CN108224692B - Consider the air-conditioning flexible control responding ability prediction technique of outside air temperature prediction error - Google Patents
Consider the air-conditioning flexible control responding ability prediction technique of outside air temperature prediction error Download PDFInfo
- Publication number
- CN108224692B CN108224692B CN201810018982.5A CN201810018982A CN108224692B CN 108224692 B CN108224692 B CN 108224692B CN 201810018982 A CN201810018982 A CN 201810018982A CN 108224692 B CN108224692 B CN 108224692B
- Authority
- CN
- China
- Prior art keywords
- conditioning
- air
- flexible control
- formula
- value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000004378 air conditioning Methods 0.000 title claims abstract description 147
- 238000000034 method Methods 0.000 title claims abstract description 32
- 230000004044 response Effects 0.000 claims abstract description 83
- 238000002948 stochastic simulation Methods 0.000 claims description 41
- 238000004088 simulation Methods 0.000 claims description 14
- 238000006116 polymerization reaction Methods 0.000 claims description 8
- 230000003111 delayed effect Effects 0.000 claims description 4
- NAWXUBYGYWOOIX-SFHVURJKSA-N (2s)-2-[[4-[2-(2,4-diaminoquinazolin-6-yl)ethyl]benzoyl]amino]-4-methylidenepentanedioic acid Chemical compound C1=CC2=NC(N)=NC(N)=C2C=C1CCC1=CC=C(C(=O)N[C@@H](CC(=C)C(O)=O)C(O)=O)C=C1 NAWXUBYGYWOOIX-SFHVURJKSA-N 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 230000008859 change Effects 0.000 abstract description 6
- 238000007619 statistical method Methods 0.000 abstract 1
- 230000005611 electricity Effects 0.000 description 6
- 238000004422 calculation algorithm Methods 0.000 description 5
- 238000009795 derivation Methods 0.000 description 4
- 238000007796 conventional method Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 240000002853 Nelumbo nucifera Species 0.000 description 2
- 235000006508 Nelumbo nucifera Nutrition 0.000 description 2
- 235000006510 Nelumbo pentapetala Nutrition 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 239000004744 fabric Substances 0.000 description 2
- 241000196324 Embryophyta Species 0.000 description 1
- 238000000342 Monte Carlo simulation Methods 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 239000012141 concentrate Substances 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000000178 monomer Substances 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
- 230000002459 sustained effect Effects 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000011426 transformation method Methods 0.000 description 1
Landscapes
- Air Conditioning Control Device (AREA)
Abstract
The invention discloses a kind of air-conditioning flexible control responding ability prediction techniques of consideration outside air temperature prediction error, comprising: 1. establish the White Noise Model of outside air temperature prediction error；2. the indoor air temperature change procedure in room where describing air-conditioning using stochastic differential equation；3. emulating using Method of Stochastic to the course of work of air-conditioning cluster, the sample of air-conditioning flexible control responding ability is obtained, the sample including response capacity and response delay；4. obtaining the prediction result of air-conditioning flexible control responding ability using statistical method: sample average, sample standard deviation and the estimation interval of response capacity and response delay.The present invention can polymerize quotient for air conditioner load and provide reference frame to the effective demand response management of air conditioner load implementation.
Description
Technical field
The invention belongs to electric load demand side management field, the air-conditioning for being related to a kind of consideration outside air temperature prediction error is soft
Property control response energy force prediction method.
Background technique
In recent years, with the increasingly improvement of economic fast development and people's lives, power load (especially electricity consumption peak
Lotus) sharp increase, load curve peak-valley difference problem highlights.For the power demand for meeting load rapid growth, traditional way is
Newly-built power plant and transformation dilatation power grid, but since the utilization rate of these new additional issue transmission facilities is low, eventually result in cost increasing
Sum it up the wasting of resources.Practical experience both domestic and external shows alleviation electric power confession that only can not be effective, economic by increasing hair transmission of electricity scale
Need contradiction, it is necessary to transfer Demand-side resource and participate in peak load regulation network.Electricity needs response refers to that power consumer receives supplier of electricity hair
After inductivity out reduces the direct compensation notice or power price rising signals of load, change its intrinsic use power mode,
The power load of certain period is reduced or elapses, thus the acts and efforts for expediency for ensureing the stabilization of power grids, and electricity price being inhibited to rise.In demand
Before responding implementing plan, usual demand response enforcement body will sign a contract in advance with participating user, arrange demand in contract
The content (cutting down power load size and costing standard, duration of response, the peak response number in the indentured period etc.) of response,
Advance notification times, compensation or electricity price discount criteria and the punitive measures of promise breaking etc..
With the propulsion of Re-search on Urbanization process and frequently occurring for extreme climate, air conditioner load maintains sustained and rapid growth.Often
Hot season in year, air-conditioning system concentrate starting, exacerbate network load peak-valley difference, finally jeopardize the safe and stable operation of power grid.
Currently, China's air-conditioning peak load accounting is larger, some areas are even more than 50%, become the major reason of summer power shortages
One of.Air conditioner load is concentrated mainly on peak times of power consumption summer, if simple meet of short duration point by installed capacity is increased
Peak load is bound to cause the significant wastage of social resources；On the contrary, if effective Demand Side Response can be taken to arrange air conditioner load
It applies, then can inhibit power spikes load, slow down the pressure of newly-built variable load plant, and reduce environmental pollution.
