CN107612041A - One kind consideration is probabilistic to be based on the automatic demand response method of event driven micro-capacitance sensor - Google Patents
One kind consideration is probabilistic to be based on the automatic demand response method of event driven micro-capacitance sensor Download PDFInfo
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Abstract
One kind consideration is probabilistic to be based on the automatic demand response method of event driven micro-capacitance sensor, and the continuous time is carried out into sliding-model control；Analyze the workload demand response characteristic of residents micro-capacitance sensor, constructing system model；Then a kind of combination Spot Price RTP and tou power price IBR new Spot Price mechanism is constructed, the electricity price of current k periods is calculated by Price Mechanisms；And using the automatic demand response ADR strategies based on event-driven mechanism, judge whether each event triggers by system, according to default priority processing event, the terminal user in RMG is carried out online energy-optimised.After the completion of optimization, the optimization time is advanced to next moment, Optimization Steps before repeating, until all the period of time optimization is completed.The present invention effectively guides the electricity consumption behavior of active load with economic incentives, can efficiently handle emergency situations in time；It can also be slowed down by the electricity consumption behavior of correct guidance active load and fluctuation is gone out to caused by system as new energy impact.
Description
Technical field
The invention belongs to home energy source local area network management field, and in particular to one kind consideration is probabilistic to be based on event
The automatic demand response method of micro-capacitance sensor of driving.
Background technology
Under the promotion of global energy structural adjustment, new energy and DSM are developed rapidly.Future
Intelligent building will introduce regenerative resource, energy-storage system and intelligent controllable burden, particularly electric automobile extensively with smart home
(EV), how new energy is efficiently utilized, realizes that the autonomous equilibrium of supply and demand inside intelligent building becomes one now under study for action
Important topic.
Because the energy resource consumption in building accounts for nearly the 40% of global total energy, the energy of residents micro-capacitance sensor (RMG) in recent years
Amount control becomes study hotspot.In RMG, the electricity consumption behavior of each user relative to business microgrid or industrial microgrid more with
Machine, user power utilization behavior is set not possess predictability.On the other hand, continuing to increase with regenerative resource ratio, its with
Machine, intermittence are by as one of urgent problems highly necessary solved of RMG.To coordinate the consumer behavior of all participants to improve supply and demand
Balance and solve RMG uncertainty, the effective automatic demand response of micro-capacitance sensor is most important to reaching above target.Need
Efficient method is proposed, micro-capacitance sensor is carried out entirely autonomous control to load in demand response, while to electronic vapour
Car participates in power network regulation and carries out operation control, to improve the economy of micro-capacitance sensor.
The content of the invention
In order to overcome existing micro-capacitance sensor control mode to meeting, can not to carry out entirely autonomous control, economy poor
Deficiency, the present invention propose it is a kind of consider it is probabilistic be based on the automatic demand response method of event driven micro-capacitance sensor, this
Method is directed to the randomness of the electricity consumption behavior of user, and honourable output prediction has the problems such as error, builds residents micro-capacitance sensor
(RMG) model, with reference to Spot Price (RTP) and tou power price (IBR) mechanism, propose that one kind is based on microgrid broad sense net load
New Price Mechanisms, calculate the electricity consumption behavior that new electricity price effectively guides active load with economic incentives, and drive based on event
Dynamic to propose new type auto demand response strategy, the strategy can not only efficiently handle all kinds of living electric apparatus access electricity consumptions in time
When the emergency situations that are likely to occur；It can also be slowed down by the electricity consumption behavior of correct guidance active load and fluctuation is gone out by new energy
The impact to caused by system.
To achieve these goals, the technical scheme is that：
One kind consideration is probabilistic to be based on the automatic demand response method of event driven micro-capacitance sensor, comprises the following steps：
S1：System initialization, the continuous time is subjected to sliding-model control, the optimization period is divided into J period, each
A length of Δ t during the period, for any kth time period, there is k={ k0,k0+ 1 ..., K }, wherein, k0Current sampling point is represented, K is represented
Last sampled point, and K≤J；Initial samples point k0=1；
S2：The workload demand response characteristic of comprehensive analysis residents micro-capacitance sensor, constructing system model；
S3：Construction is a kind of to combine Spot Price (RTP) and the Spot Price mechanism of tou power price (IBR), passes through electricity price machine
The electricity price of current k periods is calculated in system；
S4：Using a kind of automatic demand response (Event-driven ADR) strategy based on event-driven mechanism, by being
System judges whether each event triggers, and according to default priority processing event；
S5：After detecting event triggering, event is handled according to Event Priority, the terminal user in RMG is carried out online
It is energy-optimised；
S6：After the completion of optimization, the optimization time is advanced to subsequent time, k=k0+ 1, repeat step S2~S6, until full-time
Duan Youhua is completed.
Further, it is power supply unit that residents micro-capacitance sensor is made up of blower fan with photovoltaic array, electronic in the step S2
Controllable power unit that automobile (EV) combines with deferrable load, key control unit, this 4 part of energy-storage system (ESS) are formed：
Power supply unit, in view of single photovoltaic exports very little, in general photovoltaic generation unit is by a large amount of photovoltaic cell strings
The photovoltaic array that parallel connection is formed, while wind energy is directly proportional to the cube of wind speed, therefore, the conversion of weather can be serious in one day
Influence scene to contribute, be the mainly uncertain source of regenerative resource (RESs).
Controllable power unit, i.e., by EV, time it is adjustable/power adjustable load forms.
Core controls power supply, i.e., local control (Local control, LC).LC can provide for the program each asked
Power consumption predicts, and it is expected that in the near future power consumption can be adjusted by changing its behavior, while keep servicing.
ESS, it is regarded as special EV.
Further, the processing procedure of the step S2 is as follows：
S21：EV is modeled
If the vehicle collection of micro-grid system access is combined into N, then vehicle scale isThe main use of electric automobile
Way is the trip requirements for meeting user, and according to the driving feature of user, the situation of each vehicle is different, for any vehicle l
∈ N, its relevant parameter are：
Vl=[Tin,l,Tout,l,S0,l,SE,l,Qs,l,Pc,l,Pd,l] (1)
In formula, Tin,l、Tout,lThe time of vehicle l access micro-capacitance sensors and expected time departure are represented respectively；S0,l、SE,lPoint
Not Biao Shi power cell of vehicle starting state-of-charge (State of Charge, SOC) and expectation when leaving micro-capacitance sensor
SOC, SOC represent battery remaining power and the ratio of battery capacity, therefore have 0≤S0,l≤1、 0≤SE,l≤1；Qs,lRepresent electricity
Tankage；Pc,l、Pd,lSpecified charge and discharge power is represented respectively.
Assuming that the EV electrokinetic cells for participating in scheduling are lithium battery.According to the discharge and recharge correlation properties of lithium battery, it is appropriate to make
Simplify, within the single period, regard lithium battery as invariable power discharge and recharge.Ignore the influence of self-discharge rate, electrokinetic cell discharge and recharge
Power Pl(k) it is considered as and inputs：
In formula, Pl CH(k)、Pl DCH(k) absolute value of the charging and discharging power of vehicle l kth time periods is represented respectively.Establish
Electrokinetic cell SOC discrete state equations：
In formula, Sl(k+1)、Sl(k) represent vehicle in kth+1, the state-of-charge of k periods respectively.Formula (3) is transformed into square
Formation formula, while wushu (2) is substituted into formula (3), is obtainedWherein input matrixFeedforward matrix is Dl=[- 1 1].
