CN108321810A - Inhibit the distribution Multiple Time Scales powerless control method of grid-connected voltage fluctuation - Google Patents
Inhibit the distribution Multiple Time Scales powerless control method of grid-connected voltage fluctuation Download PDFInfo
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Classifications
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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
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/16—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by adjustment of reactive power
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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
- H02J3/18—Arrangements for adjusting, eliminating or compensating reactive power in networks
-
- 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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- H02J3/383—
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/30—Reactive power compensation
Abstract
The present invention provides the distribution Multiple Time Scales powerless control method for inhibiting grid-connected voltage fluctuation, is as follows：First, distribution network structure, adjustment equipment parameter and next day each hour load and photovoltaic power generation output forecasting value and prediction error are collected；Then, with the minimum target of power distribution network total operating cost, the optimal reactive power dispatch model a few days ago of the power distribution network based on chance constrained programming is established；In turn, using catastrophic genetic algorithm solve power distribution network a few days ago optimal reactive power dispatch model and issue operation plan instruction；Finally, load is active and reactive and photovoltaic active power output data for acquisition in real time, calculates the reactive power variable capacity of photovoltaic DC-to-AC converter, is contributed by comparing the size of idle variable capacity and idle output desired value to control the reactive power of inverter.The present invention proposes the distribution Multiple Time Scales powerless control method for inhibiting grid-connected voltage fluctuation, can effectively inhibit grid-connected voltage fluctuation, and improve the economy of distribution network operation.
Description
Technical field
The present invention relates to grid-connected voltage fluctuation suppression technology fields, more particularly to inhibit grid-connected voltage wave
Dynamic distribution Multiple Time Scales powerless control method, voltage is violent caused by being suitable for solving high permeability photovoltaic access power distribution network
Fluctuation problem.
Background technology
Under the overall background of current global energy exhaustion and environmental pollution, distributed generation resource (Distributed
Generation, DG) it is grown rapidly by the features such as of low cost, control is flexible, clean environment firendly, especially distributed light
It lies prostrate (Distributed Photovoltaic, DPV), but its power generation is with intermittent and randomness, it is steady to the safety of power distribution network
Fixed operation proposes new challenge.
Centralized Optimized Operation based on optimal load flow can effectively solve the problem that the coordination control of each regulating measure in power distribution network
Problem, but Distribution Network Communication lag, automatization level are low at this stage, and centralized optimization algorithm solution efficiency can not ensure,
Dispatch command is caused to be difficult to real time down, each control unit is difficult to the operating condition of real-time response variation.Distributing controls on the spot
The adverse effect that DG contributes to power distribution network safety and stability at random, but its adjusting dependent on control parameter can be successfully managed, is controlled
The economy of system is often unable to get guarantee.
Based on this, the present invention proposes the idle controlling party of distribution Multiple Time Scales for inhibiting grid-connected voltage fluctuation
Method.The Readjusting cost of on-load regulator transformer and grouping switching capacitor is considered a few days ago, it is minimum with power distribution network total operating cost
Target establishes the GA for reactive power optimization scheduling model for considering node voltage chance constraint, advantageously reduces the action of discrete device
Number reduces network loss and voltage out-of-limit probability；The real-time fluctuations situation contributed according to load and photovoltaic in day, with grid-connected point
Voltage optimization value is to track the reactive power output of objective self-adapting control photovoltaic DC-to-AC converter, is conducive to inhibit grid entry point voltage
Big ups and downs, and the economy of distribution network operation is made to tend to optimum state.
Invention content
It is an object of the invention to coordinate discrete device and photovoltaic in power distribution network using the control method of Multiple Time Scales
The Reactive-power control of inverter, to inhibit the grid-connected caused sharp voltage fluctuation of high permeability, it is ensured that the safety of system operation
Property and economy.