Air-conditioning as a kind of typical temperature control load, have response speed is very fast, controllability preferably, have energy stores spy
The advantages that property, so having become one of main study subject of load control system.However, monomer air conditioning capacity is small, large number of, dispersion
Distribution, response randomness are strong, it is therefore necessary to numerous air-conditionings are polymerized to air-conditioning cluster, by air conditioner load polymerization quotient to air conditioner load
Carry out demand response management.The control mode of air conditioner load mainly includes rigidity control and flexible control: air-conditioning rigidity control side
Formula is general directly completely or partially to shut down air-conditioning equipment, such as shuts down host, shut-down cycles system or shuts down tail-end blower fan coil pipe
Deng；And air-conditioning flexible control is reached part and is cut by the power output of the Load adjustments such as change air-conditioning equipment operating parameter, operational mode
The purpose of load shedding.Influence due to the control of air-conditioning flexible load to users'comfort is smaller, thus is easier to promote and apply.
Air-conditioning rigidity control and the Accurate Prediction of flexible control responding ability be air conditioner load polymerization quotient to air-conditioning cluster into
The premise of row effective demand response management；Wherein, responding ability includes two aspects of response capacity and response delay.At present in sky
In terms of adjusting the research of flexible control responding ability, usually only response capacity is predicted, without predicting response delay；
And response capacity is predicted on the basis of air conditioner heat dynamic (dynamical) deterministic models, there is no consider outside air temperature
The random error of prediction, however, since there are random errors for outside air temperature prediction, so the responding ability of air-conditioning flexible control has
There is uncertainty.In conclusion the obtained response capacity predicted value of conventional method does not account for outside air temperature prediction error
It influences, and without providing the prediction to response delay, these all implement effectively to need to air conditioner load polymerization quotient to air conditioner load
Response management is asked to cause difficulty.
Summary of the invention
The present invention does not account for the defect of outside air temperature prediction error, unpredictable response delay for conventional method, mentions
For a kind of air-conditioning flexible control responding ability prediction technique of consideration outside air temperature prediction error, to by establishing outside air temperature
It predicts the model of error and the stochastic simulation to the air-conditioning cluster course of work, obtains more reasonable air-conditioning flexible control response energy
The prediction result of power (including response capacity and response delay), so that polymerizeing quotient for air conditioner load provides more comprehensive information,
In order to which it implements more scientific, effective demand response management to air conditioner load.
The present invention adopts the following technical scheme that in order to solve the technical problem
The present invention is a kind of to consider that the characteristics of outside air temperature predicts the air-conditioning flexible control responding ability prediction technique of error is
It carries out as follows:
Step 1. obtains initial data, comprising: the initial time t that stochastic simulation starts0；The air-conditioning that air-conditioning cluster is included
Number of units K；The thermal capacitance C in room where kth platform air-conditioningk, it is air-conditioning number that unit, which is kWh/ DEG C, k=1,2 ..., K,；Kth platform air-conditioning
The thermal resistance R in place roomk, unit be DEG C/kW；The rated power P of kth platform air-conditioningk, unit kW；The Energy Efficiency Ratio of kth platform air-conditioning
ηk；Kth platform air-conditioning carves t at the beginning0When switch state sk(t0): work as sk(t0) value be 1 when, indicate kth platform air-conditioning first
Begin moment t0" booting ", works as sk(t0) value be 0 when, indicate kth platform air-conditioning carve t at the beginning0" shutdown "；Where kth platform air-conditioning
T is carved at the beginning in room0When Indoor Air temperature value θk(t0), unit is DEG C；Air conditioner load polymerization quotient assigns " soft to air-conditioning cluster
Property control sign on " at the time of tS；Air conditioner load polymerize quotient and assigns " END instruction of flexible control " to air-conditioning cluster
Moment tE；Indoor air temperature setting value θ before the response of kth platform air-conditioningset,k, unit is DEG C；Indoor air temperature after the response of kth platform air-conditioning
Setting value θ 'set,k, unit is DEG C；The dead zone temperature θ of kth platform air-conditioning hysteresis controld,k, unit is DEG C；The outside air temperature of t moment
Predicted valueUnit is DEG C；Outside air temperature predicts the proportionality constant q, 0 < q < 1 in error White Noise Model；
Step 2. establishes the White Noise Model of outside air temperature prediction error using formula (1):
In formula (1),For the outside air temperature prediction error value of t moment；{ X (t), 0≤t≤∞ } be mean value be zero, side
The limited white noise of difference；
The indoor air temperature in room becomes where step 3. describes kth platform air-conditioning using stochastic differential equation shown in formula (2)
Change:
In formula (2), θk(t) in the Indoor Air temperature value of t moment, unit is DEG C in room where kth platform air-conditioning；skIt (t) is the
Switch state of the k platform air-conditioning in t moment: work as sk(t) when value is 1, indicate kth platform air-conditioning in t moment " booting "；Work as sk(t) it takes
When value is 0, indicate kth platform air-conditioning in t moment " shutdown "；
Simulation parameter: a length of T when emulation is arranged in step 4.s；Simulation step length is Δ t；Random simulation times are J；
Step 5. enables j=1；Jth time stochastic simulation is carried out to the air-conditioned course of work of institute in air-conditioning cluster:
Step 5.1. enables k=1；
Step 5.2. gives indicator variable IbeginAssign initial value 0；Give indicator variable IoverAssign initial value 0；
Wherein, IbeginIndicator variable whether assigning for the sign on of flexible control: value is 0 expression flexible control
Sign on is not assigned, and value is that the sign on of 1 expression flexible control has been assigned；IoverFor under the END instruction of flexible control
Up to whether indicator variable: value be 0 expression flexible control END instruction do not assign, value be 1 indicate flexible control knot
Shu Zhiling has been assigned；
Step 5.3. enables i=0；By θk(t0) and sk(t0) it is assigned to θ respectivelyk,j(ti) and sk,j(ti)；
Wherein, θk,j(ti) indicate that the sign on of the flexible control in jth time stochastic simulation is assigned before, kth platform air-conditioning institute
In room in tiThe Indoor Air temperature value at moment；sk,j(ti) indicate that the sign on of the flexible control in jth time stochastic simulation is assigned
Before, kth platform air-conditioning is in tiThe switch state at moment；
Step 5.4. judges ti=tSIt is whether true: if so, by θk,j(ti) and sk,j(ti) it is assigned to θ ' respectivelyk,j(ti)
With s 'k,j(ti), and enable indicator variable Ibegin=1, then execute step 5.5；Otherwise, step 5.5 is executed；
Wherein, θ 'k,j(ti) indicate that the sign on of the flexible control in jth time stochastic simulation is assigned after, kth platform air-conditioning
Place room is in tiThe Indoor Air temperature value at moment；s′k,j(ti) indicate in jth time stochastic simulation under the sign on of flexible control
After reaching, kth platform air-conditioning is in tiThe switch state at moment；
Step 5.5. judges ti=tEIt is whether true: if so, enable indicator variable Iover=1, then, execute step 5.6；
Otherwise, step 5.6 is executed；
Step 5.6. generates the t in jth time stochastic simulation using the methods of sampling of stochastic variableiThe standard normal at moment point
Cloth stochastic variable εj(ti)；
Step 5.7. is by θk,j(ti) and sk,j(ti), using the numerical computation method of stochastic differential equation calculate jth time with
Before the sign on of flexible control is assigned in machine simulation, room is in t where kth platform air-conditioningi+1The Indoor Air temperature value θ at momentk,j
(ti+1)；
Before step 5.8. is assigned by the sign on of formula (3) determining flexible control in jth time stochastic simulation, kth platform is empty
It adjusts in ti+1The switch state s at momentk,j(ti+1):
In formula (3), ti+1=ti+Δt；
If step 5.9. Ibegin=1 and Iover=0 sets up, and executes step 5.10；Otherwise, step 5.12 is executed；
Step 5.10. is by θ 'k,j(ti) and s 'k,j(ti), jth time is calculated using the numerical computation method of stochastic differential equation
After the sign on of flexible control is assigned in stochastic simulation, room is in t where kth platform air-conditioningi+1The Indoor Air temperature value θ ' at momentk,j
(ti+1)；
Step 5.11. by formula (4) determine flexible control in jth time stochastic simulation sign on assign after, kth platform air-conditioning
In ti+1The switch state s ' at momentk,j(ti+1):
In formula (4), ti+1=ti+Δt；
If step 5.12. ti+1-t0< TsIt sets up, after enabling i+1 be assigned to i, executes step 5.4；It is no to then follow the steps 5.13；
If step 5.13. k < K is set up, after enabling k+1 be assigned to k, step 5.2 is executed；It is no to then follow the steps 5.14；
Step 5.14. is calculated the response capacity of the air-conditioning flexible control in jth time stochastic simulation by formula (5)
Step 5.15. is calculated the response delay Δ t of the air-conditioning flexible control in jth time stochastic simulation by formula (6)d,j:
If step 5.16. j < J is set up, after enabling j+1 be assigned to j, step 5.1 is executed；It is no to then follow the steps 6；
Step 6. withWith Δ td,j, j=1,2 ..., J are calculated as random sample by statistics
Obtain the prediction result of air-conditioning flexible control responding ability:
Step 6.1. calculates t by formula (7)iThe functions of sample means μ of time of day response capacityP(ti):
Step 6.2. calculates t by formula (8)iThe sample canonical difference function δ of time of day response capacityp(ti):
The functions of sample means μ of step 6.3. capacity according to responseP(ti) and sample canonical difference function δp(ti), obtain sky
Adjust the estimation interval [μ of flexible control response capacityP(ti)-δp(ti),μP(ti)+δp(ti)],ti∈[tS,tE]；
Step 6.4. is calculated the sample average of response delay by formula (9)
Step 6.5. is calculated the sample standard deviation of response delay by formula (10)
The sample average that step 6.6. is delayed according to responseAnd sample standard deviationObtain the estimation of response delay
Section
Compared with the prior art, the invention has the advantages that:
The defect that the present invention overcomes conventional methods to ignore outside air temperature prediction error, is unable to predicated response delay, passes through
The White Noise Model of outside air temperature prediction error and the stochastic simulation to the air-conditioning cluster course of work are established, it is not only more reasonable
The response capacity of air-conditioning flexible control is predicted, and predicts its response delay, it is negative to air-conditioning to polymerize quotient for air conditioner load
Lotus implements more scientific, effective demand response management and provides important reference frame.Specific effect is embodied in following
Aspect:
1. the present invention establishes the White Noise Model of outside air temperature prediction error, so that it is random to consider outside air temperature prediction
The influence of error；
2. the present invention establishes the stochastic differential equation for describing indoor air temperature change procedure, for simulation air-conditioning cluster
The course of work is laid a good foundation；
3. the present invention obtains the sample of response capacity and response delay, carries out statistics calculating to sample by stochastic simulation
Prediction result is obtained, which embodies the uncertainty of prediction result caused by outside air temperature prediction random error,
It polymerize quotient for air conditioner load and provides useful information more abundant.
