CN104063255A - Grid-connected type micro-grid economic operating method based on sequence operation - Google Patents
Grid-connected type micro-grid economic operating method based on sequence operation Download PDFInfo
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Abstract
The invention relates to a grid-connected type micro-grid economic operating method based on sequence operation. Sequence operation is conducted on multiple random variables such as draught fan output, photovoltaic power generation and loads in a grid-connected type micro-grid to generate an equivalent load probabilistic sequence, the probability of meeting the demands of equivalent load power is calculated, and thus the probability of meeting reliability constrains is calculated. The random variables such as draught fan output, photovoltaic power generation and the loads in the grid-connected type micro-grid are taken into consideration, and the actual operating state is better met; compared with a traditional random simulating method, the calculating efficiency is obviously improved through the application of the sequence operation theory; the defect that the calculation results of all times are different in the random simulating method is overcome; the met constrain conditions are expressed in a probability mode, and higher visibility is achieved.
Description
Technical field
The present invention relates to a kind of microgrid operation optimisation technique, particularly a kind of grid type microgrid economical operation method based on Sequence Operation Theory.
Background technology
Microgrid generally accesses wind-power electricity generation, the photovoltaic generation distributed power supply of larger proportion, to system, operation has brought larger negative effect to the undulatory property of its randomness and intermittent and load, therefore in Optimized Operation using uncertain factor as stochastic variable, more meet actual motion state.
For the Optimized Operation of considering uncertain factor in microgrid, conventionally set up the scheduling model based on chance constrained programming, and apply monte carlo method and simulate stochastic variable, the number of times that calculates simulation total degree and meet constraint, and by law of great numbers, try to achieve the probability that meets constraint, with this, judge whether to meet chance constraint.This kind of method realizes than being easier in the situation that stochastic variable is less, but when the stochastic variable of considering is more, the drawback that its consuming time and each result of calculation is different is further obvious.
Summary of the invention
The present invention be directed to the problem of the drawback that the each result of calculation of stochastic simulation method is different, a kind of grid type microgrid economical operation method based on Sequence Operation Theory has been proposed, the expression uncertain factor of the formal intuition by probability, has simplified calculating, has improved optimization efficiency.
Technical scheme of the present invention is: a kind of grid type microgrid economical operation method based on Sequence Operation Theory, specifically comprises the steps:
1) sequence of random variables modeling:
The probability density function of known stochastic variable is
f (p), its Probabilistic sequences is:
In formula:
n f for sequence length, be taken as [
p max /△
p], [
p max /△
p] for being not more than
p max /△
pinteger;
p max for stochastic variable maximal value; △
pfor discretize step-length, generally get a plurality of stochastic variable common divisors, by formula, by the discrete Probabilistic sequences that turns to of continuous probability distribution, can obtain that blower fan is exerted oneself, probability density and the corresponding Probabilistic sequences of photovoltaic generation and load;
2) blower fan Probabilistic sequences and photovoltaic generation Probabilistic sequences volume and the computing generation Probabilistic sequences of jointly exerting oneself at random of exerting oneself:
Try to achieve
tperiod blower fan is exerted oneself
p wTt and photovoltaic generation
p pVt probabilistic sequences be respectively
a(
i at ),
b(
i bt ), its sequence length is respectively
n at , N bt , order is exerted oneself jointly at random
p wTPVt probabilistic sequences is
c(
i ct ), sequence length is
n ct ,
c(
i ct ) by
a(
i at ) with
b(
i bt ) roll up and calculate:
c(
i ct )=
a(
i at ) ⊕ b (
i bt ),
n ct =N at + N bt , according to volume and definition, have:
Condition for peace in summation wherein number " ∑ " is illustrated in span and meets
i at +
i bt =
