Voltage support method for cooperative operation of roof photovoltaic system and static var generator

Abstract

The invention discloses a reactive voltage support method for cooperative operation of a roof photovoltaic system and a static var generator. The reactive voltage support method comprises the following steps: establishing a distribution network branch load flow model based on second-order cone programming; based on the adjustment capability of the photovoltaic converter, establishing an optimal control model of the operation mode of the roof photovoltaic system; establishing a resource optimization configuration model of the static var generator; and based on the minimum static var generator capacity meeting the voltage requirement, designing a reactive voltage support strategy for cooperative configuration of the roof photovoltaic system and the static var generator. According to the method, the roof photovoltaic operation mode and the static var generator are subjected to collaborative optimization control, fine regulation and control of the output of the roof photovoltaic system are realized, the supporting efficiency of the distribution network node voltage is remarkably improved, meanwhile, the active power loss of the roof photovoltaic system in the operation process is reduced, the control cost is saved, and the control efficiency is improved. And a powerful guarantee is provided for stable operation and energy efficiency improvement of a power system.

Description

Technical Field

[0001] The invention relates to the technical field of power system voltage regulation, and in particular to a reactive voltage support method for coordinated operation of a rooftop photovoltaic system and a static reactive generator. Background Art

[0002] As the global energy supply gradually shifts toward low-carbonization, photovoltaic power generation has attracted widespread attention due to its advantages of flexible installation and sustainable development. Technological progress and subsidy policies have enabled more households and businesses to access photovoltaic power generation at low cost. Therefore, the penetration rate of rooftop photovoltaics in the distribution network has gradually increased.

[0003] In order to ensure that the voltage meets the safety operation requirements in extreme scenarios, the rooftop photovoltaic system can be switched to the grid voltage support control mode. However, due to the limitations of the capacity and location of the existing photovoltaic system, the reactive power it provides is relatively limited and cannot provide sufficient voltage support for distant nodes. The static VAR generator (SVG) provides an effective technical approach to solve the problem of insufficient grid voltage support by virtue of its flexible configuration and continuous and rapid adjustment of reactive power. In the prior art, the installation cost of the static VAR generator (SVG) is relatively high, which to a certain extent limits its widespread application. Therefore, the present invention proposes a reactive voltage support method for the coordinated operation of a rooftop photovoltaic system and a static VAR generator, which can provide sufficient voltage support for the distribution network and control costs. Summary of the invention

[0004] In order to solve the above problems, the present invention proposes a reactive voltage support method for the coordinated operation of a rooftop photovoltaic system and a static VAR generator, which can coordinate and optimize the control of the rooftop photovoltaic operation mode and the static VAR generator, realize the fine regulation of the output of the rooftop photovoltaic system, significantly improve the support efficiency of the distribution network node voltage, and at the same time reduce the active power loss of the rooftop photovoltaic system during operation, save control costs, and provide a strong guarantee for the stable operation and energy efficiency improvement of the power system.

[0005] In order to achieve the above object, the present invention is implemented by the following technical solutions:

[0006] The present invention is a reactive voltage support method for cooperative operation of a rooftop photovoltaic system and a static reactive generator, comprising the following operations:

[0007] Establish a distribution network branch power flow model based on second-order cone programming;

[0008] Based on the regulation capability of the photovoltaic inverter, an optimization control model for the operation mode of the rooftop photovoltaic system is established;

[0009] Establish a resource optimization configuration model for static VAR generators;

[0010] Based on the minimum static VAR generator capacity that meets the voltage requirements, a reactive voltage support strategy for the coordinated configuration of the rooftop photovoltaic system and the static VAR generator is designed.

[0011] A further improvement of the present invention is that the establishment of a distribution network branch power flow model based on second-order cone programming includes the following steps:

[0012] The relationship between the current, voltage and power of each branch in the distribution network is shown in the following formula:

[0013]

[0014] Where U k,t , U j,t They represent the voltages of nodes k and j at time t respectively; They represent the active power and reactive power of branch jk at time t respectively; r jk 、x jk Respectively represent the resistance and reactance of branch jk; I jk,t represents the current of branch jk at time t; S ki,t , S jk,t represents the apparent power of branches ki and jk at time t; z jk represents the reactance of branch jk; S k,t represents the apparent power of node k at time t; Ω B represents the set of all branches; Ω E represents the set of all nodes in the distribution network; σ(k) and δ(k) represent the set of parent nodes and child nodes of node k respectively; T represents the set of all time nodes;

[0015] By performing phase relaxation on equation (2), we can obtain equation (4) and equation (5):

[0016]

[0017] In the formula, They represent the active power and reactive power of branch ki at time t respectively; They represent the active power and reactive power of branch jk at time t respectively; r jk 、x jk Respectively represent the resistance and reactance of branch jk; I jk,t represents the current of branch jk at time t; Respectively represent the active power and reactive power of node k at time t; Ω E represents the set of all nodes in the distribution network; σ(k) and δ(k) represent the set of parent nodes and child nodes of node k respectively; T represents the set of all time nodes;

