDA0003039454500000048
respectively setting the upper limit and the lower limit of the actual charging capacity and the rated capacity of the ith energy storage load device at the time t;
the rated capacity of the energy storage load equipment is defined as the maximum capacity adjustable range at the current moment, and
Figure BDA0003039454500000049
wherein the content of the first and second substances,
Figure BDA00030394545000000410
the maximum capacity adjustable range at the moment t;
according to the normalized electric quantity adjustable margin, utilizing a formula
Figure BDA00030394545000000411
Determining a group of energy storage load devices
Figure BDA00030394545000000412
And (4) corresponding index sets.
Optionally, the method for performing heterogeneous aggregation modeling of the integrated service station according to the normalization processing result and the homogeneous aggregation model includes:
according to the running state of the controllable load, carrying out group division on the controllable load;
extracting key operation parameters of the controllable load, wherein the key operation parameters are parameters capable of reflecting main physical attributes in the load operation process;
formulating a normalization index according to the key operation parameters;
and carrying out power aggregation on the controllable load by adopting a homogenization aggregation modeling method according to the group division result and the normalization index of the controllable load.
Optionally, the method for formulating the normalization index according to the key operation parameter specifically includes:
and formulating a normalization index according to the key operation parameters by adopting a weight method.
A step aggregation system of an integrated service station based on large-scale controllable loads comprises:
a homogenization aggregation module, configured to perform homogenization aggregation modeling of the integrated service station according to the controllable load, where the controllable load includes: temperature control load and energy storage load;
the normalization processing module is used for performing normalization processing on the energy state of the controllable load;
and the heterogeneous aggregation module is used for carrying out heterogeneous aggregation modeling on the comprehensive service station according to the normalization processing result and the homogeneous aggregation model.
Optionally, the heterogeneous aggregation module comprises:
the group division unit is used for carrying out group division on the controllable load according to the running state of the controllable load;
the normalization index formulation unit is used for extracting key operation parameters of the controllable load and formulating the normalization index according to the key operation parameters, wherein the key operation parameters are parameters capable of reflecting main physical attributes in the load operation process;
the integration unit is used for integrating the normalization indexes of the key operation parameters to obtain comprehensive normalization indexes;
and the power aggregation unit is used for carrying out power aggregation on the controllable loads by adopting a homogenization aggregation modeling method according to the group division result and the comprehensive normalization index of the controllable loads.
The technical scheme provided by the embodiment of the application can have the following beneficial effects:
the method comprises the steps of firstly carrying out homogenization aggregation modeling on the comprehensive service station according to the controllable load, then carrying out normalization processing on the energy state of the controllable load, and finally carrying out heterogeneous aggregation modeling on the comprehensive service station according to a normalization processing result and a homogenization aggregation model, thereby finally realizing the cascade aggregation of the comprehensive service station. The cascade polymerization method is oriented to the whole comprehensive service station, and is used for sequentially carrying out homogenization polymerization modeling, normalization processing and heterogeneous modeling based on the operation mechanism and the power characteristic of the controllable load. The whole cascade aggregation method can take user requirements and equipment operation requirements into consideration, extract key operation parameters of controllable load equipment, construct a homogeneous aggregation model and a heterogeneous aggregation model, determine individuals capable of participating in response according to the key parameters, perform power aggregation, and finally determine response individuals according to the instruction condition of a superior power grid. The method in the embodiment can comprehensively consider and balance the requirements of all links of the whole comprehensive service station, determine the final response individual, and has higher control accuracy on energy.
The application also provides a comprehensive service station step aggregation system based on the large-scale controllable load. The system mainly comprises: the device comprises a homogenization polymerization module, a normalization processing module and a heterogeneous polymerization module. The homogeneous polymerization module is used for constructing a homogeneous polymerization model according to key operation parameters of controllable load equipment, the normalization processing module is used for normalizing the energy state of the controllable load, and finally the heterogeneous polymerization module is used for heterogeneous polymerization according to the results of the first two modules, so that the cascade polymerization of the whole comprehensive service station is finally realized. The system can consider the requirements of users and the operation requirements of equipment, comprehensively balance the requirements of all links of the comprehensive service station, and determine the final response individual, and compared with the prior art, the accuracy and flexibility of the structure on energy control are greatly improved. Moreover, the system in the embodiment is oriented to the whole large-scale controllable load comprehensive service station, is not limited to a part of small systems, and is more deeply researched on the space-time scale of the physical characteristics of the resources in the system, so that the control on the energy is more accurate and effective.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a large-scale controllable load-based integrated service station step aggregation method according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram illustrating a dynamic process of load temperature and power when an electric heat pump is used as a temperature control load in the embodiment of the present application;
FIG. 3 is a schematic diagram of an equivalent thermodynamic model of an electric heat pump device in an embodiment of the present application;
FIG. 4 is a schematic diagram of a model of the indoor temperature variation and the controllable range of the electric heat pump according to the embodiment of the present application;
FIG. 5 is a schematic diagram of a temperature extension margin;
FIG. 6 is a schematic diagram of a charging trace of an electric vehicle according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an integrated service station step aggregation system based on large-scale controllable loads according to an embodiment of the present application.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Aggregate modeling is to establish a model based on the characteristics of an aggregate of load clusters as an organic whole. The step aggregation is characterized in that after a certain part of loads are aggregated, the aggregated loads are used as a subset of another aggregation model to participate in the aggregation process, and steps are presented. The polymerization process can be classified into homogeneous polymerization and heterogeneous polymerization according to whether the internal parameters of the load involved in the polymerization are the same or not. The homogeneous polymerization refers to the polymerization of controllable load groups with the same internal parameters, and is suitable for load groups with the same operation parameters. Heterogenous aggregation refers to aggregation of controllable load groups with different internal parameters, and is suitable for load groups with different operation parameters. Typically, homogeneous aggregation is used at a single load type level, and heterogeneous aggregation is used at multiple load type levels. The invention combines homogeneous polymerization and heterogeneous polymerization to be applied to the step polymerization method of the comprehensive service station.