The present invention proposes the distribution Multiple Time Scales powerless control method of grid-connected voltage fluctuation of inhibition, including following
Step：
(1) distribution network structure parameter, including network topology structure, line resistance r, line reactance x and susceptance over the ground are collected
b；Collect power distribution network adjustment equipment parameter, including the node set Ω where on-load regulator transformerT, the specified appearance of every transformer
Measure ST, equiva lent impedance (RT+jXT), high-pressure side rated voltage VHN, low-pressure side rated voltage VLN, gear number nTWith span αT, grouping
Switched capacitor installs node set ΩC, each node capacitor group number nCWith single group capacitor compensation capacity QC0, photovoltaic generation system
System installation node set ΩpvWith inverter capacity Spv；Collect the desired value of next day each active and reactive prediction of hour loadAnd standard deviationThe desired value of photovoltaic active power output predictionAnd standard deviation
(2) meter and the Readjusting cost of on-load regulator transformer and grouping switching capacitor, most with power distribution network total operating cost
Small is target, using on-load regulator transformer no-load voltage ratio, grouping switching capacitor reactive compensation amount and grid-connected voltage as decision
Variable establishes the power distribution network optimal reactive power dispatch model a few days ago for considering node voltage chance constraint；
(3) it uses catastrophic genetic algorithm to solve power distribution network and optimal reactive power dispatch model and issues corresponding operation plan a few days ago
Instruction；
(4) adaptively become in day excellent control during, acquire that load is active and reactive and photovoltaic active power output number in real time
According to, the reactive power variable capacity of inverter is calculated, it is next by comparing the size of idle variable capacity and idle output desired value
The reactive power for controlling inverter is contributed.
In the distribution Multiple Time Scales powerless control method of grid-connected voltage fluctuation of above-mentioned inhibition, the meter and
The Readjusting cost of on-load regulator transformer and grouping switching capacitor is referred to on-load regulator transformer and grouping switching capacitance
The action situation conversion of device is power attenuation value, and specific calculating is as follows：
In formula,WithThe respectively Readjusting cost of t periods on-load regulator transformer and grouping switching capacitor；ΔPT、
ΔPCThe respectively unit Readjusting cost of transformer, capacitor；Respectively t period f platforms transformer tapping gear
With g platform capacitor dispensing group numbers；nT、nCThe respectively sum of transformer and capacitor.
In the distribution Multiple Time Scales powerless control method of above-mentioned grid-connected voltage fluctuation of inhibition, the consideration
The power distribution network of node voltage chance constraint a few days ago optimal reactive power dispatch model refer to coordinate power distribution network in on-load regulator transformer,
The optimal reactive power dispatch model a few days ago of grouping switching capacitor and photovoltaic DC-to-AC converter regulating power, it is specific as follows：
1) object function of model is as follows：
In formula,For t period active power loss desired values；
2) equality constraint of model is as follows：
In formula, PisAnd QisThe respectively given active power injection rate of node i and reactive power injection rate；ViAnd VjRespectively
For the voltage magnitude of node i and node j；GijAnd BijRespectively circuit LijConductance and susceptance；δijFor node i and node j voltages
The difference of phase angle；Ω is all node sets of power distribution network；
3) inequality constraints of model includes control variable inequality constraints and state variable inequality constraints：
It includes on-load voltage regulation transformer voltage ratio T to control variableK, grouping switching capacitor reactive compensation amount QCWith it is grid-connected
Point voltage Vpv, state variable is each node voltage in power distribution network, and using chance constrained programming, each inequality constraints is as follows：
In formula, ΩT、ΩCNode set respectively where transformer and capacitor；ΩpvFor grid-connected node set； The respectively upper limit value and lower limit value of t period f platforms on-load regulator transformer no-load voltage ratio；Respectively t
The upper limit value and lower limit value of period g platforms capacitor group reactive-load compensation amount；Respectively h-th of t periods are grid-connected
The upper limit value and lower limit value of point voltage；The respectively upper limit value and lower limit value of t period interior nodes i voltages；βvIt is set for node voltage
Letter is horizontal；Pr { } indicates the probability that event is set up；
For the whether true judgement of node voltage chance constraint, it can first use and be based on cumulant combination Gram-
The probability distribution of the Probabilistic Load Flow algorithm solution node voltage of Charlier series expansions, then calculate it and be in interval of acceptance
Interior probability.First, it solves to obtain the k rank cumulant of each node voltage using cumulant Probabilistic Load Flow algorithmThen
The probability-distribution function of each node voltage is calculated in conjunction with Gram-Charier series expansions, is finally calculated it and is in interval of acceptance
Probability simultaneously judges whether to be more than chance constraint confidence level, specifically calculate as follows：
Pr(Vmin≤v≤Vmax)=FV(Vmax)-FV(Vmin)
In formula,For stochastic variable after node voltage V standardizationCumulative distribution function；φ () is indicating standard just
The probability density function of state distribution；mkIndicate stochastic variable after standardizingKth rank cumulant.