[0018] Let l jk,t=I jk,t 2 、u k,t =U k,t 2 and u j,t l=U j,t 2 , formula (1) and (3) are equivalent to formula (6) and (7):

[0019]

[0020] In the formula, u k,t represents the square of the voltage of node k at time t; l jk,t represents the square of the current of branch jk at time t; u j,t represents the square of the voltage of node j at time t; I jk,t represents the current of branch jk at time t; U k,t represents the voltage of node k at time t; U j,t represents the voltage of node j at time t; r jk 、x jk They represent the resistance and reactance of branch jk respectively; Respectively represent the active power and reactive power of branch jk at time t; Ω B represents the set of all branches; T represents the set of all time nodes;

[0021] Performing second-order cone relaxation on equation (7) yields equation (8):

[0022]

[0023] In the formula, u j,t represents the square of the voltage of node j at time t; l jk,t represents the square of the current in branch jk at time t; Respectively represent the active power and reactive power of branch jk at time t; Ω B represents the set of all branches; T represents the set of all time nodes;

[0024] Formula (8) is expressed as a standard second-order cone constraint form, as shown in formula (9):

[0025]

[0026] In the formula, They represent the active power and reactive power of branch jk at time t respectively; l jk,t represents the square of the current of branch jk at time t; u j,t l represents the square of the voltage of node j at time t; Ω B represents the set of all branches; T represents the set of all time nodes.

[0027] A further improvement of the present invention is that the optimization control model for establishing the operation mode of the rooftop photovoltaic system comprises the following steps:

[0028] It is assumed that some nodes in the distribution network are equipped with rooftop photovoltaic inverters, and the output of each photovoltaic system is constrained by the maximum photovoltaic capacity:

[0029]

[0030] In the formula, They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; represents the capacity of the photovoltaic system at node k; Ω PV represents the set of nodes equipped with rooftop photovoltaic systems; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes;

[0031] The power sources and consumption in the distribution network include photovoltaic systems, generator sets and loads. Equations (4) and (5) are expanded into equations (11) and (12), where the output power of the power generation system is subject to the upper and lower limits of the generator output (13) and (14):

[0032]

[0033] In the formula, They represent the active power and reactive power of the power generation system of node k at time t respectively; They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; They represent the active power and reactive power of branch jk at time t respectively; They represent the active power and reactive power of branch ki at time t respectively; r jk 、x jk Respectively represent the resistance and reactance of branch jk; l jk,t represents the square of the current of branch jk at time t; σ(k) and δ(k) represent the set of parent nodes and child nodes of node k respectively; w represents the load expansion rate, w∈(0,1); Respectively represent the active load and reactive load of node k at time t; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; They represent the upper and lower limits of the active output of the power generation system at node k respectively; Respectively represent the upper and lower limits of reactive power output of the power generation system at node k; Ω GEN represents the set of nodes connected to the generator;

[0034] The rooftop photovoltaic power generation system installed in the distribution network has two modes. When the load is light, the rooftop photovoltaic system operates in a constant power factor mode, that is, m k =0, which means that the power demand for the whole day is met, as shown in formula (15):

[0035]

[0036] In the formula, They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; represents the maximum active power output of the photovoltaic system of node k at time t; θ k represents the power factor angle of the photovoltaic system at node k; tan represents the tangent function; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; m k = represents the operation mode of the photovoltaic system of node k;

[0037] In extreme scenarios, the rooftop photovoltaic system switches to the grid voltage support control mode, that is, m k =1, as shown in formula (16):

[0038]

[0039] In the formula, represents the active power of the photovoltaic system of node k at time t; represents the maximum active power output of the photovoltaic system of node k at time t; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; m k = represents the operation mode of the photovoltaic system of node k;

[0040] The penalty factor method is used to transform equations (15) and (16), and a positive value M is introduced. The positive value is not infinite. The nonlinear constraints of equations (15) and (16) are linearized, and equations (15) and (16) are relaxed to equations (17) to (19):

[0041]

[0042] In the formula, They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; represents the maximum active power output of the photovoltaic system of node k at time t; M represents the introduced positive value; m k = represents the operation mode of the photovoltaic system of node k; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; θ krepresents the power factor angle of the photovoltaic system at node k; tan represents the tangent function;

[0043] The model constraints of the rooftop photovoltaic system installed in some nodes of the distribution network include: voltage constraint (6), voltage constraint (20), current constraint (9), current constraint (21), power flow constraint (11), power flow constraint (12), photovoltaic system constraint (10), photovoltaic system constraint (17), photovoltaic system constraint (18), photovoltaic system constraint (19), photovoltaic system constraint (22), photovoltaic system constraint (23), generator output constraint (13), generator output constraint (14):

[0044]

[0045] In the formula, u k,t represents the square of the voltage of node k at time t; U Respectively represent the upper and lower limits of the square of the voltage at node k; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; l jk,t Represents the square of the current of branch jk at time t; Ω B represents the set of all branches; They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; represents the capacity of the photovoltaic system at node k; Ω PV represents the set of nodes equipped with rooftop photovoltaic systems; w represents the load expansion rate, w∈(0,1); η PV represents the photovoltaic penetration rate; max represents the maximum value; They represent the active load and reactive load of node k at time t respectively.