S.22 energy-storage system models
The EV of access system is load and DER condensate, similar, energy storage battery can be considered all the period of time access,
One kind " special electric automobile " without charging workload demand.Analogy EV electrokinetic cell model Chinese styles (2), formula (3), establish electric power storage
Pool model.
S.23 load model is unified
The intelligent load of resident can be divided into as follows according to its different electrical characteristics and running statuses：
Can not Load adjustment (Non-shiftable loads, NSLs)：The type load connects smart jack, meets distribution
It is predictable, but can not control it, such as room lighting, TV, telephone set, whether normal operation is related to user for it
Primary demand whether can normally meet；
Adjustable load (Plannable loads, PLs)：The working hour of the type load or operation power exist certain
Scope, further can be transferable negative for time transferable load (time-plannable loads, TLs) and power by PLs points
Lotus (power-plannable loads, PLs), the type load that TLs refers to working time schedulable, operation power is fixed, such as
Washing machine, dish-washing machine etc.；PLs refers to the working time and runs the type load that power can be scheduled according to optimization demand, such as
Water heater etc..
Classify based on more than, CLs and PLs operation power time series can be formulated according to optimization demand, on the other hand,
With reference to NSLs, the daily load amplitude and trend in the microgrid region can be predicted.
The various load of quantity in micro-grid system is treated with a certain discrimination, can cause occur poor flexibility in scheduling process,
Therefore, for convenience of analyzing, unified load model is established, each type load that each connection networks is summarized as possessing consistent attribute
Unified physics model is described, and different features is shown by the difference of each attribute value.
The feature of j-th of intelligent load of i-th of family is described as follows：
In formula,Represent all family's set of the microgrid；Represent all of i-th family
Conventional load number；Represent all load aggregations of i-th of family；A is represented respectivelyi,jSpecified electric power and power-adjustable scope；Represent device Ai,jIt is expected Operational Zone
Between；Represent Ai,jTime regulatable scope；Qi,jRepresent power demand.
Respectively transferable time, transferable power, for embodying different load characteristics, so as to carry out phase
The coordination division of labor answered, the flag bit of each type load are set as shown in table 1.
Table 1
The unified load characteristic model described according to above formula (4), to k period electric powersIt is described as follows：
In formula,Load A is represented respectivelyi,jCan as time adjustable type and power in kth time period
The electric power of tune type.
In formula, Li,j(k+1)、Li,j(k) load A is represented respectivelyi,jIn kth+1, the power consumption of k periods, formula (5) is turned
Become matrix form, while wushu (6) is substituted into formula (5), is obtainedIts
Middle input matrix isFeedforward matrix is Dl=[- 1 1].
Electricity consumption behavior restraint：
In formula, [u]+Represent max { 0, u }；Represent that j-th of intelligent load of i-th of family meets
The specified run time of its power demand
ForAbove-mentioned formula can determine its all effective scheduling strategy, define possible strategy space：
In formula,The operation plan of all loads is represented, only meets x ∈ χ, load scheduling plan
X just comes into force.Formula (11) represents load Ai,jElectric power operation plan.
Further, in the step S3, relative to static tou power price, a distinguishing feature of new Spot Price
It is that dynamic updates, relation between supply and demand can be reflected in real time；In addition, Spot Price in reaction system dynamic relation between supply and demand and
There is more preferable flexibility in terms of guiding user power utilization behavior.
S31：New Spot Price mechanism is based on total load information and new energy output power calculation, for micro-capacitance sensor area
Each load and EV cluster in domain.Work as Ai,jOr VlWhen triggering access events, the broad sense net load of the microgrid is represented by：
In formula,Represent load Ai,jDuring access, the completed load aggregation of electricity consumption plan；NlRepresent that vehicle l connects
It is fashionable, the completed vehicle cluster of discharge and recharge plan.PPV(k)、PWT(k) k period energy storage battery charge and discharges are represented respectively
Electrical power, photovoltaic, blower fan are contributed.
S32：Spot Price mechanism based on total load information
In formula,Represent load Ai,jOr vehicle VlDuring access, the Spot Price of k periods； It is Spot Price regulation coefficient；priR,j、φR,jRepresent to refer to electricity price and reference load value respectively；Correspondingly,Prediction total load is represented, whereinRepresent base load predicted value.
S33：The setting of IBR prices, IBR are formulated based on current total load information, and the IBR of k periods represents as follows：
In formula,Represent the IBR prices of k periods；Represent the specific load consumption of k periods
Threshold value；ak、bk、ckRepresent the IBR price values of specific k periods.
With reference to above-mentioned Spot Price mechanism and IBR motor mechanism, a kind of new Spot Price is obtained：
In formula, ζ1、ζ2The price multiplying power under different brackets is represented, and has ζ1,ζ2＞ 1, ζ2＞ ζ1.In any k periods, haveWherein, t1、t2Represent the boundary multiplying power under different brackets, and t1, t2>0、t2＞
t1, when the total load amount of k periodsIt is bigger,It is smaller.New Spot Price schematic diagram of mechanism is as shown in Figure 1.
WhenWhen can obtain：
Similarly, can obtainWithDerivative under situation is not less than 0.It can be seen that generally newly
Type Spot Price and being proportionate property of current loads level, it is association electric automobile interaction power, load electricity consumption plan and new energy
The medium that source is contributed.In addition, new Spot Price is individually set for single electric automobile or load, each vehicle and set
Apply (appliance) and enjoy its privately owned new Spot Price, conveniently become more meticulous and implement electric automobile discharge and recharge scheduling and set
Dispatched using electricity.
In the step S4, to realize that RMG systems should keep the equilibrium of supply and demand to make the minimum target of operating cost again,
Invention proposes a kind of EDAR strategies.
S41：For the uncertainty of Demand-side and supply side, different driving signal is controlled by event-driven mechanism, made
Go out corresponding electricity consumption planned dispatching；Based on above-mentioned new Spot Price optimization Demand-side resource power usage plan, make part throttle characteristics more
Generation of electricity by new energy curve is matched, so as to improve regenerative resource grid connection efficiency, reduces the purchase of electricity to power network and the configuration of energy storage
Demand, reach the purpose of lifting micro-capacitance sensor whole economic efficiency.
EADR business needs the coordinated of different field main body, and demand response in micro-capacitance sensor is realized by EADR systems
The function of business automation, the system generally comprise EADR servers, event management system and intelligent load, DER control systems
Deng.
S42：System and equipment related EADR is described as follows：
EADR servers：Based on the conventional load in system, regenerative resource output level and PEV clusters, energy storage power
Information formulates new Spot Price, issue demand response (DR) event notice；
Incident management (Event Manager)：Monitoring micro-grid system internal loading power demand, regenerative resource go out in real time
The information such as power, intelligent electric meter, user power utilization wish, triggering access events, vacancy event, overload event or user are failed to keep an appointment event,
DR demands are formed, and demand is issued EADR servers, monitoring system operation, monitoring DR implementation results；
Intelligent load ESS control systems (Smart load/ESS Controller)：Upstream EADR services are connected simultaneously
All kinds of web response body Webs for participating in DR, and the event notice based on the issue of EADR servers are declared in device and downstream, formulate corresponding thing
Part triggers response mechanism, is realized with this to the web response body Web Optimized Operation for participating in DR qualifications；
Web response body Web (Response Executor)：That is the control object of EADR projects, including PEV clusters, energy storage store
Battery and PLs.
