CN114498651B - Hybrid load cluster control method and system - Google Patents
Hybrid load cluster control method and system Download PDFInfo
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- CN114498651B CN114498651B CN202210117782.1A CN202210117782A CN114498651B CN 114498651 B CN114498651 B CN 114498651B CN 202210117782 A CN202210117782 A CN 202210117782A CN 114498651 B CN114498651 B CN 114498651B
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- 238000000034 method Methods 0.000 title claims abstract description 48
- 230000002776 aggregation Effects 0.000 claims abstract description 61
- 238000004220 aggregation Methods 0.000 claims abstract description 61
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 255
- 238000004378 air conditioning Methods 0.000 claims description 35
- 238000010521 absorption reaction Methods 0.000 claims description 33
- 239000011159 matrix material Substances 0.000 claims description 31
- 230000029087 digestion Effects 0.000 claims description 14
- 230000008859 change Effects 0.000 claims description 12
- 238000007726 management method Methods 0.000 claims description 12
- 230000001276 controlling effect Effects 0.000 claims description 8
- 238000009826 distribution Methods 0.000 claims description 8
- 238000010438 heat treatment Methods 0.000 claims description 8
- 230000033228 biological regulation Effects 0.000 claims description 7
- 238000004321 preservation Methods 0.000 claims description 7
- 238000006116 polymerization reaction Methods 0.000 claims description 6
- 229910052799 carbon Inorganic materials 0.000 claims description 5
- 238000001816 cooling Methods 0.000 claims description 5
- 239000011810 insulating material Substances 0.000 claims description 4
- 238000005457 optimization Methods 0.000 claims description 4
- 238000003860 storage Methods 0.000 claims description 4
- 230000004931 aggregating effect Effects 0.000 claims description 3
- 230000017525 heat dissipation Effects 0.000 claims description 3
- 230000001105 regulatory effect Effects 0.000 claims description 3
- 230000000379 polymerizing effect Effects 0.000 claims description 2
- 238000005057 refrigeration Methods 0.000 claims description 2
- 238000009413 insulation Methods 0.000 claims 1
- 238000005265 energy consumption Methods 0.000 abstract description 7
- 238000010586 diagram Methods 0.000 description 7
- 230000004044 response Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000004146 energy storage Methods 0.000 description 2
- 230000003750 conditioning effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
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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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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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
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
-
- 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
- H02J2310/52—The controlling of the operation of the load not being the total disconnection of the load, i.e. entering a degraded mode or in current limitation
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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
- 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
-
- 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
- H02J2310/62—The condition being non-electrical, e.g. temperature
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- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Air Conditioning Control Device (AREA)
Abstract
The invention relates to a hybrid load cluster management and control method. The method comprises the steps of firstly, distributing scheduling tasks based on power adjustable capacity of an electric heater cluster and an air conditioner cluster, and then carrying out coordinated scheduling of the electric heater and the air conditioner in different modes by combining a first aggregation model of the electric heater cluster and a second aggregation model of the air conditioner cluster. According to the invention, different aggregation models are respectively established for different loads in the hybrid load cluster, and optimized scheduling is performed in different modes, so that the stable scheduling control of the load cluster with hybrid characteristics is realized, the clean energy consumption is promoted, and the unbalance of supply and demand is improved.
Description
Technical Field
The invention relates to the technical field of electric energy consumption, in particular to a hybrid load cluster management and control method and system.
Background
Currently, the global face of great reform of new energy technologies, the clean development of energy is promoted, and the effort of realizing the transformation from traditional energy to low-carbon and high-efficiency clean energy is the main direction of energy development. Under the environment of green development, a new installation on the power generation side of the power system mainly uses clean energy sources such as wind power, photovoltaic and the like, and is widely focused on providing low-carbon energy services through the resources on the demand side in order to adapt to the access of high-proportion renewable energy sources. The resources on the demand side are rich, the load power transfer can be realized through reasonable resource management and scheduling, the clean energy consumption is promoted, and the unbalance of supply and demand is improved.
The load quantity is more in the isothermal control of the air conditioner and the electric water heater at the demand side, the heat energy can be stored temporarily, the energy can be equivalently used as an energy storage system after scientific aggregation control, the energy storage system has considerable power transfer capability, and the method is a feasible method for providing low-carbon energy service. The existing load aggregation control research is mainly based on homogeneous load, but in the actual process, the quantity of adjustable loads capable of generating effective power transfer in the regional power distribution network is limited, if the existing control model is used for only aggregating the homogeneous load in the region, the aggregation power is insufficient to meet the power transfer requirement, so that all callable loads in the region are necessarily aggregated, but due to the difference of load parameters, the whole cluster presents unordered and hybrid system characteristics, the controllability is reduced, and the control process of the whole system is more complex. Therefore, it is necessary to study the implementation method of the overall system stability control for the hybrid characteristics of the clusters.
Disclosure of Invention
In view of the above, the present invention provides a hybrid load cluster control method and system to realize stable scheduling control of load clusters with hybrid characteristics, promote clean energy consumption, and improve unbalanced supply and demand.
