CN108227489A - A kind of load participates in the double-deck control method of demand response - Google Patents
A kind of load participates in the double-deck control method of demand response Download PDFInfo
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
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Abstract
The present invention discloses the double-deck control method that a kind of load participates in demand response, includes the following steps：Step 1, the aggregate response potential value of different load agent institute compass of competency load is collected by control centre, and gives different load agents according to potential value proportional assignment power shortage amount；Step 2, each load agent receives the demand response amount that control centre issues, and considers various factors, further establishes the response condition that Optimized model determines each family's load.Such control method can cope with the situation that emergency high power vacancy occurs in power grid.
Description
Technical field
The invention belongs to electricity needs response technology field, more particularly to a kind of load participates in the double-deck control of demand response
Method and technology.
Background technology
In recent years, permeability of the renewable energy power generation in power grid is higher and higher, and line transmission capacity is increasing, this
So that power grid is more prone to urgent power shortage occur, very big threat is caused to mains frequency stable operation.With intelligent end
The access of end equipment, the development of power system telecommunications technology and the advanced construction for measuring framework, resident load is from traditional sense
On the physical terminal that passively controls be transformed into the schedulable resource with active response ability.Utilize this active response of load
Ability can reduce or even avoid the situation of the urgent cutting load of power grid.
About active load curtailment strategy classification there are mainly two types of：One kind is by control framework point, including centralized Control
Strategy, distributed AC servo system strategy and hybrid control strategy；Also one kind is that temporally scale divides, including primary frequency modulation scale
(second grade), frequency modulation frequency modulation scale (minute grade) and three times frequency modulation scale (grade for 24 hours).Although grinding about load curtailment strategy at present
Study carefully very much, but most control methods do not account for the time-varying response potentiality of family's load, consider different home load comprehensively
The constraints such as dynamic operational behaviour, response times, response time accurate load responding strategy it is even more fewer and fewer.
Therefore, it based on load group's variable response potentiality calculated value, proposes a kind of double-deck control method, can fully excavate negative
There is great guidance to anticipate for the aggregate response potentiality of lotus, the strategy that is precisely controlled for participating in the response of electric network active vacancy to formulating load
Justice.
Invention content
The purpose of the present invention is to provide the double-deck control method that a kind of load participates in demand response, can cope with power grid
There is the situation of emergency high power vacancy.
In order to achieve the above objectives, solution of the invention is：
A kind of load participates in the double-deck control method of demand response, includes the following steps：
Step 1, the aggregate response potential value of different load agent institute compass of competency load, and foundation are collected by control centre
Potential value proportional assignment power shortage amount gives different load agents；
Step 2, each load agent receives the demand response amount that control centre issues, and considers various factors, into
One step establishes the response condition that Optimized model determines each family's load.
The detailed content of above-mentioned steps 1 is：Load agent collect information on load, according to the polymerization property of intelligent load with
And the electric network active vacancy time, the equivalent response energy that can be provided at current time of load group of its management is sent to control centre
Power ρ；Then, load agent assigns on the finger of cutting load amount according to the agential equivalent responding ability of each load in control centre
It enables.
The calculation formula of instruction that cutting load amount is assigned to i-th of load agent by above-mentioned control centre is：
Wherein, Δ Pi--- i-th of load agent's load responding amount；Δ P --- electric network active vacancy amount；ρi--- i-th
A equivalent responding ability of load agent；M --- load agent's quantity.
In above-mentioned steps 2, the factor considered includes load responding cost, active balance, user response number and sound
Between seasonable.
