CN106992523A - A kind of tidal current computing method for the power system containing photovoltaic and thermic load - Google Patents
A kind of tidal current computing method for the power system containing photovoltaic and thermic load Download PDFInfo
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- CN106992523A CN106992523A CN201710274716.4A CN201710274716A CN106992523A CN 106992523 A CN106992523 A CN 106992523A CN 201710274716 A CN201710274716 A CN 201710274716A CN 106992523 A CN106992523 A CN 106992523A
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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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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- G—PHYSICS
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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
- 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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Abstract
The present invention relates to a kind of tidal current computing method for the power system containing photovoltaic and thermic load, comprise the following steps：The thermic load power in active power output data and weather sensitive load system in collection distributed photovoltaic power system is used as variable；Calculate the edge cumulative distribution function of each variable；According to the variable of collection and edge cumulative distribution function, joint probability distribution is obtained by asking for Copula functions；According to joint probability distribution, the edge cumulative probability Distribution Value of each variable of stochastic production specified quantity, jointing edge cumulative distribution function obtains the simulation sample value of each variable；Load flow calculation is carried out using the simulation sample value of all variables as input.Compared with prior art, the present invention have the advantages that to have taken into full account weather sensitive load and photovoltaic exert oneself between meteorological correlation, improve the model accuracy of power system and lift comprehensive utilization rate of energy source.
Description
Technical field
The present invention relates to Power System Analysis field, it is used for the power system containing photovoltaic and thermic load more particularly, to a kind of
Tidal current computing method.
Background technology
Meteorological system is a complicated system, between the meteorological variables such as illumination, temperature, humidity and wind speed and different empty
Between position same meteorological variables between all having differences property, similitude, correlation and coupling.Phase between meteorologic factor
Closing property causes there is certain dependency relation between the intermittent distributed energy such as distributed photovoltaic power and thermic load.It is distributed
Dependency relation between photo-voltaic power supply has been obtained for academia widely concern and research.For negative containing photovoltaic at high proportion and heat
The power system of lotus, in addition to the dependency relation between distributed photovoltaic power, building heating system and distributed photovoltaic electricity
There is the linearly or nonlinearly dependency relation of complexity between source.For building heating system, illumination, temperature and wind speed are
Calculate the principal element of heat load.When using electric air-conditioning or co-generation unit heating, consume power network electric power or to
The electric power of power network injection will be influenceed by meteorologic factor.The electric power that the electric power of electric air-conditioning consumption or cogeneration of heat and power are sent is with dividing
Cloth photo-voltaic power supply is exerted oneself with certain dependency relation.It is existing for the power system containing photovoltaic at high proportion and thermic load
Load flow calculation, is still only to consider that the parameter that photovoltaic is exerted oneself obtains sample and a consideration weather sensitive load that photovoltaic is exerted oneself respectively
Parameter obtain the sample of weather sensitive load, carry out Load flow calculation again afterwards, this mode do not account for photovoltaic exert oneself it is gentle
As the contact between sensitive load, so as to cause final result of calculation authenticity and accuracy relatively low.
The content of the invention
The purpose of the present invention is to provide a kind of trend for the power system containing photovoltaic and thermic load regarding to the issue above
Computational methods.
The purpose of the present invention can be achieved through the following technical solutions：
A kind of tidal current computing method for the power system containing photovoltaic and thermic load, the electricity containing photovoltaic and thermic load
Force system includes distributed photovoltaic power system and thermic load, and methods described comprises the following steps：
1) the thermic load power in the active power output data and thermic load in collection distributed photovoltaic power system is used as change
Amount；
2) calculation procedure 1) in each variable edge cumulative distribution function；
3) according to step 1) in collection variable and step 2) in obtained edge cumulative distribution function, by asking for
Copula functions obtain joint probability distribution；
4) according to step 3) in obtained joint probability distribution, the edge accumulation of each variable of stochastic production specified quantity
Probability distribution value, with reference to step 2) in edge cumulative distribution function obtain the simulation sample value of each variable；
5) Load flow calculation is carried out using the simulation sample value of all variables as input.
The step 2) be specially：
21) the edge cumulative distribution function of each variable is asked for using method for parameter estimation；
22) to step 21) in obtained edge cumulative distribution function carry out hypothesis testing, and judge that hypothesis testing is
It is no to pass through, if then entering step 3), if otherwise return to step 21).
The method for parameter estimation includes point estimations, moments estimation method, order statistic method, maximum likelihood estimate or most
Small square law.
The hypothesis testing includes u-test method, t methods of inspection, Chi-square method, F methods of inspection or rank test method.