In order to achieve the above object, the present invention provides the following solutions:
a method of controlling a hybrid load cluster including all electric water heater loads and air conditioner loads within a research area, the method comprising the steps of:
Grouping to form homogeneous groups based on the similarity of all electric water heater load parameters in the research area, wherein the electric water heater parameters comprise rated power of the electric water heater, temperature set value of the electric water heater, volume of a water storage tank of the electric water heater and heat dissipation coefficient of the electric water heater;
Homogeneously polymerizing a plurality of electric water heaters into an electric water heater cluster;
determining estimated power of each electric water heater homogeneous group based on a Monte Carlo model of parameter probability distribution;
determining the adjusting range of each electric water heater homogeneous group according to the estimated power of each electric water heater homogeneous group;
determining the power adjustable capacity of the electric water heater cluster according to the adjusting range of each electric water heater homogeneous group;
grouping the air conditioner load parameters in the research area based on the similarity of all the air conditioner load parameters in the research area to form a plurality of air conditioner homogeneous groups, wherein the air conditioner load parameters comprise air conditioner thermal resistance, air conditioner heat capacity, air conditioner average power and air conditioner initial set temperature;
Aggregating a plurality of air conditioner homogeneous groups into an air conditioner cluster;
determining estimated power of each air conditioner homogeneous group based on a Monte Carlo model of parameter probability distribution;
Determining the adjusting range of each air conditioner homogeneous group according to the estimated power of each air conditioner homogeneous group;
determining the power adjustable capacity of the air conditioner clusters according to the adjusting range of each air conditioner homogeneous group;
According to the power adjustable capacity of the electric water heater cluster and the power adjustable capacity of the air conditioner cluster, dispatching tasks are distributed, and a digestion target of the electric water heater cluster and a digestion target of the air conditioner cluster are determined;
constructing an aggregation model of each electric water heater homogeneous group facing switching control as a first aggregation model;
determining the optimal switching state of each homogeneous group of electric water heaters in the electric water heater cluster according to the absorption target of the electric water heater cluster;
Optimizing and controlling the running state of each electric water heater in the electric water heater homogeneous group based on the optimal control state of each electric water heater homogeneous group and the first aggregation model;
Determining an adjustment task of each air conditioner homogeneous group in the air conditioner cluster according to the absorption target of the air conditioner cluster;
Constructing an aggregation model of each air conditioner homogeneous group facing slip form control as a second aggregation model;
And determining the set temperature change rate of each air conditioner homogeneous group by adopting a sliding mode control method according to the second polymerization mode based on the adjustment task of each air conditioner homogeneous group, thereby adjusting the running state of each air conditioner.
Optionally, the adjusting range of each homogeneous group of electric water heaters is determined according to the estimated power of each homogeneous group of electric water heaters, respectively, as follows:
Wherein, The upper limit of the power adjusting range of the homogeneous group of the j-th electric water heater at the moment t is shown,The lower limit of the power adjusting range of the homogeneous group of the j-th electric water heater at the moment t is shown,The switch state of the hl electric water heater in the homogeneous group of the j electric water heater under the '1' switching state is shown,The switching state of the hl electric water heater in the J-th electric water heater homogeneous group under the switching state of 0 is shown, J h is the number of the electric water heater homogeneous groups, and P 0,j is the estimated power of the J-th electric water heater homogeneous group.
Optionally, the adjusting range of each air conditioner homogeneous group is determined according to the estimated power of each air conditioner homogeneous group:
Wherein, AndRespectively represent the lower limit and the upper limit of the power adjustment range of the ith air conditioner homogeneous group at the moment t, AndRespectively representing a lower limit and an upper limit of a stable power level of the ith air conditioning group, N L,i representing the number of air conditioners contained in the ith air conditioning group; And Respectively represents that the ith air conditioner homogeneous group is at the upper limit of the temperature set pointThe cooling time and the closing time of the lower part,AndRespectively represent that the ith air conditioner homogeneous group is at the lower limit of the temperature set pointThe refrigeration time and the closing time are under, P a,i (t) represents the estimated power of the ith air conditioner homogeneous group at the moment t,S al,i (t) is the on-off state of the ith air conditioner in the ith air conditioner homogeneous group, I a represents the number of the air conditioner homogeneous groups, P As,i (t) represents the stable power level of the ith air conditioner homogeneous group at the time t, P i represents the average power of the air conditioners in the ith air conditioner homogeneous group, and η i represents the energy efficiency ratio of the air conditioners in the ith air conditioner homogeneous group.
Optionally, the determining, according to the target of the air conditioner cluster to be consumed, an adjustment task of each air conditioner homogeneous group in the air conditioner cluster specifically includes:
according to the power adjusting range of each air conditioner homogeneous group, determining the power adjusting range of the air conditioner cluster as follows:
Wherein P s,a (t) represents the target of the air conditioner cluster at the moment t, AndRespectively representing the lower limit and the upper limit of the power adjusting range of the ith air conditioner homogeneous group at the t moment, wherein I a represents the number of the air conditioner homogeneous groups;
according to the power adjusting range of the air conditioner cluster, determining the target power adjusting range of the electric water heater cluster as follows:
Wherein P s (t) represents a scheduling task at the time t, and P s,h (t) represents a digestion target of the electric water heater cluster at the time t;
the method comprises the following steps of determining the digestion targets of the electric water heater cluster by taking the first target function as a target: The first objective function is
Wherein f 1 represents a first objective function, P H,j (t) represents a target for the digestion of the j-th homogeneous group of electric water heaters at time t, and P H,j (t) has a value ofOr (b)The upper limit of the power adjusting range of the homogeneous group of the j-th electric water heater at the moment t is shown,The lower limit of the power adjusting range of the J-th electric water heater homogeneous group at the t moment is represented, and J h represents the number of the electric water heater homogeneous groups;
According to the absorption target of the electric water heater cluster, determining the absorption target of the air conditioner cluster as follows: p s,a(t)＝Ps(t)-Ps,h (t).
Optionally, the first aggregation model includes a first aggregation model in a "1" switching state and a first aggregation model in a "0" switching state;
the first aggregation model in the "1" switching state is:
Wherein x h,j (t) represents a state vector of Q h,j ×1 composed of the number of electric water heaters in each state interval in the switching state of the j-th electric water heater homogeneous group "1", y h,j (t) is the output power of the first aggregation model of the j-th electric water heater homogeneous group, a h,j represents the first load transfer rate matrix of Q h,j×Qh,j of the j-th electric water heater homogeneous group, B h,j represents the first power matrix of 1×q h,j of the j-th electric water heater homogeneous group, and Q h,j represents the number of state intervals in the j-th electric water heater homogeneous group;
The rate of heat transfer is indicated as, Representing the heat preservation transfer rate, wherein the blank area in the matrix A h,j corresponds to zero elements;
N h,j represents the number of heating state intervals in a1 switching state in the j-th electric water heater homogeneous group, and P 0,j represents the rated power of electric water heaters in the j-th electric water heater homogeneous group;
The first aggregation model in the "0" switching state is:
In the '0' switching state, all loads (including loads which are about to reach a set upper limit temperature interval) which are originally in a heating state in the homogeneous group of the electric water heater are converted into a heat preservation state and move towards the direction of the lowest temperature limit; the load which originally reaches the set lower limit temperature interval changes the state of the heat-insulating material from heat preservation to heating, and the heat-insulating material is changed into a heat-insulating state after reaching the set upper limit temperature interval. Wherein x h1,j (t) represents a state vector of N h,j ×1 consisting of the number of electric water heaters originally in the heating state in the "0" switching state of the jth electric water heater homogeneous group, x h2,j (t) represents a state vector of (Q h,j-Mh,j) ×1 consisting of electric water heaters in the heat preservation-heating-heat preservation cycle state interval in the jth electric water heater homogeneous group, E h1,j represents a second load transfer rate matrix of the jth electric water heater homogeneous group, E h2,j represents a third load transfer rate matrix of the jth electric water heater homogeneous group, and F h,j represents a second power matrix of the jth electric water heater homogeneous group;
M h,j represents the number of state intervals below the temperature set lower limit.