Detailed description of the invention
Fig. 1 is the air-conditioning flexible control responding ability prediction technique for considering outside air temperature prediction error of the present invention
Flow diagram；
Fig. 2 be jth time stochastic simulation is carried out to air-conditioning cluster in the present invention, and calculate air-conditioning flexible control response capacity and
Respond the flow chart of time extension sample.
Specific embodiment
In the present embodiment, the response of air-conditioning flexible control refers to the behavior of air-conditioning reduction plans under flexible control mode,
That is user's behavior for reducing burden with power demand by adjusting desired temperature in air conditioning chamber；Air-conditioning cluster refers to air conditioner load
The set for the air-conditioning that polymerization quotient is controlled.In the case of considering outside air temperature prediction error, air-conditioning flexible control responding ability
The overall procedure schematic diagram of (including response capacity and response delay) prediction technique is as shown in Figure 1, specific carry out as follows:
Step 1. obtains initial data:
t0, initial time that stochastic simulation starts；
K, the air-conditioning number of units that air-conditioning cluster is included；
Ck, the thermal capacitance in room where kth platform air-conditioning, unit is kWh/ DEG C；
Wherein, k (k=1,2 ..., K) is air-conditioning number；
Rk, the thermal resistance in room where kth platform air-conditioning, unit is DEG C/kW；
Pk, the rated power of kth platform air-conditioning, unit kW；
ηk, the Energy Efficiency Ratio of kth platform air-conditioning；
sk(t0), kth platform air-conditioning carves t at the beginning0When switch state: work as sk(t0) value when being 1, indicates that kth platform is empty
Tune carves t at the beginning0" booting "；Work as sk(t0) value be 0 when, indicate kth platform air-conditioning carve t at the beginning0" shutdown "；
θk(t0), t is carved in room where kth platform air-conditioning at the beginning0When Indoor Air temperature value, unit be DEG C；
tS, at the time of air conditioner load polymerization quotient assigns " sign on of flexible control " to air-conditioning cluster；
tE, at the time of air conditioner load polymerization quotient assigns " END instruction of flexible control " to air-conditioning cluster；
θset,k, kth platform air-conditioning response before indoor air temperature setting value, unit be DEG C；
θ′set,k, kth platform air-conditioning response after indoor air temperature setting value, unit be DEG C；
θd,k, the dead zone temperature of kth platform air-conditioning hysteresis control, unit is DEG C；
The outside air temperature predicted value of t moment, unit are DEG C；
Q, outside air temperature predict the proportionality constant in error White Noise Model, 0 < q < 1；
Step 2. establishes the White Noise Model of outside air temperature prediction error using formula (1):
In formula (1),For the outside air temperature prediction error value of t moment；{ X (t), 0≤t≤∞ } be mean value be zero, side
The limited white noise of difference；SoAnd mean value is zero, the limited white noise of variance.
The White Noise Model that error is predicted by establishing outside air temperature introduces and responds capacity and sound to air-conditioning flexible control
Should be delayed the factor impacted: the random error of outside air temperature prediction.
Step 3. describes room where kth (k=1,2 ..., K) platform air-conditioning using stochastic differential equation shown in formula (2)
Indoor air temperature variation:
In formula (2), θk(t) in the Indoor Air temperature value of t moment, unit is DEG C in room where kth platform air-conditioning；skIt (t) is the
Switch state of the k platform air-conditioning in t moment: work as sk(t) when value is 1, indicate kth platform air-conditioning in t moment " booting "；Work as sk(t) it takes
When value is 0, indicate kth platform air-conditioning in t moment " shutdown "；
The derivation of formula (2) is explained as follows:
According to the single order thermodynamics Equivalent Model of air-conditioning, the indoor air temperature in room changes such as formula (* 1) where kth platform air-conditioning
It is shown:
In formula (* 1), θa(t) be t moment outside air temperature value, unit be DEG C, it can be pre- by the outside air temperature of t moment
Measured valueIn addition prediction error valueAnd obtain, as shown in formula (* 2):
Formula (1), formula (* 2) are substituted into formula (* 1), so that it may obtain formula (2), thus establish room where kth platform air-conditioning
Between indoor air temperature variation random differential equation models, thus introduce outside air temperature prediction error influence, i.e., in formula (2)
The 2nd of right side of the equal sign:
Stochastic differential equation shown in formula (2) can using a variety of numerical computation methods solve, as Euler algorithm,
Milstein algorithm etc. is solved using Euler algorithm in the present embodiment, then the indoor air temperature in room where kth platform air-conditioning is pressed
Recurrence formula shown in formula (* 3) solves:
In formula (* 3), ε (ti) it is in ti(its mean value is 0 to moment standardized normal distribution stochastic variable generated, and variance is
1).The derivation process of formula (* 3) is as follows:
Formula (2) can be write as the form of formula (* 4):
In formula (* 4), dW (t)=X (t) dt, { W (t), 0≤t≤∞ } is standard Wiener-Hopf equation.
