Unbalanced power distribution network-oriented reactive power-active power combined voltage regulation method

Abstract

The invention discloses a reactive power-active power combined voltage regulation method for an unbalanced power distribution network, and relates to a voltage regulation method for the power distribution network. The scheme is as follows: (1) in order to realize voltage distribution optimization of the unbalanced power distribution network, a distributed power supply and reactive power compensator equipment are adopted to carry out active-reactive power combined voltage regulation; the distributed power supply comprises a photovoltaic power generation power supply and a wind power generation power supply; constructing a photovoltaic active power support model, a wind power generation active power support model, a reactive compensator active power support model and a reactive power support model respectively; (2) in order to adjust the unbalanced power distribution network voltage, constructing a power distribution network voltage distribution enhancement index and a voltage imbalance index respectively; (3) aiming at a voltage distribution enhancement index and a voltage imbalance index of the power distribution network, realizing unbalanced power distribution network voltage distribution optimization, and constructing a power distribution network voltage optimization objective function; and (4) solving the constructed multi-objective optimization model by using a grey wolf intelligent optimization algorithm.

Description

Technical Field

[0001] The present invention discloses a reactive-active power combined voltage regulation method for an unbalanced distribution network, which relates to a method for voltage regulation in a distribution network. Background Art

[0002] In the face of a global energy crisis and a sharp increase in electricity demand, the stable operation and efficient management of power systems have become particularly important. This is especially true for distribution networks, which serve as a critical hub connecting the transmission grid and end users. Their operational status directly determines the quality and reliability of power supply. In recent years, with the widespread integration of distributed generation resources and nonlinear loads, the operating environment of distribution networks has become more complex and volatile, and traditional voltage regulation methods have been unable to meet the increasingly stringent power supply quality requirements. Therefore, research on advanced distribution network voltage regulation technologies will not only help achieve accurate and rapid responses to power quality issues such as voltage fluctuations and asymmetry, but will also effectively improve the grid's ability to accommodate distributed energy resources, reduce grid losses, and thus enhance the economy and reliability of the entire power system.

[0003] At present, a large number of research results have been achieved in the research on voltage regulation of distribution networks. For example, the book "Research on Voltage Control Strategy of Distributed Photovoltaic Cluster Considering Net Load Balancing" by Huang Dongmei, Yang Kai, Yu Jingpeng, etc. discloses the challenge of voltage exceeding the limit in distribution networks caused by distributed photovoltaic grid connection, and proposes an innovative voltage management strategy. The core of this strategy is to cluster distributed photovoltaics in the distribution network to achieve more effective voltage regulation; the book "Reactive Power Optimization and Loss Reduction Method of Distribution Network Considering the Interaction of High-Proportion Multi-Regulation Resources" by Ma Xiping, Li Yaxin, Liang Chen, etc.

[0004] Traditional voltage regulation methods include adjusting on-load voltage regulators and switching shunt capacitor banks. Meanwhile, distributed power sources and energy storage resources offer new approaches to voltage regulation in distribution networks. Therefore, further exploring the combined active and reactive voltage regulation of distributed power sources and reactive compensation resources in distribution networks is crucial for improving the voltage stability of distribution networks. While considerable research has been conducted on active and reactive voltage regulation in distribution networks, research on combined active and reactive voltage regulation in unbalanced distribution networks remains significantly lacking. Therefore, it is necessary to design a new regulation method to meet these needs. Summary of the Invention

[0005] Existing research on distribution network voltage regulation has also adopted the active-reactive power combined voltage regulation method, but there are still deficiencies in the research on unbalanced distribution networks. Therefore, the method proposed in the present invention mainly adopts the active-reactive power combined voltage regulation method to solve the voltage limit problem of unbalanced distribution networks.