Optionally, the determining, according to the target of the electric water heater cluster for the absorption, an optimal switching state of each homogeneous group of electric water heaters in the electric water heater cluster specifically includes:
Solving a second objective function by adopting an optimization algorithm, and determining a control state of each electric water heater homogeneous group in the electric heater cluster when the second objective function is optimal as an optimal switching state of each electric water heater homogeneous group in the electric heater cluster;
the second objective function is:
Wherein f 2 represents a second objective function, P s,h (t) is a target of the electric water heater cluster at time t, J h represents the number of homogeneous groups of electric water heaters, P H,j (t) represents the estimated power of the J-th homogeneous group of electric water heaters at time t, when the control state is a "1" switching state, When the control state is a "0" switching state, The upper limit of the power adjusting range of the homogeneous group of the j-th electric water heater at the moment t is shown,The lower limit of the power regulation range of the homogeneous group of the j-th electric water heater at the moment t is shown.
Optionally, the changing the switching state of each electric water heater homogeneous group and the operation state of each electric water heater in the homogeneous group based on the optimal control state of each electric water heater homogeneous group and the first aggregation model specifically includes:
Determining a first aggregation model of each electric water heater homogeneous group according to the optimal control state of each electric water heater homogeneous group;
The operation state of each electric water heater in each electric water heater homogeneous group is adjusted according to the first aggregation model of each electric water heater homogeneous group aiming at minimizing the absolute value of the difference value between the sum of the output powers of the first aggregation models of each electric water heater homogeneous group and the absorption target of the electric water heater cluster.
Optionally, the determining, according to the target of the air conditioner cluster to be consumed, an adjustment task of each air conditioner homogeneous group in the air conditioner cluster specifically includes:
According to the absorption target of the air conditioner cluster, determining the adjustment task of each air conditioner homogeneous group in the air conditioner cluster as follows:
Psa,i(t)＝Pa,i(t)+ΔPi(t),i＝1,2,…,Ia；
Wherein P sa,i (t) represents the adjustment task of the ith air conditioner homogeneous group at the moment t, P a,i (t) represents the estimated power of the ith air conditioner homogeneous group at the moment t, I a represents the number of the air conditioner homogeneous groups, and DeltaP i (t) represents the change amount of the adjustment task of the ith air conditioner homogeneous group at the moment t; p s,a (t) represents the target of the air conditioning cluster at time t.
Optionally, the second aggregation model is:
Wherein x a,i (t) represents a state vector formed by the number of air conditioners in each state interval in the ith air conditioner homogeneous group at the moment t, Is the input variable of the ith air conditioner homogeneous group at the moment t,The change rate of the set temperature of the ith air conditioner homogeneous group at the t moment is shown; y a,i (t) represents the second polymerization die output power of the ith air conditioner homogeneous group at time t; a a,i、Ba,i and C a,i respectively represent a fourth load transfer rate matrix, an input variable state matrix and a third power matrix of the ith air conditioner homogeneous group, blank areas in the matrix A a,j、Ba,j are zero elements correspondingly, and the dimension numbers are Q a,i×Qa,i、Qa,j×Qa,i、1×Qa,i;Qa,i respectively to represent the number of state intervals in the ith air conditioner homogeneous group;
indicating the off-state load transfer rate of the ith air conditioning group, The cooling state load transfer rate of the i-th air-conditioning homogeneous group is represented, N a,i represents the number of state sections in the off state in the i-th air-conditioning homogeneous group, P i represents the average power of the air conditioners in the i-th air-conditioning homogeneous group, and η i represents the energy efficiency ratio of the air conditioners in the i-th air-conditioning homogeneous group.