For a better understanding of the present application, embodiments of the present application are explained in detail below with reference to the accompanying drawings.
Example one
Referring to fig. 1, fig. 1 is a schematic flow chart of a large-scale controllable load-based integrated service station step aggregation method according to an embodiment of the present application. As shown in fig. 1, the step aggregation method for a comprehensive service station based on large-scale controllable loads in this embodiment mainly includes the following steps:
s1: and carrying out homogeneous aggregation modeling on the comprehensive service station according to the controllable load.
Wherein, the controllable load in this embodiment includes: temperature control load and energy storage load. The temperature control load mainly comprises: air conditioners, electric heat pumps, and the like. The energy storage load mainly comprises: energy storage stations, electric vehicles, and the like.
When the controllable load is the temperature control load, the homogeneous polymerization modeling method of the comprehensive service station is carried out according to the controllable load, and the method comprises the following steps:
s111: according to the on-off state, the equipment group of the temperature control load is divided into an on group and an off group, and the on state and the off state of any temperature control load equipment are described by a state variable.
Taking an electric heating pump as an example, when a large number of electric heating pumps participate in response control, the aggregated load adjusting effect can be equivalent to an energy efficiency motor.
The schematic diagram of the load temperature and power dynamic process of the electric heating pump device in this embodiment can be seen in fig. 2. A schematic diagram of a thermodynamic equivalent model of an electrothermal pump device can be seen in fig. 3. In fig. 3, the physical Model and key parameters of the building are retained, and the indoor air temperature regulated by the electric heat pump and the surface temperature of the indoor substance are used as state variables of the Model, which is also referred to as a Two Mass Model (Two Mass Model) for short. The model of the equipment is established by using thermodynamic concepts such as heat capacity, heat resistance and the like, and the specific formula is expressed as follows:
Figure BDA0003039454500000071
in the formula, C a Indicating indoor air heat capacity, C m Denotes the heat capacity of the indoor material, R a Indicating the thermal resistance of the air in the standby room, R m Representing the thermal resistance of the matter in the standby chamber, K representing the operation thermal ratio of the electric heat pump device, T o Indicating the outdoor temperature, T a Indicating the temperature of the indoor air, T m Indicating the temperature of the contents of the room.
When the electric heat pump is turned off, the following conditions are satisfied:
Figure BDA0003039454500000072
when the electric heat pump is started, the following conditions are met:
Figure BDA0003039454500000081
in the formula, theta room The indoor temperature regulated by the electric heat pump is represented by C in unit of equivalent thermal capacitance and J/DEG C in unit of equivalent thermal resistance, R in unit of equivalent thermal ratio and W, and Q in unit of equivalent thermal ratio out The outdoor temperature is shown in unit ℃, t is simulation time, and delta t is simulation step length.
Based on the model, when a large number of electric heating pumps participate in response control, the aggregated load regulation effect can be equivalent to an energy-efficiency motor.
Taking an electric heat pump as an example, according to the method in step S111, the equipment groups of the temperature-controlled load are first divided into an on group and an off group. With a state variable n i Describing the on or off state of the ith electrothermal pump when n i When the voltage is equal to 1, the electric heat pump is in an on state, and when n is equal to i When the value is 0, the electric heat pump is in a closed state. Assuming that there are 20 temperature-controlled load devices in the temperature-controlled load device group, 5 are in an on state, and 15 are in an off state, the entire temperature-controlled load device group is divided into an "on group (n) 1 ～n 5 ) And closing group (n) 6 ～n 20 ) "two groups of devices.
S112: and respectively determining the controlled groups in the opening group and the closing group according to the set controllable temperature range threshold.
In practical application, when temperature control load homogenization polymerization modeling is carried out, the factors such as the service life of temperature control load equipment, user comfort constraint and the like can be referred to. And respectively determining the controlled population of the opening population and the controlled population of the closing population according to the set controllable temperature range threshold. If the temperature of the current temperature-controlled load equipment is within the set controllable temperature range threshold, the temperature-controlled load equipment can participate in response control as an individual, otherwise, if the temperature of the current temperature-controlled load equipment is outside the set controllable temperature range threshold, the current temperature-controlled load equipment is judged to be the individual, the starting or closing time of the current temperature-controlled load equipment is short, the limit requirement of equipment operation constraint is not met, and the current temperature-controlled load equipment is not suitable for participating in response control.
Taking an electric heat pump as an example, the temperature changes within the room
Figure BDA0003039454500000082
In the method, the controllable range of the electric heat pump is defined as
Figure BDA0003039454500000083
And
Figure BDA0003039454500000084
the controllable temperature range threshold can be seen in fig. 4.
The temperature control load groups and the controlled groups are classified, so that the accuracy of energy control is further improved, and when some groups need to be closed or opened, individuals to be closed or opened can be flexibly and accurately determined, the accuracy and flexibility of energy control are improved, and the control efficiency is further improved.
S113: using a formula based on the determined controlled population
Figure BDA0003039454500000085
And calculating the homogenization aggregate power of the temperature-controlled load equipment group under the uncontrolled condition.
Wherein, P T1 (t) homogeneous aggregate power when the temperature-controlled load device performs natural state update at time t, w k For the switching state of the kth temperature-controlled load device,
Figure BDA0003039454500000086
the rated power of the temperature control load equipment is N, the number of the temperature control load equipment is t, the current moment is t, and the next moment is t + delta t.
The homogenization aggregate power of the temperature-controlled load equipment group under the uncontrolled condition, that is, the natural power consumption of the temperature-controlled load equipment group under the uncontrolled condition, that is: and the output under the condition of uncontrolled aggregate load represents the aggregate power when the temperature-controlled load equipment carries out natural state updating.
S114: using a formula based on the determined controlled population
Figure BDA0003039454500000091
And calculating the homogenization aggregate power of the temperature control load equipment group under the controlled condition. Wherein, P T2 (t) is the output response of the controllable load according to the load control signal, Δ P 1 And (t) is the adjustment amount borne by the temperature-controlled load equipment.