The step 3) be specially：
31) according to step 1) in collection variable and step 2) in each variable edge cumulative distribution function, meter
The Copula function expressions of all variables of joint are calculated, the species of the Copula function expressions is no less than 3 kinds；
32) square Euclidean distance of each Copula function expression is asked for；
33) the minimum Copula functions of square Euclidean distance are chosen and are used as joint probability distribution.
The step 31) be specially：
311) according to step 2) in obtained edge cumulative distribution function, calculation procedure 1) in collection variable correspondence
Edge cumulative distribution function value；
312) according to step 311) in obtained edge cumulative distribution function value, calculate all variables of joint
Copula function expressions.
The Copula function expressions include normal state Copula functions, t-Copula functions and Archimedean Copula letter
Number.
Described square of Euclidean distance be specially：
Wherein, d is square Euclidean distance, H (U1,j,U2,j,...,Um,j) it is Copula functions,
For experience Copula functions, Um,jFor the edge cumulative distribution function of j-th of sample of m-th of variable.
The step 4) be specially：
41) according to step 3) in obtained joint probability distribution, the edge of each variable of random generation specified quantity tires out
Product probability distribution value；
42) by step 41) in the obtained edge cumulative probability Distribution Value of each variable be substituting to step 2) edge tire out
In product probability-distribution function, the corresponding simulation sample value of each variable is obtained.
Compared with prior art, the invention has the advantages that：
(1) by using Copula functions, by the heat in the active power output and thermic load in distributed photovoltaic power system
Load power two parts variable is combined, and has obtained united probability distribution, then obtains institute by joint probability distribution
Have the edge cumulative probability distribution sample of variable, as the input of Load flow calculation, this method with it is traditional by distributed photovoltaic
Power-supply system carries out separate computations with weather sensitive load system and compared, and has taken into full account distributed photovoltaic power system and meteorology
The correlation of the family of sensitive load system, thus two systems can be accurately calculated by the coupling of multipotency stream to source-net-lotus
Combined effect, can significantly improve the accuracy of power system Stochastic Production Simulation.
(2) this method is regarded distributed photovoltaic power system and weather sensitive load system as an entirety and analyzed,
The importance of different type energy supplier and user collaborative cooperation is highlighted, by Demand-side and supply side depth integration, is planned as a whole
Optimization so that energy operation management is more efficient, can significantly lift the comprehensive utilization ratio of the energy.
(3) when asking for the edge cumulative distribution function of each variable, hypothesis testing has been carried out to asking for result, and
Result not by hypothesis testing is recalculated, this method can greatly promote edge cumulative distribution function
Order of accuarcy, so as to improve the confidence level of final calculation result.
(4) substantial amounts of method is all contained in parameter Estimation and hypothesis testing, can be chosen and best suited according to actual conditions
Method for parameter estimation and hypothesis testing method under current environment, degree of flexibility are high.
(5) when asking for joint probability distribution function by Copula function expressions, be first calculate it is a variety of
Copula function expressions, then calculate square Euclidean distance of every kind of expression formula, choose square Euclidean distance drunk
Copula function expressions can cause the joint probability distribution function asked for reach as joint probability distribution function, this mode
To optimal, the order of accuarcy calculated is improved.
Brief description of the drawings
Fig. 1 is flow chart of the method for the present invention.
Embodiment
The present invention is described in detail with specific embodiment below in conjunction with the accompanying drawings.The present embodiment is with technical solution of the present invention
Premised on implemented, give detailed embodiment and specific operating process, but protection scope of the present invention is not limited to
Following embodiments.
