CN104600695B - Trend tidal current computing method with Real-Time Scheduling plan is estimated based on presence - Google Patents
Trend tidal current computing method with Real-Time Scheduling plan is estimated based on presence Download PDFInfo
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Abstract
The present invention provides a kind of trend tidal current computing method estimated based on presence with Real-Time Scheduling plan, comprises the following steps：Determine power network future trend running mode data；Reasonability identification is carried out to Real-Time Scheduling plan, and it is automatically adjusted；Many section real power control models are set up, automatic fine tuning generating active power controller is carried out；Carry out reactive voltage to control on the spot, and distribute hub node idle amount of unbalance；Load flow calculation is carried out, the Load flow calculation data for power network future trend dynamic secure estimation are generated.The present invention is used to solve the problem of traditional online dynamic secure estimation algorithm effectively can not analyze safety and stability in the following power network short time, following power grid security variation tendency is analyzed in advance, auxiliary dispatching personnel carry out arrangement adjustment to the current method of operation.
Description
Technical field
The invention belongs to powernet simulation analysis field, and in particular to one kind is based on presence estimation and Real-Time Scheduling
The trend tidal current computing method of plan.
Background technology
With gradually forming for China's extra-high voltage alternating current-direct current series-parallel connection bulk power grid general layout, power system security stability characteristic (quality) and machine
Reason it is increasingly sophisticated, operation of power networks control difficulty continue to increase, to in-circuit emulation analyze accuracy and it is advanced propose it is new
It is required that.The advanced basis for carrying out powernet safety analysis is to form the trend flow data for characterizing following power system operating mode.
Constituting the key factor of following power system operating mode includes：
1) plan in real time, multiple labour, power trade adjustment, temporary scheduling operation and electricity are stopped according to load variations situation, equipment
The changes of operating modes such as net failure, it is considered to which systematic economy is run and security constraint, each generating generating set is opened in the given short time
Stop planning and the plan of exerting oneself, interregional active power exchange plan；
2) ultra-short term bus load is predicted, as the important foundation of power network Real-time generation control, in historical load data and
On the basis of the factors such as Changes in weather, each bus burden with power variation tendency in the forecast short time；
3) presence estimated data, describes the lower equipment static parameter of power network currently operation, topological structure, generator amount
The operating mode such as survey and control parameter, load active power factor, load tap changer position.
The convergence and precision of trend trend have been largely fixed following power system operating mode safety analysis result
Accuracy and reasonability.At present, the AC power flow computational methods based on operation plan have been studied, and effective power flow precision is constantly carried
Height, has substantially met the accuracy requirement of the out-of-limit check of effective power flow.But, due to lack generating set it is idle plan and bus without
Workload predicts that the idle plan trend reasonability in power flow solutions is poor.On the one hand, the larger reactive power flow of deviation can influence
The out-of-limit check of circuit rated current and the precision of the out-of-limit check result of main transformer rated capacity；On the other hand, irrational idle electricity
Pressure distribution also can influence the computational accuracy of effective power flow to a certain extent, and have a strong impact on voltage out-of-limit check and stability check
As a result reasonability.Meanwhile, ultra-short term error, new energy fluctuating error, electric energy Plan rescheduling and operation of power networks behaviour
The uncertain factors such as work, can have a negative impact to the robustness of trend Load flow calculation, also result in computational convergence by data
The problem of quality influence is serious.
The content of the invention
In order to overcome the above-mentioned deficiencies of the prior art, the present invention provides a kind of based on presence estimation and Real-Time Scheduling meter
The trend tidal current computing method drawn, can not be effectively to following power network in short-term for solving traditional online dynamic secure estimation algorithm
The problem of interior safety and stability is analyzed, is analyzed following power grid security variation tendency, auxiliary dispatching personnel couple in advance
The current method of operation carries out arrangement adjustment.
In order to realize foregoing invention purpose, the present invention is adopted the following technical scheme that：
The present invention provides a kind of trend tidal current computing method estimated based on presence with Real-Time Scheduling plan, the side
Method comprises the following steps：
Step 1：Determine power network future trend running mode data；
Step 2：Reasonability identification is carried out to Real-Time Scheduling plan, and it is automatically adjusted；
Step 3：Many section real power control models are set up, automatic fine tuning generating active power controller is carried out；
Step 4：Carry out reactive voltage to control on the spot, and distribute hub node idle amount of unbalance；
Step 5：Load flow calculation is carried out, the Load flow calculation data for power network future trend dynamic secure estimation are generated.
In the step 1, power network future trend running mode data includes presence estimated data, Real-Time Scheduling plan
Data and ultra-short term data.