The homogenization aggregate power of the temperature-controlled load equipment group under the controlled condition, namely the output response of the controllable load according to the load control signal, is represented as the difference between the natural state update power and the regulated quantity.
The homogenization polymerization power calculation of the temperature control load equipment group under the controlled condition and the uncontrolled condition can provide a basis for subsequent adjustment, and further improve the accuracy and efficiency of energy control.
When the controllable load is an energy storage load, according to the controllable load, a method for performing homogenization polymerization modeling of the comprehensive service station specifically comprises the following processes:
s121: using formulas
Figure BDA0003039454500000092
And calculating the homogenization aggregation power of the energy storage load equipment in a natural charging state.
Wherein, P N (t) Natural charging Power of the energy storage load device at time t, N t The number of the energy storage load devices connected to the network at the time t is as follows: the number of energy storage batteries connected to the network at time t, s k For the state of the kth energy storage load device at time t, when the energy storage load device is in an idle state s k 0, when the energy storage load device is in a charging state k ＝1。
In this embodiment, the energy storage load device is an electric vehicle, so N t Number of electric vehicles networked at time t, s k For the state of the kth electric vehicle at time t, when the electric vehicle is in an idle state s k 0, when the electric vehicle is in a charging state k ＝1。
S122: and judging whether the time interval between the current time and the last state switching time of the energy storage load equipment is greater than the set time interval.
If the time interval between the current time and the last state switching time of the energy storage load device is greater than the set time interval, executing step S123: and judging that the energy storage load equipment is controllable energy storage load equipment.
If the time interval between the current time and the last state switching time of the energy storage load device is less than or equal to the set time interval, step S124 is executed: and judging that the energy storage load equipment is uncontrollable energy storage load equipment.
Through the steps S122 to S124, the time interval between the current time and the last state switching time of the energy storage load device is compared with the set time interval, when the current time is larger, it is determined that the current energy storage load device satisfies the condition, and the subsequent steps are executed for the current energy storage load device, otherwise, it is determined that the energy storage load device is uncontrollable, and the process is ended. Through the set time interval, the service life of the energy storage load equipment can be prevented from being shortened due to frequent switching of the charging and discharging states of the energy storage load equipment, and the performance of the energy storage load equipment is protected.
S125: controllable energy storage load equipment in the large-scale controllable load is gathered, and a controllable energy storage load equipment group is established.
After the controllable energy storage load device group is established, step S126 is executed: and dividing the controllable energy storage load equipment group into a controllable charging group, a controllable discharging group and a controllable idle group.
In this embodiment, C is used for the controllable charging group, the controllable discharging group and the controllable idle group t 、D t And S t And (4) showing. Wherein the content of the first and second substances,
Figure BDA0003039454500000101
Figure BDA0003039454500000102
Figure BDA0003039454500000103
respectively the number of the energy storage load devices in the respective energy storage load device group at the time t, and
Figure BDA0003039454500000104
respectively the numbers of the energy storage load devices in the respective energy storage load device groups,
Figure BDA0003039454500000105
for the time interval between the current time and the last state switching time of the energy storage load device,
Figure BDA0003039454500000106
at set time intervals.
S127: using a formula based on the obtained response control signal
Figure BDA0003039454500000107
And calculating the charge and discharge power of the controllable charge group, the controllable discharge group and the controllable idle group at the current moment, namely calculating the charge power of the controllable charge group, calculating the discharge power of the controllable discharge group and calculating the charge and discharge power of the controllable idle group.
Wherein, C t For a controllable charging group, D t Is a controllable discharge group, S t Is a controlled idle group.
S128: and determining the adjusting direction of the energy storage load equipment group according to the acquired tracking target of the controllable energy storage load equipment group.
Specifically, step S128 includes the following procedure:
s1281: according to the tracking target of the controllable energy storage load equipment group obtained at the time t, a formula delta P is utilized 2 (t)＝ P target (t)-P N And (t), calculating to-be-adjusted power of the controllable energy storage load equipment group.
Wherein, P target (t) represents a tracking target which is sent to the energy storage load equipment group by the system control center at the moment t, and delta P 2 (t) regulating Power of the energy storage load group, P N And (t) is the natural charging power of the energy storage load equipment at the moment t.
S1282: when Δ P 2 And when the (t) is less than 0, reducing the charging power of the controllable energy storage load equipment group.
The method for reducing the charging power can be used for controlling part of the energy storage load equipment to stop charging in advance, and can also be used for discharging to a power grid through the energy storage load equipment group.
S1283: when Δ P is 2 When the t is 0, the controllable energy storage load equipment group has no charging power;
s1284: when Δ P 2 And when the (t) > 0, increasing the charging power of the controllable energy storage load equipment group.
Step S128 can specify the direction to be adjusted of the energy storage load device group by setting the calculation formula of the power to be adjusted of the controllable energy storage load device group, thereby improving the accuracy of energy control.
With continued reference to fig. 1, after performing homogeneous aggregation modeling of the integrated service station in the present embodiment, step S2 is executed: and carrying out normalization processing on the energy state of the controllable load.
Specifically, according to different controllable loads, the energy state of the controllable load is normalized.
When the controllable load is a temperature-controlled load, the normalizing the energy state of the controllable load comprises the following steps:
s211: using formulas
Figure BDA0003039454500000111
And determining the temperature extension margin of the temperature-controlled load equipment at the current moment.
Wherein, O t And B t The number of the temperature control load devices corresponding to the opening group and the closing group is n 1 And n 2 Over time, n 1 And n 2 Can also change along with the running state of the temperature control load equipment, and the total number of the temperature control load equipment is n-n 1 +n 2 ，T i，t ，
Figure BDA0003039454500000112
And
Figure BDA0003039454500000113
the operating temperature and the upper limit and the lower limit of the operating temperature at time t of the ith temperature-controlled load device,
Figure BDA0003039454500000114
and extending the margin for the temperature of the temperature-controlled load equipment at the current moment.
