CN105006821A - Method and system for researching power distribution network operation mode optimization - Google Patents

Abstract

The invention provides a method and system for researching power distribution network operation mode optimization. The method comprises steps: a current operation mode of a power distribution network is determined, and historical data corresponding to the current operation mode of the power distribution network is obtained; an object function and constraint conditions of power distribution network operation optimization are constructed, corresponding flexible parameters are introduced, and flexible description of the constructed object function and constraint conditions is carried out respectively; based on the object function and the constraint conditions after flexible processing, a multidimensional flexible integrated optimization model of power distribution network operation is formed, the obtained historical data is introduced into the multidimensional flexible integrated optimization model for solving, and the optimal desired value of the current operation mode of the power distribution network is obtained. The constructed optimal model of power distribution network operation is subjected to border flexibility, power distribution network operation structure and parameter change is adapted flexibly, the research flexibility is raised, research is carried out from many aspects and thus research is comprehensive.

Description

A kind of method and system studying power distribution network optimizing operating mode

Technical field

The present invention relates to system for distribution network of power technical field, particularly relate to a kind of method and system studying power distribution network optimizing operating mode.

Background technology

Along with the fast development of power industry and the continuous progress of industrial technology, the particularly deep enforcement of intelligent grid construction, the operation of people to power distribution network proposes more and more higher requirement, this is optimized the operational mode of power distribution network with regard to needing, and makes the operational mode of in fail safe, reliability, economy " optimum ".

Specifically, by adjusting various power equipment in power distribution network, to change the running status of power distribution network, realizing the optimizing operation of power distribution network, being called the optimization of power distribution network operational mode.In the research of power distribution network operational mode, because people's attention degree is inadequate, and be subject to the restriction of existing harvester configuration, be still in the starting stage to the research of power distribution network optimizing operating mode.At present, the method of research power distribution network optimizing operating mode mainly deposits deficiency both ways: the optimal model one, owing to adopting deterministic method establishment power distribution network to run, and the border of these model feasible solutions is rigidity, therefore be difficult to the change tackling power distribution network operating structure and parameter, make formulated optimal operation mode lack flexibility; Two, due to studying in a certain respect only for power distribution network optimizing operating mode, can not study all sidedly, therefore make formulated power distribution network optimal operation mode cannot reach comprehensive optimum.

Therefore, a kind of method needing research power distribution network optimizing operating mode newly badly can solve the problem, and makes formulated power distribution network optimal operation mode reach comprehensive optimum.

Summary of the invention

Embodiment of the present invention technical problem to be solved is, a kind of method and system studying power distribution network optimizing operating mode are provided, the power distribution network set up is run optimal models and carries out border flexibility, the change of flexible adaptation power distribution network operating structure and parameter, improve the flexibility of research, and set about research from many aspects, make research more comprehensive.

In order to solve the problems of the technologies described above, embodiments provide a kind of method studying power distribution network optimizing operating mode, described method comprises:

Determine the current operational mode of power distribution network, and obtain historical data corresponding to the current operational mode of described power distribution network;

Build target function and the constraints of power distribution network running optimizatin, and introduce corresponding flexible parameter, respectively flexibility description is carried out to the target function of described structure and constraints;

Based on the target function after described flexibility process and constraints, form the multidimensional flexible comprehensive Optimized model that power distribution network runs, and the described historical data got is directed in described multidimensional flexible comprehensive Optimized model solves, obtain the optimum desired value of the current operational mode of described power distribution network.

Wherein, the target function of described structure power distribution network running optimizatin and constraints, and introduce corresponding flexible parameter, comprise the concrete steps that the target function of described structure and constraints carry out flexibility description respectively:

Building with via net loss is the target function optimizing economic index, and structure comprises the constraint of node power equilibrium equation, node voltage retrains and the constraints of Branch Power Flow constraint;

Process in described target function, the constraint of node power equilibrium equation, node voltage constraint and the corresponding flexible parameter of the about intrafascicular introducing of Branch Power Flow respectively.