In the distribution Multiple Time Scales powerless control method of above-mentioned grid-connected voltage fluctuation of inhibition, the catastrophe
Genetic algorithm is a kind of intelligent optimization algorithm for being usually used in solving multivariable, multiple constraint nonlinear programming problem.
In the distribution Multiple Time Scales powerless control method of above-mentioned grid-connected voltage fluctuation of inhibition, in the day
Adaptively become " adaptive " of excellent control is embodied in photovoltaic DC-to-AC converter according to the load of acquisition is active and reactive and photovoltaic active power output
Data adjust idle output in real time, and coordinate the action situation real-time tracking day of on-load regulator transformer and grouping switching capacitor
Preceding Optimized Operation plan, help to solve because day preload and photovoltaic power generation output forecasting error model inaccuracy caused by control in day
The problem of Optimized Operation plan a few days ago can not be tracked；" becoming excellent " is embodied in since scheduling model does not consider photovoltaic DC-to-AC converter a few days ago
Capacity-constrained, acquired results are ideal optimal plans, go out force data in real time in conjunction with load and photovoltaic when being controlled in day, in inversion
Device is idle it is abundant in the case of can real-time tracing ideal optimal plan, insufficient control idle output in the case that inverter is idle
In limiting condition, can tend to track ideal optimal plan.
In the distribution Multiple Time Scales powerless control method of above-mentioned grid-connected voltage fluctuation of inhibition, described "
Adaptively become in day during excellent control, acquire that load is active and reactive and photovoltaic active power output data in real time, calculates inverter
Reactive power variable capacity controls the real-time of inverter by comparing the size of idle variable capacity and idle output desired value
The reactive power variable capacity of inverter and idle output target value calculating method are as follows in idle output "：
Acquire h-th of photovoltaic active power output value of t momentIn conjunction with its gird-connected inverter capacity SpvhCurrent time can be calculated
The upper limit value and lower limit value of photovoltaic combining inverter is idle variable capacityIt is specific as follows：
Then, m moment each on-load regulator transformer switching gear, capacitance are determined according to the instruction of operation plan a few days ago issued
On-load regulator transformer both high side node 22 is considered as balance nodes, grid-connected point by device switching group number and grid-connected voltage
Be considered as PV node, other load bus are considered as PQ nodes, in conjunction with the load that collects is active and reactive and photovoltaic active power output number
According to, pass through Load flow calculation solve h-th of grid-connected idle output desired value of point of current timeFinally, when more current
The magnitude relationship of grid-connected point idle output desired value and the idle variable capacity of its inverter is carved, if at idle output desired value
Then be idle output desired value by the control of contributing of inverter reactive power within the scope of idle variable capacity, conversely, ought it is idle go out
When power desired value is more than idle variable capacity upper limit value, inverter reactive power is contributed into control as the idle variable capacity upper limit
Value, when idle output desired value be less than idle variable capacity lower limiting value when, by inverter reactive power contribute control be it is idle can
Capacitance-adjustable lower limiting value, specific control logic are as follows：
By above-mentioned comparing element can the grid-connected point of real time correction without work output, realize the excellent control that adaptively becomes in day
System.
Compared with existing power distribution network containing photovoltaic optimizes progress control method, the invention has the advantages that：
(1) optimal reactive power dispatch model considers node voltage chance constraint a few days ago, efficiently solves and controls process in day
Due to load and photovoltaic output fluctuation it is big caused by voltage out-of-limit problem；
(2) adaptively become in day excellent control strategy with grid-connected voltage optimization value be tracking target, can effectively press down
Grid entry point voltage big ups and downs problem caused by high permeability photovoltaic access processed.
Description of the drawings
Fig. 1 is the distribution Multiple Time Scales powerless control method flow chart for inhibiting grid-connected voltage fluctuation.