In above-mentioned steps 2, cost minimization Optimized model is established, object function is：
Wherein, a --- participate in the compensation of demand response；Si--- the response shape of a certain lower i-th air-conditioning of load agent
State；Sj--- the responsive state of jth platform water heater under a certain load agent；Sk--- kth is electronic under a certain load agent
The responsive state of automobile；PAC,i--- the responding power of i-th air-conditioning；PWH,j--- the responding power of jth platform water heater；
PEV,k--- the responding power of kth electric vehicle；IAC,i--- i-th air-conditioning comfort value after normalization；IWH,j--- normalization
Jth platform water heater comfort value afterwards；IEV,k--- kth electric vehicle comfort value after normalization；n1--- air-conditioning quantity；n2——
Water heater quantity；n3--- electric vehicle quantity；
Constraints is as follows：
1) intelligent load meets power shortage
In formula, Δ Pi--- i-th of load agent's load responding amount；PAg,i--- it is intelligently born under i-th of load agent
The responding power that lotus provides；
2) response times constrain
0≤N≤2
In formula, N --- response times
3) response time constrains
t≤tr
In formula, tr--- load can response time.
After using the above scheme, the present invention is realized by load agent, is included the following steps：Step 1) control centre receives
Collect the aggregate response potential value of different load agent institute compass of competency load, and power shortage is divided in portion according to potential value
It measures to different load agents；Each load agent of step 2) receives the demand response amount that control centre issues, and synthesis is examined
Consider the factors such as load responding cost, active balance, user response number, response time, further establish Optimized model and determine often
The response condition of one family load.
Compared with prior art, double-deck control method provided by the invention, Layer assignment is to close to ring based on load clustering thereon
The proportional assignment strategy of potentiality is answered, the potentiality of different load agent compass of competency load can be maximally utilised；Under
In layer load responding strategy, consider the factors such as load responding cost, active balance, user response number, response time, build
Vertical Optimized model determines the accurate response condition of each family's load.The present invention can accurately cope with power grid emergency high power
Vacancy situation under the premise of various response constraints and users'comfort is met, minimizes power grid and intelligent load is participated in needing
The cost of compensation of response is sought, so as to farthest using the flexibility of intelligent load start and stop, fully excavate intelligent load group's
Responding ability.
Description of the drawings
Fig. 1 is the dual-layer optimization control strategy flow chart of the present invention；
Fig. 2 is that control effect compares figure under Different Strategies of the invention；
Fig. 3 is response condition definition graph of 10 electric vehicles of the present invention in 15min；
Specific embodiment
Below with reference to attached drawing, technical scheme of the present invention and advantageous effect are described in detail.
1st, all kinds of intelligent load responding models
According to existing literature, the input and output object of this three classes wired home load of air-conditioning, water heater and electric vehicle is established
Model is managed, and provides corresponding comfort level characterizing method, its quick reply power shortage aggregate response ability provides for follow-up study
Foundation.
1.1 intelligent load operation models
1.1.1 operation of air conditioner model
Under refrigeration mode, air-conditioning physical model, that is, output variable t periods room temperature such as following formula (1-1)：
Wherein, TAC,t+1--- t+1 period room temperatures；TAC,t--- t period room temperatures；Gt--- t period indoor and outdoor heat exchange values；
Δ c --- indoor temperature coefficient, i.e. room temperature often increases by 1 DEG C of institute's calorific requirement；CAC--- air-conditioning thermal capacity under refrigeration mode；Δ
T --- period interval；SAC,t--- t period running state of air conditioner.
After carrying out linearization process to above-mentioned variable, air-conditioning physical model represents such as following formula (1-2)：
TAC,t+1=TAC,t+0.4-0.8SAC,t (1-2)
Work as SAC,tWhen=1, TAC,t+1=TAC,t-0.4；Work as SAC,tWhen=0, TAC,t+1=TAC,t+0.4。
1.1.2 water heater moving model
Under heating mode, water heater physical model, that is, output variable t period water heater temperatures calculation formula such as following formula (1-3)
It is shown：
Wherein, TWH,t+1--- t+1 period water heater temperatures；TWH,t--- t period water temperatures；Tin--- in injection water heater
Cold water water temperature；flt--- t period hot water flows；VWH--- water heater volume；α --- water heater heating temperature coefficient, i.e. volume
Determine the increasing water temperature in the heating power lower water-heater unit interval；pWH,t--- water heater power；ξ --- hot water cooling system
Number, i.e., in the room temperature lower water-heater internal hot-water unit interval from cooling temperature reduced value.