[0046] A further improvement of the present invention is that the establishment of a resource optimization configuration model for a static VAR generator includes the following operations:

[0047] In extreme scenarios, the rooftop photovoltaic system cannot meet the voltage safety requirements. Static VAR generators are installed at some key nodes of the power grid. The operating constraints of the static VAR generators are:

[0048]

[0049] In the formula, They represent the upper and lower limits of the reactive power output of the static VAR generator at node k respectively; represents the reactive power of the static VAR generator at node k at time t; Ω SVG represents the set of nodes to which static VAR generators are installed; and Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes;

[0050] The original node power balance equations (11) and (12) are rewritten as:

[0051]

[0052] In the formula, represents the active power of the power generation system of node k at time t; They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; They represent the active power and reactive power of branch jk at time t respectively; r jk 、x jk Respectively represent the resistance and reactance of branch jk; l jk,t represents the square of the current in branch jk at time t; They represent the active power and reactive power of branch ki at time t respectively; Respectively represent the active load and reactive load of node k at time t; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; represents the reactive power of the static VAR generator at node k at time t; σ(k) and δ(k) represent the set of parent nodes and child nodes of node k respectively; w represents the load expansion rate, w∈(0,1);

[0053] While meeting the voltage stability requirements of the power grid, the total construction cost of the static VAR generator is minimized, and the minimum total cost of installing the static VAR generator is taken as the objective function. The resource optimization configuration model for the static VAR generator is shown in formula (27):

[0054]

[0055] (27)

[0057] In the formula, Represents the upper limit of the reactive power output of the static VAR generator at node k; Ω SVG represents the set of nodes equipped with static VAR generators; st(6),(9)-(14),(17)-(26) represents the constraints of equation (27) as equations (6), (9) to (14), (17) to (26); min represents the minimum value.

[0058] A further improvement of the present invention is that the reactive voltage support strategy for the coordinated configuration of the rooftop photovoltaic system and the static VAR generator comprises the following steps:

[0059] According to the resource optimization configuration model of the static VAR generator, the photovoltaic operation mode optimization control is performed, as shown in formula (28):

[0060]

[0061] In the formula, represents the upper limit of the reactive power output of the static VAR generator at node k; Represents the configuration capacity of the static VAR generator of the k-node; Ω SVG represents the set of nodes equipped with static VAR generators; the optimization goal is to minimize the active power loss of the photovoltaic system, and the optimization model is shown in formula (29):

[0062]

[0063]

[0064] In the formula, Ω PV represents the set of nodes equipped with rooftop photovoltaic systems; T represents the set of all time nodes; represents the maximum active power output of the photovoltaic system of node k at time t; represents the active power of the photovoltaic system of node k at time t; st(6), (9)-(14), (17)-(26), (28) represents the constraints of equation (29) as equations (6), (9) to (14), (17) to (26), (28); min represents the minimum value.

[0065] The beneficial effects of the present invention are as follows: the present invention proposes a reactive voltage support method for the coordinated operation of a rooftop photovoltaic system and a static VAR generator, and by establishing an optimization control model for the operation mode of the rooftop photovoltaic system, efficient utilization of the existing rooftop photovoltaic system is achieved; a resource optimization configuration model for the static VAR generator is established, and a reasonable configuration of the static VAR generator is achieved, thereby improving the support capacity for the distribution network voltage; based on the minimum static VAR generator capacity that meets the voltage requirements, a reactive voltage support strategy for the coordinated configuration of the rooftop photovoltaic system and the static VAR generator is designed, which avoids the occurrence of voltage over-limit situations, reduces the active power loss of the rooftop photovoltaic system during operation, and improves the overall efficiency of photovoltaic power generation. Through the above method, the present invention can coordinate and optimize the control of the rooftop photovoltaic operation mode and the static VAR generator, realize the refined regulation of the output of the rooftop photovoltaic system, significantly improve the supporting efficiency of the distribution network node voltage, and at the same time reduce the active power loss of the rooftop photovoltaic system during operation, saving control costs, and providing strong guarantees for the stable operation and energy efficiency improvement of the power system. It not only ensures the voltage stability of the distribution network, but also optimizes the operation loss of the photovoltaic system, providing strong support for the widespread application of photovoltaic power generation and the reliable operation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 A schematic flow chart of a reactive voltage support method for a rooftop photovoltaic system and a static VAR generator operating in coordination provided by an embodiment of the present invention;

[0067] Figure 2 A voltage distribution curve diagram of the distribution network before the optimization configuration provided by the embodiment of the present invention;

[0068] Figure 3 A voltage distribution curve diagram of a distribution network after optimization configuration provided by an embodiment of the present invention;