Optionally, the sliding mode control method has the following formula:
The input variable of the ith air conditioner homogeneous group at the moment of t is input into the second aggregation model to obtain the output power of the second aggregation model of the ith air conditioner homogeneous group; e (t) represents the difference between the regulating task of the ith air conditioning homogeneous group and the second polymeric pattern output power of the ith air conditioning homogeneous group at time t, κ (t) is typically a time-varying control gain that satisfies the robustness condition, sat (·) represents an adjustable saturation function for suppressing boundary buffeting, f i (X) and g i (X) represent a first intermediate function and a second intermediate function respectively, X represents a state variable, P i represents the average power of the air conditioners in the ith air conditioner homogeneous group, eta i represents the energy efficiency ratio of the air conditioners in the ith air conditioner homogeneous group, beta off,i and beta on,i represent the off-state load transfer rate and the refrigerating-state load transfer rate of the ith air conditioner homogeneous group respectively, T a,i,Ti a,low and T i a,high respectively represent an initial temperature set value, a lower temperature regulation limit and an upper temperature regulation limit of the ith air-conditioning homogeneous group, and X on,i(t,Ti a,low) is the number of air-conditioning units in a refrigerating state at a temperature T i a,low of the ith air-conditioning homogeneous group at a time T; X off,i(t,Ti a,high) is the number of air conditioners in which the ith air conditioner group is in an off state at a temperature T i a,high at time T, epsilon is a small control parameter arbitrarily selected, and sgn (·) represents a sign function.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
The invention discloses a hybrid load cluster management and control method. According to the invention, different aggregation models are respectively established for different loads in the hybrid load cluster, and optimized scheduling is performed in different modes, so that the stable scheduling control of the load cluster with hybrid characteristics is realized, the clean energy consumption is promoted, and the unbalance of supply and demand is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a hybrid load cluster management and control method provided by the invention;
Fig. 2 is a schematic diagram of a virtual-real fusion control process provided by the present invention;
Fig. 3 is a schematic diagram of the result of the target control layer provided by the present invention, fig. 3 (a) is a schematic diagram of the target of the electric water heater cluster, and fig. 3 (b) is a schematic diagram of the target of the air conditioner cluster;
Fig. 4 is a schematic diagram of a control result of an electric water heater cluster according to the present invention, fig. 4 (a) is a schematic diagram of response power of each homogeneous electric water heater group in the electric water heater cluster, and fig. 4 (b) -4 (f) are schematic diagrams of switching states of homogeneous electric water heater groups 1,2, 3,4 and 5, respectively.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a hybrid load cluster control method and system, so as to realize stable scheduling control of a load cluster with hybrid characteristics, promote clean energy consumption and improve unbalance of supply and demand.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1
As shown in fig. 1 and 2, embodiment 1 of the present invention provides a hybrid load cluster control method, where the hybrid load cluster includes all electric water heater loads and air conditioner loads in a research area, and the method includes the following steps:
Step 101, grouping to form a plurality of electric water heater homogeneous groups based on the similarity of all electric water heater load parameters in a research area; parameters of the electric water heater load comprise rated power of the electric water heater, temperature set value of the electric water heater, volume of a water storage tank of the electric water heater and heat dissipation coefficient of the electric water heater;
102, carrying out homogeneous aggregation on a plurality of electric water heaters to form an electric water heater cluster, and determining estimated power of each electric water heater homogeneous group based on a Monte Carlo model with parameter probability distribution; determining the adjusting range of each electric water heater homogeneous group according to the estimated power of each electric water heater homogeneous group; and determining the power adjustable capacity of the electric water heater cluster according to the adjustment range of each electric water heater homogeneous group. That is, the electric water heater homogeneous groups are further aggregated into an electric water heater cluster, estimated power of each electric water heater homogeneous group is determined based on a Monte Carlo model with parameter probability distribution, an adjusting range of the electric water heater homogeneous groups is determined according to the estimated power, and adjustable capacity of the electric water heater cluster is estimated.
Step 102 specifically includes:
Step 1: the electric water heater cluster adopts a switching control method, and the switching state of a homogeneous group is changed based on a switching rule, and the switching state has two types: the "1" and "0" have different adjustment capabilities under different switching states, so that estimated powers of homogeneous groups under the two switching states of "1" and "0" need to be obtained. Wherein, the estimated power of the homogeneous group of the electric water heater in the state of 1 and the estimated power of the homogeneous group of the electric water heater in the state of 0 are respectively:
Wherein, The upper limit of the power adjusting range of the homogeneous group of the j-th electric water heater at the moment t is shown,The lower limit of the power adjusting range of the homogeneous group of the j-th electric water heater at the moment t is shown,The switch state of the hl electric water heater in the homogeneous group of the j electric water heater under the '1' switching state is shown,The switching state of the hl electric water heater in the J-th electric water heater homogeneous group under the '0' switching state is shown, and J h represents the number of the electric water heater homogeneous groups.
Step 2: the adjustable capacity of the electric water heater clusters was evaluated.
Step 103, grouping and forming homogeneous groups based on the similarity of all air conditioner load parameters in the research area, wherein the air conditioner parameters comprise air conditioner thermal resistance, air conditioner heat capacity, air conditioner average power and air conditioner initial set temperature;
Step 104, the air conditioner homogeneous groups are further aggregated into an air conditioner cluster, estimated power of each air conditioner homogeneous group is determined based on a Monte Carlo model with parameter probability distribution, an adjusting range of the air conditioner homogeneous groups is determined according to the estimated power, and adjustable capacity of the air conditioner cluster is estimated.
Step 104 specifically includes:
Step 3: the calculation formula of the dynamic estimated power of the air conditioner homogeneous group is as follows:
wherein s i,j (t) is the on-off state of the air conditioner in the group.
Step 4: the steady power level at different temperature set points for each homogeneous group of air conditioners is calculated. The homogeneous group of air conditioners changes output power by adjusting temperature set point, and the acceptable air conditioner setting temperature adjustment range of a user is assumed to be within a certain homogeneous groupAnd according to the set temperature range acceptable by the user, obtaining a variation interval of the stable power level. The calculation formula for the stable power level is:
Wherein: η j is the energy efficiency ratio of the air conditioner homogeneous group j; n L,j is the number of air conditioners contained in the homogeneous group j; τ on,j(Tset,j (t)) and τ off,j(Tset,j (t)) are the cooling time and the off time of the air conditioner, respectively; Δt db,j is the dead zone temperature of homobank j.
When (when)AndBringing in a lower limit and an upper limit, respectively, where a stable power level variation interval can be obtained
Step 5: by combining the estimated power and the stable power level of the homogeneous group, the adjustable range of the aggregate power can be obtained as follows:
Therefore, the power adjustment range of the air conditioner homogeneous group j at the time t is as follows
Step 6: the adjustable capacity of the air conditioning clusters is evaluated.
And 105, distributing scheduling tasks according to the power adjustable capacity of the electric water heater cluster and the power adjustable capacity of the air conditioner cluster, and determining the absorption target of the electric water heater cluster and the absorption target of the air conditioner cluster.
Step 105 specifically includes:
Step 7: considering the aggregation characteristics of different clusters, the digestion target of each cluster is determined on the premise of meeting the adjustment range of the air conditioner clusters and not affecting the use of the electric water heater clusters.
When task allocation is performed, the adjustment task amount obtained by the air conditioner cluster must meet the following conditions:
wherein P s,a (t) is the conditioning task obtained by the air conditioning cluster.