According to the grid measurement data obtained online, dynamic power system internal state is estimated using statistical method, obtained
To presence estimated data；
On the basis of operation plan a few days ago, with reference to ultra-short term information, ad hoc inspection and repair information and transregional electricity
Transaction application information, is formulated in power network future 5min or the real-time generation schedule of corresponding period and real-time contact transaction in 60min
Plan, obtains Real-Time Scheduling planning data；
Using existing history daily load data and meteorological data, to the corresponding period in power network future 5min or in 60min
Load value estimated, complete include system loading prediction and bus load prediction ultra-short term, obtain ultrashort
Phase load prediction data.
The step 2 specifically includes following steps：
Step 2-1：To Real-Time Scheduling plan carry out reasonability identification, including plan Time-Series analysis, plan association analysis and
Plan degree of balance analysis；
Step 2-2：The expertise arranged according to power network plan, sets up the constraint knowledge storehouse of Real-Time Scheduling plan, and right
Real-Time Scheduling plan is automatically adjusted, and the expertise constraint in constraint knowledge storehouse includes generate electricity maintenance mutual exclusion constraint, generating
Plan temporal constraint, repair schedule mutual exclusion constraint and generating set units limits.
Plan in Time-Series analysis, be divided into following two situations：
A) judge that Real-Time Scheduling planning data or ultra-short term data whether there is the shortage of data at certain time point,
If in the presence of if the Real-Time Scheduling planning data or ultra-short term data at the time point be considered as singular point；
B) whether generating set plan power generating value rate of change in sequential exceedes generating set plan in real-time generation schedule
Exert oneself given threshold, as being considered as singular point more than if.
Plan in association analysis, rational Real-Time Scheduling plan is determined whether according to following four Rule of judgment, if its
In have it is any be unsatisfactory for, then be determined as irrational Real-Time Scheduling plan；
A) generating set plan power generating value is not higher than the actual upper limit of exerting oneself of generating set in real-time generation schedule；
B) not grid-connected generating set is exerted oneself without plan；
C) generating set plan power generating value and real-time examination and repair putting equipment in service state holding one in the works in real-time generation schedule
Cause；
D) putting equipment in service state numerical value contradiction to real-time examination and repair does not occur in the works.
Plan in degree of balance analysis, ultra-short term, real-time generation schedule, real-time contact trading program are counted
Degree of balance analysis is drawn, is had：
Wherein,For system loading predicted value, PgFor generating set plan power generating value, PexchFor contact trading program in real time
Power generating value, PdFor bus load predicted value, PlossFor system losses, PplFor the station service active power in power plant, M is generator
Group quantity, N is bus load quantity, and O is power plant quantity.
Generate electricity in maintenance mutual exclusion constraint, when real-time generation schedule has mutual exclusion with real-time examination and repair plan and conflicted, to examine in real time
Repair to exert oneself to generating set on the basis of state and be adjusted, specifically have：
Wherein,For generating set plan power generating value in real-time generation schedule after adjustment,To be generated electricity in real time before adjustment
Generating set plan power generating value in the works,For real-time examination and repair putting equipment in service state in the works；
In generation schedule temporal constraint, when real-time generation schedule has singular point in sequential, near its time point
Generating set plan power generating value is adjusted, and is specifically had：
Wherein, Pα,t-1Generating set plan power generating value near time t-1 where singular point, Pα,t+1For singular point institute
Plan power generating value near time t+1；
In repair schedule mutual exclusion constraint, real-time examination and repair is when in the works there is mutual exclusion constraint in putting equipment in service state, with system
Repair schedule is adjusted on the basis of equipment actual motion state, specifically had：
S′β,plan=Sβ,ope
Wherein, S 'β,planThe real-time examination and repair equipment β in the works state that puts into operation, S after adjustmentβ,opeFor devices in system β reality
Border running status；
In generating set units limits, generating set plan power generating value is deposited with generating set in system in real-time generation schedule
When mutual exclusion is constrained, generating set plan power generating value in real-time generation schedule is adjusted on the basis of generating set in system
It is whole, specifically have：
Wherein,For,WithGenerating set is exerted oneself upper and lower bound respectively in system.
The step 3 specifically includes following steps：
Step 3-1：Many section real power control models are set up, increase section active power deviation side in power flow algorithm
Journey, section active power deviation equation is expressed as：
Wherein, Δ Pcut(γ) is section γ active power deviation, PlineFor section γ active power, for the section
NlineThe active power summation of bar circuit；Pdes(γ) is section γ active power desired value；
Step 3-2：Using the active power adjustable strategies of the method for successive approximation, passed through according to the active power deviation of section many
Successive step, is gradually adjusted to active power desired value by section active power；
Step 3-3：Generating set active power controller equation is set up, is specifically had：
Pδ(α)=fp(α)+η(δ)ΔPvail(α)
Wherein, Pδ(α) is the active power of α platform generating sets in the δ control group of planes, fp(α) is generating set node
Topological constraints, η (δ) be the δ control a group of planes the active power controller factor, Δ Pvail(α) is the generating set of Weight
It is adjustable to exert oneself.