i ct [
i at , i bt ] all combinations, the sequence that participates in computing is all Probabilistic sequences;
3) Load Probability sequence and the Probabilistic sequences of jointly exerting oneself at random volume difference operation generate equivalent load Probabilistic sequences, definition equivalent load power (
p eL ) and load power (
p l ), blower fan exert oneself (
p wT ) and photovoltaic exert oneself (
p pV ) relation be expressed as follows:
Try to achieve the period
tinterior load
p l (
t) Probabilistic sequences is
d(
i dt ), sequence length is
n dt , make equivalent load
p eL (
t) Probabilistic sequences be
f(
i ft ), sequence length
n ft , by Load Probability sequence
d(
i dt ) and the Probabilistic sequences of jointly exerting oneself at random
c(
i ct ) volume difference operation obtain:
f(
i ft )=
d(
i dt ) Θ
c(
i ct ), N
ft=N
dt, according to volume difference operation, have:
；
4) standby probability constraint is calculated:
Equivalent load
p eL (
t) Probabilistic sequences is the equivalent Probabilistic sequences of all stochastic variables of internal system, calculates for convenience the standby probability that meets, as
r(
t) represent the margin capacity that micro-grid system can provide, define the Probabilistic sequences of equivalent load
f(
i ft ) corresponding 0-1 variable
h(
i ht ) as follows:
, exist
tperiod, when micro-grid system meets Reserve Constraint, 0-1 variable gets 1, meets system reserve demand, otherwise gets 0,
e(
p eL (
t)) be the period
tthe expectation value of interior equivalent load, is equivalent load Probabilistic sequences 1 rank moment of the orign, is expressed as follows:
The satisfied probability of Reserve Constraint is:
While meeting reliability constraint
f(
i ft ) * 1, while not meeting
f(
i ft ) * 0, be then added the probability sum that obtains all satisfied constraints, when
β > αtime, standbyly meet chance constraint, wherein
αfor meeting standby confidence level.
Beneficial effect of the present invention is: the present invention is based on the grid type microgrid economical operation method of Sequence Operation Theory, considered that grid type microgrid inner blower is exerted oneself, a plurality of stochastic variables such as photovoltaic generation and load, more realistic running status; Application sequence operation theory is compared traditional Method of Stochastic and has been significantly improved counting yield; Avoided the different drawback of the each result of calculation of stochastic simulation method; Meet constraint condition and represent with the form of probability, more directly perceived.
Accompanying drawing explanation
Fig. 1 is 10 wind speed probability distribution and blower fan capability diagram in the morning of the present invention;
Fig. 2 is 10 blower fans Probabilistic sequences figure that exerts oneself in the morning of the present invention;
Fig. 3 is 10 photovoltaic generation probability distribution and Probabilistic sequences figure in the morning of the present invention;
Fig. 4 is point load probability distribution and Probabilistic sequences figure in mornings 10 of the present invention;
Fig. 5 is 10 equivalent load Probabilistic sequences figure in the morning of the present invention;
Fig. 6 is microgrid structural drawing of the present invention;
Fig. 7 is the optimum results figure under the different discretize step-lengths of the present invention.
Embodiment
The present invention by grid type microgrid inner blower is exerted oneself, a plurality of stochastic variables such as photovoltaic generation and load generate an equivalent load Probabilistic sequences by Sequence Operation Theory, by calculating, meet the probability of equivalent load power demand, calculate the probability that meets reliability constraint.
Technical scheme is as follows:
For convenience of computing to a plurality of stochastic variables, by blower fan exert oneself, the equivalence value of photovoltaic generation and load is defined as equivalent load (
equivalent Load, EL), equivalent load power (
p eL ) itself and load power (
p l ), blower fan exert oneself (
p wT ) and photovoltaic exert oneself (
p pV ) relation be expressed as follows:
The load of the stochastic variable available equivalents in microgrid represents.Wind-power electricity generation and photovoltaic generation Probabilistic sequences application volume and computing are obtained to the Probabilistic sequences of jointly exerting oneself at random, equivalent load Probabilistic sequences by Load Probability sequence and the Probabilistic sequences of jointly exerting oneself at random roll up difference operation and obtain.