Assuming that the total scheduling task is P s (t), on the premise of meeting the adjusting task of the air conditioner cluster, the adjusting task obtained by the electric water heater cluster meets the following conditions:
Wherein P s,h (t) is an adjustment task obtained by the electric water heater cluster. Because the electric water heater has the characteristics of high power, wide adjustable range and the like, the user experience sensitivity is relatively weak, and the electric water heater is suitable for maximally completing the absorption target. Thus, the objective function of the electric water heater regulating task, namely the first objective function, is:
Through the switching control of the homogeneous groups of the electric water heater, the electric water heater can complete the absorption target as much as possible. After determining that the absorption capacity of the electric water heater is P s,h(t)(Ps,h(t)≤fh (t)), the absorption task obtained by the air conditioner is as follows:
Ps,a(t)＝Ps(t)-Ps,h(t)
And 106, constructing an aggregation model of each electric water heater homogeneous group facing switching control, using the aggregation model as a first aggregation model, determining the optimal switching state of each homogeneous group in the electric water heater cluster by adopting a switching control method according to the absorption target of the electric water heater cluster, and controlling the homogeneous groups to be switched to the aggregation model in the corresponding state, thereby adjusting the running state of each electric water heater.
Step 106 specifically includes:
Step 8: the finite difference discretization is different in different switching states. The discrete finite difference state space aggregation model of the homogeneous group of the electric water heater under the '1' switching state is as follows:
yh,j(t)＝Bh,jxh,j(t)
Wherein x h,j(t)＝[xh,1(t),xh,2(t),…,xh,Q (t) ] is a state vector of Q h,j x 1; y h,j (t) is the output power in homogeneous group j "1" state; a h,j is a Q h,j×Qh,j state matrix, B h,j is a1×q h,j state matrix, respectively:
Wherein the blank area in matrix a h,j corresponds to zero elements.
The discrete finite difference state space aggregation model of the electric water heater under the '0' switching state is as follows:
yh,j(t)＝Fh,jxh,j(t)
Wherein x h1,j(t)＝[xh,1(t),xh,2(t),…,xh,N (t) ] is a state vector of N h,j ×1, and x h2,j(t)＝[xh,N+1(t),xh,N+2(t),…,xh,Q+N-M (t) ] is a state vector of (Q h,j-Mh,j) ×1; y h,j (t) is the output power in the homogeneous group j "0" state; e h1,j is an N h,j×Nh,j state matrix, E h2,j is a (Q h,j-Mh,j)×(Qh,j-Mh,j) state matrix, F h,j is a1× (Q h,j+Nh,j-Mh,j) state matrix, and the matrix and vector structures are:
wherein the blank area in matrix E h1,j、Eh2,j corresponds to zero elements.
Step 9: according to the absorption target of the electric water heater cluster, determining an optimal control state of each electric water heater homogeneous group in the electric water heater cluster by adopting a switching control method, wherein the method specifically comprises the following steps of:
Step 9-1: each homogeneous group is in an initial state of 1, and the electric water heater in each homogeneous group moves according to the temperature interval unit in the 1 state and gradually reaches a stable state.
Step 9-2: when the error between the actual aggregate power curve and the absorption target power curve meets the adjustment condition e > e 0, obtaining a new control state of each homogeneous group by utilizing an optimizing algorithm; otherwise, the control state of each homogeneous group is kept unchanged.
And taking the absolute value of the difference between the sum of the powers of the homogeneous groups in different control states and the required power to be consumed as an objective function, solving the objective function through an optimizing algorithm, and finally determining the new control state of each homogeneous group of the electric water heater. The artificial immune algorithm is utilized to solve the new control state of each homogeneous group, and the method has the advantages of high convergence rate, guarantees the diversity of antibodies, and avoids local optimization. The expression of the objective function is:
Wherein P s,h (t) is the total consumed target power of the electric water heater cluster; p H,j (t) is the estimated power of the j-th group of homogeneous groups participating in the digestion task.
Step 10: based on the optimal control state of each electric water heater homogeneous group and the first aggregation model, changing the switching state of each electric water heater homogeneous group and the running state of each electric water heater in the homogeneous group specifically comprises:
Step 10-1: determining a first aggregation model of each electric water heater homogeneous group according to the optimal control state of each electric water heater homogeneous group;
Step 10-2: and adjusting the running state of each electric water heater in each electric water heater homogeneous group according to the first aggregation model of each electric water heater homogeneous group. Namely, solving a second objective function by adopting an optimization algorithm, and determining a control state of each electric water heater homogeneous group in the electric heater cluster when the second objective function is optimal as an optimal switching state of each electric water heater homogeneous group in the electric heater cluster;
the second objective function is:
Wherein f 2 represents a second objective function, P s,h (t) is a target of the electric water heater cluster at time t, J h represents the number of homogeneous groups of electric water heaters, P H,j (t) represents the estimated power of the J-th homogeneous group of electric water heaters at time t, when the control state is a "1" switching state, When the control state is a "0" switching state, The upper limit of the power adjusting range of the homogeneous group of the j-th electric water heater at the moment t is shown,The lower limit of the power regulation range of the homogeneous group of the j-th electric water heater at the moment t is shown.
And step 107, determining the adjustment task of each air conditioner homogeneous group in the air conditioner cluster according to the consumption target of the air conditioner cluster.
Step 107 specifically includes:
Step 11: and adjusting the digestion tasks of each homogeneous group in the air conditioning cluster in real time according to the task allocation of the target control layer. Because the air conditioner has the characteristics of small power and small adjustable range, when the larger change of the absorption target occurs, the conditions of low response speed and large error can occur, and in order to achieve a better tracking effect, all the homogeneous groups in the air conditioner cluster are controlled to adjust the absorption task, namely, all the homogeneous groups of the air conditioner are involved in the clean energy absorption task, and when the larger change of the absorption task occurs, each homogeneous group can obtain smaller task change amount, so that the completion of the absorption task is ensured, the error is reduced, and meanwhile, the change of the temperature set point is gentle due to the smaller change of each group of the absorption task, thereby ensuring the comfort level of a user.
Assuming that the total task of the air conditioning cluster is P s,a (t), the adjustable range of each homogeneous group is The estimated power is P a,j (t), J a groups are all provided, and the adjustment task of each group is:
Psa,j(t)＝Pa,j(t)+ΔPj(t),j＝1,2,…,Ja
wherein P sa,j (t) is the adjustment task of each air conditioner homogeneous group.
