CN110322079A - A kind of flow of power plan optimization method - Google Patents
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Abstract
The invention discloses a kind of flow of power plan optimization methods, comprising steps of establishing the uncertain collection of new energy power output according to historical data；To minimize overall society cost as target, flow of power plan optimization model is established；Solving model, and export optimal solution.The present invention considers in the operation of power grid physical planning, the uncertainty of the new energy such as wind-powered electricity generation, photovoltaic power output, the section contributed according to new energy, target is minimised as with overall society cost, the model solution for establishing optimization flow of power planning goes out optimal solution, while realizing saving cost, flow of power has effectively been planned.
Description
Technical field
The present invention relates to Power System Planning fields, and in particular to a kind of flow of power plan optimization method.
Background technique
The Energy Base in China is concentrated mainly on western part, and load center is located at east.This production of energy and consumption are inverse
Determine that the transregional transmission of the energy and consumption become the important model of China's using energy source to the characteristics of distribution.Electric power is as main
Secondary energy sources can be transmitted on a large scale, at a distance by advanced UHV transmission technology.China has been turned on " transferring electricity from the west to the east "
Engineering consumes the western energy by power transmission to east, this is for reasonable disposition resource, Optimization of Energy Structure, promotion
Chinese society sustainable economic development are of great significance.In this context, how rational deployment passway for transmitting electricity construction, optimization
Flow of power scale value must be furtherd investigate.
The optimization of flow of power is needed in view of sending the matching of receiving end supply and demand and the constraint of electric network composition.Especially with wind-powered electricity generation
Power grid is accessed with intermittent new energy that photovoltaic is representative, it is electric power that new energy power output, which is stochastic variable and non-deterministic constant,
Stream planning brings very strong uncertainty.Currently used flow of power planing method is based primarily upon Deterministic Methods, uses
The prediction power output of the new energy such as wind-powered electricity generation, photovoltaic participates in power balance, this ignores the prediction as caused by scene power output randomness
Error.
In view of this, it is urgent to provide a kind of probabilistic flow of power plan optimization sides for reasonably considering new energy power output
Method.
Summary of the invention
In order to solve the above-mentioned technical problem, the technical scheme adopted by the invention is that providing a kind of flow of power plan optimization
Method, which comprises the following steps:
The uncertain collection of new energy power output is established according to historical data；To minimize overall society cost as target, electricity is established
Force flow plan optimization model；Solving model, and export optimal solution.
In the above-mentioned methods, the uncertain collection for establishing new energy power output is specific as follows: being established according to historical data embedding
Uncertain collection { the Ω of set1, Ω2…ΩNs,Wherein Ns is the number of uncertain collection；
For each uncertain collection ΩNs, ξi,sIt is stochastic variable, indicates the new energy power output of sending end region i, M sending end
The corresponding random vector ξ of region new energy power outputs=[ξ1,s,ξ2,s,…,ξi,s；I=1 ... M]；
Each uncertain collection ΩNsOne Probability p is all corresponded tos, indicate random vector ξs∈ΩNsProbability be ps, p1<
p2< ... < ps=1；
Construct probability sequence π1=p1, π2=p2﹣ p1, πs=ps﹣ ps-1。
In the above-mentioned methods, the overall society cost includes transregional power channel construction cost, fired power generating unit fuel cost
With receiving end electric power deficiency punishment cost.
In the above-mentioned methods, the overall society cost under the objective function optimization least favorable scene, and consider it is each not
Determine collection ΩNsCorresponding Probability ps, overall society cost is each uncertain collection ΩNsThe desired value of corresponding operating cost；
Meet the security constraint of Operation of Electric Systems, including unit output constraint, power balance, spinning reserve constraint, electricity
Force flow and power channel construction constraint and the external electric power ratio upper limit of receiving end.