Wherein, described based on the target function after described flexibility process and constraints, form the multidimensional flexible comprehensive Optimized model that power distribution network runs, and the described historical data got is directed in described multidimensional flexible comprehensive Optimized model solves, the concrete steps obtaining the optimum desired value of the current operational mode of described power distribution network comprise:

Based on the target function after described flexibility process and constraints, form the multidimensional flexible comprehensive Optimized model that power distribution network runs, and according to the condition preset, simplify processes is carried out to described multidimensional flexible comprehensive Optimized model;

The described historical data got is directed in the multidimensional flexible comprehensive Optimized model after described simplify processes, and adopts certain algorithm to solve, obtain the optimum desired value of the current operational mode of described power distribution network.

Wherein, described algorithm is Meta-heurist algorithm, comprises genetic algorithm and particle cluster algorithm.

The embodiment of the present invention additionally provides a kind of system studying power distribution network optimizing operating mode, and described system comprises:

Data capture unit, for determining the current operational mode of power distribution network, and obtains historical data corresponding to the current operational mode of described power distribution network;

Flexible parameter introduces unit, for building target function and the constraints of power distribution network running optimizatin, and introduces corresponding flexible parameter, carries out flexibility description respectively to the target function of described structure and constraints;

Model construction and solve unit, for based on the target function after described flexibility process and constraints, form the multidimensional flexible comprehensive Optimized model that power distribution network runs, and the described historical data got is directed in described multidimensional flexible comprehensive Optimized model solves, obtain the optimum desired value of the current operational mode of described power distribution network.

Wherein, described flexible parameter introducing unit comprises:

Building module, is the target function optimizing economic index for building with via net loss, and structure comprises the constraint of node power equilibrium equation, node voltage retrains and the constraints of Branch Power Flow constraint;

Handling flexibly module, for processing in described target function, the constraint of node power equilibrium equation, node voltage constraint and the corresponding flexible parameter of the about intrafascicular introducing of Branch Power Flow respectively.

Wherein, described model construction and solve unit and comprise:

Model construction and simplification module, for based on the target function after described flexibility process and constraints, form the multidimensional flexible comprehensive Optimized model that power distribution network runs, and according to the condition preset, carry out simplify processes to described multidimensional flexible comprehensive Optimized model;

Model solution module, for the described historical data got being directed in the multidimensional flexible comprehensive Optimized model after described simplify processes, and adopting certain algorithm to solve, obtaining the optimum desired value of the current operational mode of described power distribution network.

Wherein, described algorithm is Meta-heurist algorithm, comprises genetic algorithm and particle cluster algorithm.

Implement the embodiment of the present invention, there is following beneficial effect:

In embodiments of the present invention, because constraints in the multidimensional flexible comprehensive Optimized model set up carries out flexibility process by introducing flexible parameter, make the border flexibility of constraints, can the change of flexible adaptation power distribution network operating structure and parameter, improve the flexibility of research; Also introducing flexible parameter due to target function in multidimensional flexible comprehensive Optimized model carries out flexibility process simultaneously, therefore can take into account the optimal operation mode research of power distribution network safety in operation, reliability and economy, make research more comprehensive.

Accompanying drawing explanation

In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, the accompanying drawing obtaining other according to these accompanying drawings still belongs to category of the present invention.

A kind of flow chart studying the method for power distribution network optimizing operating mode that Fig. 1 provides for the embodiment of the present invention;

A kind of structural representation studying the system of power distribution network optimizing operating mode that Fig. 2 provides for the embodiment of the present invention.

Embodiment

For making the object, technical solutions and advantages of the present invention clearly, below in conjunction with accompanying drawing, the present invention is described in further detail.