And 108, constructing an aggregation model of each air conditioner homogeneous group facing the sliding mode control, and based on the adjustment task of each air conditioner homogeneous group, determining the set temperature change rate of each air conditioner homogeneous group by adopting a sliding mode control method as a second aggregation model so as to adjust the running state of each air conditioner.
Step 108 specifically includes:
step 12: the discrete finite difference state space aggregation model of the air conditioner is as follows:
ya,j(t)＝Ca,jxa,j(t)
Where x a,j(t)＝[xa,1(t),xa,2(t),…,xa,Q (t) ] is a state vector of Q a,j x 1; The input variable is the air conditioner homogeneous group j; y a,j (t) is the output power of homogeneous group j; a a,j、Ba,j、Ca,j is a Q a,j×Qa,j、Qa,j×Qa,j、1×Qa,j state matrix, respectively, the matrix and vector structure being:
Wherein the blank area in matrix a a,j、Ba,j corresponds to zero elements.
Step 13: constructing a sliding mode control model of the air conditioner homogeneous group, and defining a tracking error function s of the air conditioner homogeneous group j group, namely, a sliding mode function is as follows:
s＝e(t)＝Psa,j(t)-PA,j(t)
defining the Lyapunov function as:
To maintain system stability, it is necessary to ensure The slip-form control law is thus designed as:
Wherein f j(α,X),gj (X), sat [ e (t)/ε ] are each:
Wherein X on,j(t,Tj a,low) is the number of air conditioners of j groups, which are distributed at the temperature T j a,low at the time T and are in an ON state; x off,j(t,Tj a,high) is the number of air conditioners in the OFF state that the j group of air conditioners are distributed at the temperature T j a,high at the time T.
Step 14: and adjusting the set temperature in each air conditioner homogeneous group by utilizing a sliding mode control model based on the adjusting task of each air conditioner homogeneous group and the second aggregation model, and adjusting the running state of each air conditioner.
Example 2
As shown in fig. 2, embodiment 2 of the present invention provides a hybrid load cluster management and control system, which is used to implement the hybrid load cluster management and control method in embodiment 1. The system includes a target control portion, a cluster control portion, an aggregation control portion, and an embedded control portion.
Example 3
Taking a certain residential area as an example, the users in the residential area have about 900 users, and the brands of water heaters used by residents comprise sea, ten thousand, and America, and the like, and the types mainly comprise electric water heaters and gas water heaters, wherein the number of the water storage type electric water heaters accounts for about 43 percent, and 385 stations are counted.
The method according to example 1 of the present invention:
1) 385 electric water heaters are divided into 5 groups, 195 air conditioners participating in demand response are selected, and the 195 air conditioners are cooperatively matched with the electric water heaters to divide the 195 air conditioners into 5 groups.
2) The tunability of each homogeneous group was evaluated.
3) Fig. 3 shows the result of the target control layer of the present invention, fig. 3 (a) shows the target of the electric water heater cluster, and fig. 3 (b) shows the target of the air conditioner cluster, reflecting the different aggregation characteristics of the electric water heater cluster and the air conditioner cluster.
4) And constructing an electric water heater aggregation model oriented to switching control, and controlling each homogeneous group in the electric water heater cluster to respond by using a switching control method. Fig. 4 shows the control result of the electric water heater cluster, fig. 4 (a) shows the response power of each homogeneous group in the electric water heater cluster, and fig. 4 (b) -4 (f) show the switching states of each homogeneous group.
5) And controlling each homogeneous group in the air conditioner cluster to adjust the digestion task in real time.
6) And constructing an air conditioner aggregation model facing sliding mode control, and adjusting the temperature set point of the air conditioner homogeneous group through the sliding mode control.
The invention provides a hybrid load cluster management and control method. Firstly, the sensing process is as follows: all electric water heaters and air conditioner load parameters in the sensing area are uploaded; the next is to aggregate the packets: grouping the mixed loads according to the parameter similarity to form a plurality of homogeneous groups as basic control units; then evaluate cluster capacity: each homogeneous group is further integrated into a cluster with considerable power transfer capacity according to response similarity, and is divided into an electric water heater cluster and an air conditioner cluster, and the adjustment capacity of the clusters is evaluated; the target control is then: considering the aggregation characteristics of different clusters, determining the absorption target of each cluster on the premise of meeting the adjustment range of the air conditioner clusters and not affecting the use of the electric water heater clusters; then cluster control: according to the absorption targets of the electric water heater clusters, an electric water heater aggregation model facing switching control is constructed, the switching state of each homogeneous group of electric water heaters is adjusted by using the switching control, and according to the absorption targets of the air conditioner clusters, the absorption tasks of each homogeneous group of air conditioners are controlled based on the adjustment capacity of each homogeneous group of air conditioners; the polymerization control is followed: constructing an aggregation model of the air conditioner homogeneous groups facing the sliding mode control, and adjusting the temperature set points of the air conditioner homogeneous groups by utilizing a sliding mode control method; finally, the method comprises the following steps: executing the control instruction, adjusting the running state of the load physical entity, completing clean energy consumption, improving the utilization rate of the clean energy and ensuring the stable running of the power grid.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (9)
1. A method for controlling a hybrid load cluster, wherein the hybrid load cluster comprises all electric water heater loads and air conditioner loads in a research area, the method comprising the following steps:
Grouping the electric water heaters based on the similarity of the parameters of the loads of all the electric water heaters in the research area to form a plurality of electric water heater homogeneous groups; parameters of the electric water heater load comprise rated power of the electric water heater, temperature set value of the electric water heater, volume of a water storage tank of the electric water heater and heat dissipation coefficient of the electric water heater;
Homogeneously polymerizing a plurality of electric water heaters into an electric water heater cluster;
determining estimated power of each electric water heater homogeneous group based on a Monte Carlo model of parameter probability distribution;
determining the adjusting range of each electric water heater homogeneous group according to the estimated power of each electric water heater homogeneous group;
determining the power adjustable capacity of the electric water heater cluster according to the adjusting range of each electric water heater homogeneous group;
grouping the air conditioner load parameters in the research area based on the similarity of all the air conditioner load parameters in the research area to form a plurality of air conditioner homogeneous groups, wherein the air conditioner load parameters comprise air conditioner thermal resistance, air conditioner heat capacity, air conditioner average power and air conditioner initial set temperature;
Aggregating a plurality of air conditioner homogeneous groups into an air conditioner cluster;
determining estimated power of each air conditioner homogeneous group based on a Monte Carlo model of parameter probability distribution;
Determining the adjusting range of each air conditioner homogeneous group according to the estimated power of each air conditioner homogeneous group;
determining the power adjustable capacity of the air conditioner clusters according to the adjusting range of each air conditioner homogeneous group;