The step 4 specifically includes following steps：
Step 4-1：Reactive voltage is carried out based on voltage power-less subregion to control on the spot；
Step 4-2：The idle amount of unbalance of hub node is distributed to the reactive power source in voltage power-less subregion.
In the step 5, calculating is iterated using the Newton method based on node power equilibrium equation, and determine system
Running status, it is determined that the Load flow calculation data for power network future trend dynamic secure estimation, including the voltage on each bus
Amplitude and power distribution and power attenuation in phase angle, network.
Compared with prior art, the beneficial effects of the present invention are：
The present invention solves traditional online dynamic secure estimation algorithm can not be effectively to safety in the following power network short time
The problem of stabilization is analyzed, accurate trend flow data is provided for the following method of operation safety analysis of power network.To tune in real time
Degree plan carries out error message in reasonability identification, automatic identification planning data, and is counted according to actual electric network expertise
Adjustment is drawn, good data basis is provided for trend Load flow calculation；Many section real power control models of large-scale interconnected power system are set up,
Using the adjustable strategies of Step wise approximation true value, automatic fine tuning generating real power control, it is to avoid trend is not when the active deviation of system is larger
Convergent situation；Using hierarchical and regional balance principle, reactive voltage is carried out based on idle partition method and controlled on the spot, is further carried
The convergence of high trend power flow algorithm.
Brief description of the drawings
Fig. 1 is the trend tidal current computing method stream based on presence estimation and Real-Time Scheduling plan in the embodiment of the present invention
Cheng Tu.
Fig. 2 is the 500kV voltage class branch road accuracy rate statistical result schematic diagrames of system in the embodiment of the present invention；
Fig. 3 is the 220kV voltage class branch road accuracy rate statistical result schematic diagrames of system in the embodiment of the present invention.
Embodiment
The present invention is described in further detail below in conjunction with the accompanying drawings.
Such as Fig. 1, the present invention provides a kind of trend tidal current computing method estimated based on presence with Real-Time Scheduling plan,
It the described method comprises the following steps：
Step 1：Determine power network future trend running mode data；
Step 2：Reasonability identification is carried out to Real-Time Scheduling plan, and it is automatically adjusted；
Step 3：Many section real power control models are set up, automatic fine tuning generating active power controller is carried out；
Step 4：Carry out reactive voltage to control on the spot, and distribute hub node idle amount of unbalance；
Step 5：Load flow calculation is carried out, the Load flow calculation data for power network future trend dynamic secure estimation are generated.
In the step 1, power network future trend running mode data includes presence estimated data, Real-Time Scheduling plan
Data and ultra-short term data.
According to the grid measurement data obtained online, dynamic power system internal state is estimated using statistical method, obtained
To presence estimated data；
On the basis of operation plan a few days ago, with reference to ultra-short term information, ad hoc inspection and repair information and transregional electricity
Transaction application information, is formulated in power network future 5min or the real-time generation schedule of corresponding period and real-time contact transaction in 60min
Plan, obtains Real-Time Scheduling planning data；
Using existing history daily load data and meteorological data, to the corresponding period in power network future 5min or in 60min
Load value estimated, complete include system loading prediction and bus load prediction ultra-short term, obtain ultrashort
Phase load prediction data.
The step 2 specifically includes following steps：
Step 2-1：To Real-Time Scheduling plan carry out reasonability identification, including plan Time-Series analysis, plan association analysis and
Plan degree of balance analysis；
Step 2-2：The expertise arranged according to power network plan, sets up the constraint knowledge storehouse of Real-Time Scheduling plan, and right
Real-Time Scheduling plan is automatically adjusted, and the expertise constraint in constraint knowledge storehouse includes generate electricity maintenance mutual exclusion constraint, generating
Plan temporal constraint, repair schedule mutual exclusion constraint and generating set units limits.
Plan in Time-Series analysis, be divided into following two situations：
A) judge that Real-Time Scheduling planning data or ultra-short term data whether there is the shortage of data at certain time point,
If in the presence of if the Real-Time Scheduling planning data or ultra-short term data at the time point be considered as singular point；
B) whether generating set plan power generating value rate of change in sequential exceedes generating set plan in real-time generation schedule
Exert oneself given threshold, as being considered as singular point more than if.