As shown in Figure 1, be a kind of method studying power distribution network optimizing operating mode that the embodiment of the present invention provides, described method comprises:

Step S101, determine the current operational mode of power distribution network, and obtain historical data corresponding to the current operational mode of described power distribution network;

Detailed process is, determines the historical data of the current operational mode of power distribution network and correspondence, and this historical data is in this, as the input data of optimizing operating mode method, and it selects typical Historic Section to analyze from the historical data base of the current operational mode of power distribution network.

In embodiments of the present invention, historical data includes but not limited to resistance, active power, reactive power and the terminal voltage amplitude that the sum of branch road in the current operational mode of power distribution network, each branch road are respectively corresponding, and the active power that in each branch road, each node sends and the burden with power power that reactive power, each node flow through and load or burden without work power, each node voltage magnitude etc.

Step S102, the target function building power distribution network running optimizatin and constraints, and introduce corresponding flexible parameter, carry out flexibility description to the target function of described structure and constraints respectively;

Detailed process is, building with via net loss is the target function optimizing economic index, and builds the constraints comprising the constraint of node power equilibrium equation, node voltage constraint and Branch Power Flow and retrain, specific as follows:

(1) target function built is generally optimize economic index with via net loss, is expressed as:

$\min f=\underset{i=1}{\overset{N_b}{\Σ}}\frac{R_i(P_i^2+Q_i^2)}{V_i^2}---\left(1\right)$

In formula (1): N _brepresent the branch road sum in distribution network; R _irepresent the resistance of i-th branch road; P _i, Q _irepresent the active power and the reactive power that flow through i-th branch road respectively; V _irepresent the terminal voltage amplitude of i-th branch road.

(2) constraints built is mainly fail safe, reliability constraint, generally comprises:

I) node power equilibrium equation constraint

The operation of power distribution network must meet meritorious, the constraint of reactive power equilibrium equation of each node, as follows:

$\left\{\begin{array}{c}{P}_{Gi}-P_{Li}-V_i\underset{j\∈i}{\Σ}{V}_j\left(G_{ij}{\mathrm{cos\θ}}_{ij}+B_{ij}{\mathrm{sin\θ}}_{ij}\right)=0\\ Q_{Gi}-Q_{Li}-V_i\underset{j\∈i}{\Σ}{V}_j\left(G_{ij}{\mathrm{sin\θ}}_{ij}-B_{ij}{\mathrm{cos\θ}}_{ij}\right)=0\end{array}\right.---\left(2\right)$

In formula (2): P _gi, Q _girepresent the active power that node i sends and reactive power respectively; P _li, Q _lirepresent the burden with power power that node i flows through and load or burden without work power respectively; V _irepresent the voltage magnitude of node i; G _ij, B _ij, θ _wjrepresent conductance, susceptance and the phase angle difference between node i and node j respectively.

II) node voltage constraint

In order to ensure the fail safe that power distribution network runs and power supply quality, require the actual conditions in conjunction with power distribution network, by the voltage magnitude Deviation Control of each node in the scope that national standard allows, the voltage magnitude of each node need meet for this reason:

V _i,min≤V _i≤V _i,maxi＝1,2,...,N (3)

In formula (3): V _i, V _{i, max}, V _{i, min}represent voltage magnitude and higher limit, the lower limit of node i respectively; N represents the node total number of distribution system.

III) Branch Power Flow constraint

By the restriction of distribution current carrying capacity of conductor, require that power that each bar branch road flows through is within the specific limits, as follows:

S _i≤S _i,maxi＝1,2,...,N _b(4)

In formula (4): S _l, S _{l, max}represent the apparent power on i-th branch road and restriction respectively.