According to the power adjustable capacity of the electric water heater cluster and the power adjustable capacity of the air conditioner cluster, dispatching tasks are distributed, and a digestion target of the electric water heater cluster and a digestion target of the air conditioner cluster are determined;
constructing an aggregation model of each electric water heater homogeneous group facing switching control as a first aggregation model;
determining the optimal switching state of each homogeneous group of electric water heaters in the electric water heater cluster according to the absorption target of the electric water heater cluster;
Optimizing and controlling the running state of each electric water heater in the electric water heater homogeneous group based on the optimal control state of each electric water heater homogeneous group and the first aggregation model;
Determining an adjustment task of each air conditioner homogeneous group in the air conditioner cluster according to the absorption target of the air conditioner cluster;
Constructing an aggregation model of each air conditioner homogeneous group facing slip form control as a second aggregation model;
Based on the adjustment task of each air conditioner homogeneous group, determining the set temperature change rate of each air conditioner homogeneous group by adopting a sliding mode control method according to the second polymerization model, thereby adjusting the running state of each air conditioner;
according to the target of the air conditioner cluster, determining the adjustment task of each air conditioner homogeneous group in the air conditioner cluster specifically comprises the following steps:
according to the power adjusting range of each air conditioner homogeneous group, determining the power adjusting range of the air conditioner cluster as follows:
Wherein P s,a (t) represents the target of the air conditioner cluster at the moment t, AndRespectively representing the lower limit and the upper limit of the power adjusting range of the ith air conditioner homogeneous group at the t moment, wherein I a represents the number of the air conditioner homogeneous groups;
according to the power adjusting range of the air conditioner cluster, determining the target power adjusting range of the electric water heater cluster as follows:
Wherein P s (t) represents a scheduling task at the time t, and P s,h (t) represents a digestion target of the electric water heater cluster at the time t;
the method comprises the following steps of determining the digestion targets of the electric water heater cluster by taking the first target function as a target: The first objective function is
Wherein f 1 represents a first objective function, P H,j (t) represents a target for the digestion of the j-th homogeneous group of electric water heaters at time t, and P H,j (t) has a value ofOr (b)The upper limit of the power adjusting range of the homogeneous group of the j-th electric water heater at the moment t is shown,The lower limit of the power adjusting range of the J-th electric water heater homogeneous group at the t moment is represented, and J h represents the number of the electric water heater homogeneous groups;
According to the absorption target of the electric water heater cluster, determining the absorption target of the air conditioner cluster as follows: p s,a(t)＝Ps(t)-Ps,h (t).
2. The hybrid load cluster control method according to claim 1, wherein the adjustment range of each homogeneous group of electric water heaters is determined according to the estimated power of each homogeneous group of electric water heaters, respectively, as follows:
Wherein, The upper limit of the power adjusting range of the homogeneous group of the j-th electric water heater at the moment t is shown,The lower limit of the power adjusting range of the homogeneous group of the j-th electric water heater at the moment t is shown,The switch state of the hl electric water heater in the homogeneous group of the j electric water heater under the '1' switching state is shown,The switching state of the hl electric water heater in the J-th electric water heater homogeneous group under the switching state of 0 is shown, J h is the number of the electric water heater homogeneous groups, and P 0,j is the estimated power of the J-th electric water heater homogeneous group.
3. The hybrid load cluster management method according to claim 1, wherein the adjustment range of each air conditioner homogeneous group is determined according to the estimated power of each air conditioner homogeneous group as follows:
Wherein, AndRespectively represent the lower limit and the upper limit of the power adjustment range of the ith air conditioner homogeneous group at the moment t, AndRespectively representing a lower limit and an upper limit of a stable power level of the ith air conditioning group, N L,i representing the number of air conditioners contained in the ith air conditioning group; And Respectively represents that the ith air conditioner homogeneous group is at the upper limit of the temperature set pointThe cooling time and the closing time of the lower part,AndRespectively represent that the ith air conditioner homogeneous group is at the lower limit of the temperature set pointThe refrigeration time and the closing time are under, P a,i (t) represents the estimated power of the ith air conditioner homogeneous group at the moment t,S al,i (t) is the on-off state of the ith air conditioner in the ith air conditioner homogeneous group, I a represents the number of the air conditioner homogeneous groups, P As,i (t) represents the stable power level of the ith air conditioner homogeneous group at the time t, P i represents the average power of the air conditioners in the ith air conditioner homogeneous group, and η i represents the energy efficiency ratio of the air conditioners in the ith air conditioner homogeneous group.
4. The hybrid load cluster management method of claim 1, wherein the first aggregate model comprises a first aggregate model in a "1" switching state and a first aggregate model in a "0" switching state;
the first aggregation model in the "1" switching state is:
Wherein x h,j (t) represents a state vector of Q h,j ×1 composed of the number of electric water heaters in each state interval in the switching state of the j-th electric water heater homogeneous group "1", y h,j (t) is the output power of the first aggregation model of the j-th electric water heater homogeneous group, a h,j represents the first load transfer rate matrix of Q h,j×Qh,j of the j-th electric water heater homogeneous group, B h,j represents the first power matrix of 1×q h,j of the j-th electric water heater homogeneous group, and Q h,j represents the number of state intervals in the j-th electric water heater homogeneous group;
The rate of heat transfer is indicated as, Representing the heat preservation transfer rate, wherein the blank area in the matrix A h,j corresponds to zero elements;
N h,j represents the number of heating state intervals in a1 switching state in the j-th electric water heater homogeneous group, and P 0,j represents the rated power of electric water heaters in the j-th electric water heater homogeneous group;
The first aggregation model in the "0" switching state is:
In the '0' switching state, all loads (including loads which are about to reach a set upper limit temperature interval) which are originally in a heating state in the homogeneous group of the electric water heater are converted into a heat preservation state and move towards the direction of the lowest temperature limit; the load reaching the set lower limit temperature range originally changes the state of the heat-insulating material from heat insulation to heating, and the heat-insulating material is changed into a heat-insulating state after reaching the set upper limit temperature range; wherein x h1,j (t) represents a state vector of N h,j ×1 consisting of the number of electric water heaters originally in the heating state in the "0" switching state of the jth electric water heater homogeneous group, x h2,j (t) represents a state vector of (Q h,j-Mh,j) ×1 consisting of electric water heaters in the heat preservation-heating-heat preservation cycle state interval in the jth electric water heater homogeneous group, E h1,j represents a second load transfer rate matrix of the jth electric water heater homogeneous group, E h2,j represents a third load transfer rate matrix of the jth electric water heater homogeneous group, and F h,j represents a second power matrix of the jth electric water heater homogeneous group;
M h,j represents the number of state intervals below the temperature set lower limit.