Plan in association analysis, rational Real-Time Scheduling plan is determined whether according to following four Rule of judgment, if its
In have it is any be unsatisfactory for, then be determined as irrational Real-Time Scheduling plan；
A) generating set plan power generating value is not higher than the actual upper limit of exerting oneself of generating set in real-time generation schedule；
B) not grid-connected generating set is exerted oneself without plan；
C) generating set plan power generating value and real-time examination and repair putting equipment in service state holding one in the works in real-time generation schedule
Cause；
D) putting equipment in service state numerical value contradiction (numerical value contradiction refers to there is same equipment real-time examination and repair does not occur in the works
Two records, the state that puts into operation is opposite).
Plan in degree of balance analysis, ultra-short term, real-time generation schedule, real-time contact trading program are counted
Degree of balance analysis is drawn, is had：
Wherein,For system loading predicted value, PgFor generating set plan power generating value, PexchFor contact trading program in real time
Power generating value, PdFor bus load predicted value, PlossFor system losses, PplFor the station service active power in power plant, M is generator
Group quantity, N is bus load quantity, and O is power plant quantity.
Generate electricity in maintenance mutual exclusion constraint, when real-time generation schedule has mutual exclusion with real-time examination and repair plan and conflicted, to examine in real time
Repair to exert oneself to generating set on the basis of state and be adjusted, specifically have：
Wherein,For generating set plan power generating value in real-time generation schedule after adjustment,To be generated electricity in real time before adjustment
Generating set plan power generating value in the works,For real-time examination and repair putting equipment in service state in the works；
In generation schedule temporal constraint, when real-time generation schedule has singular point in sequential, near its time point
Generating set plan power generating value is adjusted, and is specifically had：
Wherein, Pα,t-1Generating set plan power generating value near time t-1 where singular point, Pα,t+1For singular point institute
Plan power generating value near time t+1；
In repair schedule mutual exclusion constraint, real-time examination and repair is when in the works there is mutual exclusion constraint in putting equipment in service state, with system
Repair schedule is adjusted on the basis of equipment actual motion state, specifically had：
S′β,plan=Sβ,ope (4)
Wherein, S 'β,planThe real-time examination and repair equipment β in the works state that puts into operation, S after adjustmentβ,opeFor devices in system β reality
Border running status；
In generating set units limits, generating set plan power generating value is deposited with generating set in system in real-time generation schedule
When mutual exclusion is constrained, generating set plan power generating value in real-time generation schedule is adjusted on the basis of generating set in system
It is whole, specifically have：
Wherein,For,WithGenerating set is exerted oneself upper and lower bound respectively in system.
The step 3 specifically includes following steps：
Step 3-1：Many section real power control models are set up, increase section active power deviation side in power flow algorithm
Journey, section active power deviation equation is expressed as：
Wherein, Δ Pcut(γ) is section γ active power deviation, PlineFor section γ active power, for the section
NlineThe active power summation of bar circuit；Pdes(γ) is section γ active power desired value；
Step 3-2：Using the active power adjustable strategies of the method for successive approximation, passed through according to the active power deviation of section many
Successive step, is gradually adjusted to active power desired value by section active power；
Control measure are divided into the active power adjustment strategy of Step wise approximation into one-step control and multistep is controlled.It is every in multistep control
One step sets a substep target, the desired value of the substep target Step wise approximation section.Equivalent to one list of each decoupled method
Step control, its step-length is the difference of substep target and this step initial value.
The calculation procedure of one-step control is as follows：
1) unit and number of units of control and a balance group of planes are selected according to previously given principle；
2) using the processing constrained generator limit value, section power control is made to become continuous generator start and stop and automatic
Adjustment process, adjustment process adjusts non-regulation and control unit by priority and regulation and control unit is realized.
On the basis of one-step control, the calculation procedure of multistep control adds following content：
1) the maximum variable quantity of line voltage is inversely proportional during next step step-length is controlled with this step；
2) flow solution that previous step is calculated makes iteration starting point close to true solution as this step initial value；
Do not restrained if 3) calculate, step-length halves automatically, this step control again is calculated；
4) when step-length is less than default threshold, trend does not restrain still, then control failure, terminates to calculate.
Step 3-3：Generating set active power controller equation is set up, is specifically had：
Pδ(α)=fp(α)+η(δ)ΔPvail(α) (7)
Wherein, Pδ(α) is the active power of α platform generating sets in the δ control group of planes, fp(α) is generating set node
Topological constraints, η (δ) be the δ control a group of planes the active power controller factor, Δ Pvail(α) is the generating set of Weight
It is adjustable to exert oneself.
The step 4 specifically includes following steps：
Step 4-1：Reactive voltage is carried out based on voltage power-less subregion to control on the spot；
Step 4-2：The idle amount of unbalance of hub node is distributed to the reactive power source in voltage power-less subregion.