As shown in figure 1, the present embodiment proposes a kind of Load flow calculation side for the power system containing photovoltaic and thermic load
Method, wherein the power system containing photovoltaic and thermic load includes distributed photovoltaic power system and thermic load, this method includes following
Step：
1) the thermic load power in the active power output data and thermic load in collection distributed photovoltaic power system is used as change
Amount；
2) calculation procedure 1) in each variable edge cumulative distribution function：
21) using method for parameter estimation (including point estimations, moments estimation method, order statistic hair, maximum likelihood estimate
Or least square method) ask for the edge cumulative distribution function of each variable；
22) to step 21) in obtained edge cumulative distribution function carry out hypothesis testing (including u-test method, t inspection
Test method, Chi-square method, F methods of inspection or rank test method), and judge whether hypothesis testing passes through, if then entering step 3),
If otherwise return to step 21)；
3) according to step 1) in collection variable and step 2) in obtained edge cumulative distribution function, by asking for
Copula functions obtain joint probability distribution：
31) 31) according to step 1) in collection variable and step 2) in each variable edge cumulative distribution function,
Calculate the Copula function expressions of all variables of joint, the species of the Copula function expressions is no less than 3 kinds (including just
State Copula functions, t-Copula functions and Archimedean Copula function)：
311) according to step 2) in obtained edge cumulative distribution function, calculation procedure 1) in collection variable correspondence
Edge cumulative distribution function value；
312) according to step 311) in obtained edge cumulative distribution function value, calculate all variables of joint
Copula function expressions；
32) square Euclidean distance of each Copula function expression is asked for, is specially：
Wherein, d is square Euclidean distance, H (U1,j,U2,j,...,Um,j) it is Copula functions,
For experience Copula functions, Um,jFor the edge cumulative distribution function of j-th of sample of m-th of variable；
33) the minimum Copula functions of square Euclidean distance are chosen and are used as joint probability distribution function；
4) according to step 3) in obtained joint probability distribution, the edge accumulation of each variable of stochastic production specified quantity
Probability distribution value, with reference to step 2) in edge cumulative distribution function obtain the simulation sample value of each variable：
41) according to step 3) in obtained joint probability distribution, the edge of each variable of random generation specified quantity tires out
Product probability distribution value；
42) by step 41) in the obtained edge cumulative probability Distribution Value of each variable be substituting to step 2) edge tire out
In product probability-distribution function, the corresponding simulation sample value of each variable is obtained；
5) Load flow calculation is carried out using the simulation sample value of all variables as input.
Specific Load flow calculation is carried out according to above-mentioned steps, process is as follows：
(s1) the active power output data of whole heating season are gathered from distributed photovoltaic system；From the electric air-conditioning system of building
The thermic load power of whole heating season is gathered in system；Collection is whole from co-generation unit (method of operation is electricity determining by heat)
The active power output data of heating season；Described active power output, thermic load power are gathered from electric energy management system database；Electricity
Can Management System Data storehouse without data gathered from distributed photovoltaic power system, the electric energy meter of co-generation unit；Institute
Distributed photovoltaic system, the electric air-conditioning system of building, the co-generation unit each single item stated all can arrive multiple systems for 0, depending on connecing
Depending on the situation for entering power network, the active power output of a specific system or burden with power are referred to as i-th of variable, it is assumed that shared m
Variable, each n timed sample sequence of variable.
(s2) active power output or thermic load power gathered according to above-mentioned steps (s1), is counted respectively using method for parameter estimation
Calculate the edge cumulative distribution function of i-th of variable.Method for parameter estimation uses the point estimation method, including moments estimation method, suitable
Sequence statistics variable method, maximum likelihood method and least square method.If the edge cumulative probability distribution of j-th of sample of i-th of variable is public
Formula is as follows：
Ui,j=F (xi,j)
Wherein, xi,jFor j-th of sample of i-th of variable, Ui,jFor sample xi,jThe distribution of edge cumulative probability.
(s3) distribution pattern and parameter property of the edge cumulative probability distribution calculated above-mentioned steps (s2) are assumed
Examine.Conventional hypothesis testing method has u-method of inspection, t methods of inspection, chi-square criterion method (Chi-square Test), F-method of inspection, sum of ranks
Examine etc..By assuming that the continuation step (s4) examined, not by assuming that the return to step (s2) examined.
(s4) it is that the active power output or thermic load power and above-mentioned steps (s2) gathered according to above-mentioned steps (s1) is calculated and
The marginal probability distribution formula examined by above-mentioned steps (s3), calculates a variety of Copula function expressions, includes normal state
Copula functions, t-Copula functions and Archimedean Copula function etc..The one of which Copula function expressions of calculating
It is as follows：
H(U1,j,U2,j,...,Um,j)=C (F (x1,j),F(x2,j),...,F(xm,j))
(s5) it is that the active power output or thermic load power and above-mentioned steps (s2) gathered according to above-mentioned steps (s1) is calculated and
The marginal probability distribution formula examined by above-mentioned steps (s3), calculates experience Copula functions, and its expression formula is as follows：
(s6) a kind of Copula function representations are chosen in above-mentioned steps (s4) according to the minimum principle of square Euclidean distance
Formula, square Euclidean distance calculation formula is as follows：
(s7) the Copula functions selected according to above-mentioned steps (s6), generate the edge cumulative probability point of each variable at random
Cloth, cumulative probability distribution sample in each variable edge is N.
(s8) the variable edge cumulative probability generated according to above-mentioned steps (s7) is distributed sample and above-mentioned steps (s2) are calculated
And by above-mentioned steps (s3) examine marginal probability distribution formula inverse operation, generate the N number of corresponding variable sample bands of m ╳
Accounting equation after the fashion, can calculate and obtain N number of corresponding calculation of tidal current.