5. The method for controlling a hybrid load cluster according to claim 1, wherein the determining the optimal switching state of each homogeneous group of electric water heaters in the electric water heater cluster according to the absorption target of the electric water heater cluster specifically comprises:
Solving a second objective function by adopting an optimization algorithm, and determining a control state of each electric water heater homogeneous group in the electric heater cluster when the second objective function is optimal as an optimal switching state of each electric water heater homogeneous group in the electric heater cluster;
the second objective function is:
Wherein f 2 represents a second objective function, P s,h (t) is a target of the electric water heater cluster at time t, J h represents the number of homogeneous groups of electric water heaters, P H,j (t) represents the estimated power of the J-th homogeneous group of electric water heaters at time t, when the control state is a "1" switching state, When the control state is a "0" switching state,The upper limit of the power adjusting range of the homogeneous group of the j-th electric water heater at the moment t is shown,The lower limit of the power regulation range of the homogeneous group of the j-th electric water heater at the moment t is shown.
6. The hybrid load cluster control method according to claim 5, wherein the changing the switching state of each electric water heater homogeneous group and the operation state of each electric water heater in the homogeneous group based on the optimal control state of each electric water heater homogeneous group and the first aggregation model specifically comprises:
Determining a first aggregation model of each electric water heater homogeneous group according to the optimal control state of each electric water heater homogeneous group;
The operation state of each electric water heater in each electric water heater homogeneous group is adjusted according to the first aggregation model of each electric water heater homogeneous group aiming at minimizing the absolute value of the difference value between the sum of the output powers of the first aggregation models of each electric water heater homogeneous group and the absorption target of the electric water heater cluster.
7. The hybrid load cluster management and control method according to claim 1, wherein the determining, according to the consumption target of the air conditioning cluster, the adjustment task of each air conditioning homogeneous group in the air conditioning cluster specifically includes:
According to the absorption target of the air conditioner cluster, determining the adjustment task of each air conditioner homogeneous group in the air conditioner cluster as follows:
Psa,i(t)＝Pa,i(t)+ΔPi(t),i＝1,2,…,Ia；
Wherein P sa,i (t) represents the adjustment task of the ith air conditioner homogeneous group at the moment t, P a,i (t) represents the estimated power of the ith air conditioner homogeneous group at the moment t, I a represents the number of the air conditioner homogeneous groups, The change amount of the i-th air conditioner homogeneous group adjusting task at the moment t is represented; p s,a (t) represents the target of the air conditioning cluster at time t.
8. The hybrid load cluster management method of claim 1, wherein the second aggregate model is:
Wherein x a,i (t) represents a state vector formed by the number of air conditioners in each state interval in the ith air conditioner homogeneous group at the moment t, Is the input variable of the ith air conditioner homogeneous group at the moment t,The change rate of the set temperature of the ith air conditioner homogeneous group at the t moment is shown; y a,i (t) represents the second polymerization die output power of the ith air conditioner homogeneous group at time t; a a,i、Ba,i and C a,i respectively represent a fourth load transfer rate matrix, an input variable state matrix and a third power matrix of the ith air conditioner homogeneous group, blank areas in the matrix A a,j、Ba,j are zero elements correspondingly, and the dimension numbers are Q a,i×Qa,i、Qa,j×Qa,i、1×Qa,i;Qa,i respectively to represent the number of state intervals in the ith air conditioner homogeneous group;
indicating the off-state load transfer rate of the ith air conditioning group, The cooling state load transfer rate of the i-th air-conditioning homogeneous group is represented, N a,i represents the number of state sections in the off state in the i-th air-conditioning homogeneous group, P i represents the average power of the air conditioners in the i-th air-conditioning homogeneous group, and η i represents the energy efficiency ratio of the air conditioners in the i-th air-conditioning homogeneous group.
9. The hybrid load cluster management and control method according to claim 8, wherein the sliding mode control method has a formula as follows:
The input variable of the ith air conditioner homogeneous group at the moment of t is input into the second aggregation model to obtain the output power of the second aggregation model of the ith air conditioner homogeneous group; e (T) represents the difference between the regulating task of the ith air conditioning homogeneous group and the second polymerization mode output power of the ith air conditioning homogeneous group at time T, κ (T) is typically a time-varying control gain satisfying the robustness condition, sat (·) represents an adjustable saturation function for suppressing boundary buffeting, f i (X) and g i (X) represent a first intermediate function and a second intermediate function, respectively, X represents a state variable, P i represents the average power of the air conditioners in the ith air conditioning homogeneous group, η i represents the energy efficiency ratio of the air conditioners in the ith air conditioning homogeneous group, β off,i and β on,i represent the off-state load transfer rate and the refrigeration-state load transfer rate of the ith air conditioning homogeneous group, respectively, T a,i, AndRespectively representing the initial temperature set value, the lower temperature regulation limit and the upper temperature regulation limit of the ith air conditioner homogeneous group,For the ith air conditioning homogeneous group at temperature at time tThe number of air conditioners in the lower refrigerating state; For the ith air conditioning homogeneous group at temperature at time t The number of air conditioners in the lower off state, ε, is an arbitrarily chosen small control parameter, sgn (·) represents a sign function.
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