Voltage power-less subregion is that by hierarchical and regional balance principle whole system is divided into some sub-regions, to realize nothing
The layering and zoning of power control, in-situ balancing provide basis.Specifically, hub node set is preselected by electric network composition, according to
System node is divided into several reactive balance regions being made up of hub node and multiple reactive power source nodes by electrical distance
Ωi, and calculate ΩiIdle distribution coefficient λ of the interior each reactive power source node to hub node iki, have：
Wherein, xijFor the branch road reactance between hub node i and reactive power source node j.
Reactive voltage is controlled on the spot, increases new expanding node type in power flow equation, and in the increase of its iterative process
Var-volt regulation measure, distributes the idle amount of unbalance of node to each reactive source according to idle units limits and voltage constraint,
Realize the adjust automatically on the spot of reactive voltage.
New extensions node type：Type, its active P that generates electricityG, it is known that the idle Q that generates electricityGIt is unknown with voltage magnitude V, Type, its generating active-power PGIt is unknown, electricity
Phase theta is pressed, it is known that the idle and voltage magnitude that generates electricity is unknown, but can change within the specific limits.Based on above-mentioned expanding node type,
Increase var-volt regulation equation, such as following formula in power flow equation iterative process：
Wherein, QfpiBe assigned in node i during for the t-1 times iteration idle exerts oneself；WithRespectively node i without
The iterative value of the t-1 times and t times that work(is exerted oneself.
In idle iterative process, the idle amount of unbalance of node i is distributed to reactive balance according to idle distribution coefficient
Each reactive source in region, and calculate node i idle amount of unbalance againAs shown in formula (10)~(11).
In formula, lbc1And lbc2For step-size factor；WithRespectively t-1 times iteration node i, j it is idle not
Aequum；ΔQdyyxjTo be assigned to node j reactive power because of node i voltage out-of-limit；ΔQdyyxiFor node i voltage out-of-limit
When its own reactive power adjustment amount；ΔQclyxjTo be assigned to node j reactive power because node i reactive power is out-of-limit；
ΔQclyxiThe adjustment amount for its own reactive power of more being prescribed a time limit for node i reactive power.
According to the Reactive-power control ability and its voltage-regulation nargin of each reactive power source node, by the idle imbalance of hub node
Measure Δ QiDistribute to each reactive power source node of surrounding, as shown in formula (12)~(13).
Q′Gi=QGi-lbc1|ΔQi|sgn(ΔQi) (12)
Q′Gk=QGk-lbc2λki|ΔQi|sgn(ΔQi) (13)
In formula, QGk、Q′GkIdle exerting oneself before reactive power source node k adjustment and after adjustment respectively in subregion；sgn(Δ
Qi) it is variable Δ QiSign function, value -1 or 1.
In the step 5, calculating is iterated using the Newton method based on node power equilibrium equation, and determine system
Running status, it is determined that the Load flow calculation data for power network future trend dynamic secure estimation, including the voltage on each bus
Amplitude and power distribution and power attenuation in phase angle, network.
According to the method described above, using certain real system as Knowledge Verification Model, to the trend trend accuracy on April 16th, 2014
Statistical analysis is carried out, the wherein sampling interval is 15min, i.e., 0:15-24:00 96 time points.Statistic analysis result such as following table
Shown, the Average Accuracies of 550kV trend trends is that the Average Accuracy of 94.56%, 220kV trend trends is 94.56%, tool
Body such as table 1：
Table 1
| Accuracy statistical information | Content |
| 500kV number of branches | 380~410 |
| 220kV number of branches | 2640~2660 |
| 500kV trend accuracys rate | 94.56% |
| 220kV trend accuracys rate | 95.48% |
Examples detailed above analysis shows：This method overcomes the traditional online dynamic secure estimation algorithm of solution can not be effectively right
The problem of safety and stability is analyzed in the following power network short time, based on presence estimated data and Real-Time Scheduling plan, mould
Intend actual electric network plan operation characteristic, calculate rational reactive voltage plan and generator output control, be power network future
The dynamic secure estimation of trend provides accurate flow data.
Finally it should be noted that：The above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof, institute
The those of ordinary skill in category field with reference to above-described embodiment still can to the present invention embodiment modify or
Equivalent substitution, these any modifications or equivalent substitution without departing from spirit and scope of the invention are applying for this pending hair
Within bright claims.
