CN109494816A - The methods of risk assessment and device of the multipotency streaming system of electric-thermal coupling - Google Patents

The methods of risk assessment and device of the multipotency streaming system of electric-thermal coupling Download PDF

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CN109494816A
CN109494816A CN201811628612.XA CN201811628612A CN109494816A CN 109494816 A CN109494816 A CN 109494816A CN 201811628612 A CN201811628612 A CN 201811628612A CN 109494816 A CN109494816 A CN 109494816A
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electric
streaming system
thermal coupling
multipotency streaming
power
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CN109494816B (en
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孙宏斌
郭庆来
王彬
车浩田
沈欣炜
王莉
熊文
刘育权
蔡莹
吴任博
华煌圣
曾顺奇
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Tsinghua Berkeley Shenzhen College Preparatory Office
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Tsinghua Berkeley Shenzhen College Preparatory Office
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Supply And Distribution Of Alternating Current (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses methods of risk assessment, device and the storage mediums of a kind of multipotency streaming system of electric-thermal coupling.This method includes establishing the stochastic model of the multipotency streaming system operation of electric-thermal coupling, sn random scene of the multipotency streaming system of electric-thermal coupling is generated according to stochastic model, the constraint condition and cost function of the multipotency streaming system of electric-thermal coupling are established simultaneously, using cost function as objective function, wherein, constraint condition includes heat supply network trend constraint condition, allow to establish the coupled relation of the active power of heat supply network and the active power of power grid, therefore the minimum value of the objective function of the multipotency streaming system of the electric-thermal coupling under sn random scene can be solved by the electric-thermal coupling constraint condition for the multipotency streaming system that electric-thermal couples, and the value-at-risk of the multipotency streaming system of electric-thermal coupling is determined according to the minimum value of the corresponding objective function of sn random scene, so that the multipotency streaming system of the electric-thermal coupling solved Value-at-risk is more acurrate.

Description

The methods of risk assessment and device of the multipotency streaming system of electric-thermal coupling
Technical field
It is coupled the present embodiments relate to the risk assessment technology field of multipotency streaming system more particularly to a kind of electric-thermal Methods of risk assessment, device and the storage medium of multipotency streaming system.
Background technique
Multipotency streaming system covers the multiple kinds of energies stream subsystem such as electric, hot, cold, gas, and each subsystem passes through cogeneration, heat The equipment such as pump are converted and are coupled.The rise of energy internet in recent years, so that being transmitted with electric, hot, cold, gas diversified forms The multipotency network of energy shows its superiority.But multipotency coupling also leads to the uncertain factor phase interaction in each subsystem With influence user just commonly uses energy, or even will affect the overall security of multipotency streaming system.
In the prior art, comprehensive analysis can be carried out to these uncertain factors by risk assessment, obtains multipotency The size of streaming system operation risk.But the time scale of the factor general analysis of risk assessment consideration in the prior art is very It is long, promptly and accurately the risk of multipotency streaming system operation accurately can not be assessed.
Summary of the invention
The present invention provides methods of risk assessment, device and the storage medium of a kind of multipotency streaming system of electric-thermal coupling, with reality Now more accurately analysis electric-thermal coupling multipotency streaming system be more than be incorporated into the power networks agreement active power threshold value risk, simultaneously Shorten assessment cycle.
In a first aspect, the embodiment of the invention provides a kind of methods of risk assessment of the multipotency streaming system of electric-thermal coupling, packet It includes:
Establish the stochastic model of the multipotency streaming system operation of electric-thermal coupling；
Sn random scene of the multipotency streaming system of the electric-thermal coupling is generated according to the stochastic model；Wherein, sn For integer, and sn is greater than 1；
Establish the constraint condition and cost function of the multipotency streaming system of the electric-thermal coupling；Wherein, the constraint condition packet Include heat supply network trend constraint condition；
Using the cost function as objective function, it is corresponding that the sn random scene is solved according to the constraint condition The minimum value of objective function；
The multipotency stream system of the electric-thermal coupling is determined according to the minimum value of the corresponding objective function of the sn random scene The value-at-risk of system.
Specifically, the stochastic model of the multipotency streaming system operation of the electric-thermal coupling includes the more of the electric-thermal coupling It can the stochastic model of predicted value of power generation active power of the following one day each scheduling instance of streaming system, electric load active power The stochastic model of predicted value and the stochastic model of thermic load active power predicted value, the predicted value of the power generation active power Stochastic model and the electric load active power predicted value stochastic model specifically:
Epv(t)~N (μpv(t),δpv(t)2)
Ee(t)~N (μe(t),δe(t)2)
Ppv(t)=PFpv(t)+Epv(t)
Pe(t)=PFe(t)+Ee(t)
Wherein, t is following one day t-th scheduling instance, t=1, for the scheduling instance that 2 ..., T, T are following one day Number, PFpvIt (t) is the predicted value of t-th of scheduling instance power generation active power, PFe(t) active for t-th of scheduling instance electric load The predicted value of power, EpvIt (t) is the deviation of the predicted value of t-th of scheduling instance power generation active power, EeFor t-th of scheduling instance The deviation of the predicted value of electric load active power, μpvIt (t) is the deviation of the predicted value of t-th of scheduling instance power generation active power Desired value, δpvIt (t) is the standard deviation of the prediction deviation of the predicted value of t-th of scheduling instance power generation active power, μeIt (t) is t The desired value of the deviation of the predicted value of a scheduling instance electric load active power, δe(t) active for t-th of scheduling instance electric load The standard deviation of the prediction deviation of the predicted value of power, PpvIt (t) is t-th of scheduling instance power generation active power, Pe(t) it is t-th Scheduling instance electric load active power；
The stochastic model of the thermic load active power predicted value specifically:
Ph,1(t)~Beta (A=10, B=10 (Pmax/Phf,1(t)-1))
Ph,2(t)~Beta (A=10, B=10 (Pmax/Phf,2(t)-1))
...
Ph,L1(t)~Beta (A=10, B=10 (Pmax/Phf,L1(t)-1))
Wherein, Phf,1(t)、Phf,2(t)、...、Phf,L1(t) t-th of tune of each thermic load that sum is L1 is respectively indicated Spend the prediction active power at moment, Ph,1(t)、Ph,2(t)、...、Ph,L1(t) t-th of scheduling instance of each thermic load is respectively indicated Active power, PmaxThe maximum power of total heat duties in multipotency streaming system is coupled for electric-thermal.
Specifically, the sn of the multipotency streaming system that the electric-thermal coupling is generated according to the stochastic model is a random Scene includes:
Determine the one day T for including schedulable moment of multipotency streaming system of the electric-thermal coupling；
The number of the thermic load of the multipotency streaming system coupled according to the number at the schedulable moment and the electric-thermal determines The dimension of each random scene, the dimension w of each random scene are w=T (2+L1)；Wherein, T be one day described in can The number of scheduling instance, L1 are the number of the thermic load；
The stochastic model that the multipotency streaming system operation of the electric-thermal coupling is solved by SN times, forms SN random field Scape；
Scene reduction is carried out to the SN random scenes, obtains the sn random scenes, wherein SN is integer, and SN is greater than sn.
Specifically, the heat supply network trend constraint condition are as follows:
Wherein, A is incidence matrix, thereon incidence matrixWith lower incidence matrixA:
Wherein, i=1,2 ... N, N are the serial number of node, and j=1,2 ... B, B are the serial number of branch, CpFor heat supply network heat transfer mediator Specific heat capacity, ATFor the transposition of incidence matrix A, m is the heat flow of a branch in B branch, and the subscript of m indicates branch Serial number, M are the vector of the flow composition of B branch, TnFor the vector of each node temperature composition of heat supply network, TeFor each branch end of heat supply network The vector of the temperature composition at end, TaFor environment temperature, QJFor the vector that the thermic load of each node of heat supply network forms, C is with each branch Diagonal matrix of the pipeline heat loss coefficient as diagonal element, λ are the unit length thermal conductivitys of each branch of heat supply network, and the subscript of λ indicates branch Serial number, L is the length of each branch of heat supply network, and the subscript of L indicates the serial number of branch.
Specifically, the constraint condition further includes cogeneration units operation constraint condition, the cogeneration units fortune Row constraint condition are as follows:
Wherein, t is following one day t-th scheduling instance, t=1, for the scheduling instance that 2 ..., T, T are following one day Number, s are s-th of cogeneration units in the S cogeneration units, and Ds is s-th of cogeneration units The number on the vertex of feasible zone, (Pd,s(t),Qd,s(t)), d=1,2...DsIt is adjusted for s-th t-th of the cogeneration units Spend the coordinate on the vertex of the feasible zone at moment, (ps(t),qsIt (t)) is s-th of cogeneration units, t-th of scheduling instance In feasible zone a bit, kd,sIt (t) is the coordinate on the vertex of the feasible zone of s-th of cogeneration units, t-th of scheduling instance (Pd,s(t),Qd,s(t)), d=1,2...DsWeight, p1(t)、p2(t)、...、pSIt (t) is each cogeneration units The electric load active power of t-th of scheduling instance, q1(t)、q2(t)、...、qSIt (t) is the heat of each cogeneration units Load active power.
Specifically, the cogeneration units operation constraint condition further includes the cogeneration units active power climbing Constraint condition, i.e., are as follows:
S=1,2...S
Wherein, RAMPs downAnd RAMPs upUpward, the downward climbing speed of respectively s-th cogeneration units active power The maximum value of rate, time difference of the Δ t between t-th of scheduling instance and the t-1 scheduling instance, ps(t) and ps(t-1) respectively For s-th of cogeneration units t-th of scheduling instance and the t-1 scheduling instance active power.
Specifically, the constraint condition of the multipotency streaming system of the electric-thermal coupling further includes the multipotency stream of the electric-thermal coupling The constraint condition of electric energy storage device and hot energy storage device in system, are as follows:
0≤Pdis(t)≤Pdmax, 0≤Pchar(t)≤Pcmax
0≤SoC(t)≤SoCmax
SoC (t)=SoC (t-1)-Pdis(t)+Pchar(t), t=2,3 ..., T
Wherein, t is following one day t-th scheduling instance, t=1, for the scheduling instance that 2 ..., T, T are following one day Number, E are the number of electric energy storage device, PdisIt (t) is total discharge power of t-th of scheduling instance all E electric energy storage devices, PcharIt (t) is total charge power of t-th of scheduling instance all E electric energy storage devices, PdmaxFor the maximum value of total discharge power, PcmaxFor the maximum value of total charge power, SoC (t) is all E total storage states of electric energy storage device of t-th of scheduling slot, SoCmaxFor the maximum value of the stored energy capacitance of all E electric energy storage devices；
The constraint condition of H hot energy storage devices are as follows:
0≤Qdis,hh(t)≤Qdmax,hh, 0≤Qchar,hh(t)≤Qcmax,hh,0≤EHhh(t)≤EHmax,hh
EHhh(t)=EHhh(t-1)+Qchar,hh(t)-Qdis,hh(t)
Hh=1,2 ..., H
Wherein, H is the number of hot energy storage device, Qdis,hhIt (t) is the heat release function of each hot energy storage device of t-th of scheduling instance Rate, Qdmax,hhFor the heat release power maximum value of each hot energy storage device, Qchar,hh(t) it is inhaled for each hot energy storage device of t-th of scheduling instance Thermal power, Qcmax,hhFor the Endothermic power maximum value of each hot energy storage device, EHhhIt (t) is each hot energy storage device of t-th of scheduling instance Heat accumulation state, EHmax,hhFor the maximum value of each hot energy storage device heat storage capacity.
Specifically, the constraint condition of the multipotency streaming system of the electric-thermal coupling further includes thermo-electrically coupling multipotency stream system The trend constraint condition for the interconnection that system is connect with external electrical network, specifically:
Ppv(t)+Pe(t)+ps(t)+Ptie(t))=0
Wherein, PtieIt (t) is the active power transmitted on interconnection described in t-th of scheduling instance, pSIt (t) is the thermo-electrically Couple the electric load active power of t-th of scheduling instance of multipotency streaming system cogeneration units.
Specifically, the cost function are as follows:
Wherein, Hprices(t) point of unit thermal power is issued for s-th of cogeneration units, t-th of scheduling instance When price, EpricesIt (t) is the timesharing valence of the sending specific electric power of s-th of cogeneration units, t-th of scheduling instance Lattice, Ctie(t) it is
Ctie(t)=Price_n (t) * Ptie1(t)+Price_ex*Ptie2(t)
Ptie(t)=Ptie1(t)+Ptie2(t)
0≤Ptie1(t)≤Ptie_limit
0≤Ptie2(t)
Wherein, CtieThe interconnection purchases strategies that multipotency streaming system is connect with external electrical network, P are coupled for the thermo-electricallytie1 The permitted imbalance power threshold value of interconnection, P when grid-connected for the multipotency streaming system of electric-thermal couplingtie2For more than The Partial Power of the permitted imbalance power threshold value of interconnection, Price_n (t) are the permitted injustice of the interconnection The tou power price on interconnection when weighing power in threshold value, Price_ex are more than the permitted injustice of the interconnection The punishment electricity price of weighing apparatus power threshold part, Ptie_limitFor the upper limit of the power of interconnection carrying.
Specifically, using the cost function as objective function, the sn random field is solved according to the constraint condition When the minimum value of the corresponding objective function of scape, the corresponding different scheduling instances of the sn random scene are solved using interior point method The minimum value of objective function.
Specifically, the minimum value according to the corresponding objective function of the sn random scene determines the electric-thermal coupling The value-at-risk of the multipotency streaming system of conjunction includes:
Determine the probability that the sn random scene occurs；
It is determined according to the minimum value of the objective function of the sn random scene of a certain scheduling instance each described random Value-at-risk of the scene in the scheduling instance；
The probability meter occurred according to the value-at-risk of the sn random scene of same scheduling instance and the sn scene Calculate the value-at-risk of a certain scheduling instance of the multipotency streaming system of the electric-thermal coupling.
Second aspect, the embodiment of the invention also provides a kind of electric-thermal coupling multipotency streaming system risk assessment device, Include:
Stochastic model establishes module, the stochastic model of the multipotency streaming system operation for establishing electric-thermal coupling；
Random scene generation module, for generating the multipotency streaming system of the electric-thermal coupling according to the stochastic model Sn random scene；Wherein, sn is integer, and sn is greater than 1；
Constraint condition and cost function establish module, the constraint item of the multipotency streaming system for establishing the electric-thermal coupling Part and cost function；Wherein, the constraint condition includes heat supply network trend constraint condition；
Objective function solves module, using the cost function as objective function, according to constraint condition solution The minimum value of the corresponding objective function of sn random scene；
Risk determining module, for according to the determination of the minimum value of the corresponding objective function of the sn random scene The value-at-risk of the multipotency streaming system of electric-thermal coupling.
The third aspect, the embodiment of the invention also provides a kind of computer readable storage mediums, are stored thereon with computer Program, which is characterized in that the multipotency for the electric-thermal coupling that the embodiment of the present invention arbitrarily provides is realized when the program is executed by processor The methods of risk assessment of streaming system.
The stochastic model that the present invention is run by establishing the multipotency streaming system of electric-thermal coupling, and according to stochastic model Sn random scene of the multipotency streaming system of electric-thermal coupling is generated, while establishing the constraint item of the multipotency streaming system of electric-thermal coupling Part and cost function, wherein constraint condition includes heat supply network trend constraint condition, allows to establish the active power and electricity of heat supply network The coupled relation of the active power of net, therefore the electric-thermal coupling constraint condition for the multipotency streaming system that can be coupled by electric-thermal is asked The minimum value of the objective function of the multipotency streaming system of the electric-thermal coupling under sn random scene is solved, and according to sn random scene The minimum value of corresponding objective function determines the value-at-risk of the multipotency streaming system of electric-thermal coupling, so that the electric-thermal coupling solved The risk of the active power threshold value more than agreement of being incorporated into the power networks is interacted when the multipotency streaming system operation of conjunction with the power of external electrical network It is worth more acurrate.And the stochastic model for establishing the multipotency streaming system of electric-thermal coupling, shortens assessment cycle.In addition, electricity- The stochastic model of the multipotency streaming system operation of thermal coupling considers cogeneration units, electric energy storage device, hot energy storage device, electricity The Optimized Operation of load, thermic load and photovoltaic plant is on the uncertain influence of risk assessment, to improve the more of electric-thermal coupling The accuracy of the risk assessment of energy streaming system.
Detailed description of the invention
Fig. 1 is a kind of process of the methods of risk assessment of the multipotency streaming system of electric-thermal coupling provided in an embodiment of the present invention Figure；
Fig. 2 is a kind of structural schematic diagram of the multipotency streaming system of electric-thermal coupling provided in an embodiment of the present invention；
Fig. 3 is a kind of power schematic diagram of the working method of cogeneration units provided in an embodiment of the present invention；
Fig. 4 is that a kind of electric-thermal provided in an embodiment of the present invention couples multipotency streaming system using the prediction of thermic load active power The result schematic diagram of the stochastic model fitting of value；
Fig. 5 is the stream of the methods of risk assessment of the multipotency streaming system of another electric-thermal coupling provided in an embodiment of the present invention Cheng Tu；
Fig. 6 is a kind of interconnection active power probability of the multipotency streaming system of electric-thermal coupling provided in an embodiment of the present invention Distribution schematic diagram；
Fig. 7 is the stream of the methods of risk assessment of the multipotency streaming system of another electric-thermal coupling provided in an embodiment of the present invention Cheng Tu；
Fig. 8 is a kind of structure of the risk assessment device of the multipotency streaming system of electric-thermal coupling provided in an embodiment of the present invention Schematic diagram.
Specific embodiment
The present invention is described in further detail with reference to the accompanying drawings and examples.It is understood that this place is retouched The specific embodiment stated is used only for explaining the present invention rather than limiting the invention.It also should be noted that in order to just Only the parts related to the present invention are shown in description, attached drawing rather than entire infrastructure.
The coupling of assessment electric-thermal is more when the multipotency streaming system that the embodiment of the present invention is applicable to electric-thermal coupling is incorporated into the power networks The case where risk for the active power threshold value that the active power of energy streaming system is reached an agreement on when exceeding grid-connected.Specifically, when electric-thermal couples Multipotency streaming system when being incorporated into the power networks, there are power to interact between the multipotency streaming system and external electrical network of electric-thermal coupling.And Before the multipotency streaming system of electric-thermal coupling is incorporated into the power networks, the threshold value for the active power that can be interacted with external electrical network contracted power.When When the multipotency streaming system of electric-thermal coupling interacts the threshold value more than the active power of agreement with the power of external electrical network, electric-thermal coupling Multipotency streaming system the stabilization of external electrical network can be impacted, while external electrical network can to electric-thermal couple multipotency streaming system Power more than the threshold portion of the active power of agreement carries out punishment price adjustment.Therefore, the multipotency that the present invention is coupled by electric-thermal The methods of risk assessment of streaming system carries out risk assessment to the multipotency streaming system that electric-thermal couples, to realize more accurately analysis electricity- The active power threshold value more than agreement of being incorporated into the power networks is interacted when the multipotency streaming system operation of thermal coupling with the power of external electrical network Risk, while shortening analytical cycle.
Fig. 1 is a kind of process of the methods of risk assessment of the multipotency streaming system of electric-thermal coupling provided in an embodiment of the present invention Figure, this method can be executed by the risk assessment device of the multipotency streaming system of electric-thermal coupling, as shown in Figure 1, this method is specific Include the following steps:
The stochastic model that S110, the multipotency streaming system for establishing electric-thermal coupling are run.
Wherein, Fig. 2 is a kind of structural schematic diagram of the multipotency streaming system of electric-thermal coupling provided in an embodiment of the present invention.Such as Shown in Fig. 2, the multipotency streaming system of electric-thermal coupling generally comprises cogeneration units, electric energy storage device, hot energy storage device (in figure Be not shown), electric load, thermic load (not shown) and photovoltaic plant, and the multipotency streaming system coupled in different electric-thermals In, the quantity not necessarily phase of cogeneration units, electric energy storage device, hot energy storage device, electric load, thermic load and photovoltaic plant Together, thus when in the multipotency streaming system of electric-thermal coupling cogeneration units, electric energy storage device, hot energy storage device, electric load, When thermic load and the quantity of photovoltaic plant change, the methods of risk assessment of the multipotency streaming system of electric-thermal coupling equally can be with Risk assessment is carried out to it, it is contemplated that cogeneration units, electric energy storage device, hot energy storage device, electric load, thermic load and photovoltaic The Optimized Operation in power station is on the uncertain influence of risk assessment, so that the risk for improving the multipotency streaming system of electric-thermal coupling is commented The accuracy estimated.Photovoltaic plant is used for photovoltaic power generation, and the multipotency streaming system for electric-thermal coupling provides electric energy, electric energy storage device with Hot energy storage device is for storing electric energy and thermal energy.Electric load and thermic load are for consuming power.Cogeneration units are used for as electricity- The multipotency streaming system of thermal coupling provides power.Under normal circumstances, cogeneration units working method includes back pressure type and extraction condensing type, It is realized respectively by back pressure type thermal power plant unit and extraction condensing type thermal power plant unit.Fig. 3 is a kind of cogeneration of heat and power provided in an embodiment of the present invention The power schematic diagram of the working method of unit.As shown in figure 3, generated output P (the i.e. power generation wattful power of back pressure type thermal power plant unit Rate) it is directly proportional to heat supply power output Q (i.e. heat supply active power), and generated output P (the i.e. power generation wattful power of extraction condensing type thermal power plant unit Rate) with heat supply power output Q (i.e. heat supply active power) formed a quadrangle feasible zone.The multipotency streaming system of electric-thermal coupling is logical It crosses interconnection 101 to be connected with external electrical network, the threshold value that interacts with the power of external electrical network of multipotency streaming system of electric-thermal coupling can be with The difference generated for the power consumption and power of the multipotency streaming system of electric-thermal coupling.Under normal circumstances, in the more of electric-thermal coupling Can be in streaming system, transmission range is shorter, electric energy be lost when transmitting it is smaller, therefore in the multipotency streaming system of electric-thermal coupling Power generation active power and electric load active power are considered as an entirety.And thermal energy transmission when be lost it is bigger, therefore Different thermic loads all has different active power in the multipotency streaming system of electric-thermal coupling.Therefore, the multipotency of electric-thermal coupling The stochastic model of streaming system operation generally comprises power generation active power, electric load active power and multiple thermic load wattful powers Rate.Moreover, stochastic model is generally comprised to power generation active power, the electric load active power and more in following assessment cycle The predicted value and deviation of a thermic load active power.Illustratively, when the multipotency streaming system of electric-thermal coupling includes that each heat of L1 is negative When lotus, stochastic model may include 2+L1 formula.The probability density function of stochastic model can obey Beta distribution.
It should be noted that cogeneration units in Fig. 2, electric energy storage device, hot energy storage device, electric load, thermic load and The quantity of photovoltaic plant is only a kind of example, rather than is limited.
In addition, different scheduling instances may have different loads, therefore, can be to one within following assessment cycle A assessment cycle is divided into different scheduling instances, preferably to assess the risk in different scheduling instances.Moreover, this hair It is bright the technical solution adopted is that establish electric-thermal coupling multipotency streaming system stochastic model, therefore, assessment cycle can be big Big shortening.Illustratively, assessment cycle can be following one day, have by scheduling instance different in one day different Electric load and thermic load, can be scheduled the division at moment to one day, such as can be divided into T scheduling instance, each scheduling Moment corresponds to a stochastic model, to improve the accuracy of stochastic model.
S120, the sn random scene that the multipotency streaming system that electric-thermal couples is generated according to stochastic model；Wherein, sn is Integer, and sn is greater than 1.
Wherein, the precision of selection to risk assessment of random scene number is related.It is higher to the required precision of risk assessment, The number of random scene is more.Under normal circumstances, when the confidence interval of the risk assessment of the multipotency streaming system of electric-thermal coupling exists When 90%, it is 1000 that the number of random scene, which can choose,.
Power generation active power, electric load when random scene is the multipotency streaming system operation to an electric-thermal coupling is active The case where power and thermic load active power, carries out stochastic model, therefore, the multipotency stream that random scene is not only coupled with electric-thermal Power generation active power, electric load active power when system is run is related with thermic load active power, and what is also coupled with electric-thermal is more The scheduling instance of energy streaming system operation is related.Therefore, the stochastic model of the multipotency streaming system of solution electric-thermal coupling can be passed through Obtain the random scene of the multipotency streaming system of electric-thermal coupling.
It should be noted that needing to solve electric-thermal when the random scene of the multipotency streaming system of electric-thermal coupling has sn Stochastic model sn times of the multipotency streaming system of coupling.It every time can be with to the stochastic model of the multipotency streaming system of electric-thermal coupling Obtain a random scene.
S130, the constraint condition and cost function for establishing the multipotency streaming system that electric-thermal couples；Wherein, constraint condition includes Heat supply network trend constraint condition.
Wherein, condition when constraint condition is the multipotency streaming system normal operation of electric-thermal coupling, electric-thermal couple more The constraint condition of energy streaming system includes a variety of.Illustratively, constraint condition may include heat supply network trend constraint condition, heat supply network trend Constraint condition is the condition that thermal energy meets in transmission process in heat supply network, such as the multipotency streaming system of electric-thermal coupling operates normally When heat supply network node temperature allow maximum value, heat supply network node temperature that minimum value, heat supply network bypass flow is allowed to allow maximum value and heat supply network Bypass flow allows minimum value etc..In addition, including sharing between heat supply network and power grid in the multipotency streaming system of electric-thermal coupling Node, as shown in Fig. 2, the dotted line in Fig. 2 is heat supply network line, the solid line in Fig. 2 is grid line.Electric network swim also includes constraint item Part, such as grid branch active power allow maximum value and grid branch active power to allow minimum value, and heat supply network and power grid Total active power it is equal with total active power of multipotency streaming system that electric-thermal couples.Therefore when constraint condition includes heat supply network tide When flowing constraint condition, the coupled relation of the active power of heat supply network and the active power of power grid can establish.So as to pass through electricity- The risk of the multipotency streaming system of the electric-thermal coupling assessment electric-thermal coupling of the multipotency streaming system of thermal coupling.
The cost function of the multipotency streaming system of electric-thermal coupling is that the multipotency streaming system of electric-thermal coupling generates electrical power and heat The expense generated when power interacts is carried out with external electrical network when the multipotency streaming system of expense and the electric-thermal coupling of power is incorporated into the power networks With.Under normal circumstances, the multipotency streaming system of electric-thermal coupling generates electrical power and the expense of thermal power is more steady.And electric-thermal When the multipotency streaming system of coupling is incorporated into the power networks with external electrical network carry out power interact when, when electric-thermal coupling multipotency streaming system and When the power of the interaction of external electrical network is in the threshold range of the active power of agreement, the multipotency streaming system of electric-thermal coupling is grid-connected Carry out when operation with external electrical network when power interaction the expense that generates also relatively steadily.When electric-thermal coupling multipotency streaming system with When the power of the interaction of external electrical network is more than the threshold range of the active power of agreement, external electrical network can couple electric-thermal more Energy streaming system is more than that the power of the threshold portion of the active power of agreement carries out punishment price adjustment, the multipotency streaming system of electric-thermal coupling The expense for generate when power interacts with external electrical network when being incorporated into the power networks will increase, while the multipotency streaming system of electric-thermal coupling The stabilization of external electrical network can be impacted, therefore the multipotency streaming system of electric-thermal coupling can be analyzed by the value of cost function Interact when operation with the power of external electrical network be more than be incorporated into the power networks agreement active power threshold value risk.
S140, using cost function as objective function, the corresponding target letter of sn random scene is solved according to constraint condition Several minimum values.
When cost function is as objective function, the feasible zone of objective function is formed by constraint condition, to each random The cost function of scene carries out optimal solution, that is, the minimum value of the cost function of each random scene is solved, at this point, electric-thermal coupling Each random scene in the multipotency streaming system of conjunction is the best situation of safety in operation.Corresponding, sn random scene needs Solve sn cost function.It is interacted with the power of external electrical network equal to grid-connected when the multipotency streaming system operation of electric-thermal coupling When the active power threshold value of operation agreement, the corresponding value at cost of cost function can be used as the multipotency stream system for judging electric-thermal coupling System interacts the risk judgment condition of the active power threshold value more than agreement of being incorporated into the power networks with the power of external electrical network.I.e. according to constraint When the minimum value for the corresponding objective function of random scene that condition solves is greater than Rule of judgment, then it is assumed that under the random scene It is interacted with the power of external electrical network when the multipotency streaming system operation of electric-thermal coupling with the active power more than agreement of being incorporated into the power networks The risk of threshold value.
S150, the multipotency streaming system that electric-thermal coupling is determined according to the minimum value of the corresponding objective function of sn random scene Value-at-risk.
Specifically, random according to sn after cost function solves the optimal value of sn random scene as objective function The minimum value of the corresponding objective function of scene determines the random scene situation best in safety in operation in sn random scene It is interacted with the power of external electrical network when the multipotency streaming system operation of lower electric-thermal coupling with the wattful power more than agreement of being incorporated into the power networks The probability that the number of the risk of rate threshold value and different random scenes occur, the probability occurred according to random scene and number Determine the value-at-risk of the multipotency streaming system of electric-thermal coupling.
The technical solution of the present embodiment, the stochastic model of the multipotency streaming system operation by establishing electric-thermal coupling, and root Sn random scene of the multipotency streaming system of electric-thermal coupling is generated according to stochastic model, while establishing the multipotency stream of electric-thermal coupling The constraint condition and cost function of system, wherein constraint condition includes heat supply network trend constraint condition, allows to establish heat supply network The coupled relation of active power and the active power of power grid, therefore the electric-thermal coupling for the multipotency streaming system that can be coupled by electric-thermal The minimum value of the objective function of the multipotency streaming system of electric-thermal coupling under conjunction constraint condition sn random scene of solution, and according to The minimum value of the corresponding objective function of sn random scene determines the value-at-risk of the multipotency streaming system of electric-thermal coupling, so that The wattful power more than agreement of being incorporated into the power networks is interacted with the power of external electrical network when the multipotency streaming system operation of the electric-thermal coupling of solution The value-at-risk of rate threshold value is more acurrate.And the stochastic model for establishing the multipotency streaming system of electric-thermal coupling shortens assessment week Phase.In addition, the stochastic model of the multipotency streaming system operation of electric-thermal coupling considers cogeneration units, electric energy storage device, heat Energy storage device, electric load, thermic load and photovoltaic plant Optimized Operation on the uncertain influence of risk assessment, to improve The accuracy of the risk assessment of the multipotency streaming system of electric-thermal coupling.
On the basis of above-mentioned each technical solution, the stochastic model of the multipotency streaming system operation of electric-thermal coupling includes electricity- The predicted value of the power generation active power of the following one day each scheduling instance of the multipotency streaming system of thermal coupling and electric load active power Predicted value, specifically:
Epv(t)~N (μpv(t),δpv(t)2) (1.1)
Ee(t)~N (μe(t),δe(t)2) (1.2)
Ppv(t)=PFpv(t)+Epv(t) (1.3)
Pe(t)=PFe(t)+Ee(t) (1.4)
Wherein, t is following one day t-th scheduling instance, t=1, for the scheduling instance that 2 ..., T, T are following one day Number, PFpvIt (t) is the predicted value of t-th of scheduling instance power generation active power, PFe(t) active for t-th of scheduling instance electric load The predicted value of power, EpvIt (t) is the deviation of the predicted value of t-th of scheduling instance power generation active power, EeFor t-th of scheduling instance The deviation of the predicted value of electric load active power, μpvIt (t) is the deviation of the predicted value of t-th of scheduling instance power generation active power Desired value, δpvIt (t) is the standard deviation of the prediction deviation of the predicted value of t-th of scheduling instance power generation active power, μeIt (t) is t The desired value of the deviation of the predicted value of a scheduling instance electric load active power, δe(t) active for t-th of scheduling instance electric load The standard deviation of the prediction deviation of the predicted value of power, PpvIt (t) is t-th of scheduling instance power generation active power, Pe(t) it is t-th Scheduling instance electric load active power.
Specifically, formula (1.1) is that t-th of scheduling instance power generation that electric-thermal couples multipotency streaming system in assessment cycle has The deviation of the predicted value of function power, formula (1.2) are t-th of scheduling instance that electric-thermal couples multipotency streaming system in assessment cycle The deviation of the predicted value of electric load active power.Formula (1.1) and formula (1.2) obey Beta distribution.Formula (1.3) is assessment T-th of scheduling instance power generation active power of electric-thermal coupling multipotency streaming system can pass through electric-thermal coupling in assessment cycle in period The deviation for closing the predicted value of t-th of scheduling instance power generation active power of multipotency streaming system and the predicted value of power generation active power obtains It arrives, formula (1.4) is that t-th of the scheduling instance electric load active power that electric-thermal couples multipotency streaming system in assessment cycle can be with The predicted value of t-th of scheduling instance electric load active power of multipotency streaming system is coupled by electric-thermal in assessment cycle and electricity is born The deviation of the predicted value of lotus active power obtains.It is possible thereby to obtain electric-thermal coupling multipotency streaming system in assessment cycle in advance T-th of scheduling instance power generation active power and electric load active power couple multipotency for use in electric-thermal in assessment assessment cycle The value-at-risk of streaming system.The active-power P in addition, t-th of scheduling instance generates electricitypv(t) it can be coupled in multipotency streaming system for electric-thermal Photovoltaic power generation output power generation active power.
In addition, stochastic model can also include thermic load active power predicted value, specifically:
Ph,1(t)~Beta (A=10, B=10 (Pmax/Phf,1(t)-1))
Ph,2(t)~Beta (A=10, B=10 (Pmax/Phf,2(t)-1))
...
Ph,L1(t)~Beta (A=10, B=10 (Pmax/Phf,L1(t)-1))
Wherein, Phf,1(t)、Phf,2(t)、...、Phf,L1(t) t-th of tune of each thermic load that sum is L1 is respectively indicated Spend the prediction active power at moment, Ph,1(t)、Ph,2(t)、...、Ph,L1(t) t-th of scheduling instance of each thermic load is respectively indicated Active power, PmaxThe maximum power of total heat duties in multipotency streaming system is coupled for electric-thermal, it is (A, B) that thermic load, which obeys parameter, Beta distribution.Electric-thermal in assessment cycle can be obtained in advance by the stochastic model of thermic load couples multipotency streaming system T-th of scheduling instance thermic load power, for use in the value-at-risk of electric-thermal coupling multipotency streaming system in assessment assessment cycle.
Specifically, Fig. 4 is that a kind of electric-thermal provided in an embodiment of the present invention couples multipotency streaming system using thermic load wattful power The result schematic diagram of the stochastic model fitting of rate predicted value.As shown in figure 4, the thermic load data of electric-thermal coupling multipotency streaming system Thermic load data including a period of time, the thermic load data for example including September in June-, and daily thermic load data are with difference The bar chart of scheduling instance indicates, schematically illustrates the thermic load data of four scheduling instances in one day in Fig. 4.Thermic load The stochastic model of active power predicted value couples the thermic load data Fitting Analysis of multipotency streaming system to the electric-thermal, and marks to it Standardization obtains matched curve 102.As shown in Figure 4, using the stochastic model of thermic load active power predicted value to the electric-thermal coupling The heat that the matched curve 102 that the thermic load data of conjunction multipotency streaming system are fitted couples multipotency streaming system with electric-thermal is negative The fitting of lotus data is preferable, therefore, the stochastic model accuracy ratio of thermic load active power predicted value provided in an embodiment of the present invention It is higher.
On the basis of the various embodiments described above, Fig. 5 is the multipotency stream of another electric-thermal coupling provided in an embodiment of the present invention The flow chart of the methods of risk assessment of system, as shown in figure 5, the S120 step in Fig. 1 may include:
S121, the one day T for the including schedulable moment of multipotency streaming system for determining electric-thermal coupling.
Specifically, one day can be the assessment cycle of the multipotency streaming system of electric-thermal coupling, in different scheduling in one day It carves, the power grid of the multipotency streaming system of electric-thermal coupling and the active power of heat supply network are different, therefore can be by being divided into T for one day The schedulable moment so as to more accurately to electric-thermal coupling multipotency streaming system in active power be scheduled.
S122, it is determined often according to the number of the thermic load of the multipotency streaming system of the number and electric-thermal at schedulable moment coupling The dimension of a random scene, the dimension w of each random scene are w=T (2+L1)；Wherein, T is at one day schedulable moment Number, L1 are the number of thermic load.
Specifically, power generation active power, electric load when the multipotency streaming system operation that random scene is not only coupled with electric-thermal Active power is related with thermic load active power, and the scheduling instance of the multipotency streaming system operation also coupled with electric-thermal is related.Each Scheduling instance can have different power generation active power, electric load active power and thermic load active power, therefore, each The dimension of random scene can be w.
The stochastic model that S123, the multipotency streaming system that electric-thermal coupling is solved by SN times are run, forms SN random field Scape.
Multiple random scenes in order to obtain can carry out the stochastic model for the multipotency streaming system operation that electric-thermal couples It solves, the stochastic model for the multipotency streaming system operation that electric-thermal couples can specifically be solved by generating random number. One random scene can be solved to obtain by (2+L1) a formula of stochastic model in different scheduling instances, therefore, One random scene can be solved to obtain by w random number to stochastic model.Illustratively, w random number is generated, And the stochastic model of the multipotency streaming system operation of electric-thermal coupling is solved, w value is obtained, w value forms a vectorAs a random scene, wherein For electric-thermal coupling multipotency streaming system operation stochastic model according to the cumulative distribution letter after the requirement discretization of computational accuracy Number, rand1, rand2,...,randwFor w random number, is solved by bringing random number into cumulative distribution function, obtain one Random scene.Under normal circumstances, random scene SC1In element can be according to the power generation of preceding T scheduling instance of T element representation Active power, the electric load active power of T scheduling instance of T element representation thereafter, T element representation T tune thereafter The active power of first thermic load at moment is spent, second thermic load of T scheduling instance of T element representation thereafter has Function power, and so on.By generate SN w random number, to electric-thermal couple multipotency streaming system run with SN iterative solution of machine model, obtains SN random scene.Ordinary circumstance solves the multipotency of electric-thermal coupling by random number The random scene that the stochastic model of streaming system operation generates has randomness, therefore part random scene does not have representativeness. Sn representative random scenes in order to obtain, meet the accuracy of risk assessment, SN random scene number of generation is big In sn random scene number, in order to filter out sn representative random scene.
S124, scene reduction is carried out to SN random scene, obtains sn random scene, wherein SN is integer, and SN is big In sn.
Specifically, when cutting down SN random scene, scene reduction can be carried out using the method for cluster, obtained Sn representative random scenes, and sn obtained random scene have in SN random scene it is different general Rate.Illustratively, carrying out the probability of the sn random scene obtained after scene reduction using the method for cluster is respectively p1, p2, psn.In addition, in order to meet the accuracy requirement of risk assessment, when the sn random scene that needs are representative When, the SN random scene generated at random needs enough.It is illustratively 1000 it is necessary to have representative random scene When, the random scene generated at random can be 10000.
On the basis of above-mentioned each technical solution, heat supply network trend constraint condition are as follows:
Wherein, A is incidence matrix, thereon incidence matrixWith lower incidence matrixA:
Wherein, i=1,2 ... N, N are the serial number of node, and j=1,2 ... B, B are the serial number of branch, CpFor heat supply network heat transfer mediator Specific heat capacity, ATFor the transposition of incidence matrix A, m is the heat flow of a branch in B branch, and the subscript of m indicates branch Serial number, M are the vector of the flow composition of B branch, TnFor the vector of each node temperature composition of heat supply network, TeFor each branch end of heat supply network The vector of the temperature composition at end, TaFor environment temperature, QJFor the vector that the thermic load of each node of heat supply network forms, C is with each branch Diagonal matrix of the pipeline heat loss coefficient as diagonal element, λ are the unit length thermal conductivitys of each branch of heat supply network, and the subscript of λ indicates branch Serial number, L is the length of each branch of heat supply network, and the subscript of L indicates the serial number of branch.
Specifically, in the multipotency streaming system work of electric-thermal coupling, the vector T of each node temperature composition of heat supply networkn, heat supply network The vector T of the temperature composition of each branch endeVector M with the flow composition of B branch is controllable amount, by controlling Three amounts realize the control of the active power of heat supply network.In addition, the vector Q that the thermic load of each node of heat supply network formsJWith hot spot coproduction Unit is related to the active power of power grid, therefore, the vector Q being made up of the thermic load of each node of heat supply networkJIt can be realized electric-thermal The electric-thermal of the multipotency streaming system of coupling couples.
On the basis of above-mentioned each technical solution, constraint condition can also include that cogeneration units run constraint condition, Cogeneration units run constraint condition are as follows:
Wherein, t is following one day t-th scheduling instance, t=1, for the scheduling instance that 2 ..., T, T are following one day Number, s are s-th of cogeneration units in S cogeneration units, and Ds is the vertex of the feasible zone of s-th of cogeneration units Number, (Pd,s(t),Qd,s(t)), d=1,2...DsFor the feasible zone of s-th of cogeneration units t-th of scheduling instance The coordinate on vertex, (ps(t),qsIt (t)) is a bit in the feasible zone of s-th of cogeneration units, t-th of scheduling instance, kd,s It (t) is the coordinate (P on the vertex of the feasible zone of s-th of cogeneration units, t-th of scheduling instanced,s(t),Qd,s(t)), d=1, 2...DsWeight, p1(t)、p2(t)、...、pS(t) active for the electric load of t-th of scheduling instance of each cogeneration units Power, q1(t)、q2(t)、...、qSIt (t) is the thermic load active power of each cogeneration units.
Specifically, in cogeneration units, each cogeneration units all have multiple constraint conditions, such as thermoelectricity connection Produce the maximum active power of unit generation.The constraint condition of cogeneration units indicates by the mode of feasible zone, feasible zone it is every A side is a constraint condition of hot spot coproduction unit.Therefore, the point for the feasible zone that the constraint condition of cogeneration units is formed It is all satisfied the constraint condition of cogeneration units.
Furthermore, it is contemplated that the variation of the active power of hot spot coproduction unit is a process in actual motion, and therefore, heat Electricity Federation produces the constraint condition that unit operation constraint condition can also include the climbing of cogeneration units active power, i.e., are as follows:
S=1,2...S
Wherein, RAMPs downAnd RAMPs upUpward, the downward climbing speed of respectively s-th cogeneration units active power The maximum value of rate, time difference of the Δ t between t-th of scheduling instance and the t-1 scheduling instance, ps(t) and ps(t-1) respectively For s-th of cogeneration units t-th of scheduling instance and the t-1 scheduling instance active power.
On the basis of above-mentioned each technical solution, the constraint condition of the multipotency streaming system of electric-thermal coupling further includes electric-thermal coupling The constraint condition of electric energy storage device and hot energy storage device in the multipotency streaming system of conjunction, are as follows:
0≤Pdis(t)≤Pdmax, 0≤Pchar(t)≤Pcmax
0≤SoC(t)≤SoCmax
SoC (t)=SoC (t-1)-Pdis(t)+Pchar(t), t=2,3 ..., T
Wherein, t is following one day t-th scheduling instance, t=1, for the scheduling instance that 2 ..., T, T are following one day Number, E are the number of electric energy storage device, PdisIt (t) is total discharge power of t-th of scheduling instance all E electric energy storage devices, PcharIt (t) is total charge power of t-th of scheduling instance all E electric energy storage devices, PdmaxFor the maximum value of total discharge power, PcmaxFor the maximum value of total charge power, SoC (t) is all E total storage states of electric energy storage device of t-th of scheduling slot, SoCmaxFor the maximum value of the stored energy capacitance of all E electric energy storage devices.
The constraint condition of H hot energy storage devices are as follows:
0≤Qdis,hh(t)≤Qdmax,hh, 0≤Qchar,hh(t)≤Qcmax,hh,0≤EHhh(t)≤EHmax,hh
EHhh(t)=EHhh(t-1)+Qchar,hh(t)-Qdis,hh(t)
Hh=1,2 ..., H
Wherein, H is the number of hot energy storage device, Qdis,hhIt (t) is the heat release function of each hot energy storage device of t-th of scheduling instance Rate, Qdmax,hhFor the heat release power maximum value of each hot energy storage device, Qchar,hh(t) it is inhaled for each hot energy storage device of t-th of scheduling instance Thermal power, Qcmax,hhFor the Endothermic power maximum value of each hot energy storage device, EHhhIt (t) is each hot energy storage device of t-th of scheduling instance Heat accumulation state, EHmax,hhFor the maximum value of each hot energy storage device heat storage capacity.
Specifically, either electric energy storage device or hot energy storage device, each energy storage device have its maximum stored energy capacitance, Therefore, the constraint condition of each energy storage device includes that its energy storage is less than or equal to its maximum stored energy capacitance.Also, E electricity storage Total energy storage of energy equipment is less than the sum of the maximum stored energy capacitance of each electric energy storage device, and total energy storage of H hot energy storage devices is less than The sum of the maximum stored energy capacitance of each hot energy storage device.
In addition, constraint condition can also include the tide for the interconnection that thermo-electrically coupling multipotency streaming system is connect with external electrical network Stream constraint.If the symbol that external electrical network flows into the active power of thermo-electrically coupling multipotency streaming system is positive, thermo-electrically couples multipotency stream The symbol that system flows into the active power of external electrical network is negative, and flows into thermo-electrically from external electrical network by interconnection and couples multipotency stream It is zero that the active power of system, which couples the sum of the active power of multipotency streaming system inflow external electrical network with from thermo-electrically, i.e.,
Ppv(t)+Pe(t)+ps(t)+Ptie(t))=0
Wherein, PtieIt (t) is the active power transmitted on t-th of scheduling instance interconnection, Ppv(t) multipotency is coupled for thermo-electrically T-th of scheduling instance power generation active power of streaming system, Pe(t) t-th of scheduling instance electric load of multipotency streaming system is coupled for thermo-electrically Active power, pSIt (t) is the electric load active power of t-th of scheduling instance of each cogeneration units.Moreover, Ptie(t) being can The amount of control.Therefore, by adjusting Ptie(t) active power balance in thermo-electrically coupling multipotency streaming system is realized.
On the basis of above-mentioned each technical solution, cost function are as follows:
Wherein, Hprices(t) the timesharing valence of unit thermal power is issued for s-th of cogeneration units, t-th of scheduling instance Lattice, EpricesIt (t) is the timesharing price of the sending specific electric power of s-th of cogeneration units, t-th of scheduling instance, Ctie (t) it is
Ctie(t)=Price_n (t) * Ptie1(t)+Price_ex*Ptie2(t)
Ptie(t)=Ptie1(t)+Ptie2(t)
0≤Ptie1(t)≤Ptie_limit
0≤Ptie2(t)
Wherein, CtieThe interconnection purchases strategies that multipotency streaming system is connect with external electrical network, P are coupled for thermo-electricallytie1For electricity- The permitted imbalance power threshold value of interconnection, P when the multipotency streaming system of thermal coupling is grid-connectedtie2It is permitted more than interconnection The Partial Power of imbalance power threshold value, Price_n (t) be the permitted imbalance power of interconnection in threshold value when contact Tou power price on line, Price_ex are the punishment electricity price more than the permitted imbalance power threshold portion of interconnection, Ptie_limitFor the upper limit of the power of interconnection carrying.
Specifically, the active power on the interconnection between thermo-electrically coupling multipotency streaming system and external electrical network is provided with one Threshold value, when thermo-electrically, which couples the active power on the interconnection between multipotency streaming system and external electrical network, is more than this threshold value, outside Portion's power grid can carry out punishment price adjustment to the active power for being more than threshold value, and the value of cost function will increase, while electric-thermal coupling is more Energy streaming system can impact the stabilization of external electrical network, therefore can pass through the value of cost function and analyze the more of electric-thermal coupling The risk of the active power threshold value more than agreement of being incorporated into the power networks is interacted when energy streaming system operation with the power of external electrical network.In addition, Using cost function as objective function, the target of the corresponding different scheduling instances of sn random scene can be solved using interior point method Functional minimum value.Illustratively, the solution of the minimum value of the objective function of the corresponding different scheduling instances of sn random scene is
Γ1(t),Γ2(t),...,Γsn(t), t=1,2 ..., T
Wherein, Γ1(t),Γ2(t),...,Γsn(t) real power component of the interconnection in is successively denoted as Tie1(t), Tie2(t) ..., Tiesn(t), as sn random scene sn random scene when objective function obtains minimum value is corresponding The active power on interconnection that the multipotency streaming system of electric-thermal coupling is connect with external electrical network.
In addition, the methods of risk assessment of the multipotency streaming system coupled by electric-thermal obtains the electric-thermal coupling of each scheduling instance The interconnection active power probability distribution of the multipotency streaming system of conjunction can be indicated using confidence interval.Fig. 6 is that the present invention is real A kind of interconnection active power probability distribution schematic diagram of the multipotency streaming system of electric-thermal coupling of example offer is provided, as shown in fig. 6, Different confidence intervals, the active power probability distribution on the interconnection of identical scheduling instance are different.
Based on the above technical solution, Fig. 7 is the multipotency stream of another electric-thermal coupling provided in an embodiment of the present invention The flow chart of the methods of risk assessment of system, as shown in fig. 7, the S150 step in Fig. 1 can specifically include:
S151, the probability that sn random scene occurs is determined.
Specifically, sn random scene is representative scene, the random scene for example including fine day, cloudy day. The probability that different random scenes occurs is also unequal, it is therefore desirable to determine the probability that different random scenes occurs.It is exemplary Ground can determine that the probability that different random scenes occurs, the probability that sn random scene occurs are respectively by statistical method p11, p12, p1sn。
S152, sn random scene is determined according to the minimum value of the objective function of sn random scene of a certain scheduling instance In the value-at-risk of the scheduling instance.
Specifically, in the minimum value for solving the objective function of some random scene of a certain scheduling instance, solution is obtained The active power on interconnection that corresponding thermo-electrically coupling multipotency streaming system is connect with external electrical network when minimum value.It is exemplary Ground, the solution Γ of the minimum value of the objective function of the corresponding different scheduling instances of n random scene1(t),Γ2(t),...,Γsn (t) real power component of the interconnection in is successively denoted as Tie1(t), Tie2(t) ..., Tiesn(t).Under normal circumstances, heat- The active power being electrically coupled on the interconnection that multipotency streaming system is connect with external electrical network couples the risk of multipotency streaming system with thermo-electrically Value is related, therefore can couple what multipotency streaming system was connect with external electrical network by the corresponding thermo-electrically of minimum value of objective function Active power on interconnection calculates some random scene in the risk of the thermo-electrically coupling multipotency streaming system of a certain scheduling instance Value.Illustratively, the active power on interconnection that thermo-electrically coupling multipotency streaming system is connect with external electrical network is coupled with thermo-electrically Relationship between the value-at-risk of multipotency streaming system is Risk (Tiei(t)), wherein Risk is a function, such as can be direct ratio Example function, therefore the active power that can be coupled by thermo-electrically on the interconnection that multipotency streaming system is connect with external electrical network uses Risk function acquires corresponding random scene in the value-at-risk of the thermo-electrically coupling multipotency streaming system of a certain scheduling instance.Cause The probability that different random scenes occurs is also different, therefore, is calculating some random scene in the value-at-risk of a certain scheduling instance When need the probability occurred multiplied by corresponding some scene.I.e. some random scene is in the value-at-risk of a certain scheduling instance Risk(Tiei(t))·p1i, wherein i=1,2, sn.
S153, the probability calculation occurred according to the value-at-risk of sn random scene of same scheduling instance and sn scene The value-at-risk of a certain scheduling instance of the multipotency streaming system of electric-thermal coupling.
Specifically, when each random scene is after the value-at-risk of a certain scheduling instance is calculated, to each random scene It sums in the value-at-risk of a certain scheduling instance, the risk of a certain scheduling instance of the multipotency streaming system of electric-thermal coupling can be obtained Value.That is the value-at-risk of a certain scheduling instance of the multipotency streaming system of electric-thermal coupling is Rsktie(t)=∑ Risk (Tiei(t))· pi, wherein the equation left side is the value-at-risk of a certain scheduling instance of the multipotency streaming system of electric-thermal coupling, is each on the right of equation Random scene is summed in the value-at-risk of a certain scheduling instance.In addition, different scheduling instance value-at-risks may be different, therefore different Scheduling instance needs be respectively calculated.
The embodiment of the present invention also provides a kind of risk assessment device of the multipotency streaming system of electric-thermal coupling.Fig. 8 is the present invention The structural schematic diagram of the risk assessment device of the multipotency streaming system for a kind of electric-thermal coupling that embodiment provides, as shown in figure 8, should Device includes:
Stochastic model establishes module 10, the stochastic model of the multipotency streaming system operation for establishing electric-thermal coupling.
Random scene generation module 20, sn of the multipotency streaming system for generating electric-thermal coupling according to stochastic model Random scene；Wherein, sn is integer, and sn is greater than 1.
Constraint condition and cost function establish module 30, the constraint condition of the multipotency streaming system for establishing electric-thermal coupling And cost function；Wherein, constraint condition includes heat supply network trend constraint condition；
Objective function solves module 40, using cost function as objective function, solves sn random field according to constraint condition The minimum value of the corresponding objective function of scape.
Specifically, it may include that constraint condition establishes module and cost function that constraint condition and cost function, which establish module 30, Module is established, it may include multiple submodule that constraint condition, which establishes module, can establish different constraint condition.
Risk determining module 50, for determining electric-thermal coupling according to the minimum value of the corresponding objective function of sn random scene The value-at-risk of the multipotency streaming system of conjunction.
The technical solution of the present embodiment establishes the multipotency streaming system fortune that module establishes electric-thermal coupling by stochastic model Capable stochastic model, and the multipotency streaming system that electric-thermal couples is generated according to stochastic model by random scene generation module Sn random scene, while the multipotency streaming system that module establishes electric-thermal coupling is established by constraint condition and cost function Constraint condition and cost function, wherein constraint condition includes heat supply network trend constraint condition, allows to establish the wattful power of heat supply network The coupled relation of rate and the active power of power grid, therefore the multipotency that module is coupled by electric-thermal can be solved using objective function The electric-thermal coupling constraint condition of streaming system solves the objective function of the multipotency streaming system of the electric-thermal coupling under sn random scene Minimum value, and electric-thermal coupling is determined according to the minimum value of the corresponding objective function of sn random scene by risk determining module The value-at-risk of the multipotency streaming system of conjunction, so that when the multipotency streaming system operation of the electric-thermal coupling solved and external electrical network Power interaction is more acurrate more than the value-at-risk of the active power threshold value for agreement of being incorporated into the power networks.And establish the more of electric-thermal coupling The stochastic model of energy streaming system, shortens assessment cycle.In addition, the randomness mould of the multipotency streaming system operation of electric-thermal coupling Type considers the Optimized Operation of cogeneration units, electric energy storage device, hot energy storage device, electric load, thermic load and photovoltaic plant On the uncertain influence of risk assessment, to improve the accuracy of the risk assessment of the multipotency streaming system of electric-thermal coupling.
The embodiment of the present invention also provides a kind of computer readable storage medium, is stored thereon with computer program, the program The methods of risk assessment of the multipotency streaming system of any electric-thermal coupling provided in an embodiment of the present invention is realized when being executed by processor, Therefore the beneficial effect of the methods of risk assessment of the multipotency streaming system with electric-thermal provided in an embodiment of the present invention coupling, herein It repeats no more.
Note that the above is only a better embodiment of the present invention and the applied technical principle.It will be appreciated by those skilled in the art that The invention is not limited to the specific embodiments described herein, be able to carry out for a person skilled in the art it is various it is apparent variation, It readjusts and substitutes without departing from protection scope of the present invention.Therefore, although being carried out by above embodiments to the present invention It is described in further detail, but the present invention is not limited to the above embodiments only, without departing from the inventive concept, also It may include more other equivalent embodiments, and the scope of the invention is determined by the scope of the appended claims.

Claims (13)

1. a kind of methods of risk assessment of the multipotency streaming system of electric-thermal coupling characterized by comprising
Establish the stochastic model of the multipotency streaming system operation of electric-thermal coupling；
Sn random scene of the multipotency streaming system of the electric-thermal coupling is generated according to the stochastic model；Wherein, sn is whole Number, and sn is greater than 1；
Establish the constraint condition and cost function of the multipotency streaming system of the electric-thermal coupling；Wherein, the constraint condition includes heat Net trend constraint condition；
Using the cost function as objective function, the corresponding target of the sn random scene is solved according to the constraint condition Functional minimum value；
The multipotency streaming system of the electric-thermal coupling is determined according to the minimum value of the corresponding objective function of the sn random scene Value-at-risk.
2. the methods of risk assessment of the multipotency streaming system of electric-thermal coupling according to claim 1, which is characterized in that described The stochastic model of the multipotency streaming system operation of electric-thermal coupling includes that multipotency streaming system following one day of the electric-thermal coupling is each The stochastic model of the stochastic model of the predicted value of the power generation active power of scheduling instance, the predicted value of electric load active power With the stochastic model of thermic load active power predicted value, the stochastic model of predicted value of the power generation active power and described The stochastic model of the predicted value of electric load active power specifically:
Epv(t)~N (μpv(t), δpv(t)2)
Ee(t)~N (μe(t), δe(t)2)
Ppv(t)=PFpv(t)+Epv(t)
Pe(t)=PFe(t)+Ee(t)
Wherein, t is following one day t-th scheduling instance, and t=1,2 ..., T, T are the number of the scheduling instance in one day future, PFpvIt (t) is the predicted value of t-th of scheduling instance power generation active power, PFeIt (t) is t-th of scheduling instance electric load active power Predicted value, EpvIt (t) is the deviation of the predicted value of t-th of scheduling instance power generation active power, EeIt is negative for t-th of scheduling instance electricity The deviation of the predicted value of lotus active power, μpvIt (t) is the expectation of the deviation of the predicted value of t-th of scheduling instance power generation active power Value, δpvIt (t) is the standard deviation of the prediction deviation of the predicted value of t-th of scheduling instance power generation active power, μeIt (t) is t-th of tune Spend the desired value of the deviation of the predicted value of moment electric load active power, δeIt (t) is t-th of scheduling instance electric load active power Predicted value prediction deviation standard deviation, PpvIt (t) is t-th of scheduling instance power generation active power, PeIt (t) is t-th of scheduling Moment electric load active power；
The stochastic model of the thermic load active power predicted value specifically:
PH, 1(t)~Beta (A=10, B=10 (Pmax/PHf, 1(t)-1))
PH, 2(t)~Beta (A=10, B=10 (Pmax/PHf, 2(t)-1))…
PH, L1(t)~Beta (A=10, B=10 (Pmax/PHf, Ll(t)-1))
Wherein, PHf, 1(t)、PHf, 2(t)、...、PHf, L1(t) when respectively indicating t-th of scheduling of each thermic load that sum is L1 The prediction active power at quarter, Px, 1(t)、PH, 2(t)、...、PH, L1(t) having for t-th of scheduling instance of each thermic load is respectively indicated Function power, PmaxThe maximum power of total heat duties in multipotency streaming system is coupled for electric-thermal.
3. the methods of risk assessment of the multipotency streaming system of electric-thermal coupling according to claim 1, which is characterized in that described Include: according to the sn random scene that the stochastic model generates the multipotency streaming system of the electric-thermal coupling
Determine the one day T for including schedulable moment of multipotency streaming system of the electric-thermal coupling；
The number of the thermic load of the multipotency streaming system coupled according to the number at the schedulable moment and the electric-thermal determines each The dimension of the random scene, the dimension w of each random scene are w=T (2+L1)；Wherein, T is one day described schedulable The number at moment, L1 are the number of the thermic load；
The stochastic model that the multipotency streaming system operation of the electric-thermal coupling is solved by SN times, forms SN random scene；
Scene reduction is carried out to the SN random scenes, obtains the sn random scenes, wherein SN is integer, and SN is big In sn.
4. the methods of risk assessment of the multipotency streaming system of electric-thermal coupling according to claim 1, which is characterized in that described Heat supply network trend constraint condition are as follows:
Wherein, A is incidence matrix, thereon incidence matrixWith lower incidence matrixA:
Wherein, i=1,2...N, N are the serial number of node, and j=1,2...B, B is the serial number of branch, CpFor heat supply network heat transfer mediator Specific heat capacity, ATFor the transposition of incidence matrix A, m is the heat flow of a branch in B branch, and the subscript of m indicates the sequence of branch Number, M is the vector of the flow composition of B branch, TnFor the vector of each node temperature composition of heat supply network, Te is each branch end of heat supply network Temperature composition vector, Ta is environment temperature, QJFor the vector that the thermic load of each node of heat supply network forms, C is with each branch Diagonal matrix of the pipeline heat loss coefficient as diagonal element, λ are the unit length thermal conductivitys of each branch of heat supply network, and the subscript of λ indicates branch Serial number, L is the length of each branch of heat supply network, and the subscript of L indicates the serial number of branch.
5. the methods of risk assessment of the multipotency streaming system of electric-thermal coupling according to claim 1, which is characterized in that described Constraint condition further includes cogeneration units operation constraint condition, and the cogeneration units run constraint condition are as follows:
Wherein, t is following one day t-th scheduling instance, t=1, the number for the scheduling instance that 2 ..., T, T are following one day, s For s-th of cogeneration units in the S cogeneration units, Ds is the feasible of s-th of cogeneration units The number on the vertex in domain, (PD, s(t), QD, s(t)), d=1,2...DsWhen for s-th of cogeneration units, t-th of scheduling The coordinate on the vertex of the feasible zone at quarter, (ps(t), qsIt (t)) is the feasible of s-th of cogeneration units, t-th of scheduling instance In domain a bit, kD, sIt (t) is the coordinate (P on the vertex of the feasible zone of s-th of cogeneration units, t-th of scheduling instanceD, s (t), QD, s(t)), d=1,2...DsWeight, p1(t)、p2(t)、...、ps(t) it is t-th of each cogeneration units The electric load active power of scheduling instance, q1(t)、q2(t)、...、qs(t) have for the thermic load of each cogeneration units Function power.
6. the methods of risk assessment of the multipotency streaming system of electric-thermal coupling according to claim 5, which is characterized in that described Cogeneration units operation constraint condition further includes the constraint condition of the cogeneration units active power climbing, i.e., are as follows:
S=1,2...S
Wherein, RAMPs downAnd RAMPs upUpward, the downward creep speed of respectively s-th cogeneration units active power Maximum value, time difference of the Δ t between t-th of scheduling instance and the t-1 scheduling instance, ps(t) and psIt (t-1) is respectively s Active power of a cogeneration units in t-th of scheduling instance and the t-1 scheduling instance.
7. the methods of risk assessment of the multipotency streaming system of electric-thermal coupling according to claim 1, which is characterized in that described The constraint condition of the multipotency streaming system of electric-thermal coupling further includes the electric energy storage device in the multipotency streaming system of the electric-thermal coupling With the constraint condition of hot energy storage device, are as follows:
0≤Pdis(t)≤Pdmax, 0≤Pchar(t)≤Pcmax
0≤SoC(t)≤SoCmax
SoC (t)=SoC (t-1)-Pdis(t)+Pchar(t), t=2,3 ..., T
Wherein, t is following one day t-th scheduling instance, t=1, the number for the scheduling instance that 2 ..., T, T are following one day, E For the number of electric energy storage device, PdisIt (t) is total discharge power of t-th of scheduling instance all E electric energy storage devices, Pchar(t) For total charge power of t-th of scheduling instance all E electric energy storage devices, PdmaxFor the maximum value of total discharge power, PcmaxIt is total The maximum value of charge power, SoC (t) are all E total storage states of electric energy storage device of t-th of scheduling slot, SoCmaxIt is all The maximum value of the stored energy capacitance of E electric energy storage device；
The constraint condition of H hot energy storage devices are as follows:
0≤QDis, hh(t)≤QDmax, hh, 0≤QChar, hh(t)≤QCmax, hh, 0≤EHhh(t)≤EHMax, hh
EHhh(t)=EHhh(t-1)+QChar, hh(t)-QDis, hh(t)
Hh=1,2 ..., H
Wherein, H is the number of hot energy storage device, QDis, hhIt (t) is the heat release power of each hot energy storage device of t-th of scheduling instance, QDmax, hhFor the heat release power maximum value of each hot energy storage device, QChar, hhIt (t) is each hot energy storage device heat absorption of t-th of scheduling instance Power, QCmax, hhFor the Endothermic power maximum value of each hot energy storage device, EHhhIt (t) is each hot energy storage device of t-th of scheduling instance Heat accumulation state, EHMax, hhFor the maximum value of each hot energy storage device heat storage capacity.
8. the methods of risk assessment of the multipotency streaming system of electric-thermal coupling according to claim 1, which is characterized in that described The constraint condition of the multipotency streaming system of electric-thermal coupling further includes that the thermo-electrically coupling multipotency streaming system is connect with external electrical network The trend constraint condition of interconnection, specifically:
Ppv(t)+Pe(t)+μs(t)+Ptie(t))=0
Wherein, PtieIt (t) is the active power transmitted on interconnection described in t-th of scheduling instance, ps(t) it is coupled for the thermo-electrically The electric load active power of multipotency streaming system t-th of scheduling instance of cogeneration units.
9. the methods of risk assessment of the multipotency streaming system of electric-thermal coupling according to claim 5, which is characterized in that described Cost function are as follows:
Wherein, Hprices(t) the timesharing valence of unit thermal power is issued for s-th of cogeneration units, t-th of scheduling instance Lattice, EpricesIt (t) is the timesharing price of the sending specific electric power of s-th of cogeneration units, t-th of scheduling instance, Ctie(t) it is
Ctie(t)=Price_n (t) * Ptiel(t)+Price_ex*Ptie2(t)
Ptie(t)=Ptie1(t)+Ptie2(t)
0≤Ptie1(t)≤Ptie_limit
0≤Ptie2(t)
Wherein, CtieThe interconnection purchases strategies that multipotency streaming system is connect with external electrical network, P are coupled for the thermo-electricallytie1It is described The multipotency streaming system of electric-thermal the coupling permitted imbalance power threshold value of interconnection, P when grid-connectedtie2For more than described The Partial Power of the permitted imbalance power threshold value of winding thread, Price_n (t) are the permitted imbalance power of the interconnection The tou power price on interconnection when in threshold value, Price_ex are more than the permitted imbalance power of the interconnection The punishment electricity price of threshold portion, Ptie_limitFor the upper limit of the power of interconnection carrying.
10. the methods of risk assessment of the multipotency streaming system of electric-thermal coupling according to claim 9, which is characterized in that with institute Cost function is stated as objective function, the corresponding objective function of the sn random scene is solved most according to the constraint condition When small value, the minimum value of the objective function of the corresponding different scheduling instances of the sn random scene is solved using interior point method.
11. the methods of risk assessment of the multipotency streaming system of electric-thermal coupling according to claim 10, which is characterized in that institute State the wind that the multipotency streaming system of the electric-thermal coupling is determined according to the minimum value of the corresponding objective function of the sn random scene Nearly value includes:
Determine the probability that the sn random scene occurs；
Each random scene is determined according to the minimum value of the objective function of the sn random scene of a certain scheduling instance In the value-at-risk of the scheduling instance；
The probability calculation institute occurred according to the value-at-risk of the sn random scene of same scheduling instance and the sn scene State the value-at-risk of a certain scheduling instance of the multipotency streaming system of electric-thermal coupling.
12. a kind of risk assessment device of the multipotency streaming system of electric-thermal coupling characterized by comprising
Stochastic model establishes module, the stochastic model of the multipotency streaming system operation for establishing electric-thermal coupling；
Random scene generation module, the sn of the multipotency streaming system for generating the electric-thermal coupling according to the stochastic model A random scene；Wherein, sn is integer, and sn is greater than 1；
Constraint condition and cost function establish module, for establish the multipotency streaming system of electric-thermal coupling constraint condition and Cost function；Wherein, the constraint condition includes heat supply network trend constraint condition；
Objective function solves module, using the cost function as objective function, is solved according to the constraint condition sn described The minimum value of the corresponding objective function of random scene；
Risk determining module, for determining the electric-thermal according to the minimum value of the corresponding objective function of the sn random scene The value-at-risk of the multipotency streaming system of coupling.
13. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is by processor The methods of risk assessment of the multipotency streaming system of the electric-thermal coupling as described in claim 1-11 is any is realized when execution.
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