In the above-mentioned methods, the objective function such as following formula:
In formula, PijFor sending end region i to the flow of power by end regions j；uijConstruction sending end is indicated for 0-1 decision variable, 1
Region i to the passway for transmitting electricity by end regions j, do not build by 0 expression；clAnd cpIt is passway for transmitting electricity unit length and unit capacity respectively
Construction cost；LijIt is from sending end region i to the line length by end regions j；Pij maxIt is sending end region i to by end regions j
Power transmission capacity of pow；Pi,s THIndicate uncertain collection ΩNsFired power generating unit is contributed in lower sending end region i, Pj,s THIndicate uncertain collection
ΩNsUnder contributed by fired power generating unit in end regions j,It is the electric power deficiency by end regions j；cTHIndicate thermoelectricity fuel cost,
cLSIndicate cutting load punishment；
It constrains as follows:
(3) unit output constrains
In formula,WithIt is sending end region thermoelectricity maximum output and minimum load respectively,WithBe respectively by
End regions fired power generating unit maximum output and minimum load；
(4) power balance
Met power balance, such as following formula by end regions and sending end region:
In formula,It is the electric load by end regions j；
(3) spinning reserve constrains
In formula, r is the percentage reserve by end regions j, and σ is after considering transregional power channel reliability, and external electric power participates in rotation
Turn the confidence level of spare capacity balance；
(4) related constraint of flow of power and power channel construction
In formula, M0For a constant；
(5) the external electric power ratio upper limit of receiving end
In formula, η % is that the electricity consumption that local power supply should meet needs ratio.
In the above-mentioned methods, the flow of power plan optimization model is solved by C&CG algorithm.
In the above-mentioned methods, the output optimal solution includes: minimum transregional power channel construction cost, minimum fired power generating unit
Fuel cost and minimum receiving end electric power deficiency punishment cost
The present invention considers that in the operation of power grid physical planning, the probability distribution of the new energy such as wind-powered electricity generation, photovoltaic power output is not
Certainty is minimised as target according to the section that new energy is contributed with overall society cost, establishes the mould of optimization flow of power planning
Type solves optimal solution, while realizing saving cost, has effectively planned flow of power.
Detailed description of the invention
Fig. 1 is flow chart provided by the invention；
Fig. 2 is Network Construction of Power Transmission of embodiment of the present invention schematic diagram；
Fig. 3 is the uncertain collection schematic diagram constructed in the embodiment of the present invention.
Specific embodiment
The uncertainty for reasonably considering new energy power output, using Cost for Coordination and reliability as target, optimization flow of power rule
It draws.The present invention is described in detail with Figure of description With reference to embodiment.
As shown in Figure 1, the present invention provides a kind of flow of power plan optimization methods, comprising the following steps:
In view of the actual conditions of transregional flow of power, only allow sending end to the electric power one-way flow of receiving end, as shown in Fig. 2,
For power transmission network provided in this embodiment, S in figure1,S2,…SMIt is M sending end region, R1,R2,…RNIt is N number of by end regions, figure
Middle arrow indicates the direction of flow of power.
The present embodiment considers that the mathematic programming methods of randomness according to the modeling pattern to stochastic variable, can be divided into two
Class: stochastic programming method and robust Optimal methods, the former assumes the probability distribution of stochastic variable it is known that optimizing under the probability distribution
Expected cost；The latter assumes that stochastic variable is in given section, optimizes the decision under least favorable scene, at the same make even if
Under worst scene, the security constraint of power grid is also able to satisfy.
In view of in physical planning is run, the probability distribution of the new energy such as wind-powered electricity generation, photovoltaic power output is usually that can not shift to an earlier date
It learns, so planning operation personnel are only capable of providing the section of new energy power output, the modeling framework of this and robust optimization mutually agrees with,
So the present embodiment proposes the flow of power plan optimization method based on robust optimization.
S1, according to above-mentioned power transmission network, establish the uncertain collection of new energy power output；It is specific as follows:
The present embodiment, the uncertain collection characterization of new energy power output is the possible range of new energy power output, to reduce robust
The conservative degree of optimization, as shown in figure 3, establishing nested uncertain collection { Ω according to historical data1, Ω2…ΩNs, andWherein Ns is the number of uncertain collection；
For each uncertain collection ΩNs, ξi,sIt is stochastic variable, indicates the new energy power output of sending end region i, therefore, M
The corresponding random vector ξ of sending end region new energy power outputs=[ξ1,s,ξ2,s,…,ξi,s；I=1 ... M]；
Each uncertain collection ΩNsOne Probability p is all corresponded tos, indicate random vector ξs∈ΩNsProbability be ps.By
InThere is p1< p2< ... < ps=1.Further, probability sequence π is constructed1=p1, π2=p2﹣
p1, πs=ps﹣ ps-1, this probability sequence reflects new energy power output and falls into the increased probability of more conservative uncertain collection institute.
