CN106712009A - Safe operation optimization method for initiative power distribution network based on distributed optical storage - Google Patents

Abstract

A method for optimizing the safe operation of an active distribution network based on distributed optical storage provided by the present invention includes the following steps: S1. Acquiring the node information and distribution network parameters of the distribution network and the main network connection node of the distributed optical storage, And screen out the slack nodes; S2. Construct the operation evaluation model of the distribution network, and obtain the optimal solution for the evaluation model; through the present invention, the active distribution network of photovoltaic power generation can be systematically and comprehensively analyzed, and the power distribution All aspects of the grid are considered to ensure the accuracy of the analysis results, and it is conducive to the safe and stable integration of photovoltaic power generation into the grid, and the algorithm is simple.

Description

An optimization method for safe operation of active distribution network based on distributed photovoltaic storage

technical field

The invention relates to an electric power optimization method, in particular to a method for optimizing the safe operation of an active distribution network based on distributed optical storage.

Background technique

With the depletion of fossil energy and the serious impact of fossil energy on the environment, people urgently need environmentally friendly renewable energy. At present, the existing renewable clean energy includes water energy, wind energy and solar energy. Since solar energy is cleaner during use, The distribution is also wider, therefore, solar power generation is receiving more and more attention.

The conversion of solar energy into electrical energy is generally carried out through photovoltaic cells (also known as photovoltaic cell arrays). Photovoltaic power generation includes photovoltaic cells, batteries, electronic converters (rectifiers and inverters), capacitors, and loads. The environmental requirements are extremely high, so its output power fluctuates greatly. In order to ensure the stable operation of the entire power grid system, it is necessary to analyze the operation of the distribution network of photovoltaic power generation. In the prior art, the analysis of the distribution network of photovoltaic power generation They are all analyzed based on a specific control target. Therefore, the control target is isolated from other factors during the analysis process. And other factors are ignored, therefore, the final analysis results are inaccurate, which is not conducive to the safe operation of the distribution network.

Therefore, it is necessary to propose a new method that can systematically and comprehensively analyze the active distribution network of photovoltaic power generation, and consider all aspects of the distribution network, so as to ensure the accuracy of the analysis results and facilitate the generation of electric energy by photovoltaic power generation. Safe and stable integration into the grid.

Contents of the invention

In view of this, the purpose of the present invention is to provide a method for optimizing the safe operation of the active distribution network based on distributed photovoltaic storage, which can systematically and comprehensively analyze the active distribution network of photovoltaic power generation, and integrate all links of the distribution network Taking it into account will ensure the accuracy of the analysis results and facilitate the safe and stable integration of photovoltaic power generation into the grid.

A method for optimizing the safe operation of an active distribution network based on distributed optical storage provided by the present invention includes the following steps:

S1. Obtain the node information and distribution network parameters of the distribution network and the main network connection node of the distributed optical storage, and filter out the slack nodes;

S2. Construct the operation evaluation model of the distribution network, and obtain the optimal solution for the evaluation model.

Further, it is characterized in that: in step S1, the distribution network parameters include distribution network admittance, distribution network impedance, distribution network resistance and distribution network reactance, and each parameter is formed into a corresponding matrix, wherein Y represents the conductance Nano matrix, Z is impedance matrix and Z=Y ⁻¹ , R is resistance matrix and R=real(Z), X is reactance matrix and X=imag(Z).

Further, in step S2, the operation evaluation model of the power grid is constructed according to the following method:

S21. Construct the distribution network node current injection state equation:

in, U ^re and U ^im are the real and imaginary components of the node voltage, respectively, I ^re and I ^im are the real and imaginary components of the node current, respectively, △I ^re and △I ^im are the variation of the node current The real and imaginary components of , E is the identity matrix;

S22. Obtain the active power P _i and reactive power Q _i injected by the node according to the grid node current injection state quantity:

Among them, R _ij is the resistance between node i and node j, _Xij is the reactance between node i and node j, and N represents the number of nodes in the distribution network;

S23. Pair active power P _i and reactive power Q _i to with Differentiate to obtain the sensitivity matrix of the distribution network:

Among them, J is the sensitivity matrix of distribution network, △P _i and △Q _i are the variation of active power and reactive power of node i, i=1,2,...,N;

S24. Perform de-relaxation processing on the sensitivity matrix of the distribution network: since the voltage of the relaxed node is the reference voltage, then the relaxed node s has:

Thus, for node s: its voltage has the following equation:

According to the formula (5), the following matrix is obtained:

Among them, Z2 is the coefficient matrix that does not contain the relaxed node s in _formula (5);

According to formulas (1) and (4) and matrix (6), the voltage and current equations in the distribution network except for the relaxed nodes are obtained:

in, J ₃ and J ₄ are sub-matrixes relevant to the target variable in the Jacobian matrix;