Fig. 2 is improved IEEE33 node systems topological structure schematic diagram.
Fig. 3 is that next day each hour load is active and reactive and photovoltaic active power output predicts desired value sequence diagram.
Fig. 4 is the pre- switching invitation message schematic diagram of capacitor group of optimal reactive power dispatch scheme a few days ago.
Fig. 5 is that the transformer of optimal reactive power dispatch scheme a few days ago files invitation message schematic diagram in advance.
Fig. 6 is the grid-connected voltage control plan instruction schematic diagram of optimal reactive power dispatch scheme a few days ago.
Fig. 7 is grid-connected voltage whole day simulation curve comparison diagram in day.
Specific implementation mode
The specific implementation of the present invention is further illustrated below in conjunction with attached drawing and example, but the implementation and protection of this explanation are not
It is limited to this.
Fig. 1 reflects the specific stream for the distribution Multiple Time Scales powerless control method for inhibiting grid-connected voltage fluctuation
Journey.The distribution Multiple Time Scales powerless control method of grid-connected voltage fluctuation is inhibited to include：
(1) distribution network structure parameter, including network topology structure, line resistance r, line reactance x and susceptance over the ground are collected
b；Collect power distribution network adjustment equipment parameter, including the node set Ω where on-load regulator transformerT, the specified appearance of every transformer
Measure ST, equiva lent impedance (RT+jXT), high-pressure side rated voltage VHN, low-pressure side rated voltage VLN, gear number nTWith span αT, grouping
Switched capacitor installs node set ΩC, each node capacitor group number nCWith single group capacitor compensation capacity QC0, photovoltaic generation system
System installation node set ΩpvWith inverter capacity Spv；Collect the desired value of next day each active and reactive prediction of hour loadAnd standard deviationThe desired value of photovoltaic active power output predictionAnd standard deviation
(2) meter and the Readjusting cost of on-load regulator transformer and grouping switching capacitor, most with power distribution network total operating cost
Small is target, using on-load regulator transformer no-load voltage ratio, grouping switching capacitor reactive compensation amount and grid-connected voltage as decision
Variable establishes the power distribution network optimal reactive power dispatch model a few days ago for considering node voltage chance constraint：
1) object function of model is as follows：
In formula,For t period active power loss desired values,WithRespectively t periods on-load regulator transformer and grouping is thrown
The Readjusting cost of capacitor is cut, wherein：
In formula, Δ PT、ΔPCThe respectively unit Readjusting cost of transformer, capacitor；The respectively t periods
F platform transformer tapping gears and g platform capacitor dispensing group numbers；nT、nCThe respectively sum of transformer and capacitor；
2) equality constraint of model is as follows：
In formula, PisAnd QisThe respectively given active power injection rate of node i and reactive power injection rate；ViAnd VjRespectively
For the voltage magnitude of node i and node j；GijAnd BijRespectively circuit LijConductance and susceptance；δijFor node i and node j voltages
The difference of phase angle；Ω is all node sets of power distribution network；
3) inequality constraints of model includes controlling variable inequality constraints and state variable inequality constraints,
Wherein control variable includes on-load voltage regulation transformer voltage ratio TK, grouping switching capacitor reactive compensation amount QCAnd photovoltaic
Grid entry point voltage Vpv, state variable is each node voltage in power distribution network, and using chance constrained programming, each inequality constraints is as follows：
In formula, ΩT、ΩCNode set respectively where transformer and capacitor；ΩpvFor grid-connected node set； The respectively upper limit value and lower limit value of t period f platforms on-load regulator transformer no-load voltage ratio；Respectively t
The upper limit value and lower limit value of period g platforms capacitor group reactive-load compensation amount；Respectively h-th of t periods are grid-connected
The upper limit value and lower limit value of point voltage；The respectively upper limit value and lower limit value of t period interior nodes i voltages；βvIt is set for node voltage
Letter is horizontal；Pr { } indicates the probability that event is set up；
Using the Probabilistic Load Flow algorithm solution node voltage based on cumulant combination Gram-Charlier series expansions
Probability distribution, then its probability being in interval of acceptance is calculated, whether decision node voltage chance constraint is true accordingly.It is first