A schematic diagram of the temperature extension margin in the present embodiment can be seen in fig. 5. As can be seen from FIG. 5, T EM Load units in different groups, T, related to the current operating state of the load EM Different definitions, while taking into account different loadsThe operating characteristics of (A) are different, and the upper and lower temperature limits are different. In fig. 5, the increasing direction of the temperature is shown from left to right, the shaded area is the operating temperature interval of the device, the position of the black square indicates the current temperature of the device, and the arrow points to the extending direction of the temperature of the device.
S212: using formulas
Figure BDA0003039454500000115
Determining T corresponding to equipment group of temperature control load EM And (5) aggregating.
S213: using formulas
Figure BDA0003039454500000116
T corresponding to temperature-controlled load equipment group EM And performing normalization processing on the set to obtain a normalized temperature extension margin.
Wherein the content of the first and second substances,
Figure BDA0003039454500000117
extend margin for normalized temperature, and
Figure BDA0003039454500000118
δ i，t for controlling the operating temperature of the load device at time t, and
Figure BDA0003039454500000119
s214: using a formula based on the normalized temperature extension margin
Figure BDA00030394545000001110
Determining NT corresponding to temperature-controlled load equipment group EM And (4) collecting. Wherein, the first and the second end of the pipe are connected with each other,
Figure BDA00030394545000001111
NT for temperature-controlled load group EM And (4) collecting.
When the controllable load is an energy storage load, the normalization processing of the energy state of the controllable load comprises the following steps:
s221: using formulas
Figure BDA00030394545000001112
And calculating to obtain the normalized electric quantity adjustable margin of the energy storage load equipment.
Wherein the content of the first and second substances,
Figure BDA00030394545000001113
for normalizing the electric quantity adjustable margin, and
Figure BDA00030394545000001114
D t and C t The energy storage load equipment discharging group and the energy storage load equipment charging group are respectively at the moment t, and the number of the energy storage load equipment corresponding to the energy storage load equipment discharging group and the energy storage load equipment charging group is n 1 And n 2 The total quantity of the energy storage load equipment is n ═ n 1 +n 2 ，E i，t ，
Figure BDA00030394545000001115
And
Figure BDA00030394545000001116
the upper limit and the lower limit of the actual charging capacity and the rated capacity of the ith energy storage load device at the time t are respectively.
In this embodiment, the energy storage load device is an electric vehicle, and a schematic diagram of a charging track of the electric vehicle can be shown in fig. 6. The charging trace is analogous to the temperature curve of an electrothermal pump. As can be seen from fig. 6, when the charging state of the electric vehicle changes, the power consumption changes accordingly, and the power consumption of the electric vehicle can be influenced by controlling the charging state.
S222: the rated capacity of the energy storage load equipment is defined as the maximum capacity adjustable range at the current moment, and
Figure BDA0003039454500000121
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0003039454500000122
the maximum adjustable capacity range at the moment t.
S223: according to the adjustable margin of the normalized electric quantity, a formula is utilized
Figure BDA0003039454500000123
Determining a group of energy storage load devices
Figure BDA0003039454500000124
And (4) corresponding index sets.
Through the normalization processing process, load groups under various load types can be summarized by adopting a unified standard, a basis is provided for subsequent heterogeneous polymerization, and the heterogeneous polymerization modeling efficiency is improved.
With continued reference to fig. 1, after the normalization process is performed on the energy state of the controllable load, step S3 is executed: and carrying out heterogeneous aggregation modeling on the comprehensive service station according to the normalization processing result and the homogeneous aggregation model.
The method for carrying out heterogeneous aggregation modeling of the comprehensive service station comprises the following processes:
s31: and carrying out group division on the controllable load according to the running state of the controllable load.
At each moment, the system can be divided into a plurality of load groups according to the load running state, such as: the load of the electric heating pump can be divided into an opening group and a closing group, and the load of the electric automobile can be divided into a charging group, a discharging group, an idle group and an off-grid group.
The controllable load group is then expressed as:
Figure BDA0003039454500000125
any one of the controllable load groups is:
Figure BDA0003039454500000126
wherein t is the current time, n is the number of load groups,
Figure BDA0003039454500000127
the number of the equipment contained in the load groups divided according to the load running state at the moment t is m 1 ，m 2 ，…，m i ，…，m n The total number of the devices is m ═ m 1 +m 2 +...+m i +...+m n ，
Figure BDA0003039454500000128
Is W i t The iwth burden in the population.
S32: and extracting key operation parameters of the controllable load.
The key operation parameters are parameters capable of reflecting main physical attributes in the load operation process.
The key operation parameters of the load reflect the main physical attributes of the load in the operation process, and the working state of the load can be restored by analyzing the parameters or the combination of the parameters.
Different key operation parameter sets of the response group at the time t are defined as lambda t ＝(Λ 1 t ，Λ 2 t ，...，Λ i t ，...，Λ s t ) And s is the number of key operation parameters.
In the equation, the ith set of key operating parameters can be expressed as:
Figure BDA0003039454500000129
wherein the content of the first and second substances,
Figure BDA00030394545000001210
is the ia parameter in the ith key operation parameter set at the time t, and can also be expressed as Λ i t (ia)。
As can be seen from the above equation, for the ith load, load i for short, there are s key operating parameters at time t: lambda 1 t (i)，Λ 2 t (i)，...，Λ s t (i)。
S33: and formulating a normalization index according to the key operation parameters.
Specifically, step S33 may employ the following method: and formulating a normalization index according to the key operation parameters by adopting a weight method.
According to step S32After the key operation parameters of the controllable load are taken, the key operation parameters are normalized to obtain the comprehensive normalization index at the time t
Figure BDA00030394545000001310
Wherein h (-) represents a parameter integration method.
Definition I t Is a comprehensive index set expressed as
Figure BDA0003039454500000131
Wherein the content of the first and second substances,
Figure BDA0003039454500000132
is I t The iu index in (1).