Claims (10)
1. the trend tidal current computing method with Real-Time Scheduling plan is estimated based on presence, it is characterised in that：Methods described bag
Include following steps：
Step 1：Determine power network future trend running mode data；
Step 2：Reasonability identification is carried out to Real-Time Scheduling plan, and it is automatically adjusted；
Step 3：Many section real power control models are set up, automatic fine tuning generating active power controller is carried out；
Step 4：Carry out reactive voltage to control on the spot, and distribute hub node idle amount of unbalance；
Step 5：Load flow calculation is carried out, the Load flow calculation data for power network future trend dynamic secure estimation are generated；
The step 2 specifically includes following steps：
Step 2-1：Reasonability identification, including plan Time-Series analysis, plan association analysis and plan are carried out to Real-Time Scheduling plan
The degree of balance is analyzed；
Step 2-2：The expertise arranged according to power network plan, sets up the constraint knowledge storehouse of Real-Time Scheduling plan, and to real-time
Operation plan is automatically adjusted, and the expertise constraint in constraint knowledge storehouse includes generate electricity maintenance mutual exclusion constraint, generation schedule
Temporal constraint, repair schedule mutual exclusion constraint and generating set units limits.
2. the trend tidal current computing method according to claim 1 estimated based on presence with Real-Time Scheduling plan, its
It is characterised by：In the step 1, power network future trend running mode data includes presence estimated data, Real-Time Scheduling meter
Draw data and ultra-short term data.
3. the trend tidal current computing method according to claim 2 estimated based on presence with Real-Time Scheduling plan, its
It is characterised by：According to the grid measurement data obtained online, dynamic power system internal state is estimated using statistical method, obtained
To presence estimated data；
On the basis of operation plan a few days ago, with reference to the transaction of ultra-short term information, ad hoc inspection and repair information and transregional electricity
The real-time generation schedule of corresponding period gets in touch with trading program with real-time in application information, formulation power network future 5min or in 60min,
Obtain Real-Time Scheduling planning data；
Using existing history daily load data and meteorological data, to the corresponding period is born in power network future 5min or in 60min
Charge values are estimated, complete to include the ultra-short term that system loading prediction and bus load are predicted, obtain ultra-short term and bear
Lotus prediction data.
4. the trend tidal current computing method according to claim 1 estimated based on presence with Real-Time Scheduling plan, its
It is characterised by：Plan in Time-Series analysis, be divided into following two situations：
A) judge that Real-Time Scheduling planning data or ultra-short term data whether there is the shortage of data at certain time point, if depositing
It is considered as singular point in the Real-Time Scheduling planning data or ultra-short term data at the then time point；
B) whether generating set plan power generating value rate of change in sequential exerts oneself more than generating set plan in real-time generation schedule
Given threshold, as being considered as singular point more than if.
5. the trend tidal current computing method according to claim 1 estimated based on presence with Real-Time Scheduling plan, its
It is characterised by：Plan in association analysis, rational Real-Time Scheduling plan is determined whether according to following four Rule of judgment, if its
In have it is any be unsatisfactory for, then be determined as irrational Real-Time Scheduling plan；
A) generating set plan power generating value is not higher than the actual upper limit of exerting oneself of generating set in real-time generation schedule；
B) not grid-connected generating set is exerted oneself without plan；
C) in real-time generation schedule generating set plan power generating value putting equipment in service state is consistent in the works with real-time examination and repair；
D) putting equipment in service state numerical value contradiction to real-time examination and repair does not occur in the works.
6. the trend tidal current computing method according to claim 1 estimated based on presence with Real-Time Scheduling plan, its
It is characterised by：Plan in degree of balance analysis, to ultra-short term, in real time real-time generation schedule, the progress of contact trading program
Plan degree of balance analysis, have：
<mrow>
<msub>
<mover>
<mi>P</mi>
<mo>^</mo>
</mover>
<mi>L</mi>
</msub>
<mo>=</mo>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>g</mi>
<mo>&Element;</mo>
<mi>M</mi>
</mrow>
</munder>
<msub>
<mi>P</mi>
<mi>g</mi>
</msub>
<mo>-</mo>
<msub>
<mi>P</mi>
<mrow>
<mi>e</mi>
<mi>x</mi>
<mi>c</mi>
<mi>h</mi>
</mrow>
</msub>
<mo>=</mo>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>d</mi>
<mo>&Element;</mo>
<mi>N</mi>
</mrow>
</munder>
<msub>
<mi>P</mi>
<mi>d</mi>
</msub>
<mo>+</mo>
<msub>
<mi>P</mi>
<mrow>
<mi>l</mi>
<mi>o</mi>
<mi>s</mi>
<mi>s</mi>
</mrow>
</msub>
<mo>+</mo>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>p</mi>
<mi>l</mi>
<mo>&Element;</mo>
<mi>O</mi>
</mrow>
</munder>
<msub>
<mi>P</mi>
<mrow>
<mi>p</mi>
<mi>l</mi>
</mrow>
</msub>
</mrow>
Wherein,For system loading predicted value, PgFor generating set plan power generating value, PexchExerted oneself for contact trading program in real time
Value, PdFor bus load predicted value, PlossFor system losses, PplFor the station service active power in power plant, M is generating set number
Amount, N is bus load quantity, and O is power plant quantity.