In embodiments of the present invention, because above-mentioned set up model is rigid constraint Optimized model, its optimum results has certain one-sidedness and limitation, and lack the flexibility of reply power distribution network parameter change, therefore introduce flexibility analysis to improve above-mentioned set up model, process in target function, the constraint of node power equilibrium equation, node voltage constraint and the corresponding flexible parameter of the about intrafascicular introducing of Branch Power Flow respectively, specific as follows:

I) node power equilibrium equation flexible constraint

In conventional electrical distribution net, node load is generally constant, node power equilibrium equation is caused to become rigidity, therefore node load can be considered as controlled variable, by reasonably Controlling vertex load power, realize the regulation and control objects such as peak load shifting, be expressed as after making formula (2) node power equilibrium equation constrain in the flexible parameter of introducing:

$\left\{\begin{array}{c}{P}_{Gi}-V_i\underset{j\∈i}{\Σ}{V}_j\left(G_{ij}{\mathrm{cos\θ}}_{ij}+B_{ij}{\mathrm{sin\θ}}_{ij}\right)=P_{Li}+{\mathrm{\δ}}_{Li}{\mathrm{\ΔP}}_{Li}\\ Q_{Gi}-V_i\underset{j\∈i}{\Σ}{V}_j\left(G_{ij}{\mathrm{sin\θ}}_{ij}-B_{ij}{\mathrm{cos\θ}}_{ij}\right)=Q_{Li}+{\mathrm{\δ}}_{Li}{\mathrm{\ΔQ}}_{Li}\end{array}\right.---\left(5\right)$

In formula (5): Δ P _li, Δ Q _lirepresent the meritorious of node i and load or burden without work power deviation respectively; δ _lirepresent the load flexibility index of node i, span is [0,1].

The meaning of load flexibility index is, as the δ of node i _licomparing other nodes when there is larger association with the power distribution network network loss function, illustrate that the economy that power distribution network is powered to this node load is poor, by reasonably reducing the load of this node, just can improve the macroeconomic that power distribution network runs largely.

II) node voltage flexible constraint

Introduce flexible parameter, formula (3) carried out flexibility and is expressed as:

V _i,min-δ _ViΔV _i,min≤V _i≤V _i,max+δ _ViΔV _i,max(6)

In formula (6): Δ V _{i, max}, Δ V _{i, min}represent V respectively _{i, max}, V _{i, min}the out-of-limit value of maximum permission; δ _virepresent the voltage flexibility index of node i, span is [0,1].

III) Branch Power Flow flexible constraint

The same, introduce flexible parameter, formula (4) is carried out flexibility and is expressed as:

S _i≤S _i,max+δ _FiΔS _i,max(7)

In formula (7): Δ S _{i, max}represent the out-of-limit value of maximum permission of trend on i-th branch road; δ _firepresent the trend flexibility index of branch road i, span is [0,1].

According to formula (6) and formula (7) known, when carrying out power distribution network optimizing operating mode, need rationally expand according to the actual conditions of power distribution network or reduce restrained boundary, to improve fail safe that power distribution network runs, reliability and economy.

IV) if only run the angle consideration of constraint from power distribution network, the soft evaluation index of power distribution network operational mode can run the size of feasible zone and the degree of flexibility of system by certainty annuity intuitively, but can not determine the optimal operation mode taking into account power distribution network safety in operation, reliability and economy, need to do flexibility process to target function, to set up the flexible comprehensive Optimized model of power distribution network operational mode for this reason.

Therefore, the via net loss represented by formula (1) directly reflects the economy that power distribution network runs, and introduces flexible parameter, is translated into equality constraint, as follows:

$f^{\′}=\underset{i=1}{\overset{N_b}{\Σ}}\frac{R_i(P_i^2+Q_i^2)}{V_i^2}=f_0+{\mathrm{\δ}}_f\mathrm{\Δ}f---\left(8\right)$

In formula (8): f ₀represent the minimization expected value of power distribution network via net loss; Δ f represents the acceptable maximum recruitment of power distribution network via net loss; δ _frepresent via net loss flexibility index, span is [0,1].