[0069] Figure 4 SVG installation capacity diagram provided by an embodiment of the present invention;

[0070] Figure 5 A front view of active power loss of a rooftop photovoltaic system under an SVG optimization configuration provided by an embodiment of the present invention;

[0071] Figure 6 A top view of active power loss of a rooftop photovoltaic system under an SVG optimization configuration provided by an embodiment of the present invention;

[0072] Figure 7 A front view of active power loss of a rooftop photovoltaic system supported by collaborative optimization of a rooftop photovoltaic system and SVG provided in an embodiment of the present invention;

[0073] Figure 8A top view of the active power loss of a rooftop photovoltaic system supported by the collaborative optimization of the rooftop photovoltaic system and SVG provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0074] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0075] See also Figure 1 , a reactive voltage support method for cooperative operation of a rooftop photovoltaic system and a static VAR generator in this embodiment includes the following operations:

[0076] S1. Establish a distribution network branch power flow model based on second-order cone programming;

[0077] S2. Based on the regulation capability of the photovoltaic inverter, an optimization control model for the operation mode of the rooftop photovoltaic system is established;

[0078] S3. Establishing a resource optimization configuration model for static VAR generators;

[0079] S4. Based on the minimum static VAR generator capacity that meets the voltage requirement, a reactive voltage support strategy for the coordinated configuration of the rooftop photovoltaic system and the static VAR generator is designed.

[0080] Establishing a distribution network branch power flow model based on second-order cone programming includes the following steps:

[0081] The relationship between the current, voltage and power of each branch in the distribution network is shown in the following formula:

[0082]

[0083] Where U k,t , U j,t They represent the voltages of nodes k and j at time t respectively; They represent the active power and reactive power of branch jk at time t respectively; r jk 、x jk Respectively represent the resistance and reactance of branch jk; I jk,t represents the current of branch jk at time t; S ki,t , (S jk,t represents the apparent power of branches ki and Sjk at time t; z jk represents the reactance of branch jk; S k,t represents the apparent power of node k at time t; Ω B represents the set of all branches; ΩE represents the set of all nodes in the distribution network; σ(k) and δ(k) represent the set of parent nodes and child nodes of node k respectively; T represents the set of all time nodes;

[0084] By performing phase relaxation on equation (2), we can obtain equations (4) and (5):

[0085]

[0086] In the formula, They represent the active power and reactive power of branch ki at time t respectively; They represent the active power and reactive power of branch jk at time t respectively; r jk 、x jk Respectively represent the resistance and reactance of branch jk; I jk,t represents the current of branch jk at time t; Respectively represent the active power and reactive power of node k at time t; Ω E represents the set of all nodes in the distribution network; σ(k) and δ(k) represent the set of parent nodes and child nodes of node k respectively; T represents the set of all time nodes;

[0087] Since the equation contains non-convex and difficult quadratic terms, let l jk,t =I jk,t 2 、u k,t =U k,t 2 and u j,t =U j,t 2 , formula (1) and (3) are equivalent to formula (6) and (7):

[0088]

[0089] In the formula, u k,t represents the square of the voltage of node k at time t; l jk,t represents the square of the current of branch jk at time t; u j,t represents the square of the voltage of node j at time t; I jk,t represents the current of branch jk at time t; U k,t represents the voltage of node k at time t; U j,t represents the voltage of node j at time t; r jk 、x jk They represent the resistance and reactance of branch jk respectively; Respectively represent the active power and reactive power of branch jk at time t; Ω B represents the set of all branches; T represents the set of all time nodes;

[0090] Performing second-order cone relaxation on equation (7) yields equation (8):

[0091]

[0092] In the formula, u j,t represents the square of the voltage of node j at time t; l jk,t represents the square of the current in branch jk at time t; Respectively represent the active power and reactive power of branch jk at time t; Ω B represents the set of all branches; T represents the set of all time nodes;

[0093] Formula (8) is expressed as a standard second-order cone constraint form, as shown in formula (9):

[0094]

[0095] In the formula, They represent the active power and reactive power of branch jk at time t respectively; l jk,t represents the square of the current of branch jk at time t; u j,t represents the square of the voltage of node j at time t; Ω B represents the set of all branches; T represents the set of all time nodes.

[0096] Based on the regulation capability of the photovoltaic inverter, an optimization control model for the operation mode of the rooftop photovoltaic system is established, including the following steps:

[0097] Assuming that some nodes in the distribution network are equipped with rooftop photovoltaic inverters, the output of each photovoltaic system is constrained by the maximum photovoltaic capacity:

[0098]

[0099] In the formula, They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; represents the capacity of the photovoltaic system at node k; Ω PV represents the set of nodes equipped with rooftop photovoltaic systems; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes;

[0100] The power sources and consumption in the distribution network include photovoltaic systems, generator sets and loads. Equations (4) and (5) are expanded into equations (11) and (12), where the output power of the power generation system is subject to the upper and lower limits of the generator output (13) and (14):

[0101]