7. the trend tidal current computing method according to claim 1 estimated based on presence with Real-Time Scheduling plan, its
It is characterised by：Generate electricity in maintenance mutual exclusion constraint, when real-time generation schedule has mutual exclusion with real-time examination and repair plan and conflicted, to examine in real time
Repair to exert oneself to generating set on the basis of state and be adjusted, specifically have：
<mrow>
<msubsup>
<mi>P</mi>
<mrow>
<msub>
<mi>G</mi>
<mi>&alpha;</mi>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
<mo>&prime;</mo>
</msubsup>
<mo>=</mo>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>G</mi>
<mi>&alpha;</mi>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>&CenterDot;</mo>
<msub>
<mi>S</mi>
<mrow>
<msub>
<mi>G</mi>
<mi>&alpha;</mi>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
</mrow>
Wherein,For generating set plan power generating value in real-time generation schedule after adjustment,For real-time generation schedule before adjustment
Middle generating set plan power generating value,For real-time examination and repair putting equipment in service state in the works；
In generation schedule temporal constraint, when real-time generation schedule has singular point in sequential, by the generating near its time point
Unit plan power generating value is adjusted, and is specifically had：
<mrow>
<msubsup>
<mi>P</mi>
<mrow>
<msub>
<mi>G</mi>
<mi>&alpha;</mi>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
<mo>&prime;</mo>
</msubsup>
<mo>=</mo>
<mfrac>
<mrow>
<msub>
<mi>P</mi>
<mrow>
<mi>&alpha;</mi>
<mo>,</mo>
<mi>t</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>P</mi>
<mrow>
<mi>&alpha;</mi>
<mo>,</mo>
<mi>t</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msub>
</mrow>
<mn>2</mn>
</mfrac>
</mrow>
Wherein, Pα,t-1Generating set plan power generating value near time t-1 where singular point, Pα,t+1The time where singular point
Plan power generating value near t+1；
In repair schedule mutual exclusion constraint, real-time examination and repair is when in the works there is mutual exclusion constraint in putting equipment in service state, with devices in system
Repair schedule is adjusted on the basis of actual motion state, specifically had：
S′β,plan=Sβ,ope
Wherein, S 'β,planThe real-time examination and repair equipment β in the works state that puts into operation, S after adjustmentβ,opeFor devices in system β actual fortune
Row state；
In generating set units limits, generating set plan power generating value exists mutual with generating set in system in real-time generation schedule
During reprimand constraint, generating set plan power generating value in real-time generation schedule is adjusted on the basis of generating set in system, had
Body has：
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<msubsup>
<mi>P</mi>
<mrow>
<msub>
<mi>G</mi>
<mi>&alpha;</mi>
</msub>
<mo>,</mo>
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<mo>&prime;</mo>
</msubsup>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
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<mi>P</mi>
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<mi>G</mi>
<mi>&alpha;</mi>
</msub>
<mo>,</mo>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
</mtd>
<mtd>
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<mi>P</mi>
<mrow>
<msub>
<mi>G</mi>
<mi>&alpha;</mi>
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<mo>,</mo>
<mi>t</mi>
</mrow>
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<mo>></mo>
<msub>
<mi>P</mi>
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<mi>G</mi>
<mi>&alpha;</mi>
</msub>
<mo>,</mo>
<mi>m</mi>
<mi>a</mi>
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</mrow>
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<mi>P</mi>
<mrow>
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<mi>G</mi>
<mi>&alpha;</mi>
</msub>
<mo>,</mo>
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</mtd>
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<mi>G</mi>
<mi>&alpha;</mi>
</msub>
<mo>,</mo>
<mi>m</mi>
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<mi>n</mi>
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<mo>,</mo>
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</mrow>
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<mo><</mo>
<msub>
<mi>P</mi>
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<mi>G</mi>
<mi>&alpha;</mi>
</msub>
<mo>,</mo>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>G</mi>
<mi>&alpha;</mi>
</msub>
<mo>,</mo>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
</mrow>
</msub>
</mtd>
<mtd>
<mrow>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>G</mi>
<mi>&alpha;</mi>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo><</mo>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>G</mi>
<mi>&alpha;</mi>
</msub>
<mo>,</mo>
<mi>min</mi>
</mrow>
</msub>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
</mrow>
Wherein,For,WithGenerating set is exerted oneself upper and lower bound respectively in system.