Further, in this embodiment, a method for formulating a normalization index according to the key operation parameter specifically adopts a weight method.
The integration method can adopt a weight method: and distributing the weight of each key operation parameter participating in the calculation of the comprehensive index, for example, considering the energy state serialization algorithm of the electric vehicle of the controlled times, namely weighting the energy state and the switch state after the two key operation variables are respectively per unit to obtain the comprehensive serialization index which is used as the basis for screening the energy storage load equipment group after aggregation.
In addition, in the embodiment, the structure of the comprehensive index can be realized through the operation between the key operation parameters with relevance. Such as: the ratio of the indoor temperature of different electric heat pumps and the corresponding operating temperature interval is used as a comprehensive index, and the diversity difference of the equipment is considered.
Similarly, defining the collection of load group operation control variables at time t as
Figure BDA0003039454500000133
The whole load group has e operation control variable sets.
The ith set of operating control variables may be represented as:
Figure BDA0003039454500000134
wherein the content of the first and second substances,
Figure BDA0003039454500000135
the ith variable in the ith set of run control variables at time t may also be expressed as
Figure BDA0003039454500000136
At time t, the electric power consumed by load i
Figure BDA00030394545000001311
The function for each of the above operational control variables should be:
Figure BDA0003039454500000137
definition V t Is a set of powers for the load group,
Figure BDA0003039454500000138
is a V t The power of the load group is:
Figure BDA0003039454500000139
through the transportation between the key operating parameters with relevance, the comprehensive index structure is realized, and environmental factors and user experience requirements can be further considered, such as: the users with the same area, the middle users and the side users have different requirements on cold and heat, and the method enables the energy control to be more flexible and is beneficial to further improving the accuracy of the energy control.
After the normalization index is formulated according to the key operation parameters, step S34 is executed: and carrying out power aggregation on the controllable loads by adopting a homogenization aggregation modeling method according to the group division result and the normalization index of the controllable loads.
The method for homogeneous polymerization modeling has been described in detail above and will not be described in detail here.
Example two
Referring to fig. 7 on the basis of fig. 1 to fig. 6, fig. 7 is a schematic structural diagram of an integrated service station step aggregation system based on large-scale controllable loads according to an embodiment of the present application. As can be seen from fig. 7, the integrated service station step aggregation system based on large-scale controllable load in this embodiment mainly includes: the device comprises a homogenization polymerization module, a normalization processing module and a heterogeneous polymerization module.
The homogenization aggregation module is used for carrying out homogenization aggregation modeling on the comprehensive service station according to controllable loads, and the controllable loads comprise: temperature control load and energy storage load; the normalization processing module is used for performing normalization processing on the energy state of the controllable load; and the heterogeneous aggregation module is used for carrying out heterogeneous aggregation modeling on the comprehensive service station according to the normalization processing result and the homogeneous aggregation model.
Further, the homogenization polymerization module comprises: the temperature control load homogenization polymerization unit and the energy storage load homogenization polymerization unit.
The temperature-controlled load homogenization polymerization unit further comprises: the device comprises a first device grouping subunit, a controlled group determining subunit, a first homogeneous polymerization power subunit and a second homogeneous polymerization power subunit. The first equipment grouping subunit is used for dividing the equipment group of the temperature control load into an opening group and a closing group according to the on-off state, and describing the opening state and the closing state of any temperature control load equipment by using a state variable; the controlled population determining subunit is used for respectively determining the controlled populations in the opening population and the closing population according to the set controllable temperature range threshold; a first homogeneous polymerization power subunit for utilizing a formula according to the determined controlled population
Figure BDA0003039454500000141
Calculating the homogeneous aggregate power of the temperature-controlled load equipment group under the uncontrolled condition, wherein P T1 (t) homogeneous polymerization power when the temperature-controlled load device performs natural state update at time t, w k For the switching state of the kth temperature-controlled load device,
Figure BDA0003039454500000142
for controlling temperature negativelyRated power of load equipment, wherein N is the number of temperature control load equipment; a second homogeneous aggregate power subunit for utilizing the formula according to the determined controlled population
Figure BDA0003039454500000143
Calculating the homogeneous aggregate power of the temperature-controlled load equipment group under the controlled condition, wherein P T2 (t) is the output response of the controllable load according to the load control signal, Δ P 1 And (t) the adjustment amount borne by the temperature-controlled load equipment.
The energy storage load homogenization polymerization unit further comprises: the device comprises a third homogenization polymerization power subunit, a judgment subunit, a summary subunit, a second equipment grouping subunit, a charge-discharge power calculation subunit and an adjustment direction determination subunit. Wherein the third homogeneous polymerization power subunit is used for utilizing the formula
Figure BDA0003039454500000144
Calculating the homogeneous aggregate power of the energy storage load equipment in a natural charging state, wherein P N (t) Natural charging Power of the energy storage load device at time t, N t Number of energy-storage load devices to be networked at time t, s k For the state of the kth energy storage load device at time t, when the energy storage load device is in an idle state s k 0, when the energy storage load device is in a charging state k 1 is ═ 1; the judging subunit is used for judging whether the time interval between the current time and the last state switching time of the energy storage load equipment is greater than the set time interval or not, if so, judging that the energy storage load equipment is controllable energy storage load equipment, and if not, judging that the energy storage load equipment is uncontrollable energy storage load equipment; the collecting subunit is used for collecting the controllable energy storage load equipment in the large-scale controllable load and establishing a controllable energy storage load equipment group; the second equipment grouping subunit is used for dividing the controllable energy storage load equipment group into a controllable charging group, a controllable discharging group and a controllable idle group; a charge/discharge power calculating subunit for calculating the charge/discharge power according to the obtained response control signal by using a formula
Figure BDA0003039454500000151
Calculating respective charge and discharge powers of the controllable charge group, the controllable discharge group and the controllable idle group at the current moment, wherein,
Figure BDA0003039454500000152
Figure BDA0003039454500000153
Figure BDA0003039454500000154
C t for a controllable charging group, D t Is a controllable discharge group, S t Is a controllable group of the idle objects,
Figure BDA0003039454500000155
respectively the number of the energy storage load devices in the respective energy storage load device group at the time t, and
Figure BDA0003039454500000156
respectively the numbers of the energy storage load devices in the respective energy storage load device groups,
Figure BDA0003039454500000157
for the time interval between the current time and the last state switching time of the energy storage load device,
Figure BDA0003039454500000158
is a set time interval; and the adjusting direction determining subunit is used for determining the adjusting direction of the energy storage load equipment group according to the acquired tracking target of the controllable energy storage load equipment group.