[0006] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a method for combined reactive and active power voltage regulation for an unbalanced distribution network. The method regulates the voltage of the unbalanced distribution network by providing active power support from distributed power sources (photovoltaic and wind power) and reactive power support from a reactive compensator. The technical solution of the present invention is as follows:

[0007] (1) First, in order to optimize the voltage distribution of the unbalanced distribution network, distributed power sources and reactive power compensators are used to perform active-reactive power joint voltage regulation; the distributed power sources include photovoltaic power sources and wind power sources; photovoltaic active power support, wind power active power support, reactive power compensator active power and reactive power support models are constructed respectively;

[0008] (2) Secondly, in order to regulate the unbalanced distribution network voltage, the distribution network voltage distribution enhancement index and voltage imbalance index are constructed respectively;

[0009] (3) Aiming at the distribution network voltage distribution enhancement index and voltage imbalance index, the voltage distribution of the unbalanced distribution network is optimized and the distribution network voltage optimization objective function is constructed;

[0010] (4). Finally, the constructed multi-objective optimization model is solved using the Gray Wolf intelligent optimization algorithm.

[0011] Specifically, in step (1), the photovoltaic active power support, wind power generation active power support, reactive power compensator active power and reactive power compensator reactive power support models constructed respectively are as follows;

[0012] (1.1) Photovoltaic active power support

[0013]

[0014] Where, P pv,j 、P pv,N are the active power support and rated power of the photovoltaic node j respectively; G N is the standard solar irradiance; α pv is the power temperature coefficient; T C 、T STC are the photovoltaic temperature and the battery temperature under standard test conditions; G is the solar radiation intensity.

[0015] (1.2) Active power support for wind power generation

[0016]

[0017] Where, P wt,j and P WT,N are the wind power active power support and rated power of node j, v Nis the rated wind speed; v in and v out are the cut-in wind speed and cut-out wind speed respectively; v is the wind speed.

[0018] (1.3) Reactive power support of reactive compensator

[0019]

[0020]

[0021] Where, is the reactive power compensation of the reactive compensator at node j; ω represents any one of the three phases a, b, and c; are the output voltage and input current of the reactive power compensator of phase ω.

[0022] (2) Secondly, in order to regulate the unbalanced distribution network voltage, the distribution network voltage distribution enhancement index and voltage imbalance index are constructed respectively, as follows:

[0023] (2.1) Voltage distribution enhancement index

[0024]

[0025] Where, VP device VP base They are the voltage distribution before and after the equipment is installed; V max 、V min They are the maximum and minimum voltages under safe operation of the distribution network.

[0026] (2.2) Voltage imbalance indicator

[0027]

[0028] Where VU base 、VU device They are the voltage imbalance before and after the equipment is installed; V +sequence 、V -sequence They are the positive sequence and negative sequence voltages of the three-phase voltage respectively.

[0029] (3) Furthermore, the distribution network voltage distribution enhancement index and voltage imbalance index are used to optimize the unbalanced distribution network voltage distribution and construct the distribution network voltage optimization objective function;

[0030] f=min(f VPI -1 ,f VUI )

[0031] The voltage optimization constraints of the unbalanced distribution network include: unbalanced distribution network flow constraints, power balance constraints and distribution network node and reactive compensator voltage constraints.

[0032] (3.1) Unbalanced distribution network power flow constraints

[0033]

[0034] Where, are the active power and reactive power from node j to node k respectively; are the voltages at nodes j and k respectively.

[0035] (3.2) Power balance constraints

[0036]

[0037] Where, are the active and reactive losses of the distribution network in phase ω respectively; are the active and reactive power demands of the load in phase ω respectively; They are the active power injected by the ω-phase distributed generation and the reactive power injected by the reactive compensator.

[0038] (3.3) Voltage constraints of distribution network nodes and reactive compensators

[0039]

[0040]

[0041] (4) Finally, the constructed multi-objective optimization model is solved using the Gray Wolf intelligent optimization algorithm. The specific solution process is as follows:

[0042] (4.1) Initialize the gray wolf population and calculate the fitness value of the individual gray wolves based on the objective function;

[0043] (4.2) Sort the gray wolf individuals according to their fitness, and let X α is the gray wolf with the best fitness value, X β The gray wolf with the second best fitness value, X δ The gray wolf has the third highest fitness value;

[0044] (4.3) Update the gray wolf's position in sequence according to the following formula

[0045]

[0046] Where,

[0047] X1=X α -A1D α

[0048] X2=X β -A2D β

[0049] X3=X δ -A3D δ

[0050] In the formula, A1, A2, A3 are random values, D α 、D β 、D δ are the distances between α, β, and δ gray wolves and other gray wolf individuals.