1) sequence of random variables modeling
According to the requirement of sequence operation theory, convert each stochastic variable to Probabilistic sequences.If the probability density function of known stochastic variable is
f (p), its Probabilistic sequences is:
In formula:
n f for sequence length, be taken as [
p max /△
p], [
x] represent to be not more than
xinteger, [
p max /△
p] for being not more than
p max /△
pinteger;
p max for stochastic variable maximal value; △
pfor discretize step-length, generally get a plurality of stochastic variable common divisors.By formula (1) by the discrete Probabilistic sequences that turns to of continuous probability distribution.Provide herein the morning 10 blower fans exert oneself, the probability density of photovoltaic generation and load and corresponding Probabilistic sequences be referring to accompanying drawing 1 and Fig. 2, Fig. 3, Fig. 4.
2) blower fan Probabilistic sequences and photovoltaic generation Probabilistic sequences volume and the computing generation Probabilistic sequences of jointly exerting oneself at random of exerting oneself
Try to achieve
tperiod blower fan is exerted oneself
p wTt and photovoltaic generation
p pVt probabilistic sequences be respectively
a(
i at ),
b(
i bt ), its sequence length is respectively
n at , N bt , order is exerted oneself jointly at random
p wTPVt probabilistic sequences is
c(
i ct ), sequence length is
n ct ,
c(
i ct ) by
a(
i at ) with
b(
i bt ) roll up and calculate:
c(
i ct )=
a(
i at ) ⊕ b (
i bt ),
n ct =N at + N bt .According to volume and definition, have:
It should be noted that, the condition for peace in the summation in formula (2) number " ∑ " is illustrated in span and meets
i at +
i bt =
i ct [
i at , i bt ] all combinations, the sequence that participates in computing is all Probabilistic sequences, in fact volume and computing represent two separate one-dimensional discrete type stochastic variable sums.
Due to night photovoltaic to exert oneself be 0, the photovoltaic Probabilistic sequences of exerting oneself can be expressed as null sequence, and the exert oneself result of Probabilistic sequences volume and computing of blower fan is still the blower fan Probabilistic sequences of exerting oneself.
3) Load Probability sequence and the Probabilistic sequences of jointly exerting oneself at random volume difference operation generate equivalent load Probabilistic sequences
Try to achieve the period
tinterior load
p l (
t) Probabilistic sequences is
d(
i dt ), sequence length is
n dt .Make equivalent load
p eL (
t) Probabilistic sequences be
f(
i ft ), sequence length
n ft , by Load Probability sequence
d(
i dt ) and the Probabilistic sequences of jointly exerting oneself at random
c(
i ct ) volume difference operation obtain:
f(
i ft )=
d(
i dt ) Θ
c(
i ct ),
n ft =
n dt .According to volume difference operation, have:
From formula (3), when
i ft ≠ 0 o'clock, presentation of events in fact
d(corresponding to sequence
d (i dt )) value and event
c(corresponding to sequence
c(i ct )) value differ into
i ft probability sum.The known difference sequence of now rolling up represents two one-dimensional discrete type stochastic variables
dwith
cpoor.
When
i ft =0time for all
devent value is less than or equal to
cthe probability sum of event value, is about to
dwith
cnegative loop in the difference of two stochastic variables merges to
i ft =in 0 this point, now making to roll up difference operation has had actual physical significance, and now equivalent load is less than 0, and standby satisfied probability is 100%, does not need to consider standby probability constraints, therefore all this situations is integrated into
i ft =0realistic analysis demand.Only be given in herein the morning 10 equivalent load Probabilistic sequences as shown in Figure 5.