Using Euler algorithm by stochastic differential equation discretization shown in formula (* 4), available formula (* 5):
In formula (* 5), W (ti+1)-W(ti) formula (* 6) are represented by,
In formula (* 6), ε (ti) it is tiMoment standardized normal distribution stochastic variable generated (its mean value is 0, variance 1)；
Δ t is simulation step length.Formula (* 6) are substituted into formula (* 5), to obtain formula (* 3).It, can according to formula (* 3) in step 5 below
It is simulated with the indoor air temperature change procedure to room where kth platform air-conditioning, and then obtains the course of work of air-conditioning.
Simulation parameter: a length of T when emulation is arranged in step 4.s；Simulation step length is Δ t；Random simulation times are J；
Step 5. enables j=1；Jth time stochastic simulation is carried out to the air-conditioned course of work of institute in air-conditioning cluster:
Step 5.1. enables k=1；
Step 5.2. gives indicator variable IbeginAssign initial value 0；Give indicator variable IoverAssign initial value 0；
Wherein, IbeginIndicator variable whether assigning for the sign on of flexible control: value is 0 expression flexible control
Sign on is not assigned, and value is that the sign on of 1 expression flexible control has been assigned；IoverFor under the END instruction of flexible control
Up to whether indicator variable: value be 0 expression flexible control END instruction do not assign, value be 1 indicate flexible control knot
Shu Zhiling has been assigned；
Step 5.3. enables i=0；By θk(t0) and sk(t0) it is assigned to θ respectivelyk,j(ti) and sk,j(ti)；
Wherein, θk,j(ti) indicate that the sign on of the flexible control in jth time stochastic simulation is assigned before, kth platform air-conditioning institute
In room in tiThe Indoor Air temperature value at moment；sk,j(ti) indicate that the sign on of the flexible control in jth time stochastic simulation is assigned
Before, kth platform air-conditioning is in tiThe switch state at moment；
Step 5.4. judges ti=tSIt is whether true: if so, by θk,j(ti) and sk,j(ti) it is assigned to θ ' respectivelyk,j(ti)
With s 'k,j(ti), and enable indicator variable Ibegin=1, then execute step 5.5；Otherwise, step 5.5 is executed；
Wherein, θ 'k,j(ti) indicate that the sign on of the flexible control in jth time stochastic simulation is assigned after, kth platform air-conditioning
Place room is in tiThe Indoor Air temperature value at moment；s′k,j(ti) indicate in jth time stochastic simulation under the sign on of flexible control
After reaching, kth platform air-conditioning is in tiThe switch state at moment；
Step 5.5. judges ti=tEIt is whether true: if so, enable indicator variable Iover=1, then, execute step 5.6；
Otherwise, step 5.6 is executed；
Step 5.6. generates the t in jth time stochastic simulation using the methods of sampling of stochastic variableiThe standard normal at moment point
Cloth stochastic variable εj(ti)；
The method for generating standardized normal distribution stochastic variable usually has inverse transformation method, rejection method and relative risk method, in this reality
It applies in example and ε is generated using rejection methodj(ti).Specific algorithm can be with bibliography: Korn, R., Korn, E., Kroisandt, G.:
‘Monte Carlo Methods and Models in Finance and Insurance’(CRC Press,USA,2010)
p34-35.
Step 5.7. is by θk,j(ti) and sk,j(ti), using the numerical computation method of stochastic differential equation calculate jth time with
Before the sign on of flexible control is assigned in machine simulation, room is in t where kth platform air-conditioningi+1The Indoor Air temperature value θ at momentk,j
(ti+1)；
Based on the formula (* 3) gone out by Euler algorithmic derivation, θk,j(ti+1) calculated by formula (* 7):
Before step 5.8. is assigned by the sign on of formula (3) determining flexible control in jth time stochastic simulation, kth platform is empty
It adjusts in ti+1The switch state s at momentk,j(ti+1):
In formula (3), ti+1=ti+Δt；
Note: being the interior before the response of kth platform air-conditioning before the sign on of flexible control is assigned, used in formula (3)
Air temperature setpoint θset,k, unit is DEG C.
If step 5.9. Ibegin=1 and Iover=0 sets up, and executes step 5.10；Otherwise, step 5.12 is executed；
Ibegin=1 and Iover=0 illustrates that the sign on of flexible control has been assigned, but the END instruction of flexible control is not yet
It assigns.
Step 5.10. is by θ 'k,j(ti) and s 'k,j(ti), jth time is calculated using the numerical computation method of stochastic differential equation
After the sign on of flexible control is assigned in stochastic simulation, room is in t where kth platform air-conditioningi+1The Indoor Air temperature value θ ' at momentk,j
(ti+1)；
Based on the formula (* 3) gone out by Euler algorithmic derivation, θ 'k,j(ti+1) calculated by formula (* 8):
Step 5.11. by formula (4) determine flexible control in jth time stochastic simulation sign on assign after, kth platform air-conditioning
In ti+1The switch state s ' at momentk,j(ti+1):
In formula (4), ti+1=ti+Δt；
Note: being the interior after the response of kth platform air-conditioning after the sign on of flexible control is assigned, used in formula (4)
Air temperature setpoint θ 'set,k, unit is DEG C.