[0051] (4.4) Update X α 、X β 、X δ Fitness value, until the iteration converges, return the optimal solution X α As the optimal solution of the multi-objective optimization model for distribution network voltage optimization.

[0052] A computer device includes a memory and a processor, wherein the memory stores a computer program. The device is characterized in that the memory stores the computer program, and when the processor executes the computer program, it implements the reactive-active power combined voltage regulation method for an unbalanced distribution network.

[0053] A computer-readable storage medium stores a computer program thereon, wherein the storage medium includes a stored program, wherein when the program is run, the device where the storage medium is located is controlled to execute the reactive-active power combined voltage regulation method for an unbalanced distribution network.

[0054] This paper proposes a combined reactive and active power voltage regulation method for unbalanced distribution networks. Based on models for active power support from photovoltaic and wind power distributed generation sources and reactive power support from reactive compensators, this method proposes a voltage optimization target for the unbalanced distribution network based on the distribution network voltage distribution enhancement index and voltage imbalance index. Finally, the objective function is solved using the Gray Wolf intelligent optimization algorithm to obtain a voltage regulation solution for the unbalanced distribution network. Compared to existing mainstream methods, this method solves the voltage over-limit problem in unbalanced distribution networks, thereby improving the safe and stable operation of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 These are the steps of the method for combined active and reactive voltage regulation of an unbalanced distribution network in the present invention;

[0056] Figure 2 Schematic diagram of the IEEE 36-node power distribution network used in the embodiments of the present invention;

[0057] Figure 3The voltage index value after voltage regulation optimization of the distribution network in the embodiment of the present invention;

[0058] Figure 4 The minimum voltage of each phase before and after the distribution network is optimized in the embodiment of the present invention. DETAILED DESCRIPTION

[0059] The following is attached with the instruction manual Figure 1-4 The present invention is further described in detail:

[0060] The steps of the active-reactive combined voltage regulation method for unbalanced distribution network proposed by the present invention are as follows: Figure 1 As shown, the specific implementation plan is as follows:

[0061] First, to optimize the voltage distribution of the unbalanced distribution network, distributed power generation and reactive power compensator equipment are used to perform active-reactive power combined voltage regulation. The distributed power generation and reactive power compensator active power and reactive power support are represented by the following models:

[0062] (1) Photovoltaic active power support

[0063]

[0064] Where, P pv,j 、P pv,N are the active power support and rated power of the photovoltaic node j respectively; G N is the standard solar irradiance; α pv is the power temperature coefficient; T C 、T STC are the photovoltaic temperature and the battery temperature under standard test conditions; G is the solar radiation intensity.

[0065] (2) Active power support for wind power generation

[0066]

[0067] Where, P wt,j and P WT,N are the wind power active power support and rated power of node j, v N is the rated wind speed; v in and v out are the cut-in wind speed and cut-out wind speed respectively; v is the wind speed.

[0068] (3) Reactive power support of reactive compensator

[0069]

[0070]

[0071] Where, is the reactive power compensation of the reactive compensator at node j; ω represents any one of the three phases a, b, and c; are the output voltage and input current of the reactive power compensator of phase ω.

[0072] Secondly, in order to regulate the unbalanced distribution network voltage, the distribution network voltage distribution enhancement index and voltage imbalance index are constructed respectively, as follows:

[0073] (1) Voltage distribution enhancement index

[0074]

[0075] Where, VP device VP base They are the voltage distribution before and after the equipment is installed; V max 、V min They are the maximum and minimum voltages under safe operation of the distribution network.

[0076] (2) Voltage imbalance index

[0077]

[0078] Where VU base 、VU device They are the voltage imbalance before and after the equipment is installed; V +sequence 、V -sequence They are the positive sequence and negative sequence voltages of the three-phase voltage respectively.

[0079] Furthermore, the distribution network voltage distribution enhancement index and voltage imbalance index are used to optimize the unbalanced distribution network voltage distribution and construct the distribution network voltage optimization objective function.

[0080] f=min(f VPI -1 ,f VUI )

[0081] The voltage optimization constraints of the unbalanced distribution network include: unbalanced distribution network flow constraints, power balance constraints and distribution network node and reactive compensator voltage constraints.