S43：Event trigger mechanism is analyzed
Event trigger mechanism is completed in Event-driven ADR systems.Event management system in system is according to solid
Determine frequency collection load power information and scene is contributed, decide whether to generate trigger signal according to the information data collected, and
It is sent in EADR servers and optimizes calculating.When being occurred according to different event to caused by micro-grid system influence degree
Difference, four kinds of events below invention main definitions, when there is corresponding event to occur, event management system will generate accordingly
Trigger signal.
The event type of supply and demand side is divided into following 4 class by invention：
The power demand event of access events, i.e. user, triggered when there is load/EV to network.Based on new in step S3
Type Price Mechanisms, contributed according to networking load/EV with electrical feature and the scene of prediction, electricity consumption is formulated to load/EV of networking
Plan.
Vacancy event, when the difference of the total load after real-time photovoltaic is contributed and is optimized exceedes given threshold, i.e.,
Intelligent load ESS controllers integrate all kinds of web response body Webs declare information, the sound to declaring the regulation and control of participation event
Answer main body to carry out schedulable ability (SA) to assess.And then SA assessment results are based on, and combine the DR issued by EADR servers and lead to
Know signal, reformulate the electricity consumption plan with participation DR qualification web response body Webs, to eliminate trigger conditions, and then
Alleviate the purpose of power unbalance.
Fail to keep an appointment event, when user uses load not in preference section, or EV is prematurely exited, trigger the event.Pass through
Comprehensive assessment to each EV or load schedulable ability, assign some load/EV according to assessment result and reformulate electricity consumption plan
Right, when these load/EV will fail to keep an appointment vacancy caused by main body make up completion when, trigger condition disappear.
In formula,Represent the host complex of failing to keep an appointment of present period；Load/EV collection of electricity consumption plan is reformulated in expression
Close.
When overload event, total load or load trend exceed the capacity of external circuit, i.e.,：
Overload event is triggered, in this case, each EV or load carry out comprehensive assessment to itself schedulable ability, so
After declare/competitive bidding response overload event, according to declare result decision-making cancel it is worst assess the electricity consumption plan of main body declared, if still
Meet trigger condition, then cancel the electricity consumption plan that main body is declared in time assessment of difference, so circulation.Until trigger condition disappears.
Adoption status machine of the present invention realizes event trigger mechanism, event trigger mechanism main mechanism bag in EADR systems
3 states are included：Event monitoring state, load scheduling state are with performing state.State machine is in event monitoring under normal circumstances
State, when having detected event triggering, then load scheduling is triggered, and scheduling is allocated to the power of controllable burden.Scheduling point
After matching somebody with somebody, execution state is triggered, is performed after scheduling result is transferred into controllable burden, the next period is entered after the completion of execution
Event monitoring state.If there are multiple events triggerings, according to the high event of the preferential executive level of the priority of event, treat
All events detected are allowed for access subsequent period after the completion of being carried out.The priority of 4 kinds of above-mentioned events is in the present invention
Triggering priority be access events>Vacancy event>Fail to keep an appointment event>Overload event.
In the step S5, according to vehicle and each appliance relevant parameter, without central control entity, it is expected
Pass through the automatic demand response model of developed distribution under conditions of user power utilization demand and transformer limitation is met, hair
Wave the assistant service potentiality of Demand-side resource load.Optimize the electricity consumption of Demand-side resource to minimize financial cost as target
Power, structure model are as follows：
In formulaDemand-side financial cost is represented,For the purchases strategies of kth time period, PESS(k) it is energy storage list
Electric power of the member in the k periods,Be k periods user to scheduling load caused by uncomfortable expense, βiFor uncomfortable expense
Coefficient, Pl k(0) it is initial values of the load l in the k periods.
Tc,l=(SE,l-S0,l)Cs,l/Pc,lηc (22)
Formula (22) constrains for time relationship, represents only to charge to expectation when the duration of vehicle access power network is more than
During shortest time needed for charge level, vehicle can be just participated in discharge and recharge scheduling.
Above-mentioned model is closed Demand-side resource power usage power and supply side new energy force information by new Price Mechanisms
Connection gets up, using the power demand of load and Power operation scope as constraint, to minimize user's financial cost as target, to negative
The electricity consumption plan of lotus optimizes.Due toWith the positive correlation of broad sense load value, the model can promote
Make Demand-side resource in the electricity consumption of load valley period or increase electric power, load peak period not electricity consumption, reduce electric power
Or electric discharge, so as to realize the target for improving solar photovoltaic utilization rate.
The beneficial effects of the invention are as follows：
1st, a kind of new Price Mechanisms based on microgrid broad sense net load are proposed, can effectively be guided by economic incentives
The electricity consumption behavior of active load, plays a part of peak load shifting, so as to reduce operation of power networks pressure.
2nd, by analyzing the physical characteristic of different event, response mechanism during all kinds of event triggerings is made, ensures system
Efficient stable is run, and reduces financial cost.
3rd, with reference to the trigger mechanism of all kinds of events and the assessment result of active load, by economy it is optimal premised on formulate
The driving ADR of outgoing event multiple step format realizes algorithm.
Brief description of the drawings
Fig. 1 is new Spot Price schematic diagram of mechanism.
Fig. 2 is event trigger mechanism schematic diagram.
Fig. 3 is typical case's prediction capability diagram of the new energy of one day.
Fig. 4 is EV scheduling appraisal curve figures.
Fig. 5 is EV power back-off amount curve maps.
Fig. 6 is kind to consider probabilistic to be based on the automatic demand response method flow diagram of event driven micro-capacitance sensor.
Embodiment
The invention will be further described below in conjunction with the accompanying drawings.
1~Fig. 6 of reference picture, one kind consideration is probabilistic to be based on the automatic demand response method of event driven micro-capacitance sensor,
Comprise the following steps：
S1：System initialization, the continuous time is subjected to sliding-model control, the optimization period is divided into J period, each
A length of Δ t during the period.For any kth time period, there are k={ k0,k0+ 1 ..., K }, wherein, k0Current sampling point is represented, K is represented
Last sampled point, and K≤J；Initial samples point k0=1；
S2：The workload demand response characteristic of comprehensive analysis residents micro-capacitance sensor, constructing system model.
Further, it is power supply unit that residents micro-capacitance sensor is made up of blower fan with photovoltaic array, electronic in the step S2
Controllable power unit that automobile (EV) combines with deferrable load, key control unit, this 4 part of energy-storage system (ESS) are formed：
Power supply unit, in view of single photovoltaic exports very little, in general photovoltaic generation unit is by a large amount of photovoltaic cell strings
The photovoltaic array that parallel connection is formed, while wind energy is directly proportional to the cube of wind speed, therefore, the conversion of weather can be serious in one day
Influence scene to contribute, be the mainly uncertain source of regenerative resource (RESs).
Controllable power unit, i.e., by EV, time it is adjustable/power adjustable load forms.
Core controls power supply, i.e., local control (Local control, LC).LC can provide for the program each asked
Power consumption predicts, and it is expected that in the near future power consumption can be adjusted by changing its behavior, while keep servicing.
ESS, it is regarded as special EV.