If step 5.12. ti+1-t0< TsIt sets up, after enabling i+1 be assigned to i, executes step 5.4；It is no to then follow the steps 5.13；
If step 5.13. k < K is set up, after enabling k+1 be assigned to k, step 5.2 is executed；It is no to then follow the steps 5.14；
Step 5.14. is calculated the response capacity of the air-conditioning flexible control in jth time stochastic simulation by formula (5)
Step 5.15. is calculated the response delay Δ t of the air-conditioning flexible control in jth time stochastic simulation by formula (6)d,j:
In formula (6),Expression is meetingTiMinimal instant is taken in set, i.e., it is empty
At the time of assembling group and begin to respond to.
If step 5.16. j < J is set up, after enabling j+1 be assigned to j, step 5.1 is executed；It is no to then follow the steps 6；
5.1~step 5.15 of above-mentioned steps is to carry out jth time stochastic simulation to the course of work of air-conditioning cluster, and calculate sky
The sample of flexible control response capacity and response delay is adjusted, specific flow chart is as shown in Figure 2.
In steps of 5, J sample of response capacity and response delay is obtained, by stochastic simulation to count in step 6
It calculates the characteristic statistics such as sample average, sample standard deviation and and then acquisition responds capacity and the estimation interval of response delay is established
Basis.
Step 6. withWith Δ td,j, j=1,2 ..., J are calculated as random sample by statistics
Obtain the prediction result of air-conditioning flexible control responding ability (including response capacity and response delay):
Step 6.1. calculates t by formula (7)iThe functions of sample means μ of time of day response capacityP(ti):
Step 6.2. calculates t by formula (8)iThe sample canonical difference function δ of time of day response capacityp(ti):
The functions of sample means μ of step 6.3. capacity according to responseP(ti) and sample canonical difference function δp(ti), obtain sky
Adjust the estimation interval [μ of flexible control response capacityP(ti)-δp(ti),μP(ti)+δp(ti)],ti∈[tS,tE]；
Step 6.4. is calculated the sample average of response delay by formula (9)
Step 6.5. is calculated the sample standard deviation of response delay by formula (10)
The sample average that step 6.6. is delayed according to responseAnd sample standard deviationObtain the zone of estimate of response delay
Between
Step 6 passes through to response capacity (its essence is a random processes) and response delay (its essence is a stochastic variables)
The statistics of sample calculates, and obtains sample average, sample standard deviation and the estimation interval of response capacity and response delay, embodies
Uncertainty caused by the random error of outside air temperature prediction can polymerize quotient for air conditioner load and provide more comprehensive letter
Breath provides reference frame to implement significantly more efficient demand response management to air conditioner load.
Claims (1)
1. a kind of air-conditioning flexible control responding ability prediction technique for considering outside air temperature prediction error, it is characterized in that by following step
It is rapid to carry out:
Step 1. obtains initial data, comprising: the initial time t that stochastic simulation starts0；The air-conditioning number of units that air-conditioning cluster is included
K；The thermal capacitance C in room where kth platform air-conditioningk, it is air-conditioning number that unit, which is kWh/ DEG C, k=1,2 ..., K,；Where kth platform air-conditioning
The thermal resistance R in roomk, unit be DEG C/kW；The rated power P of kth platform air-conditioningk, unit kW；The Energy Efficiency Ratio η of kth platform air-conditioningk；The
K platform air-conditioning carves t at the beginning0When switch state sk(t0): work as sk(t0) value be 1 when, indicate kth platform air-conditioning carve at the beginning
t0" booting ", works as sk(t0) value be 0 when, indicate kth platform air-conditioning carve t at the beginning0" shutdown "；Room where kth platform air-conditioning exists
Initial time t0When Indoor Air temperature value θk(t0), unit is DEG C；Air conditioner load polymerize quotient and assigns " flexible control to air-conditioning cluster
Sign on " at the time of tS；T at the time of air conditioner load polymerization quotient assigns " END instruction of flexible control " to air-conditioning clusterE；
Indoor air temperature setting value θ before the response of kth platform air-conditioningset,k, unit is DEG C；Indoor air temperature setting value after the response of kth platform air-conditioning
θ′set,k, unit is DEG C；The dead zone temperature θ of kth platform air-conditioning hysteresis controld,k, unit is DEG C；The outside air temperature predicted value of t momentUnit is DEG C；Outside air temperature predicts the proportionality constant q, 0 < q < 1 in error White Noise Model；
Step 2. establishes the White Noise Model of outside air temperature prediction error using formula (1):
In formula (1),For the outside air temperature prediction error value of t moment；{ X (t), 0≤t≤∞ } be mean value be zero, variance has
The white noise of limit；
The indoor air temperature variation in room where step 3. describes kth platform air-conditioning using stochastic differential equation shown in formula (2):
In formula (2), θk(t) in the Indoor Air temperature value of t moment, unit is DEG C in room where kth platform air-conditioning；skIt (t) is kth platform
Switch state of the air-conditioning in t moment: work as sk(t) when value is 1, indicate kth platform air-conditioning in t moment " booting "；Work as sk(t) value
When being 0, indicate kth platform air-conditioning in t moment " shutdown "；