[0082] (1) Unbalanced distribution network flow constraints

[0083]

[0084] Where, are the active power and reactive power from node j to node k respectively; are the voltages at nodes j and k respectively.

[0085] (2) Power balance constraints

[0086]

[0087] Where, are the active and reactive losses of the distribution network in phase ω respectively; are the active and reactive power demands of the load in phase ω respectively; They are the active power injected by the ω-phase distributed generation and the reactive power injected by the reactive compensator.

[0088] (3) Voltage constraints of distribution network nodes and reactive compensators

[0089]

[0090] Finally, the constructed multi-objective optimization model is solved using the Gray Wolf intelligent optimization algorithm. The specific solution process is as follows:

[0091] (1) Initialize the gray wolf population and calculate the individual fitness value of the gray wolf according to the objective function;

[0092] (2) Sort the gray wolf individuals according to their fitness and let X α is the gray wolf with the best fitness value, X β The gray wolf with the second best fitness value, X δ The gray wolf has the third highest fitness value;

[0093] (3) Update the gray wolf position in sequence according to the following formula

[0094]

[0095] Where,

[0096]

[0097] In the formula, A1, A2, A3 are random values, D α 、D β 、D δ are the distances between α, β, and δ gray wolves and other gray wolf individuals.

[0098] (4) Update X α 、X β 、X δ Fitness value, until the iteration converges, return the optimal solution X α As the optimal solution of the multi-objective optimization model for distribution network voltage optimization.

[0099] A computer device includes a memory and a processor, wherein the memory stores a computer program. The device is characterized in that the memory stores the computer program, and when the processor executes the computer program, it implements the reactive-active power combined voltage regulation method for an unbalanced distribution network.

[0100] A computer-readable storage medium stores a computer program thereon, wherein the storage medium includes a stored program, wherein when the program is run, the device where the storage medium is located is controlled to execute the reactive-active power combined voltage regulation method for an unbalanced distribution network.

[0101] Based on the above implementation scheme, in order to verify the beneficial effects of the present invention, a specific example is used to analyze the Figure 2 The IEEE 36-bus distribution network shown in Figure 1 is analyzed, and it is assumed that three sets of distributed generation and reactive power compensator equipment can be configured respectively.

[0102] node Active power configuration (kW) Reactive power configuration (kvar) 9 359.2 91.31 18 1661.58 143.85 32 1576.94 117.54

[0103] Table 1

[0104] Table 1 shows the configuration results of each node. It can be seen from the table that active power and reactive power compensation will be performed at nodes 9, 18, and 32 respectively. Under this configuration scheme, the distribution network voltage distribution enhancement index and voltage imbalance index results are as follows: Figure 3 As shown, it shows that the voltage distribution of the distribution network has been well regulated. Figure 4 The figure shows a comparison of the minimum three-phase voltages of an unbalanced distribution network before and after the configuration of distributed power sources and reactive power compensators. The figure shows that the optimized configuration significantly improves the minimum voltage of the distribution network. Through case analysis, it is clear that the proposed combined active and reactive power voltage regulation scheme can effectively improve the voltage stability of unbalanced distribution networks, which is of great significance for the safe and stable operation of distribution networks.

Claims

1. A reactive-active power combined voltage regulation method for an unbalanced distribution network, characterized in that: (1) First, in order to optimize the voltage distribution of the unbalanced distribution network, distributed power sources and reactive power compensator equipment are used to perform active-reactive power joint voltage regulation; the distributed power sources include photovoltaic power generation and wind power generation; photovoltaic active power support, wind power generation active power support, reactive power compensator active power and reactive power support models are constructed respectively; (2) Secondly, in order to adjust the unbalanced distribution network voltage, the distribution network voltage distribution enhancement index and voltage imbalance index are constructed respectively; (3) Aiming at the distribution network voltage distribution enhancement index and voltage imbalance index, the voltage distribution of the unbalanced distribution network is optimized and the distribution network voltage optimization objective function is constructed; (4). Finally, the constructed multi-objective optimization model is solved using the Grey Wolf intelligent optimization algorithm.

2. The method for combined reactive and active power voltage regulation for an unbalanced distribution network according to claim 1, characterized in that: The photovoltaic active power support is: Where P pv,j , P pv,N are the active power support and rated power of the photovoltaic power station j; G N is the standard solar radiation intensity; α pv is the power temperature coefficient; T C , T STC are photovoltaic temperature and battery temperature under standard test conditions respectively; G is solar radiation intensity.