S25. The power of the controllable equipment and uncontrollable equipment in the distribution network will be obtained, and the controllable active power matrix △P _u , the controllable reactive power matrix △Q _u , the uncontrollable active power matrix △P _v and the uncontrollable active power matrix △P v will be formed. Control reactive power matrix △Q _v :

△Q _v = [△Q _LOAD ];

Among them, △P _DG is the active power change of distributed power in distribution network, △P _BESS is the active power change of battery in distribution network, △Q _CAP is the reactive power change of capacitor in distribution network; △Q _DG is the reactive power change of distributed power in the distribution network, △P _LOAD is the active power change of the load in the distribution network, △P _PV is the active power change of photovoltaic cells in the distribution network, △ Q _LOAD is the reactive power variation of the load in the distribution network, and the following matrix is obtained according to the above matrix:

Among them, F is a constant matrix determined by the distribution network, △P _in is the charging active power of the battery, and △P _out is the discharging active power of the battery;

S26. Divide each parameter into state variable x ₁ , disturbance variable v ₁ and control variable u1:

x ₁ ＝[U ^re U ^im I ^re I ^im P _DG P _in P _out Q _CAP Q _DG E _B ] ^T ;

u ₁ =[△P _DG △P _in △P _out △Q _CAP △Q _DG ] ^T ;

v ₁ =[△P _LOAD △P _PV △Q _LOAD ]; where, E _B is the capacity of the storage battery;

At this point, the evaluation state model is:

in:

in:

B ₀ is the matrix A matrix composed of quantities related to controllable equipment in , D ₀ is the matrix A matrix composed of quantities related to uncontrollable equipment in ;

The relaxation factor ε of the relaxed node is added to the evaluation model to form the final evaluation model:

Further, in step S2, the optimal solution of the state evaluation model is obtained through the cplex function.

Beneficial effects of the present invention: through the present invention, the active distribution network of photovoltaic power generation can be systematically and comprehensively analyzed, and all links of the distribution network are taken into consideration, thereby ensuring the accuracy of the analysis results and facilitating the generation of electric energy by photovoltaic power generation Safe and stable integration into the grid, and the algorithm is simple.

Description of drawings

The present invention will be further described below in conjunction with accompanying drawing and embodiment:

Fig. 1 is a flowchart of the present invention.

detailed description

Fig. 1 is a flowchart of the present invention. As shown in the figure, a method for optimizing the safe operation of an active distribution network based on distributed optical storage provided by the present invention includes the following steps:

S1. Obtain the node information and distribution network parameters of the distribution network and the main network connection node of the distributed optical storage, and filter out the slack nodes;

S2. Construct the operation evaluation model of the distribution network, and obtain the optimal solution for the evaluation model; through the present invention, the active distribution network of photovoltaic power generation can be systematically and comprehensively analyzed, and all links of the distribution network will be considered Among them, the accuracy of the analysis results is ensured, and it is conducive to the safe and stable integration of the electric energy generated by photovoltaic power generation into the grid, and the algorithm is simple.

In this embodiment, it is characterized in that: in step S1, the distribution network parameters include distribution network admittance, distribution network impedance, distribution network resistance and distribution network reactance, and each parameter is formed into a corresponding matrix, wherein, Y represents the admittance matrix, Z is the impedance matrix and Z=Y ^-1 , R is the resistance matrix and R=real(Z), X is the reactance absolute array and X=imag(Z), and the resistance R is the real part of the impedance Z The reactance X is the imaginary component of the impedance Z.

In this embodiment, in step S2, the operation evaluation model of the power grid is constructed according to the following method:

S21. Construct the distribution network node current injection state equation:

in, U ^re and U ^im are the real and imaginary components of the node voltage, respectively, I ^re and I ^im are the real and imaginary components of the node current, respectively, △I ^re and △I ^im are the variation of the node current The real and imaginary components of , E is the identity matrix;

S22. Obtain the active power P _i and reactive power Q _i injected by the node according to the grid node current injection state quantity:

Among them, R _ij is the resistance between node i and node j, _Xij is the reactance between node i and node j, and N represents the number of nodes in the distribution network;

S23. Pair active power P _i and reactive power Q _i to with Differentiate to obtain the sensitivity matrix of the distribution network:

Among them, J is the sensitivity matrix of distribution network, △P _i and △Q _i are the variation of active power and reactive power of node i, i=1,2,...,N;

S24. Perform de-relaxation processing on the sensitivity matrix of the distribution network: since the voltage of the relaxed node is the reference voltage, then the relaxed node s has:

Thus, for node s: its voltage has the following equation:

According to the formula (5), the following matrix is obtained:

Among them, Z2 is the coefficient matrix that does not contain the relaxed node s in _formula (5);