The step S2 includes procedure below：
S21：EV is modeled
If the vehicle collection of micro-grid system access is combined into N, then vehicle scale isThe main use of electric automobile
Way is the trip requirements for meeting user, and according to the driving feature of user, the situation of each vehicle is different, for any vehicle l
∈ N, its relevant parameter are：
Vl=[Tin,l,Tout,l,S0,l,SE,l,Qs,l,Pc,l,Pd,l] (1)
In formula, Tin,l、Tout,lThe time of vehicle l access micro-capacitance sensors and expected time departure are represented respectively；S0,l、SE,lPoint
Not Biao Shi power cell of vehicle starting state-of-charge (State of Charge, SOC) and expectation when leaving micro-capacitance sensor
SOC, SOC represent battery remaining power and the ratio of battery capacity, therefore have 0≤S0,l≤1、 0≤SE,l≤1；Qs,lRepresent electricity
Tankage；Pc,l、Pd,lSpecified charge and discharge power is represented respectively.
Assuming that the EV electrokinetic cells for participating in scheduling are lithium battery.According to the discharge and recharge correlation properties of lithium battery, it is appropriate to make
Simplify, within the single period, regard lithium battery as invariable power discharge and recharge.Ignore the influence of self-discharge rate, electrokinetic cell discharge and recharge
Power Pl(k) it is considered as and inputs：
In formula, Pl CH(k)、Pl DCH(k) absolute value of the charging and discharging power of vehicle l kth time periods is represented respectively.Establish
Electrokinetic cell SOC discrete state equations：
In formula, Sl(k+1)、Sl(k) represent vehicle in kth+1, the state-of-charge of k periods respectively.Formula (3) is transformed into square
Formation formula, while wushu (2) is substituted into formula (3), is obtainedWherein input matrixFeedforward matrix is Dl=[- 1 1].
S.22 energy-storage system models
The EV of access system is load and DER condensate, similar, energy storage battery can be considered all the period of time access,
One kind " special electric automobile " without charging workload demand.Analogy EV electrokinetic cell model Chinese styles (2), formula (3), establish electric power storage
Pool model.
S.23 load model is unified
The intelligent load of resident can be divided into as follows according to its different electrical characteristics and running statuses：
Can not Load adjustment (Non-shiftable loads, NSLs)：The type load connects smart jack, meets distribution
It is predictable, but can not control it, such as room lighting, TV, telephone set, whether normal operation is related to user for it
Primary demand whether can normally meet；
Adjustable load (Plannable loads, PLs)：The working hour of the type load or operation power exist certain
Scope, further can be transferable negative for time transferable load (time-plannable loads, TLs) and power by PLs points
Lotus (power-plannable loads, PLs), the type load that TLs refers to working time schedulable, operation power is fixed, such as
Washing machine, dish-washing machine etc.；PLs refers to the working time and runs the type load that power can be scheduled according to optimization demand, such as
Water heater etc..
Classify based on more than, CLs and PLs operation power time series can be formulated according to optimization demand, on the other hand,
With reference to NSLs, the daily load amplitude and trend in the microgrid region can be predicted.
The various load of quantity in micro-grid system is treated with a certain discrimination, can cause occur poor flexibility in scheduling process,
Therefore, for convenience of analyzing, unified load model is established, each type load that each connection networks is summarized as possessing consistent attribute
Unified physics model is described, and different features is shown by the difference of each attribute value.
The feature of j-th of intelligent load of i-th of family is described as follows：
In formula,Represent all family's set of the microgrid；Represent all of i-th family
Conventional load number；Represent all load aggregations of i-th of family；A is represented respectivelyi,jSpecified electric power and power-adjustable scope；Represent device Ai,jIt is expected Operational Zone
Between；Represent Ai,jTime regulatable scope；Qi,jRepresent power demand.
Respectively transferable time, transferable power, for embodying different load characteristics, so as to carry out phase
The coordination division of labor answered, the flag bit of each type load are set as shown in table 1.
Table 1
The unified load characteristic model described according to above formula (4), to k period electric powersIt is described as follows：
In formula,Load A is represented respectivelyi,jCan as time adjustable type and power in kth time period
The electric power of tune type.
In formula, Li,j(k+1)、Li,j(k) load A is represented respectivelyi,jIn kth+1, the power consumption of k periods, formula (5) is turned
Become matrix form, while wushu (6) is substituted into formula (5), is obtained
Wherein input matrix isFeedforward matrix is Dl=[- 1 1].
Electricity consumption behavior restraint：
In formula, [u]+Represent max { 0, u }；Represent that j-th of intelligent load of i-th of family meets
The specified run time of its power demand
ForAbove-mentioned formula can determine its all effective scheduling strategy, define possible strategy space：
In formula,The operation plan of all loads is represented, only meets x ∈ χ, load scheduling plan
X just comes into force.Formula (11) represents load Ai,jElectric power operation plan.
S3：Construction is a kind of to combine Spot Price (RTP) and the new Spot Price mechanism of tou power price (IBR), by new
The electricity price of current k periods is calculated in type Price Mechanisms.
Further, in the step S3, relative to static tou power price, a distinguishing feature of new Spot Price
It is that dynamic updates, relation between supply and demand can be reflected in real time；In addition, Spot Price in reaction system dynamic relation between supply and demand and
There is more preferable flexibility in terms of guiding user power utilization behavior.
S31：New Spot Price mechanism is based on total load information and new energy output power calculation, for micro-capacitance sensor area
Each load and EV cluster in domain.Work as Ai,jOr VlWhen triggering access events, the broad sense net load of the microgrid is represented by：
In formula,Represent load Ai,jDuring access, the completed load aggregation of electricity consumption plan；NlRepresent that vehicle l connects
It is fashionable, the completed vehicle cluster of discharge and recharge plan.PPV(k)、PWT(k) k period energy storage battery charge and discharges are represented respectively
Electrical power, photovoltaic, blower fan are contributed.
S32：Spot Price mechanism based on total load information
In formula,Represent load Ai,jOr vehicle VlDuring access, the Spot Price of k periods； It is Spot Price regulation coefficient；priR,j、φR,jRepresent to refer to electricity price and reference load value respectively；Correspondingly,Prediction total load is represented, whereinRepresent base load predicted value.
S33：The setting of IBR prices, IBR are formulated based on current total load information, and the IBR of k periods represents as follows：
In formula,Represent the IBR prices of k periods；Represent the specific load consumption of k periods
Threshold value；ak、bk、ckRepresent the IBR price values of specific k periods.
With reference to above-mentioned Spot Price mechanism and IBR motor mechanism, a kind of new Spot Price is obtained：
In formula, ζ1、ζ2The price multiplying power under different brackets is represented, and has ζ1,ζ2＞ 1, ζ2＞ ζ1.In any k periods, haveWherein, t1、t2Represent the boundary multiplying power under different brackets, and t1, t2>0、t2＞
t1, when the total load amount of k periodsIt is bigger,It is smaller.New Spot Price schematic diagram of mechanism is as shown in Figure 1.
WhenWhen can obtain：
Similarly, can obtainWithDerivative under situation is not less than 0.It can be seen that generally newly
Type Spot Price and being proportionate property of current loads level, it is association electric automobile interaction power, load electricity consumption plan and new energy
The medium that source is contributed.In addition, new Spot Price is individually set for single electric automobile or load, each vehicle and set
Apply (appliance) and enjoy its privately owned new Spot Price, conveniently become more meticulous and implement electric automobile discharge and recharge scheduling and set
Dispatched using electricity.
S4：Using a kind of automatic demand response (Event-driven ADR) strategy based on event-driven mechanism, by being
System judges whether each event triggers, and according to default priority processing event.
Further, in the step S4, to realize that RMG systems should keep the equilibrium of supply and demand to make operating cost again most
Small target, invention propose a kind of EDAR strategies.
S41：For the uncertainty of Demand-side and supply side, different driving signal is controlled by event-driven mechanism, made
Go out corresponding electricity consumption planned dispatching；Based on above-mentioned new Spot Price optimization Demand-side resource power usage plan, make part throttle characteristics more
Generation of electricity by new energy curve is matched, so as to improve regenerative resource grid connection efficiency, reduces the purchase of electricity to power network and the configuration of energy storage
Demand, reach the purpose of lifting micro-capacitance sensor whole economic efficiency.
EADR business needs the coordinated of different field main body, and demand response in micro-capacitance sensor is realized by EADR systems
The function of business automation, the system generally comprise EADR servers, event management system and intelligent load, DER control systems
Deng.
S42：System and equipment related EADR is described as follows：
1) EADR servers：Based on the conventional load in system, regenerative resource output level and PEV clusters, energy storage work(
Rate information formulates new Spot Price, issue demand response (DR) event notice；
2) incident management (Event Manager)：Monitoring micro-grid system internal loading power demand, regenerative resource in real time
The information such as output, intelligent electric meter, user power utilization wish, triggering access events, vacancy event, overload event or user are failed to keep an appointment thing
Part, DR demands are formed, and demand is issued EADR servers, monitoring system operation, monitoring DR implementation results；
3) intelligent load ESS control systems (Smart load/ESS Controller)：Upstream EADR clothes are connected simultaneously
All kinds of web response body Webs for participating in DR, and the event notice based on the issue of EADR servers are declared in business device and downstream, formulate corresponding
Event triggers response mechanism, is realized with this to the web response body Web Optimized Operation for participating in DR qualifications；
4) web response body Web (Response Executor)：That is the control object of EADR projects, including PEV clusters, energy storage
Battery and PLs.
S43：Event trigger mechanism is analyzed
Event trigger mechanism is completed in Event-driven ADR systems.Event management system in system is according to solid
Determine frequency collection load power information and scene is contributed, decide whether to generate trigger signal according to the information data collected, and
It is sent in EADR servers and optimizes calculating.When being occurred according to different event to caused by micro-grid system influence degree
Difference, four kinds of events below invention main definitions, when there is corresponding event to occur, event management system will generate accordingly
Trigger signal.
The event type of supply and demand side is divided into following 4 class by invention：
The power demand event of access events, i.e. user, triggered when there is load/EV to network.Based on new in step S3
Type Price Mechanisms, contributed according to networking load/EV with electrical feature and the scene of prediction, electricity consumption is formulated to load/EV of networking
Plan.
Vacancy event, when the difference of the total load after real-time photovoltaic is contributed and is optimized exceedes given threshold, i.e.,
Intelligent load ESS controllers integrate all kinds of web response body Webs declare information, the sound to declaring the regulation and control of participation event
Answer main body to carry out schedulable ability (SA) to assess.And then SA assessment results are based on, and combine the DR issued by EADR servers and lead to
Know signal, reformulate the electricity consumption plan with participation DR qualification web response body Webs, to eliminate trigger conditions, and then
Alleviate the purpose of power unbalance.
Fail to keep an appointment event, when user uses load not in preference section, or EV is prematurely exited, trigger the event.Pass through
Comprehensive assessment to each EV or load schedulable ability, assign some load/EV according to assessment result and reformulate electricity consumption plan
Right, when these load/EV will fail to keep an appointment vacancy caused by main body make up completion when, trigger condition disappear.
In formula,Represent the host complex of failing to keep an appointment of present period；Load/EV collection of electricity consumption plan is reformulated in expression
Close.
When overload event, total load or load trend exceed the capacity of external circuit, i.e.,：
Overload event is triggered, in this case, each EV or load carry out comprehensive assessment to itself schedulable ability, so
After declare/competitive bidding response overload event, according to declare result decision-making cancel it is worst assess the electricity consumption plan of main body declared, if still
Meet trigger condition, then cancel the electricity consumption plan that main body is declared in time assessment of difference, so circulation.Until trigger condition disappears.
Adoption status machine of the present invention realizes event trigger mechanism in EADR systems, as shown in Figure 2.Event trigger mechanism
Main mechanism includes 3 states：Event monitoring state, load scheduling state are with performing state.Under normal circumstances at state machine
In event monitoring state, when having detected event triggering, then load scheduling is triggered, and the power of controllable burden is allocated
Scheduling.After dispatching distribution, execution state is triggered, is performed after scheduling result is transferred into controllable burden, it is laggard to perform completion
Enter the event monitoring state of next period.It is high according to the preferential executive level of the priority of event if having multiple events triggerings
Event, all events to be checked measured are allowed for access subsequent period after the completion of being carried out.The priority of 4 kinds of above-mentioned events
Triggering priority in the present invention is access events>Vacancy event>Fail to keep an appointment event>Overload event.
In the step S5, according to vehicle and each appliance relevant parameter, without central control entity, it is expected
Pass through the automatic demand response model of developed distribution under conditions of user power utilization demand and transformer limitation is met, hair
Wave the assistant service potentiality of Demand-side resource load.Optimize the electricity consumption of Demand-side resource to minimize financial cost as target
Power, structure model are as follows：
In formulaDemand-side financial cost is represented,For the purchases strategies of kth time period, PESS(k) it is energy storage list
Electric power of the member in the k periods,Be k periods user to scheduling load caused by uncomfortable expense, βiFor uncomfortable expense
Coefficient, Pl k(0) it is initial values of the load l in the k periods.
Tc,l=(SE,l-S0,l)Cs,l/Pc,lηc (22)
Formula (22) constrains for time relationship, represents only to charge to expectation when the duration of vehicle access power network is more than
During shortest time needed for charge level, vehicle can be just participated in discharge and recharge scheduling.
Above-mentioned model is closed Demand-side resource power usage power and supply side new energy force information by new Price Mechanisms
Connection gets up, using the power demand of load and Power operation scope as constraint, to minimize user's financial cost as target, to negative
The electricity consumption plan of lotus optimizes.Due toWith the positive correlation of broad sense load value, the model can promote
Make Demand-side resource in the electricity consumption of load valley period or increase electric power, load peak period not electricity consumption, reduce electric power
Or electric discharge, so as to realize the target for improving solar photovoltaic utilization rate.
S6：After the completion of optimization, the optimization time is advanced to subsequent time, k=k0+ 1, repeat step S2~S6, until full-time
Duan Youhua is completed.
To make those skilled in the art more fully understand the present invention, applicant is by taking the small-scale micro-capacitance sensor of certain cell as an example
The validity and correctness of the carried automatic demand response management of event driven of checking.A length of 24h when wherein calculating, time
Interval of delta t is 0.5h.
The small-scale micro-capacitance sensor that invention is selected is shared for 4 family families.Blower fan rated capacity in micro-capacitance sensor is 10.4kW,
Operation and maintenance factor are arranged toPhotovoltaic system rated capacity is 5.6kW, operation and maintenance system
Number is arranged toThe battery capacity of electric automobile is 30kWh, and the state-of-charge bound of battery is divided
Not Wei 0.95 and 0.2, specified charge-discharge electric power is 4kW, charge efficiencyAnd discharging efficiencyIt is 0.92, electric automobile
Discharge and recharge loss factor isEnergy-storage battery rated capacity is 30kWh, and rated power 3kW, its is every
Day initial SOC is set as that 0.6, SOC bounds are respectively 0.9 and 0.4, the charge efficiency of energy-storage batteryAnd discharging efficiencyIt is 0.92, operation and maintenance factor are arranged to
Three Spot Price regulation coefficients of New Virtual electricity priceBe respectively set as 0.5,0.014,
The threshold value of 0.0086, IBR electricity priceIt is set to be not optimised 0.48 and 0.82 times of period maximum net load；Price times
Rate ζ1、ζ2Then it is arranged respectively to 1.05 and 1.25；Send price RTPreFor 0.485RMB/kWh.
Optimum results comparative analysis
In order to intuitively verify that invention puies forward the effect of strategy, following 4 kinds of patterns are emulated：
Case1：In the case where being accessed without energy-storage battery, each family household appliances are with electric automobile in earliest run time
The interior control mode by peak power operation.
Case2：In the case of considering energy-storage battery access, one kind based on automatic demand response optimizes a few days ago.
Case3：In the case of considering energy-storage battery access, one kind based on automatic demand response carries MPC rolling optimizations
In a few days optimization.
Case4：In the case of considering energy-storage battery access, one kind based on automatic demand response carries MPC rolling optimizations
With the in a few days optimization of event trigger mechanism.
In addition, the electricity consumption rule of user can not be precisely determined in real life, basic electricity consumption rule can only be drawn.
But the electricity consumption behavior of user is actual not fully consistent with basic electricity rule, it is necessary to accident be introduced, to plan when both
The electricity consumption plan of electrical equipment when different.Therefore, to fully demonstrate the uncertainty of Demand-side resource power usage behavior, case2~
Case4 patterns perform in the case where considering accident.
Typical case's wind of one day, light power curve are as shown in figure 3, the performance data such as institute of table 2 under 4 kinds of different control models
Show.
Table 2
The peak of power consumption of Case1 pattern Xia Ge families family is concentrated mainly at night, is staggered with new energy output peak, is made
The new energy for obtaining daytime is contributed and can not effectively dissolved, and is the immediate cause of user power utilization cost increase.Simultaneously as
The increase of the peak-valley difference of load, maximum load have exceeded the capacity of external circuit, influence the safe and stable operation of power distribution network.
Case2 patterns introduce energy-storage battery, by automatic demand response control strategy, it is charged in load valley, disappear
Scene more than needed of receiving is contributed；Discharged in load peak, reduce load peak, reduce the peak-valley difference of load.So that total load becomes
Change trend is consistent with scene prediction output, and interaction power curve smooths out, so as to reduce the electric cost of user.
Case3 patterns add MPC rolling optimizations on the basis of Case2 patterns, therefore, based on more accurately honourable
Contribute prediction so that each type load obtains more accurate discharge and recharge behavior guiding, give full play to can energy storage resource effect.
Demand-side preferably the actual output of Dynamic Matching supply side, interaction power can have been obtained further stabilizing, dropped compared with Case2
It is low 0.0692 percentage point.User power utilization cost also reduces 0.3359 yuan simultaneously.
In first two pattern, Case3 and Case2 is identical for the management mode of Demand-side load, i.e., is made a reservation for each load
Enter the off-grid time to formulate its electricity consumption plan.Therefore, the actual electricity consumption behavior of load with it is default inconsistent when, both moulds
Formula can not handle this accident still with predetermined data-optimized load.Compared to first three pattern, Case4 uses thing
Part trigger mechanism, when there is electrical equipment to access micro-capacitance sensor electricity consumption, based on event driven Optimization Mechanism regulatory requirement side electricity consumption meter
Draw, while honourable output is accurately predicted by MPC rolling optimizations.Compare and understand, though Case3 is based on MPC rolling optimizations,
Still planned according to the management strategy in Case2 patterns for Demand-side resource.When event of failing to keep an appointment triggers, not fully
Consider the uncertainty of the Demand-side electric appliance behavior as caused by accident, also can not be by adjusting the use of other electrical equipment
Electricity plan it is unbalanced to alleviate the load as caused by electrical equipment of failing to keep an appointment, increase the interaction power of these periods, cause day operation into
This lifting.And Case4 calculates schedulable capability evaluation result and the numerical relation for power of failing to keep an appointment by event trigger mechanism,
The electric power of other electrical equipment of present period is adjusted, to make up due to total load vacancy numerical value caused by electric appliance of failing to keep an appointment.
The schedulable assessment performance used in the works in adjustment electric appliance under Case4 patterns will show in the next section.
Conclusions can only prove that the automatic demand response strategy based on event driven and MPC methods has practicality
And economy.It not can prove that, when there is event triggering, the assessment result based on schedulable ability (SA) is to sharing of load power
There is relation.Therefore, the relation between put forward SA comprehensive evaluation methods and load power distribution is analyzed, contrasts this two EV tune
Degree is evaluated with power back-off amount before and after event as shown in Figure 4, Figure 5
EV1 and EV2 is changed in 16-20 periods and 23-07 period power, i.e., in the two periods, two
Equal response events driving mechanisms of EV, and two EV changed power trend and EV clusters are consistent.Contrasted with reference to Fig. 5
The specific power distribution situations of two EV understand, at next day morning 05 before, EV1 power variation is all higher than EV2, with
EV2 is then less than afterwards.Evaluated in view of both scheduling, it is known that when being scheduled evaluation, EV1 evaluation result is previous
Period is all higher than EV2, is then less than EV2 afterwards.Therefore in distribution power, previous period EV1 responding ability is higher, power
Variable quantity is more larger than EV2, and the latter period is then opposite.Due to 02-04 period, EV1 charge power reaches the upper limit, therefore EV1
Evaluation result is more than EV2, and its power back-off amount is but smaller than EV2.
After event triggering, each load power in system changes, to eliminate trigger conditions.Therefore, exist
Invention is carried in the power allocation scheme in control strategy, and system can be according to schedulable energy of the web response body Web in day part
Power, the power back-off amount of each load of reasonable arrangement are quick reasonable so as to measure the power back-off of load according to parameter
Ground distributes.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or the spy for combining the embodiment or example description
Point is contained at least one embodiment or example of the present invention.In this manual, to the schematic representation of above-mentioned term not
Identical embodiment or example must be directed to.Moreover, specific features, structure, material or the feature of description can be with office
Combined in an appropriate manner in one or more embodiments or example.In addition, those skilled in the art can be by this specification
Described in different embodiments or example be combined and combine.
Although embodiments of the invention have been shown and described above, it is to be understood that this specification embodiment
Described content is only enumerating to the way of realization of inventive concept, and protection scope of the present invention is not construed as only limiting
In the concrete form that embodiment is stated, protection scope of the present invention also includes those skilled in the art according to present inventive concept
It is conceivable that equivalent technologies mean.
Claims (6)
1. one kind consideration is probabilistic to be based on the automatic demand response method of event driven micro-capacitance sensor, it is characterised in that described
Method comprises the following steps：
S1：System initialization, the continuous time is subjected to sliding-model control, the optimization period is divided into J period, during each period
A length of Δ t, for any kth time period, there are k={ k0,k0+ 1 ..., K }, wherein, k0Current sampling point is represented, K represents end sampling
Point, and K≤J；Initial samples point k0=1；
S2：The workload demand response characteristic of comprehensive analysis residents micro-capacitance sensor, constructing system model；
S3：A kind of combination Spot Price and the Spot Price mechanism of tou power price are constructed, current k is calculated by Price Mechanisms
The electricity price of period；
S4：Using a kind of automatic demand response strategy based on event-driven mechanism, judge whether each event triggers by system,
And according to default priority processing event；
S5：After detecting event triggering, event is handled according to Event Priority, the terminal user in RMG is carried out in heat input
Optimization；
S6：After the completion of optimization, the optimization time is advanced to subsequent time, k=k0+ 1, repeat step S2~S6, until all the period of time optimization
Complete.
2. a kind of consideration as claimed in claim 1 is probabilistic to be based on the automatic demand response side of event driven micro-capacitance sensor
Method, it is characterised in that in the step S2, power supply unit, electronic vapour that residents micro-capacitance sensor is made up of blower fan and photovoltaic array
Controllable power unit that car EV combines with deferrable load, key control unit, this 4 part of energy-storage system ESS are formed：
Power supply unit, photovoltaic generation unit are the photovoltaic arrays formed by a large amount of photovoltaic cell connection in series-parallel, while wind energy and wind
Speed cube it is directly proportional, therefore, in one day the conversion of weather can have a strong impact on honourable output, be regenerative resource RESs master
Source is not known；
Controllable power unit, i.e., by electric automobile EV, time it is adjustable/power adjustable load forms；
Core controls power supply, i.e., local control LC, LC can provide power consumption prediction for the program each asked, and it is expected that soon
Future can adjust power consumption by changing its behavior, while keep servicing.
3. a kind of consideration as claimed in claim 2 is probabilistic to be based on the automatic demand response side of event driven micro-capacitance sensor
Method, it is characterised in that the step S2 includes procedure below：
S21：EV is modeled
If the vehicle collection of micro-grid system access is combined into N, then vehicle scale isBeing mainly used for for electric automobile is full
The trip requirements of sufficient user, according to the driving feature of user, the situation of each vehicle is different, for any vehicle l ∈ N, its
Relevant parameter is：
Vl=[Tin,l,Tout,l,S0,l,SE,l,Qs,l,Pc,l,Pd,l] (1)
In formula, Tin,l、Tout,lThe time of vehicle l access micro-capacitance sensors and expected time departure are represented respectively；S0,l、SE,lRepresent respectively
The starting state-of-charge SOC of power cell of vehicle represents battery remaining power and electricity with the expectation SOC, SOC when leaving micro-capacitance sensor
The ratio of tankage, therefore have 0≤S0,l≤1、0≤SE,l≤1；Qs,lRepresent battery capacity；Pc,l、Pd,lRepresent respectively it is specified fill,
Discharge power；
Assuming that the EV electrokinetic cells for participating in scheduling are lithium battery；According to the discharge and recharge correlation properties of lithium battery, make suitably to simplify,
Within the single period, lithium battery is regarded as invariable power discharge and recharge；Ignore the influence of self-discharge rate, electrokinetic cell charge-discharge electric power Pl
(k) it is considered as and inputs：
In formula, Pl CH(k)、Pl DCH(k) absolute value of the charging and discharging power of vehicle l kth time periods is represented respectively；The power of foundation
Battery SOC discrete state equations：
In formula, Sl(k+1)、Sl(k) represent vehicle in kth+1, the state-of-charge of k periods respectively；Formula (3) is transformed into rectangular
Formula, while wushu (2) is substituted into formula (3), is obtainedWherein input matrixFeedforward matrix is Dl=[- 1 1]；
S.22 energy-storage system models
The EV of access system is load and DER condensate, and similar, energy storage battery can be considered that all the period of time access, nothing are filled
One kind " special electric automobile " of electrical load requirement；Analogy EV electrokinetic cell model Chinese styles (2), formula (3), establish battery mould
Type；
S.23 load model is unified
The intelligent load of resident can be divided into as follows according to its different electrical characteristics and running statuses：
Can not Load adjustment NSLs：The type load connects smart jack, meets distribution and can be predicted, but can not control it,
Whether whether normal operation is related to the primary demand of user can normally meet for it；
Adjustable load PLs：There is certain limit in the working hour of the type load or operation power, can be by PLs points further
Time transferable load TLs and the transferable load of power, one kind that PLs, TLs refer to working time schedulable, operation power is fixed
Load；PLs refers to the working time and runs the type load that power can be scheduled according to optimization demand；
Classify based on more than, CLs and PLs operation power time series are formulated according to optimization demand, on the other hand, with reference to
NSLs, daily load amplitude and trend in the microgrid region can be predicted；
Unified load model is established, the unified physics model that each type load that each connection networks is summarized as possessing to consistent attribute enters
Row description, different features is shown by the difference of each attribute value；
The feature of j-th of intelligent load of i-th of family is described as follows：
In formula, Represent all family's set of the microgrid； Represent all conventional loads of i-th of family
Number；Represent all load aggregations of i-th of family；Table respectively
Show Ai,jSpecified electric power and power-adjustable scope；Represent device Ai,jIt is expected traffic coverage；Represent Ai,j's
Time regulatable scope；Qi,jRepresent power demand；
Respectively transferable time, transferable power, for embodying different load characteristics, so as to be assisted accordingly
The division of labor is adjusted, the flag bit of each type load is set as shown in table 1；
Table 1
The unified load characteristic model described according to above formula (4), to k period electric powersIt is described as follows：
In formula,Load A is represented respectivelyi,jIn kth time period as time adjustable type and adjustable power type
Electric power；
In formula, Li,j(k+1)、Li,j(k) load A is represented respectivelyi,jIn kth+1, the power consumption of k periods, formula (5) is transformed into
Matrix form, while wushu (6) is substituted into formula (5), is obtainedWherein
Input matrix isFeedforward matrix is Dl=[- 1 1]；
Electricity consumption behavior restraint：
In formula, [u]+Represent max { 0, u }；Represent that j-th of intelligent load of i-th of family meets its electricity consumption
The specified run time of demand；
ForAbove-mentioned formula can determine its all effective scheduling strategy, define possible strategy space：
In formula,The operation plan of all loads is represented, only meets x ∈ χ, load scheduling plan x just lifes
Effect；Formula (11) represents load Ai,jElectric power operation plan.
4. a kind of consideration as claimed in claim 3 is probabilistic to be based on the automatic demand response side of event driven micro-capacitance sensor
Method, it is characterised in that the process of the step S3 is as follows：
S31：New Spot Price mechanism is based on total load information and new energy output power calculation, in micro-capacitance sensor region
Each load and EV cluster；Work as Ai,jOr VlWhen triggering access events, the broad sense net load of the microgrid is represented by：
In formula,Represent load Ai,jDuring access, the completed load aggregation of electricity consumption plan；NlWhen representing vehicle l accesses,
The completed vehicle cluster of discharge and recharge plan；PPV(k)、PWT(k) represent respectively k period energy storage batteries charge-discharge electric powers,
Photovoltaic, blower fan are contributed；
S32：Spot Price mechanism based on total load information
In formula,Represent load Ai,jOr vehicle VlDuring access, the Spot Price of k periods；
It is Spot Price regulation coefficient；priR,j、φR,jRepresent to refer to electricity price and reference load value respectively；Correspondingly,Prediction total load is represented, whereinRepresent base load predicted value；
S33：The setting of IBR prices, IBR are formulated based on current total load information, and the IBR of k periods represents as follows：
In formula,Represent the IBR prices of k periods；Represent k periods specific load threshold value；
ak、bk、ckRepresent the IBR price values of specific k periods；
With reference to above-mentioned Spot Price mechanism and IBR motor mechanism, a kind of new Spot Price is obtained：
In formula, ζ1、ζ2The price multiplying power under different brackets is represented, and has ζ1,ζ2＞ 1, ζ2＞ ζ1；In any k periods, haveWherein, t1、t2Represent the boundary multiplying power under different brackets, and t1, t2>0、t2＞
t1, when the total load amount of k periodsIt is bigger,It is smaller；
WhenShi get：
Similarly, obtainWithDerivative under situation is not less than 0；It can be seen that generally new electricity in real time
Valency and being proportionate property of current loads level, it is that association electric automobile interaction power, load electricity consumption plan and new energy are contributed
Medium；In addition, new Spot Price is individually set for single electric automobile or load, each vehicle and facility
(appliance) its privately owned new Spot Price is enjoyed, conveniently becomes more meticulous and implements electric automobile discharge and recharge scheduling and facility
Electricity consumption is dispatched.
5. a kind of consideration as claimed in claim 4 is probabilistic to be based on the automatic demand response side of event driven micro-capacitance sensor
Method, it is characterised in that in the step S4, to realize that RMG systems should keep the equilibrium of supply and demand to make operating cost minimum again
Target, propose that a kind of EDAR is tactful, process is as follows：
S41：For the uncertainty of Demand-side and supply side, different driving signal is controlled by event-driven mechanism, makes phase
The electricity consumption planned dispatching answered；Based on above-mentioned new Spot Price optimization Demand-side resource power usage plan, part throttle characteristics is set more to match
Generation of electricity by new energy curve, so as to improve regenerative resource grid connection efficiency, the purchase of electricity to power network and the configuration needs of energy storage are reduced,
Reach the purpose of lifting micro-capacitance sensor whole economic efficiency；
EADR business needs the coordinated of different field main body, realizes that demand response business is certainly in micro-capacitance sensor by EADR systems
The function of dynamicization, the system generally comprise EADR servers, event management system and intelligent load, DER control systems etc.；It is described
Event driven ADR model frameworks under environment are as shown in Figure 2；
S42：System and equipment related EADR is described as follows：
EADR servers：Based on the conventional load in system, regenerative resource output level and PEV clusters, energy storage power information
Formulate new Spot Price, issue demand response DR event notices；
Incident management：Monitoring micro-grid system internal loading power demand, regenerative resource output, intelligent electric meter, user power utilization in real time
The information such as wish, triggering access events, vacancy event, overload event or user are failed to keep an appointment event, form DR demands, and demand is sent out
Give EADR servers, monitoring system operation, monitoring DR implementation results；
Intelligent load ESS control systems：Upstream EADR servers are connected simultaneously and all kinds of response masters for participating in DR are declared in downstream
Body, and the event notice based on the issue of EADR servers, are formulated corresponding event triggering response mechanism, are realized with this to ginseng
With the web response body Web Optimized Operation of DR qualifications；
Web response body Web：That is the control object of EADR projects, including PEV clusters, energy storage battery and PLs；
S43：Event trigger mechanism is analyzed
Event trigger mechanism is completed in Event-driven ADR systems；Event management system in system is according to fixed frequency
Gather load power information and scene is contributed, decide whether to generate trigger signal according to the information data collected, and be sent to
Calculating is optimized in EADR servers；When being occurred according to different event to caused by micro-grid system influence degree difference, hair
Four kinds of events below bright main definitions, when there is corresponding event to occur, event management system will generate corresponding triggering letter
Number；
The event type of supply and demand side is divided into following 4 class：
The power demand event of access events, i.e. user, triggered when there is load/EV to network；Based on the Novel electric in step S3
Valency mechanism, contributed according to networking load/EV with electrical feature and the scene of prediction, electricity consumption plan is formulated to load/EV of networking；
Vacancy event, when the difference of the total load after real-time photovoltaic is contributed and is optimized exceedes given threshold, i.e.,
Intelligent load ESS controllers integrate all kinds of web response body Webs declare information, the web response body Web to declaring the regulation and control of participation event
Schedulable ability (SA) is carried out to assess；And then SA assessment results are based on, and the DR notification signals issued by EADR servers are combined,
Reformulate with the electricity consumption plan for participating in DR qualification web response body Webs, to eliminate trigger conditions, and then alleviate electric power
Unbalance purpose；
Fail to keep an appointment event, when user uses load not in preference section, or EV is prematurely exited, trigger the event；By to each
EV or load schedulable ability comprehensive assessment, some load/EV power for reformulating electricity consumption plan is assigned according to assessment result
Profit, when these load/EV will fail to keep an appointment vacancy caused by main body make up completion when, trigger condition disappear；
In formula,Represent the host complex of failing to keep an appointment of present period；Represent that the load/EV for reformulating electricity consumption plan gathers；
When overload event, total load or load trend exceed the capacity of external circuit, i.e.,：
Overload event is triggered, in this case, each EV or load carry out comprehensive assessment, Ran Houshen to itself schedulable ability
Report/competitive bidding response overload event, according to declare result decision-making cancel it is worst assess the electricity consumption plan of main body declared, if still meeting to touch
Clockwork spring part, then cancel the electricity consumption plan that main body is declared in time assessment of difference, so circulation；Until trigger condition disappears；
Adoption status machine realizes event trigger mechanism in EADR systems；Event trigger mechanism main mechanism includes 3 states：
Event monitoring state, load scheduling state are with performing state；State machine is in event monitoring state under normal circumstances, when detecting
When having event triggering, then load scheduling is triggered, and scheduling is allocated to the power of controllable burden；After dispatching distribution, triggering
Execution state, performed after scheduling result is transferred into controllable burden, the event monitoring state of next period is entered after the completion of execution；
If have multiple events triggerings, according to the high event of the preferential executive level of the priority of event, all events to be checked measured
It is allowed for access after the completion of being carried out subsequent period；The triggering priority of the priority of 4 kinds of above-mentioned events in the present invention is to connect
Incoming event>Vacancy event>Fail to keep an appointment event>Overload event.
6. a kind of consideration as claimed in claim 5 is probabilistic to be based on the automatic demand response side of event driven micro-capacitance sensor
Method, it is characterised in that real without center control according to vehicle and each appliance relevant parameter in the step S5
Body, it is expected that by the automatic demand response model of developed distribution and is meeting the condition of user power utilization demand and transformer limitation
Under, the assistant service potentiality of performance Demand-side resource load；Optimize Demand-side resource to minimize financial cost as target
Electric power, structure model are as follows：
In formulaDemand-side financial cost is represented,For the purchases strategies of kth time period, PESS(k) for energy-storage units in k
The electric power of section,Be k periods user to scheduling load caused by uncomfortable expense, βiFor uncomfortable cost coefficient, Pl k
(0) it is initial values of the load l in the k periods；
Tc,l=(SE,l-S0,l)Cs,l/Pc,lηc (22)
Formula (22) constrains for time relationship, represents only to charge to Expected energy water when the duration of vehicle access power network is more than
When putting down the required shortest time, vehicle can be just participated in discharge and recharge scheduling；
Above-mentioned model has been associated Demand-side resource power usage power with supply side new energy force information by new Price Mechanisms
Come, using the power demand of load and Power operation scope as constraint, to minimize user's financial cost as target, to the use of load
Electricity plan optimizes；Due toWith the positive correlation of broad sense load value, the model can promote demand
Side resource is in the electricity consumption of load valley period or increases electric power, load peak period not electricity consumption, reduction electric power or electric discharge,
So as to realize the target for improving solar photovoltaic utilization rate.
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