The normalization processing module comprises: a first normalization processing unit and a second normalization processing unit.
The first normalization processing unit includes: temperature extension margin determination subunit, T EM Set determination subunit, T EM Set normalization processing subunit and NT EM The set determines the sub-unit.
Wherein the temperature extension margin determines the sub-unit for utilizing the formula
Figure BDA0003039454500000159
Determining a temperature extension margin of the temperature-controlled load device at the current moment, wherein O t And B t The number of the temperature control load devices corresponding to the opening group and the closing group is n 1 And n 2 The total number of the temperature control load equipment is n ═ n 1 +n 2 ， T i，t ，
Figure BDA00030394545000001510
And
Figure BDA00030394545000001511
the operating temperature and the upper limit and the lower limit of the operating temperature at time t of the ith temperature-controlled load device,
Figure BDA00030394545000001512
the temperature of the temperature-controlled load device at the current moment is extended by a margin. T is EM Set determination subunit for utilizing formula
Figure BDA00030394545000001513
Determining T corresponding to equipment group of temperature control load EM Gathering; t is EM An aggregate normalization processing subunit for utilizing the formula
Figure BDA00030394545000001514
T corresponding to temperature-controlled load equipment group EM And carrying out normalization processing on the set to obtain a normalized temperature extension margin, wherein,
Figure BDA00030394545000001515
to normalize the temperature extension margin, and
Figure BDA00030394545000001516
δ i，t for controlling the operating temperature of the load device at time t, and
Figure BDA00030394545000001517
NT EM a set determination subunit for utilizing a formula based on the normalized temperature extension margin
Figure BDA00030394545000001518
Determining NT corresponding to temperature-controlled load equipment group EM A set of, among others,
Figure BDA00030394545000001519
NT for temperature-controlled load group EM And (4) collecting.
The second normalization processing unit includes: normalized electric quantity adjustable margin calculating subunit, maximum capacity adjustable range defining subunit and
Figure BDA00030394545000001520
the index set determines the sub-unit.
Wherein the operator unit of the adjustable margin of the normalized electric quantity is used for utilizing a formula
Figure BDA0003039454500000161
Calculating to obtain the normalized electric quantity adjustable margin of the energy storage load equipment, wherein,
Figure BDA0003039454500000162
for normalizing the electric quantity adjustable margin, and
Figure BDA0003039454500000163
D t and C t The energy storage load equipment discharge group and the energy storage load equipment charging group at the moment t are respectively, and the number of the energy storage load equipment corresponding to the energy storage load equipment discharge group and the energy storage load equipment charging group is n 1 And n 2 The total number of the energy storage load equipment is n ═ n 1 +n 2 ，E i，t ，
Figure BDA0003039454500000164
And
Figure BDA0003039454500000165
are respectively provided withThe upper limit and the lower limit of the actual charging capacity and the rated capacity of the ith energy storage load device at the time t; a maximum capacity adjustable range defining subunit, configured to define a rated capacity of the energy storage load device as a maximum capacity adjustable range at the current time, and
Figure BDA0003039454500000166
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0003039454500000167
the maximum capacity adjustable range at the moment t;
Figure BDA0003039454500000168
an index set determination subunit, configured to utilize a formula according to the normalized power adjustable margin
Figure BDA0003039454500000169
Determining a group of energy storage load devices
Figure BDA00030394545000001610
A corresponding set of metrics.
Further, the heterogeneous polymerization module comprises: the device comprises a group division unit, a normalization index making unit, an integration unit and a power aggregation unit. The group division unit is used for carrying out group division on the controllable load according to the running state of the controllable load; the normalization index formulation unit is used for extracting key operation parameters of the controllable load and formulating the normalization index according to the key operation parameters, wherein the key operation parameters are parameters capable of reflecting main physical attributes in the load operation process; the integration unit is used for integrating the normalization indexes of the key operation parameters to obtain comprehensive normalization indexes; and the power aggregation unit is used for carrying out power aggregation on the controllable loads by adopting a homogenization aggregation modeling method according to the group division result and the comprehensive normalization index of the controllable loads.
The working principle and the working method of the large-scale controllable load-based integrated service station cascade aggregation system in this embodiment have been explained in detail in the embodiments shown in fig. 1 to 6, and are not described again here.
The previous description is only an example of the present application, and is provided to enable any person skilled in the art to understand or implement the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (9)

1. A large-scale controllable load-based step aggregation method for an integrated service station is characterized by comprising the following steps:
according to the controllable load, carrying out homogeneous aggregation modeling of the comprehensive service station, wherein the controllable load comprises: temperature control load and energy storage load;
normalizing the energy state of the controllable load;
according to the normalization processing result and the homogenization aggregation model, carrying out heterogeneous aggregation modeling on the comprehensive service station;
when the controllable load is a temperature control load, the method for performing homogenization aggregation modeling of the comprehensive service station according to the controllable load comprises the following steps:
dividing the equipment group of the temperature control load into an opening group and a closing group according to the on-off state, and describing the opening state and the closing state of any temperature control load equipment by using a state variable;
respectively determining controlled groups in an opening group and a closing group according to a set controllable temperature range threshold;
using a formula based on the determined controlled population
Figure FDA0003808597960000011
Calculating the homogeneous aggregate power of the temperature-controlled load equipment group under the uncontrolled condition, wherein P T1 (t) homogeneous polymerization power when the temperature-controlled load device performs natural state update at time t, w k For the switching state of the kth temperature-controlled load device,
Figure FDA0003808597960000012
the rated power of the temperature control load equipment, and N is the number of the temperature control load equipment;
using a formula based on the determined controlled population
Figure FDA0003808597960000013
Calculating the homogeneous aggregate power of the temperature-controlled load equipment group under the controlled condition, wherein P T2 (t) is the output response of the controllable load according to the load control signal, Δ P 1 And (t) is the adjustment amount borne by the temperature-controlled load equipment.