From formula (8), via net loss f ' is positioned at [f ₀, f ₀+ Δ f] between, although the economy that power distribution network runs decreases, can by the damage control of economy aspect within the specific limits, make via net loss index be provided with flexibility, increase the feasible zone that power distribution network runs.

Step S103, based on the target function after described flexibility process and constraints, form the multidimensional flexible comprehensive Optimized model that power distribution network runs, and the described historical data got is directed in described multidimensional flexible comprehensive Optimized model solves, obtain the optimum desired value of the current operational mode of described power distribution network.

Detailed process is, based on the target function after flexibility process and constraints, forms the multidimensional flexible comprehensive Optimized model that power distribution network runs, specific as follows:

$\max f\left(\mathrm{\δ}\right)=-{\mathrm{\δ}}_f^2+\frac{1}{N}\underset{i=1}{\overset{N}{\Σ}}{\mathrm{\δ}}_{Li}^2+\frac{1}{N}\underset{i=1}{\overset{N}{\Σ}}{\mathrm{\δ}}_{Vi}^2+\frac{1}{N_b}\underset{j=1}{\overset{N_b}{\Σ}}{\mathrm{\δ}}_{Fj}^2$

$s.t.\left\{\begin{array}{c}{f}^{\′}=\underset{i=1}{\overset{N_b}{\Σ}}\frac{R_i(P_i^2+Q_i^2)}{V_i^2}=f_0+{\mathrm{\δ}}_f\mathrm{\Δ}f\\ P_{Gi}-V_i\underset{j\∈i}{\Σ}{V}_j\left(G_{ij}{\mathrm{cos\θ}}_{ij}+B_{ij}{\mathrm{sin\θ}}_{ij}\right)=P_{Li}+{\mathrm{\δ}}_{Li}{\mathrm{\ΔP}}_{Li}\\ Q_{Gi}-V_i\underset{j\∈i}{\Σ}{V}_j\left(G_{ij}{\mathrm{sin\θ}}_{ij}-B_{ij}{\mathrm{cos\θ}}_{ij}\right)=Q_{Li}+{\mathrm{\δ}}_{Li}{\mathrm{\ΔQ}}_{Li}\\ V_{i,\min }-{\mathrm{\δ}}_{Vi}{\mathrm{\ΔV}}_{i,\min }\≤V_i\≤V_{i,\max }+{\mathrm{\δ}}_{Vi}{\mathrm{\ΔV}}_{i,\max }\\ S_j\≤S_{j,\max }+{\mathrm{\δ}}_{Fj}{\mathrm{\ΔS}}_{j,\max }\\ 0\≤{\mathrm{\δ}}_f,{\mathrm{\δ}}_{Li},{\mathrm{\δ}}_{Vi},{\mathrm{\δ}}_{Fj}\≤1\\ i=1,2,\mathrm{...},N;j=1,2,\mathrm{...},N_b\end{array}\right.---\left(9\right)$

From formula (9), the value of each flexibility index reflects the running status of power distribution network from different angles: via net loss flexibility index δ _fless, show that via net loss f ' is less, the economy that power distribution network runs is higher; Node voltage flexibility index δ _viwith Branch Power Flow flexibility index δ _filarger, show that the margin of safety run is larger, the safety and reliability that power distribution network runs is higher.Maximization f (δ) means makes δ _findex is as far as possible little, makes δ _li, δ _viand δ _fjindex is as far as possible large, thus make tried to achieve operational mode reach economy, fail safe, the many-sided comprehensive optimum of reliability, the optimal solution of simultaneously trying to achieve also assures that to have larger flexibility, has stronger adaptibility to response to the changeable factor in power distribution network.