If need taking into account system to bear Reserve Constraint, load sequence can be extended to negative semiaxis
n ct , the maximal value of loading is constant, and minimum value is taken as-
n ct *△
p, the sequence probability that is extended part is taken as 0, obtains new Load Probability sequence
d '(
i dt '), then with the sequence of jointly exerting oneself at random
c(
i ct ) volume difference operation, try to achieve equivalent load sequence.This kind of mode avoided equivalent load to be less than 0 situation merger for a bit, can obtain the Probabilistic sequences of equivalent load all situations, and then solve the probability that meets positive Reserve Constraint and negative Reserve Constraint.
4) standby probability constraint is calculated
Equivalent load
p eL (
t) Probabilistic sequences is the equivalent Probabilistic sequences of all stochastic variables of internal system.Calculate for convenience the standby probability that meets, as R (t) represents the margin capacity that micro-grid system can provide, the Probabilistic sequences of definition equivalent load
f(
i ft ) corresponding 0-1 variable
h(
i ht ) as follows:
Formula (4) shows:
tperiod, when micro-grid system meets Reserve Constraint, 0-1 variable gets 1, illustrates and meets system reserve demand, otherwise get 0.
e(
p eL (
t)) be the period
tthe expectation value of interior equivalent load, is equivalent load Probabilistic sequences 1 rank moment of the orign, is expressed as follows:
The satisfied probability of Reserve Constraint is:
Mean while meeting reliability constraint
f(
i ft ) * 1, while not meeting
f(
i ft ) * 0, be then added the probability sum that obtains all satisfied constraints.When
β > αtime, standbyly meet chance constraint, wherein
αfor meeting standby confidence level.
5) simulating, verifying
Based on above-mentioned proposition " the grid type microgrid economic optimization strategy based on Sequence Operation Theory ", with concrete micro-grid system structure, as accompanying drawing 6, systematic parameter, as shown in subordinate list 1, is programmed and is carried out simulating, verifying by C++.Be analyzed with solve chance constraint operation result by Monte-carlo Simulation Method, as shown in subordinate list 2, simultaneously comparative analysis optimum results under different discretize step-lengths as shown in Figure 7.
Table 1
Table 2
Operation result by subordinate list 2 can be seen, because stochastic variable in Optimized model is more, by simulation, need to repeatedly simulate its probability estimate just effective, increased greatly calculated amount, and by Sequence Operation Theory, only need stochastic variable probability distribution generating probability sequence, by rolling up poor volume and computing, obtain equivalent load Probabilistic sequences and can calculate the probability that meets reliability, greatly saved computing time, and optimum results is more desirable.
Accompanying drawing 7 is in order to verify the impact of different discretize step-lengths on optimum results.Get degree of confidence
α=95%, load fluctuation rate
σ l =10%: known, to load when lighter, system reserve capacity is sufficient, and discretize step-length meets the impact of probability not obvious to reliability; Load when heavier, discretize step-length is less, and optimum results approaches set confidence level, thereby has improved computational accuracy.And meet constraint condition and represent with the form of probability, more directly perceived.
By simulating, verifying carry strategy in the superiority that solves the microgrid Optimized model of considering a plurality of stochastic variables.