2. The method for large-scale controllable load-based step aggregation of the integrated service station according to claim 1, wherein when the controllable load is an energy storage load, a method for performing homogeneous aggregation modeling of the integrated service station according to the controllable load comprises:
using formulas
Figure FDA0003808597960000014
Calculating the homogeneous aggregate power of the energy storage load equipment in a natural charging state, wherein P N (t) Natural charging Power of the energy storage load device at time t, N t Number of energy-storage load devices to be networked at time t, s k For the state of the kth energy storage load device at time t, when the energy storage load device is in an idle state s k 0, when the energy storage load device is in a charging state k ＝1；
Judging whether the time interval between the current time and the last state switching time of the energy storage load equipment is greater than a set time interval or not;
if so, judging that the energy storage load equipment is controllable energy storage load equipment;
if not, judging that the energy storage load equipment is uncontrollable energy storage load equipment;
controllable energy storage load equipment in large-scale controllable loads is collected, and a controllable energy storage load equipment group is established;
dividing the controllable energy storage load equipment group into a controllable charging group, a controllable discharging group and a controllable idle group;
using a formula based on the obtained response control signal
Figure FDA0003808597960000021
Calculating respective charge and discharge powers of the controllable charge group, the controllable discharge group and the controllable idle group at the current moment, wherein,
Figure FDA0003808597960000022
Figure FDA0003808597960000023
Figure FDA0003808597960000024
C t for a controllable charging group, D t Is a controllable discharge group, S t Is a controllable group of the idle objects,
Figure FDA0003808597960000025
respectively the number of the energy storage load devices in the respective energy storage load device group at the time t, and
Figure FDA0003808597960000026
Figure FDA0003808597960000027
respectively the numbers of the energy storage load devices in the respective energy storage load device groups,
Figure FDA0003808597960000028
for the time interval between the current time and the last state switching time of the energy storage load device,
Figure FDA0003808597960000029
to set upThe time interval of (c);
and determining the adjusting direction of the energy storage load equipment group according to the acquired tracking target of the controllable energy storage load equipment group.
3. The large-scale controllable load-based step aggregation method for the comprehensive service station, according to claim 2, wherein the determining the adjustment direction of the energy storage load device group according to the obtained tracking target of the controllable energy storage load device group comprises:
according to the tracking target of the controllable energy storage load equipment group obtained at the time t, a formula delta P is utilized 2 (t)＝P target (t)-P N (t) calculating the power to be regulated of the controllable energy storage load equipment group, wherein P target (t) is a tracking target, delta P, of the controllable energy storage load equipment group obtained at time t 2 (t) is the power to be regulated of the controllable energy storage load equipment group;
when Δ P 2 (t)<When 0, reducing the charging power of the controllable energy storage load equipment group;
when Δ P 2 When the t is 0, the controllable energy storage load equipment group has no charging power;
when Δ P 2 (t)>And when 0, increasing the charging power of the controllable energy storage load equipment group.
4. The method as claimed in claim 1, wherein when the controllable load is a temperature-controlled load, the normalizing the energy state of the controllable load comprises:
using formulas
Figure FDA00038085979600000210
Determining a temperature extension margin of the temperature controlled load device at the current moment, wherein O t And B t The number of the temperature control load devices corresponding to the opening group and the closing group is n 1 And n 2 The total number of the temperature control load equipment is n ═ n 1 +n 2 ，T i,t ，
Figure FDA00038085979600000211
And
Figure FDA00038085979600000212
the operating temperature and the upper limit and the lower limit of the operating temperature at the time t of the ith temperature-controlled load device,
Figure FDA00038085979600000213
the temperature of the temperature control load equipment at the current moment is extended by a margin;
using formulas
Figure FDA0003808597960000031
Determining T corresponding to equipment group of temperature control load EM Gathering;
using formulas
Figure FDA0003808597960000032
T corresponding to temperature-controlled load equipment group EM And performing normalization processing on the set to obtain a normalized temperature extension margin, wherein,
Figure FDA0003808597960000033
to normalize the temperature extension margin, and
Figure FDA0003808597960000034
δ i,t for controlling the operating temperature of the load device at time t, and
Figure FDA0003808597960000035
using a formula based on the normalized temperature extension margin
Figure FDA0003808597960000036
Determining NT corresponding to temperature-controlled load equipment group EM A collection of, among other things,
Figure FDA0003808597960000037
NT for temperature-controlled load group EM And (4) collecting.
5. The method as claimed in claim 1, wherein when the controllable load is an energy storage load, the normalizing the energy state of the controllable load comprises:
using a formula
Figure FDA0003808597960000038
Calculating to obtain the normalized electric quantity adjustable margin of the energy storage load equipment, wherein,
Figure FDA0003808597960000039
for normalizing the electric quantity adjustable margin, and
Figure FDA00038085979600000310
D t and C t The energy storage load equipment discharging group and the energy storage load equipment charging group are respectively at the moment t, and the number of the energy storage load equipment corresponding to the energy storage load equipment discharging group and the energy storage load equipment charging group is n 1 And n 2 The total number of the energy storage load equipment is n ═ n 1 +n 2 ，E i,t ，
Figure FDA00038085979600000311
And
Figure FDA00038085979600000312
respectively setting the upper limit and the lower limit of the actual charging capacity and the rated capacity of the ith energy storage load device at the time t;
the rated capacity of the energy storage load equipment is defined as the maximum capacity adjustable range at the current moment, and
Figure FDA00038085979600000313
wherein the content of the first and second substances,
Figure FDA00038085979600000314
the maximum capacity adjustable range at the moment t;
according to the normalized electric quantity adjustable margin, a formula is utilized
Figure FDA00038085979600000315
Determining a group of energy storage load devices
Figure FDA00038085979600000316
And (4) corresponding index sets.