After carrying out linearization process to above-mentioned variable, water heater physical model represents such as following formula (1-4)：
TWH,t+1=TWH,t+α·pWH,t- ζ=TWH,t+0.1×pWH,t-ζ (1-4)
When water heater normal use, ζ1=1/60；When water heater is stopped, ζ2=1.
1.1.3 electric vehicle moving model
Under charge mode, electric vehicle physical model, that is, output variable t period electric vehicle SOC value calculation formula such as formula
Shown in (1-5)：
In formula, SOC0--- 0 period batteries of electric automobile residual capacity；SOCi--- i period batteries of electric automobile residue is held
Amount.
Above-mentioned variable is handled, electric vehicle model represents following formula (1-6)：
SOCi=SOCi-1+3.5/Cbatt (1-6)
1.2 load comfort levels characterize
The factor for influencing thermic load (air-conditioning, water heater) comfort level includes temperature, humidity, air velocity etc., in research heat
During load comfort level, the influence for considering temperature to users'comfort will focus on；It is this kind of comfortable with user's body-sensing for electric vehicle
Degree is without more strongly connected load, then main to consider charging SOC value, i.e. battery charge is higher, and users'comfort is stronger.Three classes
Shown in the comfort level index such as following formula (1-7) of load：
In formula, TAC--- air-conditioning Current Temperatures；Tc,AC--- air-conditioning optimum temperature；ΔTAC--- air-conditioning comfort temperature section
Length；TWH--- water heater Current Temperatures；Tc,WH--- water heater optimum temperature；ΔTWH--- water heater comfort temperature section is long
Degree；SEV--- batteries of electric automobile state-of-charge.
2nd, capability evaluation is closed in intelligent load clustering
The response capacity and response time that intelligent load can be provided are by load operating region, user's plan of travel, response
The response polymerization model of load group is established in the influences such as principle on the basis of comfort level, user response principle etc. is considered below, to ginseng
It is modeled and is assessed with the responding ability of the resident intelligence load group of demand response.
2.1 load responding polymerization models
The purpose for establishing polymerization model is to study the response that the intelligent load group controlled based on direct load can be provided
Ability, the model need the constraint for considering comfort degree, meeting response times and response time, particularly electric vehicle,
It needs utmostly to ensure user's plan of travel, charge target can be completed within the corresponding time.Consider above-mentioned factor, polymerize
Shown in the mathematical description of model such as formula (2-1)：
Wherein, tf--- the intelligent load forced response time in the case of active vacancy is taken as 0min under initial situation；
n1--- air-conditioning quantity；PAC,i--- the responding power of i-th air-conditioning；n2--- water heater quantity；PWH,j--- jth platform hot water
The responding power of device；n3--- electric vehicle quantity；PEV,k--- the responding power of kth electric vehicle；Si(t) --- i-th
Air-conditioning state；Sj(t) --- jth platform water heater state；Sk(t) --- kth platform electronic vehicle attitude.
Shown in the calculation formula of air-conditioning state such as formula (2-2)：
Shown in the calculation formula of water heater state such as formula (2-3)：
Shown in the calculation formula of electronic vehicle attitude such as formula (2-4)：
Wherein, W=t | S (t-1)-S (t)>0}；ZAC--- between climate controlled comfort zone；ZWH--- the comfortable section of water heater；
ZEV--- the comfortable section of electric vehicle；IAC,i--- i-th air-conditioning comfort value；IWH,j--- jth platform water heater comfort value；
IEV,k--- kth electric vehicle comfort value；N --- response times；T --- simulation time；tEV,k--- kth electric vehicle
It can response time.It is worth noting that, comfortable section is negotiated to determine by user and load agent, the factors shadows such as electricity price are considered
It rings, the acceptable comfortable section of user can accordingly change in different periods.