[0102] In the formula, They represent the active power and reactive power of the power generation system of node k at time t respectively; They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; They represent the active power and reactive power of branch jk at time t respectively; They represent the active power and reactive power of branch ki at time t respectively; r jk 、x jk Respectively represent the resistance and reactance of branch jk; l jk,t represents the square of the current of branch jk at time t; σ(k) and δ(k) represent the set of parent nodes and child nodes of node k respectively; w represents the load expansion rate, w∈(0,1); Respectively represent the active load and reactive load of node k at time t; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; They represent the upper and lower limits of the active output of the power generation system at node k respectively; Respectively represent the upper and lower limits of reactive power output of the power generation system at node k; Ω GEN represents the set of nodes connected to the generator;

[0103] The rooftop photovoltaic power generation system installed in the distribution network has two modes. When the load is light, the rooftop photovoltaic system operates in the constant power factor mode (m k =0), the power demand for the whole day can be met, as shown in formula (15):

[0104]

[0105] In the formula, They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; represents the maximum active power output of the photovoltaic system of node k at time t; θ k represents the power factor angle of the photovoltaic system at node k; tan represents the tangent function; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; m k = represents the operation mode of the photovoltaic system of node k;

[0106] In extreme scenarios, such as cloudy days and rainy days, the intensity of light radiation received by the photovoltaic panels will be significantly reduced, resulting in a reduction in photovoltaic output power. At the same time, extreme weather is usually accompanied by an increase in load demand, which further exacerbates the voltage problem of the distribution network. Therefore, in order to provide more voltage support so that the voltage meets the operating requirements, the rooftop photovoltaic system can be converted to the grid voltage support control mode (m k=1), as shown in formula (16):

[0107]

[0108] In the formula, represents the active power of the photovoltaic system of node k at time t; represents the maximum active power output of the photovoltaic system of node k at time t; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; m k = represents the operation mode of the photovoltaic system of node k;

[0109] The penalty factor method (big M method) is used to transform equations (15) and (16), and a large positive value M is introduced. The positive value is not infinite. The nonlinear constraints of the if-then structure of equations (15) and (16) are linearized. Equations (15) and (16) are relaxed to equations (17), (18), and (19):

[0110]

[0111] In the formula, They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; represents the maximum active power output of the photovoltaic system of node k at time t; M represents the introduced positive value; m k = represents the operation mode of the photovoltaic system of node k; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; θ k represents the power factor angle of the photovoltaic system at node k; tanθ represents the tangent function;

[0112] Model constraints for rooftop photovoltaic systems installed at some nodes of the distribution network include: voltage constraint (6), voltage constraint (20), current constraint (9), current constraint (21), power flow constraint (11), power flow constraint (12), photovoltaic system constraint (10), photovoltaic system constraint (17), photovoltaic system constraint (18), photovoltaic system constraint (19), photovoltaic system constraint (22), photovoltaic system constraint (23), generator output constraint (13), generator output constraint (14):

[0113]

[0114] In the formula, u k,t represents the square of the voltage of node k at time t; U Respectively represent the upper and lower limits of the square of the voltage at node k; Ω Erepresents the set of all nodes in the distribution network; T represents the set of all time nodes; l jk,t Represents the square of the current of branch jk at time t; Ω B represents the set of all branches; They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; represents the capacity of the photovoltaic system at node k; Ω PV represents the set of nodes equipped with rooftop photovoltaic systems; w represents the load expansion rate, w∈(0,1); η PV represents the photovoltaic penetration rate; max represents the maximum value; They represent the active load and reactive load of node k at time t respectively.

[0115] Establishing a resource optimization configuration model for static VAR generators includes the following operations:

[0116] In extreme scenarios, existing rooftop PV systems alone cannot meet voltage safety requirements, so additional measures can be taken to ensure the stability and reliability of the power grid. Static VAR generators (SVGs) are considered an effective voltage support solution due to their fast response speed and continuously adjustable reactive power output. When rooftop PV systems cannot meet voltage safety requirements, static VAR generators can be installed at some key nodes of the power grid to enhance the voltage support capability of the power grid under extreme weather conditions. The operating constraints of static VAR generators are:

[0117]

[0118] In the formula, They represent the upper and lower limits of the reactive power output of the static VAR generator at node k respectively; represents the reactive power of the static VAR generator at node k at time t; Ω SVG represents the set of nodes to which static VAR generators are installed; and Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes;

[0119] The original node power balance equations (11) and (12) are rewritten as:

[0120]

[0121] In the formula, represents the active power of the power generation system of node k at time t; They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; They represent the active power and reactive power of branch jk at time t respectively; rjk 、x jk Respectively represent the resistance and reactance of branch jk; l jk,t represents the square of the current in branch jk at time t; They represent the active power and reactive power of branch ki at time t respectively; Respectively represent the active load and reactive load of node k at time t; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; represents the reactive power of the static VAR generator at node k at time t; σ(k) and δ(k) represent the set of parent nodes and child nodes of node k respectively; w represents the load expansion rate, w∈(0,1);

[0122] While meeting the requirements of grid voltage stability, the total construction cost of the static VAR generator is minimized. Taking the minimum total cost of installing the static VAR generator as the objective function, the resource optimization configuration model of the static VAR generator is established as shown in formula (27):

[0123]

[0124] (27)

[0126] In the formula, Represents the upper limit of the reactive power output of the static VAR generator at node k; Ω SVG represents the set of nodes equipped with static VAR generators; st(6),(9)-(14),(17)-(26) represents the constraints of equation (27) as equations (6), (9) to (14), (17) to (26); min represents the minimum value.