S2, to minimize overall society cost as target, based on uncertain collection Ω1, Ω2…ΩNsIt is excellent to establish flow of power planning
Change model；It is specific as follows:
In the present embodiment, overall society cost includes transregional power channel construction cost, fired power generating unit fuel cost and receiving end
Electric power deficiency punishment cost, the present embodiment to simplify the analysis, so normal power supplies only but be not limited to consider fired power generating unit；
Overall society cost under objective function optimization least favorable scene, and consider each uncertain collection ΩNsCorresponding
Probability ps, overall society cost is each uncertain collection ΩNsThe desired value of corresponding operating cost, specifically, objective function such as following formula:
In formula, PijIt is sending end region i to the flow of power by end regions j；uijIt is 0-1 decision variable, 1 indicates construction sending end
Region i to the passway for transmitting electricity by end regions j, do not build by 0 expression；clAnd cpIt is passway for transmitting electricity unit length and unit capacity respectively
Construction cost；LijIt is from sending end region i to the line length by end regions j；Pij maxIt is sending end region i to by end regions j
Power transmission capacity of pow；Pi,s THIndicate uncertain collection ΩNsFired power generating unit is contributed in lower sending end region i, Pj,s THIndicate uncertain collection
ΩNsUnder contributed by fired power generating unit in end regions j,It is the electric power deficiency by end regions j；cTHIndicate thermoelectricity fuel cost,
cLSIndicate cutting load punishment.
Following constraint is as follows:
(5) unit output constrains
In formula,WithIt is sending end region thermoelectricity maximum output and minimum load respectively,WithBe respectively by
End regions fired power generating unit maximum output and minimum load.
(6) power balance
Met power balance by end regions and sending end region, as shown in following two formula:
In formula, PijIt is sending end region i to the flow of power by end regions j；It is the electric power deficiency by end regions j；
It is the electric load by end regions j.
(3) spinning reserve constrains
In formula, r is the percentage reserve by end regions j, and σ is after considering transregional power channel reliability, and external electric power participates in rotation
Turn the confidence level of spare capacity balance.
(4) related constraint of flow of power and power channel construction
In formula, M0For a constant, value is larger.If not built from sending end region i to the power channel by end regions j
If i.e. uij=0, it is 0 which, which constrains flow of power,.
(5) the external electric power ratio upper limit of receiving end
In view of Supply Security, such as transregional direct current are latched the impact to receiving end power grid, for receiving end power grid, local electricity
Source should meet a certain proportion of electricity consumption needs, therefore the η % of peak load is not to be exceeded in external electric power ratio, i.e.,
In formula, η % is that the electricity consumption that local power supply should meet needs ratio.
S3, solving model, and export optimal solution；I.e. minimum transregional power channel construction cost, minimum fired power generating unit fuel
Cost and minimum receiving end electric power deficiency punishment cost.
The present embodiment solves the model in step S2 using arranging and constraining generating algorithm (C&CG algorithm), passes through
Construction formulates the primal problem of flow of power decision and the subproblem of identification least favorable scene, by the iteration of primal problem and subproblem,
Obtain the optimal solution of model；It is specific as follows:
The flow of power plan optimization model based on robust optimization established can be written as follow formula:
In formula, c, dsAnd hsIt is constant vector；As、BsAnd DsIt is coefficient matrix；X is decision vector { uij,Pij, ysIt is to determine
Plan vectorAssuming that iteration proceeds to kth time, primal problem model are as follows:
In formula,For the scene that nth iteration identifies, the constraint in above formula is to solve for subproblem and returns to primal problem
Constraint solves primal problem and obtains optimal objective value LB and first stage optimizing decisionLB is the lower bound of former problem, then is directed to
Each uncertain collection, solves following subproblem, finds worst scene, i.e.,
Convert dual form for the min function of internal layer, then model equivalency in
Wherein, λ is antithesis multiplier vector, solves this model and obtains optimal objective value Qs and ξsOptimal solutionIt is former at this time
The upper bound of problemGenerate new variable vector ys,n, and return and be tied to primal problem as follows:
If UB-LB is less than convergence error, iteration stopping, current decision variable x is optimal.
The present invention is not limited to above-mentioned preferred forms, and anyone should learn that the knots made under the inspiration of the present invention
Structure variation, the technical schemes that are same or similar to the present invention are fallen within the scope of protection of the present invention.