3. The method for combined reactive and active power voltage regulation for an unbalanced distribution network according to claim 1, characterized in that: The wind power generation active power support is: Where P wt,j and P WT,N are the wind power active power support and rated power of node j, v N is the rated wind speed; v in and v out are the cut-in wind speed and the cut-out wind speed respectively; v is the wind speed.

4. The method for combined reactive and active power voltage regulation for an unbalanced distribution network according to claim 1, characterized in that: The reactive power support of the reactive compensator is: In the formula, is the reactive power compensation of the reactive compensator at node j; ω represents any one of the three phases a, b, and c; are the output voltage and input current of the reactive power compensator of phase ω.

5. The method for combined reactive and active power voltage regulation for an unbalanced distribution network according to claim 1, characterized in that: The voltage distribution enhancement index is: Where, VP device VP base They are the voltage distribution before and after the equipment is installed; V max 、V min They are the maximum and minimum voltages under safe operation of the distribution network.

6. The method for combined reactive and active power voltage regulation for an unbalanced distribution network according to claim 1, characterized in that: The voltage imbalance index is: Where VU base , VU device They are respectively the voltage imbalance before and after the equipment is installed; V +sequence 、V -sequence They are the positive-sequence and negative-sequence voltages of the three-phase voltage respectively.

7. The method for combined reactive and active power voltage regulation for an unbalanced distribution network according to claim 1, characterized in that: In step (3), the distribution network voltage optimization objective function is constructed as follows: f=min(f VPI -1 ,f VUI ) The voltage optimization constraints of the unbalanced distribution network include: unbalanced distribution network power flow constraints, power balance constraints and distribution network node and reactive power compensator voltage constraints.

8. The method for combined reactive and active power voltage regulation for an unbalanced distribution network according to claim 7, characterized in that: The unbalanced distribution network power flow constraint is: In the formula, are the active power and reactive power from node j to node k respectively; are the voltages at nodes j and k respectively.

9. The method for combined reactive and active power voltage regulation for an unbalanced distribution network according to claim 7, characterized in that: The power balance constraint is: In the formula, are the active and reactive losses of the distribution network in phase ω respectively; They are the active and reactive power requirements of the load in phase ω respectively; They are respectively the active power injected by the ω-phase distributed generation and the reactive power injected by the reactive compensator.

10. The method for combined reactive and active power voltage regulation for an unbalanced distribution network according to claim 7, characterized in that: The voltage constraints of the distribution network nodes and the reactive power compensator are:

11. The method for combined reactive and active power voltage regulation for an unbalanced distribution network according to claim 1, characterized in that: The solution process of step (4) is as follows: (4.1) Initialize the gray wolf population and calculate the individual fitness values ​​of gray wolves according to the objective function; (4.2) Sort the gray wolf individuals according to their fitness and let X α is the gray wolf with the best fitness value, X β is the gray wolf with the second best fitness value, X δ The gray wolf has the third highest fitness value; (4.3) Update the gray wolf position in sequence according to the following formula In the formula, X1=X α -A1D α X2=X β -A2D β <h2 style=";text-align:left;direction:ltr">X3=X<h2 style=";text-align:left;direction:ltr"> δ <h2 style=";text-align:left;direction:ltr"> -A3D<h2 style=";text-align:left;direction:ltr"> δ In the formula, A1, A2, A3 are random values, D α , D β , D δ are the distances between α-grey wolf, β-grey wolf, δ-grey wolf and other grey wolf individuals; (4.4) Update X α , X β , X δ Fitness value, until the iteration converges, return the optimal solution X α As the optimal solution of the multi-objective optimization model for distribution network voltage optimization.

12. A computer device, characterized in that: It includes a memory and a processor, the memory stores a computer program, and is characterized in that the memory stores the computer program, and when the processor executes the computer program, it implements a reactive-active power joint voltage regulation method for an unbalanced distribution network as described in any one of claims 1 to 11.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: The storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute a reactive-active power joint voltage regulation method for an unbalanced distribution network according to any one of claims 1 to 11.

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