In embodiments of the present invention, because formula (9) introduces more flexibility index, the scale of solving model is had certain increase, and become a complicated non-linear higher-dimension mixed-integer programming model, direct solution formula (9) is very complicated, need, according to the condition preset, to carry out simplify processes to multidimensional flexible comprehensive Optimized model for this reason, specific as follows:

1) due under normal circumstances, generally to meeting the workload demand of each node as far as possible, not paying the utmost attention to the economy improving overall operation by reducing some node load, therefore get the load flexibility index δ of each node _li=0;

2) suppose that the trend flexibility index of all equal, each bar branch road of the voltage flexibility index of each node is all equal.

Further, the historical data got is directed in the multidimensional flexible comprehensive Optimized model after simplify processes, and adopts certain algorithm to solve, obtain the optimum desired value of the current operational mode of power distribution network; Wherein, algorithm is Meta-heurist algorithm, comprises genetic algorithm and particle cluster algorithm.

As shown in Figure 2, be a kind of system studying power distribution network optimizing operating mode that the embodiment of the present invention provides, described system comprises:

Data capture unit 210, for determining the current operational mode of power distribution network, and obtains historical data corresponding to the current operational mode of described power distribution network;

Flexible parameter introduces unit 220, for building target function and the constraints of power distribution network running optimizatin, and introduces corresponding flexible parameter, carries out flexibility description respectively to the target function of described structure and constraints;

Model construction and solve unit 230, for based on the target function after described flexibility process and constraints, form the multidimensional flexible comprehensive Optimized model that power distribution network runs, and the described historical data got is directed in described multidimensional flexible comprehensive Optimized model solves, obtain the optimum desired value of the current operational mode of described power distribution network.

Wherein, flexible parameter introducing unit 220 comprises:

Building module 2201, is the target function optimizing economic index for building with via net loss, and structure comprises the constraint of node power equilibrium equation, node voltage retrains and the constraints of Branch Power Flow constraint;

Handling flexibly module 2202, for processing in described target function, the constraint of node power equilibrium equation, node voltage constraint and the corresponding flexible parameter of the about intrafascicular introducing of Branch Power Flow respectively.

Wherein, model construction and solve unit 230 and comprise:

Model construction and simplification module 2301, for based on the target function after described flexibility process and constraints, form the multidimensional flexible comprehensive Optimized model that power distribution network runs, and according to the condition preset, simplify processes is carried out to described multidimensional flexible comprehensive Optimized model;

Model solution module 2302, for the described historical data got being directed in the multidimensional flexible comprehensive Optimized model after described simplify processes, and adopting certain algorithm to solve, obtaining the optimum desired value of the current operational mode of described power distribution network.

Wherein, algorithm is Meta-heurist algorithm, comprises genetic algorithm and particle cluster algorithm

Implement the embodiment of the present invention, there is following beneficial effect:

In embodiments of the present invention, because constraints in the multidimensional flexible comprehensive Optimized model set up carries out flexibility process by introducing flexible parameter, make the border flexibility of constraints, can the change of flexible adaptation power distribution network operating structure and parameter, improve the flexibility of research; Also introducing flexible parameter due to target function in multidimensional flexible comprehensive Optimized model carries out flexibility process simultaneously, therefore can take into account the optimal operation mode research of power distribution network safety in operation, reliability and economy, make research more comprehensive.

It should be noted that in said system embodiment, each included system unit is carry out dividing according to function logic, but is not limited to above-mentioned division, as long as can realize corresponding function; In addition, the concrete title of each functional unit, also just for the ease of mutual differentiation, is not limited to protection scope of the present invention.

One of ordinary skill in the art will appreciate that all or part of step realized in above-described embodiment method is that the hardware that can carry out instruction relevant by program has come, described program can be stored in a computer read/write memory medium, described storage medium, as ROM/RAM, disk, CD etc.

Above disclosedly be only present pre-ferred embodiments, certainly can not limit the interest field of the present invention with this, therefore according to the equivalent variations that the claims in the present invention are done, still belong to the scope that the present invention is contained.