First, it solves to obtain the k rank cumulant of each node voltage using cumulant Probabilistic Load Flow algorithmThen in conjunction with Gram-
Charier series expansions calculate the probability-distribution function of each node voltage, finally calculate it and are in the probability of interval of acceptance and sentence
Disconnected whether to be more than chance constraint confidence level, specific calculating is as follows：
Pr(Vmin≤v≤Vmax)=FV(Vmax)-FV(Vmin)
In formula,For stochastic variable after node voltage V standardizationCumulative distribution function；φ () is indicating standard just
The probability density function of state distribution；mkIndicate stochastic variable after standardizingKth rank cumulant；
(3) it uses catastrophic genetic algorithm to solve power distribution network and optimal reactive power dispatch model and issues corresponding operation plan a few days ago
Instruction；
(4) adaptively become in day excellent control during, acquire that load is active and reactive and photovoltaic active power output number in real time
According to, the reactive power variable capacity of inverter is calculated, it is next by comparing the size of idle variable capacity and idle output desired value
The reactive power for controlling inverter is contributed, and specific control method is as follows：
First, h-th of photovoltaic active power output value of t moment is acquiredIn conjunction with its gird-connected inverter capacity SpvhIt can calculate and work as
The upper limit value and lower limit value of the preceding idle variable capacity of moment photovoltaic combining inverterIt is specific as follows：
Then, each on-load regulator transformer switching gear of t moment, capacitance are determined according to the instruction of operation plan a few days ago issued
On-load regulator transformer both high side node 22 is considered as balance nodes, grid-connected point by device switching group number and grid-connected voltage
Be considered as PV node, other load bus are considered as PQ nodes, in conjunction with the load that collects is active and reactive and photovoltaic active power output number
According to, pass through Load flow calculation solve h-th of grid-connected idle output desired value of point of current timeFinally, when more current
The magnitude relationship for carving each grid-connected point idle output planned value and the idle variable capacity of its inverter, if idle output desired value
Within the scope of idle variable capacity, then inverter reactive power is contributed into control as idle output desired value, conversely, when idle
When output desired value is more than idle variable capacity upper limit value, inverter reactive power is contributed into control as the idle variable capacity upper limit
Value, when idle output desired value be less than idle variable capacity lower limiting value when, by inverter reactive power contribute control be it is idle can
Capacitance-adjustable lower limiting value, specific control logic are as follows：
By above-mentioned comparing element can the grid-connected point of real time correction without work output, to realize period in day from
Adapt to excellent control.
It is the simulation example of the present invention below, chooses IEEE33 node systems and tested, as shown in Figure 2.
(1) distribution network structure parameter, including the connection type of each circuit, the resistance of each circuit, reactance and susceptance ginseng are collected
Number, as shown in table 1；
Table 1IEEE33 node system line parameter circuit value (units：Ω)
Collect the parameter of adjustment equipment：An on-load regulator transformer, model SFZ9- are accessed between node 0,1
50000/110, rated capacity STFor 50kVA, equivalent resistance (RT+jXT) it is (0.0008+j0.0353) Ω, the specified electricity in high-pressure side
Press VHNFor 110kV, low-pressure side rated voltage VLNFor 10.5kV, gear number nTIt is 17, span αTBe 1.25%, i.e. high-voltage tap model
Enclose is ± 8 × 1.25%；Grouping switching capacitor installs node set ΩCFor node 4,10,16,22,25,28,33, each node
Capacitor group number nCIt is 2 groups, single group capacitor compensation capacity QC0(unit：Kvar be respectively) 25,10,10,15,10,10,
15；Photovoltaic generating system installs node set ΩpvFor node 17, inverter capacity SpvFor 2.21MVA；Next day each hour load
The desired value of active and reactive and photovoltaic active power output prediction sequential is as shown in figure 3, the standard deviation of load prediction sequential is predicted for it
The 8% of desired value, photovoltaic active power output predict that the standard deviation of sequential predicts the 10% of desired value for it；
(2) the Readjusting cost model of on-load regulator transformer and grouping switching capacitor, transformer Δ P are establishedT, capacitor
ΔPCUnit Readjusting cost be respectively 1kW/ times, 0.2kW/ times；
