CN107726533B - Air conditioner load power oscillation suppression control method - Google Patents
Air conditioner load power oscillation suppression control method Download PDFInfo
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- 230000010355 oscillation Effects 0.000 title claims abstract description 28
- 238000000034 method Methods 0.000 title claims abstract description 15
- 230000001629 suppression Effects 0.000 title claims abstract description 12
- 238000004378 air conditioning Methods 0.000 claims abstract description 27
- 238000004422 calculation algorithm Methods 0.000 claims description 10
- 230000002068 genetic effect Effects 0.000 claims description 10
- 238000005457 optimization Methods 0.000 claims description 9
- 230000035772 mutation Effects 0.000 claims description 6
- 108090000623 proteins and genes Proteins 0.000 claims description 6
- 238000004088 simulation Methods 0.000 claims description 5
- 230000000694 effects Effects 0.000 abstract description 2
- 238000011217 control strategy Methods 0.000 description 4
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Abstract
The invention discloses an air conditioner load power oscillation suppression control method, which comprises the following steps: dividing all the air conditioning loads to be restrained and controlled into M groups, wherein each group comprises the same number of air conditioning loads, and prioritizing the M groups of air conditioning loads; and selecting and closing one of the M groups of air conditioning loads according to the priority order, and executing control at intervals of a period of time h until the power oscillation range is within the set stable threshold range. The control method of the power oscillation can obviously improve the control effect and improve the robustness of control.
Description
Technical Field
The invention provides an oscillation suppression control method, in particular to an air conditioner load power oscillation suppression control method.
Background
When a large number of air conditioning loads are controlled, the diversity of the air conditioning loads is easily destroyed, aggregate power oscillation of the large number of air conditioning loads is caused after the control is finished, and in order to avoid the aggregate power oscillation of the air conditioning loads as much as possible, it is necessary to adopt a reasonable power oscillation suppression control strategy for the air conditioning loads after the control is finished.
Disclosure of Invention
The invention aims to solve the technical problem that when a large amount of air-conditioning loads are controlled, the diversity of the air-conditioning loads is easy to damage, and aggregated power oscillation of the large amount of air-conditioning loads is caused after the control is finished.
In order to solve the technical problem, the invention provides an air conditioner load power oscillation suppression control method, which comprises the following steps:
step 1, dividing all air-conditioning loads to be restrained and controlled into M groups, wherein each group comprises the same number of air-conditioning loads, and prioritizing the M groups of air-conditioning loads;
and 2, selecting and closing one of the M groups of air conditioner loads according to the priority sequence, and executing control at intervals of a period of time h until the power oscillation range is within the set stable threshold range.
As a further limiting aspect of the invention, the number M of packets and the time interval h are obtained by optimization based on genetic algorithms.
As a further limiting scheme of the invention, the specific steps of obtaining the number M of the components and the time interval h based on genetic algorithm optimization are as follows:
step a, randomly generating an initial population, wherein the population comprises a certain number of individuals coded by M and h;
b, substituting the parameters M and h corresponding to each individual into an objective function, and calculating the fitness of each individual in the population according to the objective function;
step c, selecting the individuals with higher fitness and eliminating the individuals with lower fitness;
d, performing cross operation, randomly selecting two individuals, and exchanging genes of the individuals according to a set cross probability;
e, performing mutation operation, randomly selecting an individual, and mutating the gene according to the set mutation probability;
and f, repeating the steps b to e until the maximum iteration times is reached.
As a further limiting scheme of the present invention, the objective function when the number M of the packets and the time interval h are obtained based on genetic algorithm optimization is defined as the form of the square integral of the error of the oscillation power:
where Δ P is the difference between the oscillating power and the steady state power, and T is the time of the simulation run.
The invention has the beneficial effects that: (1) selecting and closing one of the M groups of air-conditioning loads according to the priority order, so that the power oscillation of the air-conditioning loads is basically stabilized; (2) the control effect can be obviously improved, and the control robustness is improved.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a diagram of simulation results of the present invention.
Detailed Description
As shown in fig. 1, the present invention provides an air-conditioning load power oscillation suppression control method, wherein a control strategy of power oscillation adopts a centralized control architecture, a controller is required to grasp temperature state information of all air-conditioning loads through bidirectional communication with the air-conditioning loads, and the specific oscillation suppression control method comprises the following steps:
step 1, dividing all air-conditioning loads to be restrained and controlled into M groups, wherein each group comprises the same number of air-conditioning loads, and prioritizing the M groups of air-conditioning loads;
and 2, selecting and closing one of the M groups of air conditioner loads according to the priority sequence, and executing control at intervals of a period of time h until the power oscillation range is within the set stable threshold range.