Claims (7)
1. a kind of flow of power plan optimization method, which comprises the following steps:
The uncertain collection of new energy power output is established according to historical data；To minimize overall society cost as target, flow of power is established
Plan optimization model；Solving model, and export optimal solution.
2. flow of power plan optimization method as described in claim 1, which is characterized in that described to establish the not true of new energy power output
Surely collect specific as follows: establishing nested uncertain collection { Ω according to historical data1, Ω2…ΩNs,Wherein Ns is the number of uncertain collection；
For each uncertain collection ΩNs, ξi,sIt is stochastic variable, indicates the new energy power output of sending end region i, M sending end region is new
The corresponding random vector ξ of energy power outputs=[ξ1,s,ξ2,s,…,ξi,s；I=1 ... M]；
Each uncertain collection ΩNsOne Probability p is all corresponded tos, indicate random vector ξs∈ΩNsProbability be ps, p1< p2
< ... < ps=1；
Construct probability sequence π1=p1, π2=p2﹣ p1, πs=ps﹣ ps-1。
3. flow of power plan optimization method as described in claim 1, which is characterized in that the overall society cost includes transregional electricity
Power channel construction cost, fired power generating unit fuel cost and receiving end electric power deficiency punishment cost.
4. flow of power plan optimization method as claimed in claim 2, which is characterized in that objective function optimization least favorable field
Overall society cost under scape, and consider each uncertain collection ΩNsCorresponding Probability ps, overall society cost is each uncertain
Collect ΩNsThe desired value of corresponding operating cost；
Meet the security constraint of Operation of Electric Systems, including unit output constraint, power balance, spinning reserve constraint, flow of power
Constraint and the external electric power ratio upper limit of receiving end are built with power channel.
5. flow of power plan optimization method as claimed in claim 4, which is characterized in that the objective function such as following formula:
In formula, PijFor sending end region i to the flow of power by end regions j；uijConstruction sending end region i is indicated for 0-1 decision variable, 1
To the passway for transmitting electricity by end regions j, 0 expression is not built；clAnd cpIt is the construction of passway for transmitting electricity unit length and unit capacity respectively
Cost；LijIt is from sending end region i to the line length by end regions j；Pij maxIt is sending end region i defeated to the route by end regions j
Capacitance；Pi,s THIndicate uncertain collection ΩNsFired power generating unit is contributed in lower sending end region i, Pj,s THIndicate uncertain collection ΩNsUnder by
Fired power generating unit is contributed in end regions j,It is the electric power deficiency by end regions j；cTHIndicate thermoelectricity fuel cost, cLSExpression is cut
Load punishment；
It constrains as follows:
(1) unit output constrains
In formula,WithIt is sending end region thermoelectricity maximum output and minimum load respectively,WithIt is by petiolarea respectively
Domain fired power generating unit maximum output and minimum load；
(2) power balance
Met power balance, such as following formula by end regions and sending end region:
In formula,It is the electric load by end regions j；
(3) spinning reserve constrains
In formula, r is the percentage reserve by end regions j, and σ is after considering transregional power channel reliability, and it is standby that external electric power participates in rotation
With the confidence level of capacitance balance；
(4) related constraint of flow of power and power channel construction
In formula, M0For a constant；
(5) the external electric power ratio upper limit of receiving end
In formula, η % is that the electricity consumption that local power supply should meet needs ratio.
6. flow of power plan optimization method as described in claim 1, which is characterized in that solve the electric power by C&CG algorithm
Flow plan optimization model.
7. flow of power plan optimization method as described in claim 1, which is characterized in that the output optimal solution includes: minimum
Transregional power channel construction cost, minimum fired power generating unit fuel cost and minimum receiving end electric power deficiency punishment cost.
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| CN113141022A (en) * | 2021-05-14 | 2021-07-20 | 国网湖北省电力有限公司电力科学研究院 | Alternating current-direct current series-parallel connection receiving end power grid structure optimization method |
| CN113141022B (en) * | 2021-05-14 | 2022-05-03 | 国网湖北省电力有限公司电力科学研究院 | Alternating current-direct current series-parallel connection receiving end power grid structure optimization method |
| CN113206506A (en) * | 2021-06-16 | 2021-08-03 | 华能澜沧江水电股份有限公司 | Control method for suppressing active power fluctuation of photovoltaic and conventional energy networking |
| CN115471006A (en) * | 2022-09-30 | 2022-12-13 | 国网能源研究院有限公司 | Power supply planning method and system considering wind power output uncertainty |
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