2.2 load responding polymerizing powers are assessed
For responding ability of the qualitative assessment intelligence load group within certain a period of time, it is set forth below and is born using in the period
The equivalent responding power ρ of lotus group characterizes the aggregate response ability of this period, and formula is such as shown in (2-5)：
Wherein, ρi--- the equivalent responding powers of load agent i；Δ t --- the active vacancy time；Pi--- load group is real
When aggregate power；te--- initial time；ts--- terminate the time.
3rd, double-deck control strategy
3.1 upper strata response quautity allocation strategies
First, load agent collects information on load, during according to the polymerization property of intelligent load and electric network active vacancy
Between, the equivalent responding ability ρ that can be provided at current time of load group of its management is sent to control centre.Then, in control
The heart assigns load agent the instruction of cutting load amount, calculation formula is such as according to the agential equivalent responding ability of each load
Under：
Wherein, Δ Pi--- i-th of load agent's load responding amount；Δ P --- electric network active vacancy amount；ρi--- i-th
A equivalent responding ability of load agent；M --- load agent's quantity.
3.2 lower floor's load responding strategies
Upper strata allocation strategy focuses on the supporting role to network re-active power, and lower floor's allocation strategy is then concerned about how to distribute
So that the cost of compensation that power grid is paid is minimum.Therefore, it during lower Layer assignment, needs to establish cost minimization Optimized model, target letter
Number and constraints are shown below：
Wherein, a --- participate in the compensation of demand response；Si--- the response shape of a certain lower i-th air-conditioning of load agent
State；Sj--- the responsive state of jth platform water heater under a certain load agent；Sk--- kth is electronic under a certain load agent
The responsive state of automobile；PAC,i--- the responding power of i-th air-conditioning；PWH,j--- the responding power of jth platform water heater；
PEV,k--- the responding power of kth electric vehicle；IAC,i--- i-th air-conditioning comfort value (after normalization)；IWH,j--- jth
Platform water heater comfort value (after normalization)；IEV,k--- kth electric vehicle comfort value (after normalization)；n1--- air-conditioning quantity；
n2--- water heater quantity；n3--- electric vehicle quantity.
Constraints is as follows：
1) intelligent load meets power shortage
In formula, Δ Pi--- i-th of load agent's load responding amount；PAg,i--- it is intelligently born under i-th of load agent
The responding power that lotus provides；
2) response times constrain
0≤N≤2 (3-4)
In formula, N --- response times
3) response time constrains
t≤tr (3-5)
In formula, tr--- load can response time.
Formula (3-2)~(3-5) is constituted to be assisted by the intelligent load inside each load agent of object function of cost
Optimized model is adjusted, belongs to 01 integer programming problem, can be solved using CPLEX12.6.
Assuming that there is 10 load agents, the load structure that each agent is administered is as shown in table 1.Wherein, load group #
Each type load accounting is different in 1~3 but other factors are the same；Change response principle in load group #4~6 but keep other factors
Equally；Change load initial operating state in load group #7~9 but keep other factors the same.
1 different load group load structure situation of table
It is now assumed that occurring the power shortage of 3M in power grid, the duration of the failure is 15min, 10 within the period
Agential aggregate response potential value is as shown in table 2, and each agent under the power scene is calculated according to formula (3-1)
Load responding amount, this is also the result of upper Layer assignment.
Aggregate response performance number (the unit of 2 10 load groups of table：kW)
In lower Layer assignment, Precise control is carried out for the load managed under each agent, is accurate to each
Family's load is in interior response condition per minute.The effect of control strategy is as shown in Figure 2.
In fig. 2, dual-layer optimization control strategy realizes the response demand of 3M loads substantially, and error only has 0.2%；And it adopts
19% is up to the control strategy error of mean allocation.This is because in mean allocation control strategy, each load agent
300kW is all responded, and it is different that each agent can respond capacity within the period in actual conditions, using mean allocation
Method can not excavate the response potentiality of family's load to the maximum extent.For example, No.8 agent's peak response power only has
95.7kW, it is clear that the demand of 300kW cannot be provided.