According to formulas (1) and (4) and matrix (6), the voltage and current equations in the distribution network except for the relaxed nodes are obtained:

in, J ₃ and J ₄ are sub-matrixes relevant to the target variable in the Jacobian matrix;

S25. The power of the controllable equipment and uncontrollable equipment in the distribution network will be obtained, and the controllable active power matrix △P _u , the controllable reactive power matrix △Q _u , the uncontrollable active power matrix △P _v and the uncontrollable active power matrix △P v will be formed. Control reactive power matrix △Q _v :

△Q _v = [△Q _LOAD ];

Among them, △P _DG is the active power change of distributed power in distribution network, △P _BESS is the active power change of battery in distribution network, △Q _CAP is the reactive power change of capacitor in distribution network; △Q _DG is the reactive power variation of the distributed power generation in the distribution network, △P _LOAD is the active power variation of the load in the distribution network, △P _PV is the active power variation of the photovoltaic battery in the distribution network, △ Q _LOAD is the reactive power variation of the load in the distribution network, and the following matrix is obtained according to the above matrix:

Among them, F is a constant matrix determined by the distribution network, △P _in is the charging active power of the battery, and △P _out is the discharging active power of the battery;

S26. Divide each parameter into state variable x ₁ , disturbance variable v ₁ and control variable u ₁ :

x ₁ ＝[U ^re U ^im I ^re I ^im P _DG P _in P _out Q _CAP Q _DG E _B ] ^T ;

u ₁ =[△P _DG △P _in △P _out △Q _CAP △Q _DG ] ^T ;

v ₁ =[△P _LOAD △P _PV △Q _LOAD ]; where, E _B is the capacity of the storage battery;

At this point, the evaluation state model is:

in:

in:

B ₀ is the matrix A matrix composed of quantities related to controllable equipment in , D ₀ is the matrix A matrix composed of quantities related to uncontrollable equipment in ;

The relaxation factor ε of the relaxed node is added to the evaluation model to form the final evaluation model:

Find the optimal solution to the final state evaluation model through the cplex function. This function is an existing algorithm and will not be repeated here. Among them, the slack node is the node connected to the distribution network and the main network, and its relaxation factor ε is determined by the main network and The characteristics of the distribution network are determined, that is to say: the slack factors of the slack nodes between the photovoltaic-based distribution network and the main network are determined when the network is formed.

Finally, it is noted that the above embodiments are only used to illustrate the technical solutions of the present invention without limitation. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be carried out Modifications or equivalent replacements without departing from the spirit and scope of the technical solution of the present invention shall be covered by the claims of the present invention.

Claims (4)

1. A safe operation optimization method for an active power distribution network based on distributed optical storage is characterized by comprising the following steps: the method comprises the following steps:

s1, acquiring node information and power distribution network parameters of a power distribution network and a main network connection node of distributed optical storage, and screening out loose nodes;

and S2, constructing an operation evaluation model of the power distribution network, and performing optimal solution solving on the evaluation model.

2. The distributed light storage based master of claim 1The method for optimizing the safe operation of the power distribution network is characterized by comprising the following steps: in step S1, the parameters of the power distribution network include admittance, impedance, resistance and reactance of the power distribution network, and the parameters form a corresponding matrix, where Y represents an admittance matrix, Z is an impedance matrix, and Z is equal to Y^-1R is a resistance matrix and R ═ real (z), X is a reactance matrix and X ═ imag (z).

3. The distributed optical storage based active power distribution network safe operation optimization method according to claim 2, characterized in that: in step S2, an operation evaluation model of the power grid is constructed according to the following method:

s21, constructing a node current injection state equation of the power distribution network:

wherein,

U^reand U^imThe real and imaginary components, I, of the node voltage, respectively^reAnd I^imThe real and imaginary components of the node current, △ I respectively^reAnd △ I^imRespectively a real part component and an imaginary part component of the variable quantity of the node current, and E is an identity matrix;

s22, obtaining active power P injected by the node according to the current injection state quantity of the power grid node_iAnd reactive power Q_i：

$P_i=\underset{j=0}{\overset{N-1}{\Σ}}\left(I_i^{re}\right(R_{ij}{I}_j^{re}-X_{ij}{I}_j^{im})+I_i^{im}(R_{ij}{I}_j^{im}+X_{ij}{I}_j^{re}\left)\right)---\left(2\right);$

$Q_i=\underset{j=0}{\overset{N-1}{\Σ}}\left(I_i^{re}\right(R_{ij}{I}_j^{im}+X_{ij}{I}_j^{re})-I_i^{im}(R_{ij}{I}_j^{re}-X_{ij}{I}_j^{im}\left)\right)---\left(3\right);$