[0127] Based on the minimum STATCOM capacity that meets the voltage requirements, the reactive voltage support strategy for the coordinated configuration of the rooftop PV system and the STATCOM is designed, including the following steps:

[0128] The photovoltaic operation mode is optimized and controlled according to the resource optimization configuration model of the static VAR generator, as shown in formula (28):

[0129]

[0130] In the formula, represents the upper limit of the reactive power output of the static VAR generator at node k; Represents the configuration capacity of the static VAR generator of the k-node; Ω SVG represents a set of nodes equipped with static VAR generators;

[0131] The optimization goal is to minimize the active power loss of the photovoltaic system. The optimization model is shown in formula (29):

[0132]

[0133]

[0134] In the formula, Ω PV represents the set of nodes equipped with rooftop photovoltaic systems; T represents the set of all time nodes; represents the maximum active power output of the photovoltaic system of node k at time t; represents the active power of the photovoltaic system of node k at time t; st(6), (9)-(14), (17)-(26), (28) represents the constraints of equation (29) as equations (6), (9) to (14), (17) to (26), (28); min represents the minimum value.

[0135] The present invention will be further described below in conjunction with specific embodiments:

[0136] The results of the reactive voltage support method using the rooftop photovoltaic system and SVG coordinated operation proposed by the present invention are as follows:

[0137] The present invention takes the typical IEEE 33-node feeder of the distribution network as an example. When the photovoltaic penetration rate reaches 0.5 and the load expansion rate is 0.9pu, the voltage distribution of each node in the IEEE 33-node feeder is as follows: Figure 2 As shown in Figure 2. Some voltages at nodes (#6, #16, #18, #19, #22, #25, #28 and #33) are lower than the allowable limit (0.9pu-1.05pu). In this scenario, based on the coordinated optimization configuration of the rooftop PV system and SVG, the optimized voltage distribution is as follows: Figure 3 As shown, compared to Figure 2 In the case of node voltage exceeding the limit, Figure 3 The voltage of all nodes can be maintained above 0.9pu, which reflects the regulating effect of collaborative optimization control on the node voltage of distribution network.

[0138] SVG installation capacity Figure 4 As shown in the figure, by rationally configuring the location and capacity of SVG, the introduction of SVG enables the grid to operate safely even when faced with extreme load expansion rates and low PV penetration rates, and the grid’s regulation capability is significantly enhanced.

[0139] The active power loss of the rooftop PV system before and after the coordinated optimization of the rooftop PV system and SVG is as follows: Figure 5-6 and Figure 7-8As shown, therefore, the active power loss of the photovoltaic system supported by collaborative optimization is significantly reduced, and the utilization rate of photovoltaic power generation is improved.

[0140] Through the introduction of the above embodiments, the present invention establishes an optimization control model of the operation mode of the roof photovoltaic system through the reactive voltage support method of the coordinated operation of the roof photovoltaic system and the static reactive generator, and realizes the efficient utilization of the existing roof photovoltaic system; establishes a resource optimization configuration model of the static reactive generator, realizes the reasonable configuration of the static reactive generator, and improves the support capacity of the distribution network voltage; based on the minimum static reactive generator capacity that meets the voltage requirements, the reactive voltage support strategy of the coordinated configuration of the roof photovoltaic system and the static reactive generator is designed, which avoids the voltage over-limit situation, reduces the active power loss of the roof photovoltaic system during operation, and improves the overall efficiency of photovoltaic power generation. Through the above method, the present invention can coordinate and optimize the control of the roof photovoltaic operation mode and the static reactive generator, realize the refined regulation of the output of the roof photovoltaic system, significantly improve the support efficiency of the distribution network node voltage, and reduce the active power loss of the roof photovoltaic system during operation, saving the control cost, providing a strong guarantee for the stable operation and energy efficiency improvement of the power system, not only ensuring the voltage stability of the distribution network, but also optimizing the operation loss of the photovoltaic system, providing a strong support for the wide application of photovoltaic power generation and the reliable operation of the power grid.

[0141] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have the same meaning as in the context of the prior art, and will not be interpreted with an idealized or overly formal meaning unless defined similarly here.

[0142] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A reactive voltage support method for cooperative operation of a rooftop photovoltaic system and a static VAR generator, characterized in that: The following operations are included: Establish a distribution network branch power flow model based on second-order cone programming; Based on the regulation capability of the photovoltaic inverter, an optimization control model for the operation mode of the rooftop photovoltaic system is established; Establish a resource optimization configuration model for static VAR generators; Based on the minimum static VAR generator capacity that meets the voltage requirement, a reactive voltage support strategy for the coordinated configuration of the rooftop photovoltaic system and the static VAR generator is designed.