Claims (8)

1. study a method for power distribution network optimizing operating mode, it is characterized in that, described method comprises:

Determine the current operational mode of power distribution network, and obtain historical data corresponding to the current operational mode of described power distribution network;

Build target function and the constraints of power distribution network running optimizatin, and introduce corresponding flexible parameter, respectively flexibility description is carried out to the target function of described structure and constraints;

Based on the target function after described flexibility process and constraints, form the multidimensional flexible comprehensive Optimized model that power distribution network runs, and the described historical data got is directed in described multidimensional flexible comprehensive Optimized model solves, obtain the optimum desired value of the current operational mode of described power distribution network.

2. the method for claim 1, it is characterized in that, the target function of described structure power distribution network running optimizatin and constraints, and introduce corresponding flexible parameter, comprise the concrete steps that the target function of described structure and constraints carry out flexibility description respectively:

Building with via net loss is the target function optimizing economic index, and structure comprises the constraint of node power equilibrium equation, node voltage retrains and the constraints of Branch Power Flow constraint;

Process in described target function, the constraint of node power equilibrium equation, node voltage constraint and the corresponding flexible parameter of the about intrafascicular introducing of Branch Power Flow respectively.

3. the method for claim 1, it is characterized in that, described based on the target function after described flexibility process and constraints, form the multidimensional flexible comprehensive Optimized model that power distribution network runs, and the described historical data got is directed in described multidimensional flexible comprehensive Optimized model solves, the concrete steps obtaining the optimum desired value of the current operational mode of described power distribution network comprise:

Based on the target function after described flexibility process and constraints, form the multidimensional flexible comprehensive Optimized model that power distribution network runs, and according to the condition preset, simplify processes is carried out to described multidimensional flexible comprehensive Optimized model;

The described historical data got is directed in the multidimensional flexible comprehensive Optimized model after described simplify processes, and adopts certain algorithm to solve, obtain the optimum desired value of the current operational mode of described power distribution network.

4. method as claimed in claim 3, it is characterized in that, described algorithm is Meta-heurist algorithm, comprises genetic algorithm and particle cluster algorithm.

5. study a system for power distribution network optimizing operating mode, it is characterized in that, described system comprises:

Data capture unit, for determining the current operational mode of power distribution network, and obtains historical data corresponding to the current operational mode of described power distribution network;

Flexible parameter introduces unit, for building target function and the constraints of power distribution network running optimizatin, and introduces corresponding flexible parameter, carries out flexibility description respectively to the target function of described structure and constraints;

Model construction and solve unit, for based on the target function after described flexibility process and constraints, form the multidimensional flexible comprehensive Optimized model that power distribution network runs, and the described historical data got is directed in described multidimensional flexible comprehensive Optimized model solves, obtain the optimum desired value of the current operational mode of described power distribution network.

6. system as claimed in claim 5, is characterized in that, described flexible parameter is introduced unit and comprised:

Building module, is the target function optimizing economic index for building with via net loss, and structure comprises the constraint of node power equilibrium equation, node voltage retrains and the constraints of Branch Power Flow constraint;

Handling flexibly module, for processing in described target function, the constraint of node power equilibrium equation, node voltage constraint and the corresponding flexible parameter of the about intrafascicular introducing of Branch Power Flow respectively.

7. system as claimed in claim 5, is characterized in that, described model construction and solve unit and comprise:

Model construction and simplification module, for based on the target function after described flexibility process and constraints, form the multidimensional flexible comprehensive Optimized model that power distribution network runs, and according to the condition preset, carry out simplify processes to described multidimensional flexible comprehensive Optimized model;

Model solution module, for the described historical data got being directed in the multidimensional flexible comprehensive Optimized model after described simplify processes, and adopting certain algorithm to solve, obtaining the optimum desired value of the current operational mode of described power distribution network.

8. system as claimed in claim 7, it is characterized in that, described algorithm is Meta-heurist algorithm, comprises genetic algorithm and particle cluster algorithm.