8. the trend tidal current computing method according to claim 1 estimated based on presence with Real-Time Scheduling plan, its
It is characterised by：The step 3 specifically includes following steps：
Step 3-1：Many section real power control models are set up, increase section active power deviation equation in power flow algorithm,
Section active power deviation equation is expressed as：
<mrow>
<msub>
<mi>&Delta;P</mi>
<mrow>
<mi>c</mi>
<mi>u</mi>
<mi>t</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>&gamma;</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mover>
<mi>&Sigma;</mi>
<msub>
<mi>N</mi>
<mrow>
<mi>l</mi>
<mi>i</mi>
<mi>n</mi>
<mi>e</mi>
</mrow>
</msub>
</mover>
<msub>
<mi>P</mi>
<mrow>
<mi>l</mi>
<mi>i</mi>
<mi>n</mi>
<mi>e</mi>
</mrow>
</msub>
<mo>-</mo>
<msub>
<mi>P</mi>
<mrow>
<mi>d</mi>
<mi>e</mi>
<mi>s</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>&gamma;</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mn>0</mn>
</mrow>
Wherein, Δ Pcut(γ) is section γ active power deviation, PlineFor section γ active power, for the N of the sectionline
The active power summation of bar circuit；Pdes(γ) is section γ active power desired value；
Step 3-2：Using the active power adjustable strategies of the method for successive approximation, many steps are passed through according to the active power deviation of section
It is whole, section active power is gradually adjusted to active power desired value；
Step 3-3：Generating set active power controller equation is set up, is specifically had：
Pδ(α)=fp(α)+η(δ)ΔPvail(α)
Wherein, Pδ(α) is the active power of α platform generating sets in the δ control group of planes, fp(α) opens up for generating set node
Constraint is flutterred, η (δ) is the active power controller factor of the δ control group of planes, Δ Pvail(α) is adjustable for the generating set of Weight
Exert oneself.
9. the trend tidal current computing method according to claim 1 estimated based on presence with Real-Time Scheduling plan, its
It is characterised by：The step 4 specifically includes following steps：
Step 4-1：Reactive voltage is carried out based on voltage power-less subregion to control on the spot；
Step 4-2：The idle amount of unbalance of hub node is distributed to the reactive power source in voltage power-less subregion.
10. the trend tidal current computing method according to claim 1 estimated based on presence with Real-Time Scheduling plan, its
It is characterised by：In the step 5, calculating is iterated using the Newton method based on node power equilibrium equation, and determine be
The running status of system, it is determined that the Load flow calculation data for power network future trend dynamic secure estimation, including the electricity on each bus
Pressure amplitude value and power distribution and power attenuation in phase angle, network.
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| CN105071385B (en) * | 2015-08-10 | 2019-02-12 | 国家电网公司 | A kind of grid operation data real-time analyzer |
| CN106887848B (en) * | 2015-12-16 | 2019-07-19 | 南京南瑞继保电气有限公司 | Voltage power-less real-time control method based on Fuzzy Pattern Recognition |
| CN105787606A (en) * | 2016-03-24 | 2016-07-20 | 国网辽宁省电力有限公司电力科学研究院 | Power dispatching online trend early warning system based on ultra short term load prediction |
| CN106356856B (en) * | 2016-09-18 | 2018-10-09 | 国电南瑞科技股份有限公司 | A kind of Security corrective computational methods based on partition load control |
| CN106786653A (en) * | 2016-12-30 | 2017-05-31 | 国网山东省电力公司泰安供电公司 | The group of planes regulation and control method and device of many sections |
| CN110019973A (en) * | 2017-09-30 | 2019-07-16 | 日本电气株式会社 | For estimating the causal methods, devices and systems between observational variable |
| CN109961160B (en) * | 2017-12-14 | 2024-01-19 | 中国电力科学研究院有限公司 | Power grid future operation trend estimation method and system based on tide parameters |
| CN109978307B (en) * | 2017-12-28 | 2023-05-26 | 广东电网有限责任公司电力调度控制中心 | Power spot market trend analysis system |
| CN109978210A (en) * | 2017-12-28 | 2019-07-05 | 广东电网有限责任公司电力调度控制中心 | A kind of electric power dispatching system |
| EP3540530B1 (en) * | 2018-03-15 | 2022-10-19 | Siemens Aktiengesellschaft | Method and assembly for controlling a technical system |
| CN109523091A (en) * | 2018-12-04 | 2019-03-26 | 国电南瑞科技股份有限公司 | It is a kind of meter and spot exchange power grid future method of operation security analysis method |
| CN111162565B (en) * | 2019-12-26 | 2023-06-20 | 国网宁夏电力有限公司 | Online splicing method and system for medium-low voltage network based on multi-source data fusion |
| CN112734592A (en) * | 2020-12-14 | 2021-04-30 | 中国电力科学研究院有限公司 | Method and system for acquiring fusion data of multi-source information of electric power system |
| CN112701678B (en) * | 2020-12-18 | 2023-02-17 | 国网辽宁省电力有限公司 | Power grid evolution trend analysis method |
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