2. The reactive voltage support method for cooperative operation of a rooftop photovoltaic system and a static VAR generator according to claim 1, characterized in that: The establishment of a distribution network branch power flow model based on second-order cone programming includes the following steps: The relationship between the current, voltage and power of each branch in the distribution network is shown in the following formula: Where U k,t , U j,t They represent the voltages of nodes k and j at time t respectively; They represent the active power and reactive power of branch jk at time t respectively; r jk 、x jk Respectively represent the resistance and reactance of branch jk; I jk,t represents the current of branch jk at time t; S ki,t , S jk,t represents the apparent power of branches ki and jk at time t; z jk represents the reactance of branch jk; S k,t represents the apparent power of node k at time t; Ω B represents the set of all branches; Ω E represents the set of all nodes in the distribution network; σ(k) and δ(k) represent the set of parent nodes and child nodes of node k respectively; T represents the set of all time nodes; By performing phase relaxation on equation (2), we can obtain equation (4) and equation (5): In the formula, They represent the active power and reactive power of branch ki at time t respectively; They represent the active power and reactive power of branch jk at time t respectively; r jk 、x jk Respectively represent the resistance and reactance of branch jk; I jk,t represents the current of branch jk at time t; Respectively represent the active power and reactive power of node k at time t; Ω E represents the set of all nodes in the distribution network; σ(k) and δ(k) represent the set of parent nodes and child nodes of node k respectively; T represents the set of all time nodes; let l jk,t =I jk,t 2 、u k,t =U k,t 2 and u j,t l=U j,t 2 , formula (1) and (3) are equivalent to formula (6) and (7): In the formula, u k,t represents the square of the voltage of node k at time t; l jk,t represents the square of the current of branch jk at time t; u j,t represents the square of the voltage of node j at time t; I jk,t represents the current of branch jk at time t; U k,t represents the voltage of node k at time t; U j,t represents the voltage of node j at time t; r jk 、x jk They represent the resistance and reactance of branch jk respectively; Respectively represent the active power and reactive power of branch jk at time t; Ω B represents the set of all branches; T represents the set of all time nodes; Performing second-order cone relaxation on equation (7) yields equation (8): In the formula, u j,t represents the square of the voltage of node j at time t; l jk,t represents the square of the current in branch jk at time t; Respectively represent the active power and reactive power of branch jk at time t; Ω B represents the set of all branches; T represents the set of all time nodes; Formula (8) is expressed as a standard second-order cone constraint form, as shown in formula (9): In the formula, They represent the active power and reactive power of branch jk at time t respectively; l jk,t represents the square of the current of branch jk at time t; u j,t l represents the square of the voltage of node j at time t; Ω B represents the set of all branches; T represents the set of all time nodes.

3. The reactive voltage support method for cooperative operation of a rooftop photovoltaic system and a static VAR generator according to claim 2, characterized in that: The method of establishing an optimization control model for the operation mode of the rooftop photovoltaic system includes the following steps: It is assumed that some nodes in the distribution network are equipped with rooftop photovoltaic inverters, and the output of each photovoltaic system is constrained by the maximum photovoltaic capacity: In the formula, They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; represents the capacity of the photovoltaic system at node k; Ω PV represents the set of nodes equipped with rooftop photovoltaic systems; Ω E Represents the set of all nodes in the distribution network; T represents the set of all time nodes; The power sources and consumption in the distribution network include photovoltaic systems, generator sets and loads. Equations (4) and (5) are expanded into equations (11) and (12), where the output power of the power generation system is subject to the upper and lower limits of the generator output (13) and (14): In the formula, They represent the active power and reactive power of the power generation system of node k at time t respectively; They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; They represent the active power and reactive power of branch jk at time t respectively; They represent the active power and reactive power of branch ki at time t respectively; r jk 、x jk Respectively represent the resistance and reactance of branch jk; l jk,t represents the square of the current of branch jk at time t; σ(k) and δ(k) represent the set of parent nodes and child nodes of node k respectively; w represents the load expansion rate, w∈(0,1); Respectively represent the active load and reactive load of node k at time t; Ω E Represents the set of all nodes in the distribution network; T represents the set of all time nodes; They represent the upper and lower limits of the active output of the power generation system at node k respectively; Respectively represent the upper and lower limits of reactive power output of the power generation system at node k; Ω GEN represents the set of nodes connected to the generator; The rooftop photovoltaic power generation system installed in the distribution network has two modes. When the load is light, the rooftop photovoltaic system operates in a constant power factor mode, that is, m k =0, which means that the power demand for the whole day is met, as shown in formula (15): In the formula, They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; represents the maximum active power output of the photovoltaic system of node k at time t; θ k represents the power factor angle of the photovoltaic system at node k; tan represents the tangent function; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; m k = represents the operation mode of the photovoltaic system of node k; In extreme scenarios, the rooftop photovoltaic system switches to the grid voltage support control mode, that is, m k =1, as shown in formula (16): In the formula, represents the active power of the photovoltaic system of node k at time t; represents the maximum active power output of the photovoltaic system of node k at time t; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; m k = represents the operation mode of the photovoltaic system of node k; The penalty factor method is used to transform equations (15) and (16), and a positive value M is introduced. The positive value is not infinite. The nonlinear constraints of equations (15) and (16) are linearized, and equations (15) and (16) are relaxed to equations (17) to (19): In the formula, They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; represents the maximum active power output of the photovoltaic system of node k at time t; M represents the introduced positive value; m k = represents the operation mode of the photovoltaic system of node k; Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; θ k represents the power factor angle of the photovoltaic system at node k; tanθ represents the tangent function; The model constraints of the rooftop photovoltaic system installed in some nodes of the distribution network include: voltage constraint (6), voltage constraint (20), current constraint (9), current constraint (21), power flow constraint (11), power flow constraint (12), photovoltaic system constraint (10), photovoltaic system constraint (17), photovoltaic system constraint (18), photovoltaic system constraint (19), photovoltaic system constraint (22), photovoltaic system constraint (23), generator output constraint (13), generator output constraint (14): In the formula, u k,t represents the square of the voltage of node k at time t; U Respectively represent the upper and lower limits of the square of the voltage at node k; Ω E Represents the set of all nodes in the distribution network; T represents the set of all time nodes; l jk,t represents the square of the current of branch jk at time t; Ω B represents the set of all branches; They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; represents the capacity of the photovoltaic system at node k; Ω PV represents the set of nodes equipped with rooftop photovoltaic systems; w represents the load expansion rate, w∈(0,1); η PV Indicates photovoltaic penetration rate; max indicates the maximum value; They represent the active load and reactive load of node k at time t respectively.