Simulation parameter: a length of T when emulation is arranged in step 4.s；Simulation step length is Δ t；Random simulation times are J；
Step 5. enables j=1；Jth time stochastic simulation is carried out to the air-conditioned course of work of institute in air-conditioning cluster:
Step 5.1. enables k=1；
Step 5.2. gives indicator variable IbeginAssign initial value 0；Give indicator variable IoverAssign initial value 0；
Wherein, IbeginIndicator variable whether assigning for the sign on of flexible control: value is 0 beginning for indicating flexible control
Instruction is not assigned, and value is that the sign on of 1 expression flexible control has been assigned；IoverFor flexible control END instruction assign with
No indicator variable: value is that the END instruction of 0 expression flexible control is not assigned, and value is that the end of 1 expression flexible control refers to
Order has been assigned；
Step 5.3. enables i=0；By θk(t0) and sk(t0) it is assigned to θ respectivelyk,j(ti) and sk,j(ti)；
Wherein, θk,j(ti) indicate that the sign on of the flexible control in jth time stochastic simulation is assigned before, room where kth platform air-conditioning
Between in tiThe Indoor Air temperature value at moment；sk,j(ti) indicate that the sign on of the flexible control in jth time stochastic simulation is assigned before, the
K platform air-conditioning is in tiThe switch state at moment；
Step 5.4. judges ti=tSIt is whether true: if so, by θk,j(ti) and sk,j(ti) it is assigned to θ ' respectivelyk,j(ti) and
s′k,j(ti), and enable indicator variable Ibegin=1, then execute step 5.5；Otherwise, step 5.5 is executed；
Wherein, θ 'k,j(ti) indicate that the sign on of the flexible control in jth time stochastic simulation is assigned after, room where kth platform air-conditioning
Between in tiThe Indoor Air temperature value at moment；s′k,j(ti) indicate that the sign on of the flexible control in jth time stochastic simulation is assigned after,
Kth platform air-conditioning is in tiThe switch state at moment；
Step 5.5. judges ti=tEIt is whether true: if so, enable indicator variable Iover=1, then, execute step 5.6；Otherwise,
Execute step 5.6；
Step 5.6. generates the t in jth time stochastic simulation using the methods of sampling of stochastic variableiThe standardized normal distribution at moment with
Machine variable εj(ti)；
Step 5.7. is by θk,j(ti) and sk,j(ti), it is calculated using the numerical computation method of stochastic differential equation in the random mould of jth time
Before the sign on of flexible control is assigned in quasi-, room is in t where kth platform air-conditioningi+1The Indoor Air temperature value θ at momentk,j(ti+1)；
Before step 5.8. is assigned by the sign on of formula (3) determining flexible control in jth time stochastic simulation, kth platform air-conditioning exists
ti+1The switch state s at momentk,j(ti+1):
In formula (3), ti+1=ti+Δt；
If step 5.9. Ibegin=1 and Iover=0 sets up, and executes step 5.10；Otherwise, step 5.12 is executed；
Step 5.10. is by θ 'k,j(ti) and s 'k,j(ti), it is random that jth time is calculated using the numerical computation method of stochastic differential equation
After the sign on of flexible control is assigned in simulation, room is in t where kth platform air-conditioningi+1The Indoor Air temperature value θ ' at momentk,j
(ti+1)；
Step 5.11. by formula (4) determine flexible control in jth time stochastic simulation sign on assign after, kth platform air-conditioning exists
ti+1The switch state s ' at momentk,j(ti+1):
In formula (4), ti+1=ti+Δt；
If step 5.12. ti+1-t0< TsIt sets up, after enabling i+1 be assigned to i, executes step 5.4；It is no to then follow the steps 5.13；
If step 5.13. k < K is set up, after enabling k+1 be assigned to k, step 5.2 is executed；It is no to then follow the steps 5.14；
Step 5.14. is calculated the response capacity of the air-conditioning flexible control in jth time stochastic simulation by formula (5)
Step 5.15. is calculated the response delay Δ t of the air-conditioning flexible control in jth time stochastic simulation by formula (6)d,j:
If step 5.16. j < J is set up, after enabling j+1 be assigned to j, step 5.1 is executed；It is no to then follow the steps 6；
Step 6. withWith Δ td,j, j=1,2 ..., J are as random sample, by being calculated
The prediction result of air-conditioning flexible control responding ability:
Step 6.1. calculates t by formula (7)iThe functions of sample means μ of time of day response capacityP(ti):
Step 6.2. calculates t by formula (8)iThe sample canonical difference function δ of time of day response capacityp(ti):
The functions of sample means μ of step 6.3. capacity according to responseP(ti) and sample canonical difference function δp(ti), obtain air-conditioning flexibility
Estimation interval [the μ of control response capacityP(ti)-δp(ti),μP(ti)+δp(ti)],ti∈[tS,tE]；
Step 6.4. is calculated the sample average of response delay by formula (9)
Step 6.5. is calculated the sample standard deviation of response delay by formula (10)
The sample average that step 6.6. is delayed according to responseAnd sample standard deviationObtain the estimation interval of response delay
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810018982.5A CN108224692B (en) | 2018-01-09 | 2018-01-09 | Consider the air-conditioning flexible control responding ability prediction technique of outside air temperature prediction error |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810018982.5A CN108224692B (en) | 2018-01-09 | 2018-01-09 | Consider the air-conditioning flexible control responding ability prediction technique of outside air temperature prediction error |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| CN108224692A CN108224692A (en) | 2018-06-29 |
| CN108224692A8 CN108224692A8 (en) | 2018-11-23 |
| CN108224692B true CN108224692B (en) | 2019-11-08 |