The power distribution network optimal reactive power dispatch model a few days ago for considering node voltage chance constraint is established, model inequality constraints
Bound value is as follows：
It controls in variable, capacitor group on node 4,10,16,22,25,28,33(unit：Kvar) it is respectively
50,20,20,30,20,20,30,It is 0；The on-load regulator transformer tap gear upper limitFor 17, lower limitFor
1；Grid-connected upper voltage limitFor 1.07, lower limitIt is 0.93；In state variable, the node voltage upper limitFor
1.07 lower limitIt is 0.93；
(3) catastrophic genetic algorithm is used to solve power distribution network optimal reactive power dispatch model a few days ago.Mould is carried to embody the present invention
The validity of type control effect, table 2 give the control effect comparison of two kinds of scheduling schemes, scheme 1 be it is proposed by the present invention with
Grid-connected voltage is the scheduling scheme of decision variable, and scheme 2 is the dispatching party of photovoltaic DC-to-AC converter unity power factor control
Case；
The control effect of 2 optimal reactive power dispatch scheme of table
Upper table data are analyzed it is found that comparing scheme 2, scheme 1 drops damage amplitude and improves 7.2%, discrete device action frequency
Reduce 55%, voltage out-of-limit probability is reduced to 0, illustrates the power distribution network day of the considerations of present invention is carried node voltage chance constraint
Preceding optimal reactive power dispatch model is conducive to safety and the economy of system operation.In addition, the Planning Directive that scheduling scheme issues
As shown in Fig. 4~Fig. 6；
(4) adaptively become in day excellent control during, acquire that load is active and reactive and photovoltaic active power output number in real time
According to, the reactive power variable capacity of inverter is calculated, it is next by comparing the size of idle variable capacity and idle output desired value
The reactive power for controlling inverter is contributed.To embody the validity for the excellent control that adaptively becomes in the day that the present invention is put forward, Fig. 7 is provided
Grid-connected whole day voltage analog curve comparison under two kinds of control programs, wherein scheme 1 for the present invention carried with light
Volt grid entry point voltage optimization value is the excellent control that adaptively becomes in the day for tracking target, and scheme 2 is according to photovoltaic DC-to-AC converter specific work
It is controlled in the day of optimization gained operation plan when rate factor controls.7 data of analysis chart, 1 time whole day voltage fluctuation maximum value of scheme
For 0.072kV, and 2 times whole day voltage fluctuation maximum values of scheme are up to 0.434kV, and in contrast, 1 improvement amplitude of scheme is up to
83.4%, the excellent control that illustrates adaptively to become in day provided by the invention can effectively inhibit grid entry point voltage fluctuation, be conducive to complete
The stability of net voltage.
The above, the embodiment of patent only of the present invention, but scope of protection of the present invention is not limited thereto, anyone
Member is subject to equivalent replacement in the range disclosed in patent of the present invention according to the technical solution of patent of the present invention and its inventive concept
Or change, belong to the protection domain of patent of the present invention.
Claims (3)
1. inhibiting the distribution Multiple Time Scales powerless control method of grid-connected voltage fluctuation, it is characterised in that including following step
Suddenly：
(1) distribution network structure, adjustment equipment parameter and next day each hour load and photovoltaic power generation output forecasting value and prediction error are collected；
(2) meter and the Readjusting cost of on-load regulator transformer and grouping switching capacitor, it is minimum with power distribution network total operating cost
Target, using on-load regulator transformer no-load voltage ratio, grouping switching capacitor reactive compensation amount and grid-connected voltage as decision variable,
Establish the power distribution network optimal reactive power dispatch model a few days ago for considering node voltage chance constraint；
(3) it uses catastrophic genetic algorithm to solve power distribution network optimal reactive power dispatch model and to issue corresponding operation plan a few days ago and refer to
It enables；
(4) adaptively become in day excellent control during, acquire that load is active and reactive and photovoltaic active power output data in real time, meter
The reactive power variable capacity for calculating photovoltaic DC-to-AC converter is controlled by comparing the size of idle variable capacity and idle output desired value
The reactive power of inverter processed is contributed.