In the above control strategy, the number M of packets and the value of the time interval h are very important to the control result. The number M of the groups and the time interval h are obtained by optimization based on a genetic algorithm, an objective function is defined as an Integrated Square Error (ISE) of oscillation power through calculation in the optimization process, and the optimal M and h are obtained through operations such as execution, selection, variation and the like. The specific steps of optimizing the number M of the groups and the time interval h based on the genetic algorithm are as follows:
step a, randomly generating an initial population, wherein the population comprises a certain number of individuals coded by M and h;
b, substituting the parameters M and h corresponding to each individual into an objective function, and calculating the fitness of each individual in the population according to the objective function;
step c, selecting the individuals with higher fitness and eliminating the individuals with lower fitness;
d, performing cross operation, randomly selecting two individuals, and exchanging genes of the individuals according to a set cross probability;
e, performing mutation operation, randomly selecting an individual, and mutating the gene according to the set mutation probability;
and f, repeating the steps b to e until the maximum iteration times is reached.
The objective function when optimizing the number M of packets and the time interval h using a genetic algorithm is defined in the form of the square integral of error (ISE) of the oscillation power:
where Δ P is the difference between the oscillating power and the steady state power, and T is the time of the simulation run.
As shown in fig. 2, 10000 air conditioners are taken as research objects, a calculation example analysis is performed, the number M of groups of the air conditioners and a time interval h are determined by a genetic algorithm, an optimization result is assumed to be M7, h is 5min, each state of the 10000 air conditioners is divided into 7 groups in the process of suppressing the power oscillation, one group of the air conditioners in an on state is turned off at intervals of 5min, and as can be seen from a simulation result fig. 2, the power oscillation of the air conditioners after load shedding can be suppressed by adopting an additional control strategy for the 10000 air conditioners.
Claims (3)
1. An air conditioner load power oscillation suppression control method is characterized by comprising the following steps:
step 1, dividing all air-conditioning loads to be restrained and controlled into M groups, wherein each group comprises the same number of air-conditioning loads, and prioritizing the M groups of air-conditioning loads;
step 2, selecting and closing one of the M groups of air conditioner loads according to the priority sequence, and executing control at intervals of a period of time h until the power oscillation range is within a set stable threshold range;
wherein, the number M of the groups and the time interval h are obtained by optimization based on genetic algorithm.
2. The air conditioner load power oscillation suppression control method according to claim 1, wherein the specific steps of obtaining the number M of the packets and the time interval h by optimization based on a genetic algorithm are as follows:
step a, randomly generating an initial population, wherein the population comprises a certain number of individuals coded by M and h;
b, substituting the parameters M and h corresponding to each individual into an objective function, and calculating the fitness of each individual in the population according to the objective function;
step c, selecting the individuals with higher fitness and eliminating the individuals with lower fitness;
d, performing cross operation, randomly selecting two individuals, and exchanging genes of the individuals according to a set cross probability;
e, performing mutation operation, randomly selecting an individual, and mutating the gene according to the set mutation probability;
and f, repeating the steps b to e until the maximum iteration times is reached.
3. The air conditioning load power oscillation suppression control method according to claim 2, characterized in that an objective function when the number M of packets and the time interval h are obtained based on genetic algorithm optimization is defined as a form of error square integral of the oscillation power:
where Δ P is the difference between the oscillating power and the steady state power, and T is the time of the simulation run.
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| JP2001227794A (en) * | 2000-02-16 | 2001-08-24 | Daikin Ind Ltd | Method of estimating air-conditioning load, and method of controlling regenerative air-conditioning system, and these devices |
| CN104214912A (en) * | 2014-09-24 | 2014-12-17 | 东南大学 | Aggregation air conditioning load scheduling method based on temperature set value adjustment |
| CN104566868A (en) * | 2015-01-27 | 2015-04-29 | 徐建成 | Central air-conditioning control system and control method thereof |
| CN104636987A (en) * | 2015-02-06 | 2015-05-20 | 东南大学 | Dispatching method for power network load with extensive participation of air conditioner loads of institutional buildings |
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