6. The large-scale controllable load-based integrated service station step aggregation method according to claim 1, wherein the method for performing heterogeneous aggregation modeling of the integrated service station according to the normalization processing result and the homogeneous aggregation model comprises:
according to the running state of the controllable load, carrying out group division on the controllable load;
extracting key operation parameters of the controllable load, wherein the key operation parameters are parameters capable of reflecting main physical attributes in the load operation process;
formulating a normalization index according to the key operation parameters;
and carrying out power aggregation on the controllable load by adopting a homogenization aggregation modeling method according to the group division result and the normalization index of the controllable load.
7. The large-scale controllable load-based step aggregation method for the comprehensive service station, according to claim 6, is characterized in that a method for formulating a normalization index according to the key operation parameters specifically comprises:
and formulating a normalization index according to the key operation parameters by adopting a weight method.
8. An integrated service station step aggregation system based on large-scale controllable loads, the system comprising:
a homogenization aggregation module, configured to perform homogenization aggregation modeling of the integrated service station according to the controllable load, where the controllable load includes: temperature control load and energy storage load;
the normalization processing module is used for performing normalization processing on the energy state of the controllable load;
the heterogeneous aggregation module is used for carrying out heterogeneous aggregation modeling on the comprehensive service station according to the normalization processing result and the homogeneous aggregation model;
wherein the homogenization polymerization module comprises: the temperature control load homogenization polymerization unit and the energy storage load homogenization polymerization unit are connected with each other;
the temperature-controlled load homogenization polymerization unit comprises: the first equipment grouping subunit is used for dividing the equipment group of the temperature control load into an opening group and a closing group according to the on-off state, and describing the opening state and the closing state of any temperature control load equipment by using a state variable; the controlled population determining subunit is used for respectively determining the controlled populations in the opening population and the closing population according to the set controllable temperature range threshold; a first homogeneous polymerization power subunit for utilizing a formula according to the determined controlled population
Figure FDA0003808597960000041
Calculating the homogeneous aggregate power of the temperature-controlled load equipment group under the uncontrolled condition, wherein P T1 (t) homogeneous polymerization power when the temperature-controlled load device performs natural state update at time t, w k For the switching state of the kth temperature-controlled load device,
Figure FDA0003808597960000042
the rated power of the temperature control load equipment, and N is the number of the temperature control load equipment; a second homogeneous aggregate power subunit for utilizing the formula according to the determined controlled population
Figure FDA0003808597960000043
Figure FDA0003808597960000044
Calculating the homogeneous aggregate power of the temperature-controlled load equipment group under the controlled condition, wherein P T2 (t) is the output response of the controllable load according to the load control signal, Δ P 1 (t) is the adjustment borne by the temperature-controlled load equipment;
the energy storage load homogenization polymerization unit further comprises: a third homogeneous aggregate power subunit for utilizing the formula
Figure FDA0003808597960000045
Calculating the homogeneous aggregate power of the energy storage load equipment in a natural charging state, wherein P N (t) Natural charging Power of the energy storage load device at time t, N t Number of energy-storage load devices to be networked at time t, s k For the state of the kth energy storage load device at time t, when the energy storage load device is in an idle state s k 0, when the energy storage load device is in a charging state k 1 is ═ 1; the judging subunit is used for judging whether the time interval between the current time and the last state switching time of the energy storage load equipment is greater than a set time interval or not, if so, judging that the energy storage load equipment is controllable energy storage load equipment, and if not, judging that the energy storage load equipment is uncontrollable energy storage load equipment; the collecting subunit is used for collecting the controllable energy storage load equipment in the large-scale controllable load and establishing a controllable energy storage load equipment group; the second equipment grouping subunit is used for dividing the controllable energy storage load equipment group into a controllable charging group, a controllable discharging group and a controllable idle group; a charge/discharge power calculating subunit for calculating the charge/discharge power according to the obtained response control signal by using a formula
Figure FDA0003808597960000051
Figure FDA0003808597960000052
Calculating respective charge and discharge powers of the controllable charge group, the controllable discharge group and the controllable idle group at the current moment, wherein,
Figure FDA0003808597960000053
Figure FDA0003808597960000054
Figure FDA0003808597960000055
C t for a controllable charging group, D t Is a controllable discharge group, S t Is a controllable group of the idle objects,
Figure FDA0003808597960000056
respectively the number of the energy storage load devices in the respective energy storage load device group at the time t, and
Figure FDA0003808597960000057
Figure FDA0003808597960000058
respectively the numbers of the energy storage load devices in the respective energy storage load device groups,
Figure FDA0003808597960000059
for the time interval between the current time and the last state switching time of the energy storage load device,
Figure FDA00038085979600000510
is a set time interval; and the adjusting direction determining subunit is used for determining the adjusting direction of the energy storage load equipment group according to the acquired tracking target of the controllable energy storage load equipment group.
9. The large scale controllable load based integrated service station step aggregation system according to claim 8, wherein the heterogeneous aggregation module comprises:
the group division unit is used for carrying out group division on the controllable load according to the running state of the controllable load;
the normalization index formulation unit is used for extracting key operation parameters of the controllable load and formulating the normalization index according to the key operation parameters, wherein the key operation parameters are parameters capable of reflecting main physical attributes in the load operation process;
the integration unit is used for integrating the normalization indexes of the key operation parameters to obtain comprehensive normalization indexes;
and the power aggregation unit is used for carrying out power aggregation on the controllable loads by adopting a homogenization aggregation modeling method according to the group division result and the comprehensive normalization index of the controllable loads.
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