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

Abstract

The invention provides a safe operation optimization method for an initiative power distribution network based on distributed optical storage. The method comprises the following steps: S1) acquiring power distribution network parameters and node information of a connecting node of a power distribution network based on distributed optical storage and a main network, and screening out a slack node; and S2) establishing an operation evaluation model for the power distribution network, and solving the optimal solution of the evaluation model. According to the invention, the initiative power distribution network for photovoltaic power generation can be systemically and comprehensively analyzed, and all the links of the power distribution network are considered, so that the accuracy of the analysis result can be guaranteed, and the safe and stable grid connection of the electric energy generated by photovoltaic power generation is benefited; and the algorithm is simple.

Description

Active power distribution network safe operation optimization method based on distributed optical storage

Technical Field

The invention relates to a power optimization method, in particular to a safe operation optimization method of an active power distribution network based on distributed light storage.

Background

With the exhaustion of fossil energy and the serious influence of fossil energy on the environment, people urgently need environment-friendly renewable energy, at present, the existing renewable clean energy comprises water energy, wind energy and solar energy, and solar energy is cleaner and more widely distributed in the using process, so that solar power generation is more and more emphasized.

The conversion of solar energy into electric energy is generally performed by a photovoltaic cell (also called a photovoltaic cell array), in photovoltaic power generation, including a photovoltaic cell, a storage battery, an electronic converter (rectifier and inverter), a capacitor, a load, and the like, because photovoltaic distributed power generation has extremely high requirements on the environment, the output power fluctuation is large, in order to make the whole power grid system operate stably, the operation of a power distribution network for photovoltaic power generation needs to be analyzed, in the prior art, the analysis of the power distribution network for photovoltaic power generation is based on a specific control target, therefore, the control target is isolated from other factors in the analysis process, for example, the performance of the storage battery is analyzed, only the storage battery is analyzed, and the factors such as the photovoltaic cell and the load are ignored, so that the final analysis result is inaccurate, is not beneficial to the safe operation of the power distribution network.

Therefore, a new method is needed to be provided, which can perform systematic and comprehensive analysis on the active power distribution network of photovoltaic power generation, and all links of the power distribution network are considered, so that the accuracy of an analysis result is ensured, and the method is beneficial to safely and stably merging the generated electric energy of photovoltaic power generation into the power grid.

Disclosure of Invention

In view of the above, the present invention provides a method for optimizing safe operation of an active power distribution network based on distributed optical storage, which can perform a system-wide analysis on the active power distribution network for photovoltaic power generation, and consider all links of the power distribution network, so as to ensure accuracy of an analysis result, and facilitate safe and stable incorporation of electric energy generated by photovoltaic power generation into the power distribution network.

The invention provides a distributed light storage-based active power distribution network safe operation optimization method, which 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.

Further, it is characterized in that: 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).

Further, 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：

Wherein R is_ijIs node i toResistance between nodes j, X_ijThe reactance from the node i to the node j is shown, and N 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:

the following matrix is derived from equation (5):

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 the reactive power variation of a distributed power supply in a power distribution network, △ 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, mixingEach parameter being divided into state variables x₁V disturbance variable₁And control variables u 1:

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:

further, in step S2, the optimal solution is obtained for the state estimation model by the cplex function.

The invention has the beneficial effects that: according to the invention, the active power distribution network of photovoltaic power generation can be comprehensively analyzed systematically, and all links of the power distribution network are considered, so that the accuracy of an analysis result is ensured, the safe and stable integration of electric energy generated by photovoltaic power generation into the power grid is facilitated, and the algorithm is simple.

Drawings

The invention is further described below with reference to the following figures and examples:

FIG. 1 is a flow chart of the present invention.

Detailed Description

Fig. 1 is a flowchart of the present invention, and as shown in the drawing, the method for optimizing the safe operation of an active power distribution network based on distributed optical storage provided by the present invention includes 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;

s2, constructing an operation evaluation model of the power distribution network, and performing optimal solution solving on the evaluation model; according to the invention, the active power distribution network of photovoltaic power generation can be comprehensively analyzed systematically, and all links of the power distribution network are considered, so that the accuracy of an analysis result is ensured, the safe and stable integration of electric energy generated by photovoltaic power generation into the power grid is facilitated, and the algorithm is simple.

In the embodiment, the method is characterized in that: 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 reactanceAnd X ═ imag (Z), the resistance R is the real component of the impedance Z, and the reactance X is the imaginary component of the impedance Z.

In this embodiment, 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：

Wherein R is_ijIs the resistance between node i and node j, X_ijThe reactance from the node i to the node j is shown, and N 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:

the following matrix is derived from equation (5):

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 the reactive power variation of a distributed power supply in a power distribution network, △ 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:

the optimal solution is obtained for the final state evaluation model through a cplex function, and the function is an existing algorithm and is not described again; the relaxation node is a node of the power distribution network connected with the main network, and the relaxation factor of the relaxation node is determined by the characteristics of the main network and the power distribution network, namely: the relaxation factors of the photovoltaic-based power distribution network and the relaxation nodes of the main network are determined when networking is carried out.

Finally, the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered in 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.