Further verification lower floor strategy validity.Fig. 3 gives 10 electric vehicles administered under No.1 agent
Response condition in 15min.Table 3 be this 10 electric vehicles initial charge situation (start of charge, SOC) and
Charging time constrains.
The initial charge situation of 3 10 electric vehicles of table and response time
As shown in Table 3, the initial SOC value of No.4 electric vehicles is very high, this illustrates that it can ring always in this 15min
Should, but from the point of view of the response time, it can only respond 3min.From figure 3, it can be seen that No.4 electric vehicles are only rung in preceding 3min
Should, behind do not have responding ability.For another example, No.5 and No.7 electric vehicles are just begun to respond in 9min, this is because
Its initial SOC value is too low, does not have responding ability.It can be seen that load proposed by the present invention participates in the bilayer of demand response
Control method can not only maximally utilise the potentiality of different load agent compass of competency load, while can also integrate and examine
Consider the factors such as load responding cost, active balance, user response number, response time, determine the accurate of each family's load
Response condition.
Above example is merely illustrative of the invention's technical idea, it is impossible to protection scope of the present invention is limited with this, it is every
According to technological thought proposed by the present invention, any change done on the basis of technical solution each falls within the scope of the present invention
Within.
Claims (5)
1. a kind of load participates in the double-deck control method of demand response, it is characterised in that includes the following steps：
Step 1, the aggregate response potential value of different load agent institute compass of competency load is collected by control centre, and according to potentiality
Value proportional assignment power shortage amount gives different load agents；
Step 2, each load agent receives the demand response amount that control centre issues, and considers various factors, further
Establish the response condition that Optimized model determines each family's load.
2. a kind of load as described in claim 1 participates in the double-deck control method of demand response, it is characterised in that：The step
1 detailed content is：Load agent collects information on load, during according to the polymerization property of intelligent load and electric network active vacancy
Between, the equivalent responding ability ρ that can be provided at current time of load group of its management is sent to control centre；Then, in control
The heart assigns load agent the instruction of cutting load amount according to the agential equivalent responding ability of each load.
3. a kind of load as claimed in claim 2 participates in the double-deck control method of demand response, it is characterised in that：The control
The calculation formula of instruction that cutting load amount is assigned in center to i-th of load agent is：
Wherein, Δ Pi--- i-th of load agent's load responding amount；Δ P --- electric network active vacancy amount；ρi--- i-th is negative
The equivalent responding ability of lotus agent；M --- load agent's quantity.
4. a kind of load as described in claim 1 participates in the double-deck control method of demand response, it is characterised in that：The step
In 2, the factor considered includes load responding cost, active balance, user response number and response time.
5. a kind of load as described in claim 1 participates in the double-deck control method of demand response, it is characterised in that：The step
In 2, cost minimization Optimized model is established, object function is：
Wherein, a --- participate in the compensation of demand response；Si--- the responsive state of a certain lower i-th air-conditioning of load agent；
Sj--- the responsive state of jth platform water heater under a certain load agent；Sk--- the electronic vapour of kth under a certain load agent
The responsive state of vehicle；PAC,i--- the responding power of i-th air-conditioning；PWH,j--- the responding power of jth platform water heater；
PEV,k--- the responding power of kth electric vehicle；IAC,i--- i-th air-conditioning comfort value after normalization；IWH,j--- normalization
Jth platform water heater comfort value afterwards；IEV,k--- kth electric vehicle comfort value after normalization；n1--- air-conditioning quantity；n2——
Water heater quantity；n3--- electric vehicle quantity；
Constraints is as follows：
1) intelligent load meets power shortage
α·ΔPi≤PAg,i≤β·ΔPi
In formula, Δ Pi--- i-th of load agent's load responding amount；PAg,i--- intelligent load carries under i-th of load agent
The responding power of confession；
2) response times constrain
0≤N≤2
In formula, N --- response times
3) response time constrains
t≤tr
In formula, tr--- load can response time.
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