2. the distribution Multiple Time Scales powerless control method according to claim 1 for inhibiting grid-connected voltage fluctuation,
It is characterized in that：The Readjusting cost of meter and on-load regulator transformer and grouping switching capacitor described in step (2), with distribution
The minimum target of net total operating cost, simultaneously with on-load regulator transformer no-load voltage ratio, grouping switching capacitor reactive compensation amount and photovoltaic
Site voltage is decision variable, establishes the power distribution network optimal reactive power dispatch model a few days ago for considering node voltage chance constraint, specifically
It is as follows：
1) object function of model is as follows：
In formula,For t period active power loss desired values,WithRespectively t periods on-load regulator transformer and grouping switching electricity
The Readjusting cost of container, wherein：
In formula, Δ PT、ΔPCThe respectively unit Readjusting cost of transformer, capacitor；Respectively t period f platforms
Transformer tapping gear and g platform capacitor dispensing group numbers；nT、nCThe respectively sum of transformer and capacitor；
2) equality constraint of model is as follows：
In formula, PisAnd QisThe respectively given active power injection rate of node i and reactive power injection rate；ViAnd VjRespectively save
The voltage magnitude of point i and node j；GijAnd BijRespectively circuit LijConductance and susceptance；δijFor node i and node j voltage phase angles
Difference；Ω is all node sets of power distribution network；
3) inequality constraints of model includes control variable inequality constraints and state variable inequality constraints：
It includes on-load voltage regulation transformer voltage ratio T to control variableK, grouping switching capacitor reactive compensation amount QCWith grid-connected point electricity
Press Vpv, state variable is each node voltage in power distribution network, and using chance constrained programming, each inequality constraints is as follows：
In formula, ΩT、ΩCNode set respectively where transformer and capacitor；ΩpvFor grid-connected node set； The respectively upper limit value and lower limit value of t period f platforms on-load regulator transformer no-load voltage ratio；The respectively t periods
The upper limit value and lower limit value of g platform capacitor group reactive-load compensation amounts；Respectively grid-connected voltage of h-th of t periods
Upper limit value and lower limit value；The respectively upper limit value and lower limit value of t period interior nodes i voltages；βvFor node voltage confidence level；
Pr { } indicates the probability that event is set up.
3. the distribution Multiple Time Scales powerless control method according to claim 1 for inhibiting grid-connected voltage fluctuation,
It is characterized in that：Described in step (4) adaptively become in day excellent control during, in real time acquire load and photovoltaic output number
According to, the reactive power variable capacity of inverter is calculated, it is next by comparing the size of idle variable capacity and idle output desired value
The reactive power for controlling inverter is contributed, and specific control method is as follows：
First, load is active and reactive and photovoltaic active power output data for acquisition in real time, and the reactive power for calculating each photovoltaic DC-to-AC converter can
Capacitance-adjustable range：
In formula,The respectively upper limit value and lower limit value of h-th of grid-connected idle variable capacity of point of t moment；SpvhFor
The capacity of h-th of photovoltaic combining inverter；For the active power output value of h-th of photovoltaic of t moment；
Then, determine that current time each on-load regulator transformer switching gear, capacitor are thrown according to the operation plan instruction issued
Group number and grid-connected voltage are cut, on-load regulator transformer both high side node 22 is considered as balance nodes, grid-connected point is considered as
PV node, other load bus are considered as PQ nodes, in conjunction with the load that collects is active and reactive and photovoltaic active power output data,
Each idle output desired value of grid-connected point is solved by Load flow calculation；Finally, it is idle to compare current time each photovoltaic DC-to-AC converter
The magnitude relationship of variable capacity and its idle output desired value, if idle output desired value is within the scope of idle variable capacity,
Inverter reactive power is then contributed into control as idle output desired value, conversely, when idle output desired value is more than idle adjustable
When maximum size value, inverter reactive power is contributed into control for idle variable capacity upper limit value, when idle output desired value is small
When idle variable capacity lower limiting value, inverter reactive power is contributed into control as idle variable capacity lower limiting value, is specifically controlled
Logic is as follows：
In formula,Respectively h-th of photovoltaic DC-to-AC converter reactive power power generating value of t moment and desired value；By above-mentioned
Comparing element can the grid-connected point of real time correction without work output, to realize the excellent control that adaptively becomes of period in day.
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