Claims (9)
1. a kind of tidal current computing method for the power system containing photovoltaic and thermic load, the electric power containing photovoltaic and thermic load
System includes distributed photovoltaic power system and thermic load, it is characterised in that methods described comprises the following steps：
1) the thermic load power in the active power output data and thermic load in collection distributed photovoltaic power system is used as variable；
2) calculation procedure 1) in each variable edge cumulative distribution function；
3) according to step 1) in collection variable and step 2) in obtained edge cumulative distribution function, by asking for
Copula functions obtain joint probability distribution；
4) according to step 3) in obtained joint probability distribution, the edge cumulative probability of each variable of stochastic production specified quantity
Distribution Value, with reference to step 2) in edge cumulative distribution function obtain the simulation sample value of each variable；
5) Load flow calculation is carried out using the simulation sample value of all variables as input.
2. the tidal current computing method according to claim 1 for the power system containing photovoltaic and thermic load, its feature exists
In the step 2) be specially：
21) the edge cumulative distribution function of each variable is asked for using method for parameter estimation；
22) to step 21) in obtained edge cumulative distribution function carry out hypothesis testing, and judge whether hypothesis testing leads to
Cross, if then entering step 3), if otherwise return to step 21).
3. the tidal current computing method according to claim 2 for the power system containing photovoltaic and thermic load, its feature exists
In the method for parameter estimation includes point estimations, moments estimation method, order statistic method, maximum likelihood estimate or a most young waiter in a wineshop or an inn
Multiplication.
4. the tidal current computing method according to claim 2 for the power system containing photovoltaic and thermic load, its feature exists
In the hypothesis testing includes u-test method, t methods of inspection, Chi-square method, F methods of inspection or rank test method.
5. the tidal current computing method according to claim 1 for the power system containing photovoltaic and thermic load, its feature exists
In the step 3) be specially：
31) according to step 1) in collection variable and step 2) in each variable edge cumulative distribution function, calculate connection
The Copula function expressions of all variables are closed, the species of the Copula function expressions is no less than 3 kinds；
32) square Euclidean distance of each Copula function expression is asked for；
33) the minimum Copula functions of square Euclidean distance are chosen and are used as joint probability distribution.
6. the tidal current computing method according to claim 5 for the power system containing photovoltaic and thermic load, its feature exists
In the step 31) be specially：
311) according to step 2) in obtained edge cumulative distribution function, calculation procedure 1) in collection the corresponding side of variable
Edge cumulative distribution function value；
312) according to step 311) in obtained edge cumulative distribution function value, calculate the Copula letters of all variables of joint
Number expression formula.
7. the tidal current computing method according to claim 5 for the power system containing photovoltaic and thermic load, its feature exists
In the Copula function expressions include normal state Copula functions, t-Copula functions and Archimedean Copula function.
8. the tidal current computing method according to claim 5 for the power system containing photovoltaic and thermic load, its feature exists
In described square of Euclidean distance is specially：
Wherein, d is square Euclidean distance, H (U1,j,U2,j,...,Um,j) it is Copula functions,For warp
Test Copula functions, Um,jFor the edge cumulative distribution function of j-th of sample of m-th of variable.
9. the tidal current computing method according to claim 1 for the power system containing photovoltaic and thermic load, its feature exists
In the step 4) be specially：
41) according to step 3) in obtained joint probability distribution, the edge accumulation of each variable of random generation specified quantity is general
Rate Distribution Value；
42) by step 41) in the obtained edge cumulative probability Distribution Value of each variable be substituting to step 2) edge accumulation it is general
In rate distribution function, the corresponding simulation sample value of each variable is obtained.
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| CN112332416A (en) * | 2020-11-12 | 2021-02-05 | 国网内蒙古东部电力有限公司经济技术研究院 | Power distribution network load prediction method and system based on photovoltaic electric heating load correlation |
| CN112711864A (en) * | 2021-01-18 | 2021-04-27 | 国网浙江省电力有限公司电力科学研究院 | Distribution network cable quality index correlation model construction and data expansion method |
| CN112711864B (en) * | 2021-01-18 | 2024-06-07 | 国网浙江省电力有限公司电力科学研究院 | Distribution network cable quality index correlation model construction and data expansion method |
| CN113935250A (en) * | 2021-11-25 | 2022-01-14 | 华北电力大学（保定） | New energy cluster modeling method based on comprehensive probability model and Markov matrix |
| CN113935250B (en) * | 2021-11-25 | 2024-04-23 | 华北电力大学（保定） | New energy cluster modeling method based on comprehensive probability model and Markov matrix |
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