Claims (1)
1. the grid type microgrid economical operation method based on Sequence Operation Theory, is characterized in that, specifically comprises the steps:
1) sequence of random variables modeling:
The probability density function of known stochastic variable is
f (p), its Probabilistic sequences is:
In formula:
n f for sequence length, be taken as [
p max /△
p], [
p max /△
p] for being not more than
p max /△
pinteger;
p max for stochastic variable maximal value; △
pfor discretize step-length, generally get a plurality of stochastic variable common divisors, by formula, by the discrete Probabilistic sequences that turns to of continuous probability distribution, can obtain that blower fan is exerted oneself, probability density and the corresponding Probabilistic sequences of photovoltaic generation and load;
2) blower fan Probabilistic sequences and photovoltaic generation Probabilistic sequences volume and the computing generation Probabilistic sequences of jointly exerting oneself at random of exerting oneself:
Try to achieve
tperiod blower fan is exerted oneself
p wTt and photovoltaic generation
p pVt probabilistic sequences be respectively
a(
i at ),
b(
i bt ), its sequence length is respectively
n at , N bt , order is exerted oneself jointly at random
p wTPVt probabilistic sequences is
c(
i ct ), sequence length is
n ct ,
c(
i ct ) by
a(
i at ) with
b(
i bt ) roll up and calculate:
c(
i ct )=
a(
i at ) ⊕ b (
i bt ),
n ct =N at + N bt , according to volume and definition, have:
Condition for peace in summation wherein number " ∑ " is illustrated in span and meets
i at +
i bt =
i ct [
i at , i bt ] all combinations, the sequence that participates in computing is all Probabilistic sequences;
3) Load Probability sequence and the Probabilistic sequences of jointly exerting oneself at random volume difference operation generate equivalent load Probabilistic sequences, definition equivalent load power (
p eL ) and load power (
p l ), blower fan exert oneself (
p wT ) and photovoltaic exert oneself (
p pV ) relation be expressed as follows:
Try to achieve the period
tinterior load
p l (
t) Probabilistic sequences is
d(
i dt ), sequence length is
n dt , make equivalent load
p eL (
t) Probabilistic sequences be
f(
i ft ), sequence length
n ft , by Load Probability sequence
d(
i dt ) and the Probabilistic sequences of jointly exerting oneself at random
c(
i ct ) volume difference operation obtain:
f(
i ft )=
d(
i dt ) Θ
c(
i ct ), N
ft=N
dt, according to volume difference operation, have:
；
4) standby probability constraint is calculated:
Equivalent load
p eL (
t) Probabilistic sequences is the equivalent Probabilistic sequences of all stochastic variables of internal system, calculates for convenience the standby probability that meets, as
r(
t) represent the margin capacity that micro-grid system can provide, define the Probabilistic sequences of equivalent load
f(
i ft ) corresponding 0-1 variable
h(
i ht ) as follows:
Exist
tperiod, when micro-grid system meets Reserve Constraint, 0-1 variable gets 1, meets system reserve demand, otherwise gets 0,
e(
p eL (
t)) be the period
tthe expectation value of interior equivalent load, is equivalent load Probabilistic sequences 1 rank moment of the orign, is expressed as follows:
The satisfied probability of Reserve Constraint is:
While meeting reliability constraint
f(
i ft ) * 1, while not meeting
f(
i ft ) * 0, be then added the probability sum that obtains all satisfied constraints, when
β > αtime, standbyly meet chance constraint, wherein
αfor meeting standby confidence level.
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| CN106485358A (en) * | 2016-10-12 | 2017-03-08 | 国网上海市电力公司 | Binding sequence computing and the independent micro-capacitance sensor Optimal Configuration Method of particle cluster algorithm |
| CN113128071A (en) * | 2021-05-08 | 2021-07-16 | 南京工程学院 | Method for evaluating reliability of power generation system containing photovoltaic power generation |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104392389A (en) * | 2014-11-13 | 2015-03-04 | 广东电网有限责任公司电力科学研究院 | Method for evaluating load margin of photovoltaic power generation compensating peak |
| CN104392389B (en) * | 2014-11-13 | 2018-05-25 | 广东电网有限责任公司电力科学研究院 | A kind of method for assessing photovoltaic generation compensation peak load nargin |
| CN106485358A (en) * | 2016-10-12 | 2017-03-08 | 国网上海市电力公司 | Binding sequence computing and the independent micro-capacitance sensor Optimal Configuration Method of particle cluster algorithm |
| CN113128071A (en) * | 2021-05-08 | 2021-07-16 | 南京工程学院 | Method for evaluating reliability of power generation system containing photovoltaic power generation |
| CN113128071B (en) * | 2021-05-08 | 2024-02-09 | 南京工程学院 | Reliability evaluation method for power generation system containing photovoltaic power generation |
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