Wherein R is_ijIs the resistance between node i and node j, X_ijFor electricity between node i and node jN represents the number of nodes of the power distribution network;

s23, converting the active power P_iAnd reactive power Q_iTo pairAnddifferentiating to obtain a sensitivity matrix of the power distribution network:

wherein J is sensitivity matrix of the distribution network, △ P_iAnd △ Q_iIs the amount of change in active and reactive power at node i, i ═ 1,2, …, N;

s24, performing relaxation removing treatment on the sensitivity matrix of the power distribution network: since the voltage at the relaxation node is the reference voltage, the relaxation node s has:

thus, for node s: the voltage has the following equation:

$\left\{\begin{array}{c}(R_{s1}{\mathrm{\ΔI}}_1^{re}+...R_{ss}{\mathrm{\ΔI}}_s^{re}+...+R_{sN}{\mathrm{\ΔI}}_N^{re})-(X_{s1}{\mathrm{\ΔI}}_1^{im}+...X_{ss}{\mathrm{\ΔI}}_s^{im}+...+X_{sN}{\mathrm{\ΔI}}_N^{im})=0\\ (X_{s1}{\mathrm{\ΔI}}_1^{re}+...X_{ss}{\mathrm{\ΔI}}_s^{re}+...+X_{sN}{\mathrm{\ΔI}}_N^{re})+(R_{s1}{\mathrm{\ΔI}}_1^{im}+...R_{ss}{\mathrm{\ΔI}}_s^{im}+...+R_{sN}{\mathrm{\ΔI}}_N^{im})=0\end{array}\right.---\left(5\right);$

the following matrix is derived from equation (5):

$Z_1=\left[\begin{array}{cc}{R}_{ss}& -X_{ss}\\ X_{ss}& R_{ss}\end{array}\right],Z_2=\left[\begin{array}{cc}{R}_{s1}...R_{sN}& -X_{s1}...-X_{sN}\\ X_{s1}...X_{sN}& R_{s1}...R_{sN}\end{array}\right]---\left(6\right);$

wherein Z is₂Is a coefficient matrix of formula (5) which does not contain a relaxation node s;

and (3) obtaining the voltage and current equations except for the relaxation nodes in the power distribution network according to the formulas (1) and (4) and the matrix (6):

wherein,J₃and J₄A sub-matrix related to the target variable in the Jacobian matrix is obtained;

s25, acquiring the power of controllable equipment and uncontrollable equipment in the power distribution network, and forming a controllable active power matrix △ P_uControllable reactive power matrix △ Q_uUncontrollable power matrix △ P_vAnd an uncontrollable reactive power matrix △ Q_v：

△Q_v＝[△Q_LOAD]；

Wherein, △ P_DGFor active power variation of distributed power sources in a power distribution network, △ P_BESSFor active power variations of accumulators in power distribution networks, △ Q_CAP△ Q as the reactive power variation of capacitors in the distribution network_DGFor distribution networksReactive power variation of distributed power supply, △ P_LOADVariation of active power for loads in an electricity distribution network, △ P_PVVariation of active power of photovoltaic cells in distribution networks, △ Q_LOADObtaining the following matrix according to the matrix for the reactive power variation of the load in the power distribution network:

where F is a constant matrix determined by the distribution network, △ P_inActive power for charging batteries, △ P_outActive power for discharging the storage battery;

s26, dividing each parameter into state variables x₁V disturbance variable₁And a control variable u₁：

x₁＝[U^reU^imI^reI^imP_DGP_inP_outQ_CAPQ_DGE_B]^T；

u₁＝[△P_DG△P_in△P_out△Q_CAP△Q_DG]^T；

v₁＝[△P_LOAD△P_PV△Q_LOAD](ii) a Wherein E is_BIs the capacity of the battery;

at this time, the evaluation state model is:

wherein:

wherein:

B₀is a matrixOf quantities related to controllable devices, D₀Is a matrixA matrix of quantities related to the uncontrollable devices;

adding the relaxation factors of the relaxation nodes into the assessment model to form a final assessment model:

${\left[\begin{array}{c}{x}_1\\ \mathrm{\ϵ}\end{array}\right]}^{+}=\left[\begin{array}{cc}{A}_1& 0\\ 0& 0\end{array}\right]\·\left[\begin{array}{c}{x}_1\\ \mathrm{\ϵ}\end{array}\right]+\left[\begin{array}{cc}{B}_1& 0\\ 0& E\end{array}\right]\·\left[\begin{array}{c}{u}_1\\ \mathrm{\ϵ}\end{array}\right]+\left[\begin{array}{c}{D}_1\\ 0\end{array}\right]\·v_1.$

4. the distributed optical storage based active power distribution network safe operation optimization method according to claim 2, characterized in that: in step S2, the optimal solution is obtained for the state estimation model by the cplex function.