4. A reactive voltage support method for cooperative operation of a rooftop photovoltaic system and a static VAR generator according to claim 3, characterized in that: The step of establishing a resource optimization configuration model for a static VAR generator includes the following operations: In extreme scenarios, the rooftop photovoltaic system cannot meet the voltage safety requirements. Static VAR generators are installed at some key nodes of the power grid. The operating constraints of the static VAR generators are: In the formula, They represent the upper and lower limits of the reactive power output of the static VAR generator at node k respectively; represents the reactive power of the static VAR generator at node k at time t; Ω SVG represents the set of nodes to which static VAR generators are installed; and Ω E represents the set of all nodes in the distribution network; T represents the set of all time nodes; The original node power balance equations (11) and (12) are rewritten as: In the formula, represents the active power of the power generation system of node k at time t; They represent the active power and reactive power of the photovoltaic system of node k at time t respectively; They represent the active power and reactive power of branch jk at time t respectively; r jk 、x jk Respectively represent the resistance and reactance of branch jk; l jk,t represents the square of the current in branch jk at time t; They represent the active power and reactive power of branch ki at time t respectively; Respectively represent the active load and reactive load of node k at time t; Ω E Represents the set of all nodes in the distribution network; T represents the set of all time nodes; represents the reactive power of the static VAR generator at node k at time t; σ(k) and δ(k) represent the set of parent nodes and child nodes of node k respectively; w represents the load expansion rate, w∈(0,1); While meeting the voltage stability requirements of the power grid, the total construction cost of the static VAR generator is minimized, and the minimum total cost of installing the static VAR generator is taken as the objective function. The resource optimization configuration model for the static VAR generator is shown in formula (27): (27) In the formula, represents the upper limit of the reactive power output of the static VAR generator at node k; Ω SVG represents the set of nodes equipped with static VAR generators; st(6),(9)-(14),(17)-(26) represents the constraints of equation (27) as equations (6), (9) to (14), (17) to (26); min represents the minimum value.

5. A reactive voltage support method for cooperative operation of a rooftop photovoltaic system and a static VAR generator according to claim 4, characterized in that: The design of the reactive voltage support strategy for the coordinated configuration of the rooftop photovoltaic system and the static VAR generator comprises the following steps: According to the resource optimization configuration model of the static VAR generator, the photovoltaic operation mode optimization control is performed, as shown in formula (28): In the formula, represents the upper limit of the reactive power output of the static VAR generator at node k; Represents the configuration capacity of the static VAR generator of the k-node; Ω SVG represents a set of nodes equipped with static VAR generators; The optimization goal is to minimize the active power loss of the photovoltaic system. The optimization model is shown in formula (29): (29) In the formula, Ω PV represents the set of nodes equipped with rooftop photovoltaic systems; T represents the set of all time nodes; represents the maximum active power output of the photovoltaic system of node k at time t; represents the active power of the photovoltaic system of node k at time t; st(6), (9)-(14), (17)-(26), (28) represents the constraints of equation (29) as equations (6), (9) to (14), (17) to (26), (28); min represents the minimum value.

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