Family
ID=62640400
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810018982.5A Active CN108224692B (en) | 2018-01-09 | 2018-01-09 | Consider the air-conditioning flexible control responding ability prediction technique of outside air temperature prediction error |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108224692B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109063925B (en) * | 2018-08-16 | 2021-08-17 | 合肥工业大学 | Optimized operation method for regional comprehensive energy system considering load aggregators |
| CN109827310B (en) * | 2019-01-31 | 2020-12-11 | 河海大学 | Resident air conditioner load cluster die type establishing method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1808002A (en) * | 2006-03-02 | 2006-07-26 | 游善宗 | Wind-energy water-energy storage and air conditioning integrated device |
| CN104134995A (en) * | 2014-07-08 | 2014-11-05 | 东南大学 | Method of air-conditioning load for participating in secondary frequency modulation of system based on energy storage model building |
| CN104214912A (en) * | 2014-09-24 | 2014-12-17 | 东南大学 | Aggregation air conditioning load scheduling method based on temperature set value adjustment |
| CN106846179A (en) * | 2017-03-15 | 2017-06-13 | 东南大学 | A kind of resident load bilayer method for optimizing scheduling based on non-cooperative game |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101676921B1 (en) * | 2014-11-12 | 2016-11-16 | 엘지전자 주식회사 | An air conditioning system and a method for controlling the same |
-
2018
- 2018-01-09 CN CN201810018982.5A patent/CN108224692B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1808002A (en) * | 2006-03-02 | 2006-07-26 | 游善宗 | Wind-energy water-energy storage and air conditioning integrated device |
| CN104134995A (en) * | 2014-07-08 | 2014-11-05 | 东南大学 | Method of air-conditioning load for participating in secondary frequency modulation of system based on energy storage model building |
| CN104214912A (en) * | 2014-09-24 | 2014-12-17 | 东南大学 | Aggregation air conditioning load scheduling method based on temperature set value adjustment |
| CN106846179A (en) * | 2017-03-15 | 2017-06-13 | 东南大学 | A kind of resident load bilayer method for optimizing scheduling based on non-cooperative game |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108224692A (en) | 2018-06-29 |
| CN108224692A8 (en) | 2018-11-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104698843B (en) | A kind of data center's energy-saving control method based on Model Predictive Control | |
| CN109799851B (en) | User side load response method based on load cluster temperature regulation and control | |
| CN106949598B (en) | Network center's machine room energy-saving optimization method when network traffic load changes | |
| CN103513632B (en) | Energy management system | |
| CN110864414A (en) | Air conditioner power utilization load intelligent control scheduling method based on big data analysis | |
| CN105042800A (en) | Variable-frequency air conditioner load modeling and operation controlling method based on demand responses | |
| Li et al. | Reinforcement learning of room temperature set-point of thermal storage air-conditioning system with demand response | |
| CN108036468B (en) | Aggregation control method for air conditioning system | |
| CN107781947A (en) | A kind of air conditioning system Cooling and Heat Source forecast Control Algorithm and device | |
| CN107276069A (en) | Approximate the polymerization modeling method and system of a kind of area power grid resident temperature control load | |
| CN105322550B (en) | A kind of optimization method of household micro-capacitance sensor operation | |
| WO2023160110A1 (en) | System frequency modulation method and system for thermostatically controlled load cluster, and electronic device and storage medium | |
| CN101782261A (en) | Nonlinear self-adapting energy-saving control method for heating ventilation air-conditioning system | |
| Liao et al. | Robustness enhancement for chiller sequencing control under uncertainty | |
| CN108224692B (en) | Consider the air-conditioning flexible control responding ability prediction technique of outside air temperature prediction error | |
| CN113991655A (en) | Method, device and medium for evaluating load aggregation demand response potential of fixed-frequency air conditioner | |
| CN105159085A (en) | real time parameter identification method of air-conditioning belonged building second order equivalent thermal parameter model | |
| CN105937823B (en) | A kind of earth source heat pump control method and system | |
| Dong | Non-linear optimal controller design for building HVAC systems | |
| Ju et al. | Hierarchical control of air-conditioning loads for flexible demand response in the short term | |
| Zhang et al. | Research on scheduling control strategy of large-scale air conditioners based on electric spring | |
| Li et al. | Control method of multi-energy system based on layered control architecture | |
| Li et al. | Dynamic room temperature setpoints of air-conditioning demand response based on heat balance equations with thermal comfort model as constraint: On-site experiment and simulation | |
| Zhou et al. | Study on PID parameters tuning based on particle swarm optimization | |
| CN108122067B (en) | Modeling method and system for building demand response dynamic process |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CI02 | Correction of invention patent application |
Correction item: Third applicant Correct: State Grid Jiangsu Electric Power Co., Ltd. False: STATE GRID JIANGSU ELECTRIC POWER COMPANY Number: 26-02 Page: The title page Volume: 34 False: STATE GRID JIANGSU ELECTRIC POWER COMPANY |
|
| CI02 | Correction of invention patent application | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |