CN110417048A - A kind of DC grid of consideration source net lotus constraint send receiving end combined adjusting peak optimization method - Google Patents
A kind of DC grid of consideration source net lotus constraint send receiving end combined adjusting peak optimization method Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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Abstract
A kind of DC grid of consideration source net lotus constraint send receiving end combined adjusting peak optimization method, can solve the prior art and " straight line " or " anti-tune peak " transportation program often occurs, bring the technical problem of larger difficulty to receiving end peak load regulation network frequency modulation and method of operation arrangement.The present invention obtains the power output prediction data a few days ago of wind power plant and photovoltaic plant first, power grid sending end power supply is on the basis of meeting local load electricity consumption, the rich electricity of generation is conveyed to power grid receiving end by high voltage direct current interconnection, with the minimum optimization aim of network system total operating cost, with power-balance constraint, the constraint of conventional power generation unit, light constraint is abandoned in abandonment, DC link constraint, stimulable type Demand Side Response is constrained to constraint condition, establish optimal model, obtain access direct current send receiving end each powering device, the operation power programming of high voltage direct current interconnection and receiving end stimulable type Demand Side Response.The present invention not only reduces the use energy cost of user, also improves the complementation and concertedness between various energy resources.
Description
Technical field
The present invention relates to the peak regulation technique fields of electric system, and in particular to a kind of DC grid of consideration source net lotus constraint
Send receiving end combined adjusting peak optimization method.
Background technique
With the rapid development of the new energy such as wind-powered electricity generation and photovoltaic power generation, it is grid-connected that China gradually forms contrary distribution, concentration
The consumption submitting of power supply pattern, new energy is seriously restricted, there is an urgent need to pass through the transregional submitting of high voltage direct current, to expand new energy
Source dissolves range, realizes nationwide most optimum distribution of resources.Generation of electricity by new energy has the characteristics that randomness, intermittence, fluctuation,
There are close coupling relationship, direct current transportation power planning mainly considers the power generation level and direct current transmission power in new energy base at present
System restriction and according to trnamission capacity agreement, the less workload demand for considering receiving end power grid or coordinate consider new energy go out fluctuation and
It sends demand outside, " straight line " or " demodulating peak " transportation program often occurs, arrange band to receiving end peak load regulation network frequency modulation and the method for operation
Larger difficulty is carried out.Sufficiently to excavate peak load regulation network potentiality, expands new energy consumption, promote new energy sustainable and healthy development, build
A kind of vertical DC grid for fully considering the constraint of source net lotus send receiving end combined adjusting peak optimal operation model more and more important.
In current research achievement, receiving end peak regulation model is sent for DC grid, often only simply considers power grid
The traditional constraints such as the constraint of traditional fired power generating unit of sending end and receiving end and active power balance constraint, and about for DC link
The constraint conditions such as beam, generation of electricity by new energy constraint, pump-storage generator constraint, Demand Side Response constraint consider insufficient.Demand-side is rung
It answers technology and hydroenergy storage station as effective new energy consumption means, has obtained the verifying of engineering practice, but rarely have at present
The DC grid for comprehensively considering its combined operating benefit send receiving end combined adjusting peak optimal operation model.
Summary of the invention
A kind of DC grid of consideration source net lotus constraint proposed by the present invention send receiving end combined adjusting peak optimization method, can solve
The less workload demand for considering receiving end power grid of the prior art is coordinated to consider that new energy goes out fluctuation and sends demand outside, causes often
There is " straight line " or " demodulating peak " transportation program, brings larger difficulty to receiving end peak load regulation network frequency modulation and method of operation arrangement
Technical problem.
To achieve the above object, the invention adopts the following technical scheme:
A kind of DC grid of consideration source net lotus constraint send receiving end combined adjusting peak optimization method, comprising the following steps:
S100, the power supply power output model for establishing power grid sending end and receiving end；
S200, the load of DC grid sending end and receiving end prediction data a few days ago is obtained；
S300, power grid receiving end stimulable type Demand Side Response model is established；
S400, DC link power transmission model is established；
S500, foundation send receiving end combined adjusting peak optimal operation model, meet step S100 send receiving end power supply power output model,
Step S300 receiving end stimulable type Demand Side Response model, step S400 DC link transimission power model constraint condition and have
Function power-balance constraint, abandonment are abandoned on the basis of light quantity constraint, with the minimum optimization aim of network system total operating cost, benefit
It is sent with step S200 by end load prediction data a few days ago, solution obtains that the plan of receiving end power supply power output, DC contact linear heat generation rate is sent to pass
The optimization operation result a few days ago of defeated plan and the regulation plan of receiving end stimulable type Demand Side Response, therefrom determines each powering device most
The optimal peaking power source allocation plan of decision is established in excellent operation planning.
Further, in the step S100 power supply of power grid sending end and receiving end power output model include: power grid sending end and by
The generation of electricity by new energy power supply power output model at end, traditional fired power generating unit power output model of power grid sending end and receiving end, power grid receiving end pumping
Water accumulation of energy unit output model.
Further, the step S100 is to establish power grid sending end as follows and the generation of electricity by new energy power supply of receiving end goes out
Power model:
Force data is gone out to wind power plant, photovoltaic plant history and carries out acquisition arrangement, obtains the daily output of wind power plant, photovoltaic plant
Data set carries out clustering to daily output data set monthly using k means clustering algorithm, data set is divided into k cluster,
The cluster centre of each cluster is known as a typical daily output state, and each data sample number for including that clusters characterizes the shape
The probability that state occurs；
Therefore the probability distribution value of comprehensive all historical samples, each state is calculated by formula (1.1):
Wherein, N indicates the number of samples in data set, ljIndicate the number of samples in cluster j；
Thus, have
By divided state S1, S2..., SCA section between [0,1] is corresponded to, siding-to-siding block length is state probability
Value；Equally distributed random number R on [0,1] is extracted using the method for random sampling, affiliated allusion quotation is determined according to the size of random number R
Type daily output state then obtains the random power output model of new energy.
Further, the step S100 is the traditional fired power generating unit power output for establishing power grid sending end and receiving end as follows
Model:
The active power bound that fired power generating unit is subject to is constrained as shown in formula (2.1):
ui,tPi min≤Pi,t≤ui,tPi max (2.1)
In formula, Pi max、Pi minThe active power output bound of respectively i-th conventional power unit, ui,tExist for i-th conventional power unit
The start and stop state of t moment；
Shown in its Climing constant being subject to such as formula (2.2):
-RDi≤(Pi,t-Pi,t-1)/Δt≤RUi (2.2)
In formula, RDi、RUiThe creep speed limitation up and down of respectively i-th conventional power generation unit, Δ t is the duration of t period；
Its start and stop being subject to is constrained as shown in formula (2.3):
In formula, Di、OiThe minimum of respectively i-th conventional power generation unit is shut down and the available machine time.
Further, the step S100 is the pump-storage generator power output model for establishing power grid receiving end as follows:
The active power bound that pumped storage machine and water pump assembly are subject to is constrained as shown in formula (3.1) (3.2):
Pr min≤Pr,t≤Pr max (3.1)
In formula, Pr,tPower output for pumped storage machine in t moment, Pr max、Pr minRespectively pumped-storage power generation machine
The active power output bound of group；Ppld,tPower output for water pump assembly in t moment, Ppld max、Ppld minRespectively water pump assembly has
Function power output bound；
Wherein the power output of water pump assembly is step values:
Ppld,t=pi×n (3.3)
piFor the power that draws water of separate unit water pump；
The water balance that pump-storage generator is subject to is constrained as shown in formula (3.4):
In formula, Vt,Vpld,t,Vr,tThe respectively reservoir storage of t moment reservoir, the pump-out of water pump and the water consumption of generator,
Vt-ΔtFor the reservoir storage of previous moment reservoir, Vmin, VmaxThe respectively minimum and maximum reservoir storage of reservoir.
Further, the step S200 is that the load of acquisition DC grid sending end and receiving end is predicted a few days ago as follows
Data:
According to Season select typical day load curve, load curve is carried out etc. using than amplifying further according to watt level
Interpolation method obtains power grid sending end and by end load prediction data a few days ago.
Further, the step S300 is to establish power grid receiving end stimulable type Demand Side Response model as follows:
Demand-side is transferred shown in expense such as formula (4.1):
In formula, number of segment when T is total, NmFor stimulable type Demand Side Response user volume, ρmValence is compensated for the unit quantity of electricity of user m
Lattice, Pm,tFor the transfer load value of user m, Δ tmDuration is dispatched for unit；
The response quautity that stimulable type Demand Side Response meets is constrained as shown in formula (4.2):
In formula, qm1, qm2..., qmnFor the fixation transfer load value gear of user m, QmFor the peak response capacity of user m
Value；
Shown in the load transfer amount Constraints of Equilibrium such as formula (4.3) that stimulable type Demand Side Response meets:
Further, the step S400 is to establish DC link power transmission model as follows:
Shown in the direct current conveying Constraint such as formula (5.1) that DC link meets:
In formula: t=1,2 ..., T；Pdc,tActive power for DC link in period t, Edc,maxAnd Edc,minRespectively
Maximum of the DC line in planning cycle T, minimum transaction electricity；
The exchange power stepization that DC link meets is constrained as shown in formula (5.2):
Pdc,t∈{Pdc1,Pdc2,...,Pdcn} (5.2)
In formula: Pdc1,Pdc2,…,PdcnGear is adjusted for the constant power of DC link；
Shown in the adjustment spacing constraint such as formula (5.3) that DC link meets:
In formula, ctIt is to indicate whether DC link starts the 0-1 state variable of adjustment in the t period, J is DC link
Minimum adjustment interval；
DC link needs the regulations speed met to constrain as shown in formula (5.4):
In formula: Rdc +And Rdc -The respectively up and down rate limit value of DC link plan；Δ t be the t period when
It is long.
Further, receiving end combined adjusting peak optimal operation model is sent in the step S500 foundation, is sent meeting step S100
Receiving end power supply power output model, step S300 receiving end stimulable type Demand Side Response model, step S400 DC link transimission power
The constraint condition and active power balance constraint of model, are abandoned on the basis of light quantity constraint at abandonment, with network system total operating cost
Minimum optimization aim is sent using step S200 by end load prediction data a few days ago, solution obtain sending the plan of receiving end power supply power output,
The optimization operation result a few days ago of the plan of DC link power transmission and the regulation plan of receiving end stimulable type Demand Side Response, therefrom really
The optimized operation planning of fixed each powering device, establishes the optimal peaking power source allocation plan of decision；
It specifically includes:
The objective function of the optimal operation model is characterized by formula (6.1):
In formula,
Number of segment when T indicates total, n are fired power generating unit quantity；
fi() is the cost of electricity-generating function of i-th fired power generating unit, Pi,tFor i-th unit t moment optimal power output；
miIt is lost for i-th fired power generating unit start and stop, ciFor start-stop time of i-th unit within a cycle of operation；
GwtAbandonment expense for wind park in t moment, GstFor photovoltaic power plant t moment abandoning light expense；
MdcFor DC link t moment power adjustment expense；
The power grid receiving end abandonment abandons light quantity size constraint by formula (6.2) statement:
In formula, gw,t、gs,tRespectively indicate receiving end wind power plant, photovoltaic plant t moment abandonment, abandon light quantity；
The active power balance constraint of the sending end is characterized by formula (6.3):
Pgld,t≤Pgc,t+Pgw,t+Pgs,t-Pdc,t≤(1+α)Pgld,t (6.3)
P in formulagc,tFor sending end conventional power plant power output, the sum of fired power generating unit power output, P are indicatedgw,tIt contributes for sending end wind park,
Pgs,tFor sending end photovoltaic power plant power output, Pgld,tFor sending load, α institute in the range of meeting safety standard for network system
The maximum nargin that can be born；
The active power balance constraint of the receiving end is characterized by formula (6.4):
Pald,t≤Pac,t+Paw,t-gw,t+Pas,t-gs,t+Pdc,t+Pr,t-Ppld,t-Pm,t≤(1+α)Pald, (6.4)
P in formulaac,tFor receiving end conventional power plant power output, the sum of fired power generating unit power output, P are indicatedaw,tFor receiving end wind park power output, gw,t
For receiving end wind power plant abandonment amount, Pas,tFor receiving end photovoltaic power plant power output, gs,tLight quantity, P are abandoned for receiving end photovoltaic plantr,tIt is stored to draw water
Energy generating set power output, Ppld,tIt draws water load for water pump assembly, value is step values, Pm,tFor receiving end stimulable type Demand Side Response,
Pald,tFor Receiving End Load；
The powering device constraint is such as formula (1.1), (1.2), (1.3), (2.1), (2.2), (2.3), (2.4) (3.1)
(3.2) (3.3) (3.4) are represented；
The Demand Side Response constraint is as represented by formula (4.1), (4.2), (4.3)；
The DC link constraint is as represented by formula (5.1), (5.2), (5.3), (5.4)；
Using the obtained new energy for sending receiving end, prediction data, solution obtain each confession a few days ago for prediction data and load a few days ago
The running optimizatin a few days ago of energy equipment, DC contact linear heat generation rate and receiving end stimulable type Demand Side Response is as a result, therefrom determine each energy supply
The optimized operation of equipment is planned, the optimal peaking power source allocation plan of decision is established.
As shown from the above technical solution, the invention discloses a kind of DC grids for fully considering the constraint of source net lotus to send receiving end
Combined adjusting peak optimization method obtains the power output prediction data a few days ago of wind power plant and photovoltaic plant first, and power grid sending end power supply is full
On the basis of the load electricity consumption of foot locality, the rich electricity of generation is conveyed to power grid receiving end by high voltage direct current interconnection, with power grid
The minimum optimization aim of system total operating cost is abandoned light and is constrained, directly with power-balance constraint, the constraint of conventional power generation unit, abandonment
Stream interconnection constraint, stimulable type Demand Side Response be constrained to constraint condition, establish optimal model, obtain access direct current send by
Hold the operation power programming of each powering device, high voltage direct current interconnection and receiving end stimulable type Demand Side Response.
The DC grid of consideration source net lotus constraint of the invention send receiving end combined adjusting peak optimization method to have below beneficial to effect
Fruit:
The DC grid that the present invention constructs send receiving end combined adjusting peak model fully considered DC link, water-storage,
The constraint conditions such as Demand Side Response realize the generating set and DC contact sent in receiving end combined adjusting peak system to DC grid
The optimal scheduling of line transimission power enables generating set to operate in optimal operating condition.
For the present invention on the basis of guaranteeing to send receiving end electric power netting safe running, flexible modulation direct current sends plan outside, arranges direct current
Plan undertakes part peak regulation task, promotes new energy consumption, realizes direct current and send plan, new energy and conventional energy resource outside a few days ago
The coordination optimization of Unit Combination and generation schedule.
While the present invention effectively improves DC grid and send the economy of receiving end combined adjusting peak system, also sufficiently excavate straight
The peak regulation potentiality of galvanic electricity net receiving end Demand Side Response, the peak load shifting and load for realizing electric load are cut down, and use is not only reduced
Energy cost is used at family, also improves the complementation and concertedness between various energy resources.
Detailed description of the invention
Fig. 1 is the flow diagram of the method for the present invention；
Fig. 2 is structural schematic diagram of the invention.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.
As shown in Figure 1, the DC grid of consideration source net lotus constraint described in the present embodiment send receiving end combined adjusting peak optimization side
Method, comprising:
S100, the power supply power output model for establishing power grid sending end and receiving end；
S200, the load of DC grid sending end and receiving end prediction data a few days ago is obtained；
S300, power grid receiving end stimulable type Demand Side Response model is established；
S400, DC link power transmission model is established；
S500, foundation send receiving end combined adjusting peak optimal operation model, meet step S100 send receiving end power supply power output model,
Step S300 receiving end stimulable type Demand Side Response model, step S400 DC link transimission power model constraint condition and have
Function power-balance constraint, abandonment are abandoned on the basis of light quantity constraint, with the minimum optimization aim of network system total operating cost, benefit
It is sent with step S200 by end load prediction data a few days ago, solution obtains that the plan of receiving end power supply power output, DC contact linear heat generation rate is sent to pass
The optimization operation result a few days ago of defeated plan and the regulation plan of receiving end stimulable type Demand Side Response, therefrom determines each powering device most
The optimal peaking power source allocation plan of decision is established in excellent operation planning.
Wherein the power supply power output model of the power grid sending end and receiving end of step S100 includes: the new of power grid sending end and receiving end
The water-storage of traditional fired power generating unit the power output model, power grid receiving end of energy power generating source power output model, power grid sending end and receiving end
Unit output model；
Step S200 obtains the load of DC grid sending end and receiving end prediction data a few days ago；The DC grid sending end and by
Prediction data is to utilize historical load data, and obtain by interpolation method to the load at end a few days ago；
Step S300 establishes power grid receiving end stimulable type Demand Side Response model；The stimulable type Demand Side Response plan refers to
High load capacity industry, to participate in system optimization scheduling, reduces peak period electricity needs, increases low ebb by signing an agreement with power grid
Period electricity needs guarantees safe operation to alleviate power grid pressure.
Step S400 establishes DC link power transmission model；The DC link transmission plan be guarantee give/
Under the premise of receiving end electric power netting safe running, direct current is adjusted flexibly and sends plan outside, direct current plan is arranged to undertake part peak regulation task, with
Promote new energy consumption, realizes that direct current sends the coordination of plan, new energy and conventional energy resource Unit Combination and generation schedule a few days ago outside
Optimization.
Step S500, which is established and solved, send receiving end combined adjusting peak optimal operation model；It is described to send receiving end combined adjusting peak optimization fortune
Row model is with active power balance constraint, abandonment, to abandon light quantity about with the minimum optimization aim of network system total operating cost
Beam, powering device constraint, Demand Side Response constraint, DC link are constrained to constraint condition, and solution obtains that receiving end is sent respectively to energize
The power optimization a few days ago of equipment and DC link is as a result, realize that DC grid send the optimization of receiving end combined adjusting peak model to run.
It is illustrated below in conjunction with Fig. 2:
In specific implementation, the generation of electricity by new energy power supply power output model of power grid sending end and receiving end is established as follows:
Go out force data to wind power plant, photovoltaic plant history to arrange, obtains the sunrise force data of wind power plant, photovoltaic plant
Collection carries out clustering to daily output data set monthly using k means clustering algorithm, data set is divided into k cluster, each
The cluster centre of cluster is known as a typical daily output state, and each data sample number for including that clusters characterizes state hair
Raw probability.
Therefore comprehensive all historical samples, the probability distribution value of each state can be calculated by formula (1.1):
Wherein, N indicates the number of samples in data set, ljIndicate the number of samples in cluster j.
Thus, have
By divided state S1, S2..., SCA section between [0,1] is corresponded to, siding-to-siding block length is state probability
Value.Equally distributed random number R on [0,1] is extracted using the method for random sampling, affiliated allusion quotation is determined according to the size of random number R
Type daily output state then obtains the random power output model of new energy.According to the simulation to random number R, a large amount of wind can be obtained
Electric field, photovoltaic plant are contributed prediction data a few days ago.
The power output situation of the wind-powered electricity generation of sending end and receiving end, photovoltaic power generation is contributed model according to season, watt level by new energy
It provides.
Traditional fired power generating unit power output model of power grid sending end and receiving end is established as follows:
The active power bound that fired power generating unit is subject to is constrained as shown in formula (2.1):
ui,tPi min≤Pi,t≤ui,tPi max (2.1)
In formula, Pi max、Pi minThe active power output bound of respectively i-th conventional power unit, ui,tExist for i-th conventional power unit
The start and stop state of t moment.
Shown in its Climing constant being subject to such as formula (2.2):
-RDi≤(Pi,t-Pi,t-1)/Δt≤RUi (2.2)
In formula, RDi、RUiThe creep speed limitation up and down of respectively i-th conventional power generation unit, Δ t is the duration of t period.
Its start and stop being subject to is constrained as shown in formula (2.3):
In formula, Di、OiThe minimum of respectively i-th conventional power generation unit is shut down and the available machine time.
The pump-storage generator power output model of power grid receiving end is established as follows:
The active power bound that pumped storage machine and water pump assembly are subject to is constrained as shown in formula (3.1) (3.2):
Pr min≤Pr,t≤Pr max (3.1)
In formula, Pr,tPower output for pumped storage machine in t moment, Pr max、Pr minRespectively pumped-storage power generation machine
The active power output bound of group；Ppld,tPower output for water pump assembly in t moment, Ppld max、Ppld minRespectively water pump assembly has
Function power output bound.
Wherein the power output of water pump assembly is step values:
Ppld,t=pi×n (3.3)
piFor the power that draws water of separate unit water pump.
The water balance that pump-storage generator is subject to is constrained as shown in formula (3.4):
In formula, Vt,Vpld,t,Vr,tThe respectively reservoir storage of t moment reservoir, the pump-out of water pump and the water consumption of generator,
Vt-ΔtFor the reservoir storage of previous moment reservoir, Vmin, VmaxThe respectively minimum and maximum reservoir storage of reservoir, then pass through iterative calculation
Can in the hope of the reservoir storage of reservoir, for pressing the reservoir of periodic adjustment, water of drawing water in general a cycle should with water water
It measures in a basic balance.
The load of DC grid sending end and receiving end prediction data a few days ago is obtained as follows:
According to Season select typical day load curve, load curve is carried out etc. using than amplifying further according to watt level
Interpolation method obtains power grid sending end and by end load prediction data a few days ago.
Power grid receiving end stimulable type Demand Side Response model is established as follows:
Demand-side is transferred shown in expense such as formula (4.1):
In formula, number of segment when T is total, NmFor stimulable type Demand Side Response user volume, ρmValence is compensated for the unit quantity of electricity of user m
Lattice, Pm,tFor the transfer load value of user m, Δ tmDuration is dispatched for unit.
In order to guarantee the normal production of industrial user, stimulable type Demand Side Response needs the response quautity met to constrain such as formula
(4.2) shown in:
In formula, qm1, qm2..., qmnFor the fixation transfer load value gear of user m, QmFor the peak response capacity of user m
Value.
Shown in the load transfer amount Constraints of Equilibrium such as formula (4.3) that stimulable type Demand Side Response needs to meet:
DC link power transmission model is established as follows:
Sending end power supply on the basis of meeting local workload demand, by DC link by rich charge transport give by
Sending end energy consumption and receiving end peak regulation are assisted in end.
Direct current is sent electricity plan outside and is mainly determined by transregional power market transaction at present.For the execution for guaranteeing transaction, plan
In period direct current always send out electricity should be within the scope of marketing contract engagement.
Shown in the direct current conveying Constraint such as formula (5.1) that DC link needs to meet:
In formula: t=1,2 ..., T；Pdc,tActive power for DC link in period t, Edc,maxAnd Edc,minRespectively
Maximum of the DC line in planning cycle T, minimum transaction electricity.
In actual schedule operation, the effect planned a few days ago is transregional, large-scale most optimum distribution of resources transprovincially, is not necessarily to
Consider two sides power grid frequency modulation demand and power swing, DC link transimission power plan a few days ago should be relatively steady more, should not frequency
Numerous reciprocal adjustment；Simultaneously, it is contemplated that DC operation reliability, the limitation for controlling the factors such as feasibility and equipment service life, just
DC link, which should filter out factors, the i.e. transimission powers such as burr, sawtooth, frequent reciprocal fluctuation, under the normal method of operation should be presented ladder
Shape.
DC link needs the exchange power stepization met to constrain as shown in formula (5.2):
Pdc,t∈{Pdc1,Pdc2,...,Pdcn} (5.2)
In formula: Pdc1,Pdc2,…,PdcnGear is adjusted for the constant power of DC link.
For the stabilization for keeping direct current plan, DC meter draw one time adjustment (risings of single or multiple continuous times or under
Drop) after, at least one minimum time interval of even running.
Shown in the adjustment spacing constraint such as formula (5.3) that DC link needs to meet:
In formula, ctIt is to indicate whether DC link starts the 0-1 state variable of adjustment in the t period, J is DC link
Minimum adjustment interval.
Limit value of the Plan rescheduling rate no more than DC operation mode of adjacent time interval DC link, DC link
The regulations speed for needing to meet is constrained as shown in formula (5.4):
In formula: Rdc +And Rdc -The respectively up and down rate limit value of DC link plan；Δ t be the t period when
It is long.
It establishes as follows and solves DC grid and send receiving end combined adjusting peak optimal operation model:
It is described send receiving end combined adjusting peak optimal operation model be with the minimum optimization aim of network system total operating cost, with
Active power balance constraint, abandonment, the constraint of abandoning light quantity, powering device constraint, Demand Side Response constraint, DC link are constrained to
Constraint condition, solution obtain sending the power optimization a few days ago of each powering device of receiving end and DC link as a result, realizing DC grid
The optimization of receiving end combined adjusting peak model is sent to run.
The objective function of the optimal operation model is characterized by formula (6.1):
In formula,
Number of segment when T indicates total, n are fired power generating unit quantity；
fi() is the cost of electricity-generating function of i-th fired power generating unit, Pi,tFor i-th unit t moment optimal power output；
miIt is lost for i-th fired power generating unit start and stop, ciFor start-stop time of i-th unit within a cycle of operation；
GwtAbandonment expense for wind park in t moment, GstFor photovoltaic power plant t moment abandoning light expense；
MdcFor DC link t moment power adjustment expense；
The power grid receiving end abandonment abandons light quantity size constraint by formula (6.2) statement:
In formula, gw,t、gs,tRespectively indicate receiving end wind power plant, photovoltaic plant t moment abandonment, abandon light quantity.
The active power balance constraint of the sending end is characterized by formula (6.3):
Pgld,t≤Pgc,t+Pgw,t+Pgs,t-Pdc,t≤(1+α)Pgld,t (6.3)
P in formulagc,tFor sending end conventional power plant power output, the sum of fired power generating unit power output, P are indicatedgw,tIt contributes for sending end wind park,
Pgs,tFor sending end photovoltaic power plant power output, Pgld,tFor sending load, α institute in the range of meeting safety standard for network system
The maximum nargin that can be born.
The active power balance constraint of the receiving end is characterized by formula (6.4):
Pald,t≤Pac,t+Paw,t-gw,t+Pas,t-gs,t+Pdc,t+Pr,t-Ppld,t-Pm,t≤(1+α)Pald, (6.4)
P in formulaac,tFor receiving end conventional power plant power output, the sum of fired power generating unit power output, P are indicatedaw,tFor receiving end wind park power output, gw,t
For receiving end wind power plant abandonment amount, Pas,tFor receiving end photovoltaic power plant power output, gs,tLight quantity, P are abandoned for receiving end photovoltaic plantr,tIt is stored to draw water
Energy generating set power output, Ppld,tIt draws water load for water pump assembly, value is step values, Pm,tFor receiving end stimulable type Demand Side Response,
Pald,tFor Receiving End Load.
The powering device constraint is such as formula (1.1), (1.2), (1.3), (2.1), (2.2), (2.3), (2.4) (3.1)
(3.2) (3.3) (3.4) are represented；
The Demand Side Response constraint is as represented by formula (4.1), (4.2), (4.3).
The DC link constraint is as represented by formula (5.1), (5.2), (5.3), (5.4).
Using the obtained new energy for sending receiving end, prediction data, solution obtain each confession a few days ago for prediction data and load a few days ago
The running optimizatin a few days ago of energy equipment, DC contact linear heat generation rate and receiving end stimulable type Demand Side Response is as a result, therefrom determine each energy supply
The optimized operation of equipment is planned, the optimal peaking power source allocation plan of decision is established.
In conclusion the method for the embodiment of the present invention can effectively improve direct current access send receiving end peak load regulation network run
The consumption rate of economy and new energy.
The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although with reference to the foregoing embodiments
Invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each implementation
Technical solution documented by example is modified or equivalent replacement of some of the technical features；And these modification or
Replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution.
Claims (9)
1. a kind of DC grid of consideration source net lotus constraint send receiving end combined adjusting peak optimization method, it is characterised in that: including following
Step:
S100, the power supply power output model for establishing power grid sending end and receiving end；
S200, the load of DC grid sending end and receiving end prediction data a few days ago is obtained；
S300, power grid receiving end stimulable type Demand Side Response model is established；
S400, DC link power transmission model is established；
Receiving end combined adjusting peak optimal operation model is sent in S500, foundation, send receiving end power supply power output model, step meeting step S100
The constraint condition and wattful power of S300 receiving end stimulable type Demand Side Response model, step S400 DC link transimission power model
Rate Constraints of Equilibrium, abandonment are abandoned on the basis of light quantity constraint, with the minimum optimization aim of network system total operating cost, utilize step
Rapid S200 send that prediction data, solution obtain sending the plan of receiving end power supply power output, DC link power transmission meter a few days ago by end load
It draws and receiving end stimulable type Demand Side Response regulates and controls the optimization operation result a few days ago planned, therefrom determine the optimal fortune of each powering device
Professional etiquette is drawn, and the optimal peaking power source allocation plan of decision is established.
2. the DC grid of consideration source net lotus constraint according to claim 1 send receiving end combined adjusting peak optimization method, special
Sign is:
The power supply of power grid sending end and receiving end power output model includes: the generation of electricity by new energy of power grid sending end and receiving end in the step S100
Traditional fired power generating unit power output model of power supply power output model, power grid sending end and receiving end, the pump-storage generator of power grid receiving end are contributed
Model.
3. the DC grid of consideration source net lotus constraint according to claim 2 send receiving end combined adjusting peak optimization method, special
Sign is: the step S100 is the generation of electricity by new energy power supply power output model for establishing power grid sending end and receiving end as follows:
Force data is gone out to wind power plant, photovoltaic plant history and carries out acquisition arrangement, obtains the sunrise force data of wind power plant, photovoltaic plant
Collection carries out clustering to daily output data set monthly using k means clustering algorithm, data set is divided into k cluster, each
The cluster centre of cluster is known as a typical daily output state, and each data sample number for including that clusters characterizes state hair
Raw probability；
Therefore the probability distribution value of comprehensive all historical samples, each state is calculated by formula (1.1):
Wherein, N indicates the number of samples in data set, ljIndicate the number of samples in cluster j；
Thus, have
By divided state S1, S2..., SCA section between [0,1] is corresponded to, siding-to-siding block length is state probability values；Benefit
Equally distributed random number R on [0,1] is extracted with the method for random sampling, affiliated typical day is determined according to the size of random number R
Power output state then obtains the random power output model of new energy.
4. the DC grid of consideration source net lotus constraint according to claim 3 send receiving end combined adjusting peak optimization method, special
Sign is: the step S100 is the traditional fired power generating unit power output model for establishing power grid sending end and receiving end as follows:
The active power bound that fired power generating unit is subject to is constrained as shown in formula (2.1):
ui,tPi min≤Pi,t≤ui,tPi max (2.1)
In formula, Pi max、Pi minThe active power output bound of respectively i-th conventional power unit, ui,tIt is i-th conventional power unit in t
The start and stop state at quarter；
Shown in its Climing constant being subject to such as formula (2.2):
-RDi≤(Pi,t-Pi,t-1)/Δt≤RUi (2.2)
In formula, RDi、RUiThe creep speed limitation up and down of respectively i-th conventional power generation unit, Δ t is the duration of t period；
Its start and stop being subject to is constrained as shown in formula (2.3):
In formula, Di、OiThe minimum of respectively i-th conventional power generation unit is shut down and the available machine time.
5. the DC grid of consideration source net lotus constraint according to claim 4 send receiving end combined adjusting peak optimization method, special
Sign is:
The step S100 is the pump-storage generator power output model for establishing power grid receiving end as follows:
The active power bound that pumped storage machine and water pump assembly are subject to is constrained as shown in formula (3.1) (3.2):
In formula, Pr,tFor pumped storage machine t moment power output,Respectively pumped storage machine
Active power output bound；Ppld,tPower output for water pump assembly in t moment, Ppld max、Ppld minRespectively water pump assembly is active
Power output bound；
Wherein the power output of water pump assembly is step values:
Ppld,t=pi×n (3.3)
piFor the power that draws water of separate unit water pump；
The water balance that pump-storage generator is subject to is constrained as shown in formula (3.4):
In formula, Vt,Vpld,t,Vr,tThe respectively reservoir storage of t moment reservoir, the pump-out of water pump and the water consumption of generator, Vt-Δt
For the reservoir storage of previous moment reservoir, Vmin, VmaxThe respectively minimum and maximum reservoir storage of reservoir.
6. the DC grid of consideration source net lotus constraint according to claim 5 send receiving end combined adjusting peak optimization method, special
Sign is:
The step S200 is to obtain the load of DC grid sending end and receiving end prediction data a few days ago as follows:
According to Season select typical day load curve, load curve is carried out etc. than amplifying further according to watt level, with interpolation
Method obtains power grid sending end and by end load prediction data a few days ago.
7. the DC grid of consideration source net lotus constraint according to claim 6 send receiving end combined adjusting peak optimization method, special
Sign is:
The step S300 is to establish power grid receiving end stimulable type Demand Side Response model as follows:
Demand-side is transferred shown in expense such as formula (4.1):
In formula, number of segment when T is total, NmFor stimulable type Demand Side Response user volume, ρmFor the unit quantity of electricity making up price of user m,
Pm,tFor the transfer load value of user m, Δ tmDuration is dispatched for unit；
The response quautity that stimulable type Demand Side Response meets is constrained as shown in formula (4.2):
In formula, qm1, qm2..., qmnFor the fixation transfer load value gear of user m, QmFor the peak response capability value of user m；
Shown in the load transfer amount Constraints of Equilibrium such as formula (4.3) that stimulable type Demand Side Response meets:
8. the DC grid of consideration source net lotus constraint according to claim 7 send receiving end combined adjusting peak optimization method, special
Sign is:
The step S400 is to establish DC link power transmission model as follows:
Shown in the direct current conveying Constraint such as formula (5.1) that DC link meets:
In formula: t=1,2 ..., T；Pdc,tActive power for DC link in period t, Edc,maxAnd Edc,minRespectively direct current
Maximum of the route in planning cycle T, minimum transaction electricity；
The exchange power stepization that DC link meets is constrained as shown in formula (5.2):
Pdc,t∈{Pdc1,Pdc2,...,Pdcn} (5.2)
In formula: Pdc1,Pdc2,…,PdcnGear is adjusted for the constant power of DC link；
Shown in the adjustment spacing constraint such as formula (5.3) that DC link meets:
In formula, ctIt is to indicate whether DC link starts the 0-1 state variable of adjustment in the t period, J is DC link minimum
Adjustment interval；
DC link needs the regulations speed met to constrain as shown in formula (5.4):
In formula: Rdc +And Rdc -The respectively up and down rate limit value of DC link plan；Δ t is the duration of t period.
9. the DC grid of consideration source net lotus constraint according to claim 8 send receiving end combined adjusting peak optimization method, special
Sign is:
Receiving end combined adjusting peak optimal operation model is sent in the step S500 foundation, send receiving end power supply power output mould meeting step S100
The constraint condition of type, step S300 receiving end stimulable type Demand Side Response model, step S400 DC link transimission power model
On the basis of active power balance constraint, abandonment, abandoning light quantity constraint, with the minimum optimization mesh of network system total operating cost
Mark is sent using step S200 by end load prediction data a few days ago, and solution obtains sending the plan of receiving end power supply power output, DC link function
The optimization operation result a few days ago of rate transmission plan and the regulation plan of receiving end stimulable type Demand Side Response, therefrom determines each powering device
Optimized operation planning, establish the optimal peaking power source allocation plan of decision；
It specifically includes:
The objective function of the optimal operation model is characterized by formula (6.1):
In formula,
Number of segment when T indicates total, n are fired power generating unit quantity；
fi() is the cost of electricity-generating function of i-th fired power generating unit, Pi,tFor i-th unit t moment optimal power output；
miIt is lost for i-th fired power generating unit start and stop, ciFor start-stop time of i-th unit within a cycle of operation；
GwtAbandonment expense for wind park in t moment, GstFor photovoltaic power plant t moment abandoning light expense；
MdcFor DC link t moment power adjustment expense；
The power grid receiving end abandonment abandons light quantity size constraint by formula (6.2) statement:
In formula, gw,t、gs,tRespectively indicate receiving end wind power plant, photovoltaic plant t moment abandonment, abandon light quantity；
The active power balance constraint of the sending end is characterized by formula (6.3):
Pgld,t≤Pgc,t+Pgw,t+Pgs,t-Pdc,t≤(1+α)Pgld,t (6.3)
P in formulagc,tFor sending end conventional power plant power output, the sum of fired power generating unit power output, P are indicatedgw,tFor sending end wind park power output, Pgs,t
For sending end photovoltaic power plant power output, Pgld,tFor sending load, α can be held in the range of meeting safety standard for network system
The maximum nargin received；
The active power balance constraint of the receiving end is characterized by formula (6.4):
Pald,t≤Pac,t+Paw,t-gw,t+Pas,t-gs,t+Pdc,t+Pr,t-Ppld,t-Pm,t≤(1+α)Pald, (6.4)
P in formulaac,tFor receiving end conventional power plant power output, the sum of fired power generating unit power output, P are indicatedaw,tFor receiving end wind park power output, gw,tFor
Receiving end wind power plant abandonment amount, Pas,tFor receiving end photovoltaic power plant power output, gs,tLight quantity, P are abandoned for receiving end photovoltaic plantr,tFor water-storage
Generating set power output, Ppld,tIt draws water load for water pump assembly, value is step values, Pm,tFor receiving end stimulable type Demand Side Response,
Pald,tFor Receiving End Load；
The powering device constraint is such as formula (1.1), (1.2), (1.3), (2.1), (2.2), (2.3), (2.4) (3.1) (3.2)
(3.3) (3.4) are represented；
The Demand Side Response constraint is as represented by formula (4.1), (4.2), (4.3)；
The DC link constraint is as represented by formula (5.1), (5.2), (5.3), (5.4)；
Using the obtained new energy for sending receiving end, prediction data, solution obtain each energy supply and set a few days ago for prediction data and load a few days ago
Standby, DC contact linear heat generation rate and the running optimizatin a few days ago of receiving end stimulable type Demand Side Response are as a result, therefrom determine each powering device
Optimized operation planning, establish the optimal peaking power source allocation plan of decision.
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Effective date of registration: 20220920 Address after: Huangshan Future Science and Technology City, No. 59, Meilin Avenue, Huangshan High-tech Industrial Development Zone, Huangshan City, Anhui Province, 245000 Patentee after: Huangshan Science and Technology Innovation Center Co.,Ltd. Address before: 230001 floor 6, block B, blue diamond Shangjie, No. 335, Suixi Road, Bozhou road street, Luyang District, Hefei City, Anhui Province Patentee before: Hefei Luyang Technology Innovation Group Co.,Ltd. |
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Effective date of registration: 20230625 Address after: No. 88, Meilin Avenue, Huangshan City High tech Industrial Development Zone, Mount Huangshan City, Anhui Province 245000 Patentee after: Zhongke Haiao (Mount Huangshan) Energy Storage Technology Co.,Ltd. Address before: Huangshan Future Science and Technology City, No. 59, Meilin Avenue, Huangshan High-tech Industrial Development Zone, Huangshan City, Anhui Province, 245000 Patentee before: Huangshan Science and Technology Innovation Center Co.,Ltd. |