Multi-stage coordinated voltage optimization method and device for power distribution network optical storage system

Abstract

The present application relates to a multi-stage coordinated voltage optimization method for a power distribution network optical storage system, which divides the voltage regulation strategy into three stages: 1) using an analytical method for local reactive power compensation of a photovoltaic inverter; 2) selecting the reactive power output of the photovoltaic inverter as a consistency variable based on filter consistency, and performing distributed reactive power regulation of the photovoltaic inverter; 3) selecting the state of charge variation of the energy storage system as a consistency variable based on filter consistency, and performing distributed active power regulation of the energy storage system; this method can fully utilize the voltage regulation resources of the distributed photovoltaic-energy storage system to control the voltage, while solving the voltage out-of-limit problem, and as much as possible reducing the total active power output of the photovoltaic system due to participation in voltage control, and reducing the overall voltage regulation cost of the energy storage system, and at the same time, this method can well adapt to the normal changes of the information-physical topology of the power distribution system, and has better voltage regulation effect and adaptability compared with the traditional single control mode single-stage voltage regulation strategy.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power distribution network planning, and particularly relates to a multi-stage coordinated voltage optimization method and device for a power distribution network light storage system. BACKGROUND

[0002] At present, the penetration rate of distributed energy represented by photovoltaic is increasing, however, the large-scale integration of distributed photovoltaic at the grid connection point of the distribution network will reduce network loss and increase revenue for the system, but will cause the decline of system voltage stability and short-circuit capacity, greatly increasing the failure rate of system voltage out-of-limit, excessive load flow and other faults. When the voltage is out-of-limit, if the system does not intervene in voltage regulation in time, distributed power may be disconnected from the grid or even voltage collapse accidents may occur. Therefore, the voltage optimization control research to solve the voltage out-of-limit problem caused by high penetration rate photovoltaic grid connection is particularly important for the development of smart distribution network.

[0003] The system voltage regulation means caused by distributed photovoltaic grid connection mainly includes line power voltage regulation method of reactive power regulation and active power regulation, transformer voltage regulation method of regulating on-load transformer tap, and optimal line parameter regulation method of series compensation device. Most reactive power regulation methods follow the four reactive power control strategies suitable for distributed photovoltaic proposed by the German Electrical Engineers Association or its improved strategies, including photovoltaic inverter, static var compensator (generator) and shunt capacitor switching reactive power regulation, but face problems such as high investment cost of static var compensator (generator), inability of capacitor bank to be frequently switched, and high degree of equipment wear caused by voltage regulation means such as on-load transformer tap and voltage regulator. Active power control voltage means includes photovoltaic active power reduction, energy storage peak shaving, etc., but photovoltaic active power reduction reduces user power generation income as the price of voltage regulation, does not improve the actual power grid photovoltaic consumption capacity, and brings about unsatisfactory power grid benefits. Using photovoltaic inverter for reactive power regulation has fast response speed and low voltage regulation cost; active power control of energy storage system is another important means of voltage regulation, which has the advantages of unlimited voltage regulation times and fast response speed. Therefore, considering using photovoltaic storage combined voltage regulation is the first choice to solve the photovoltaic grid connection voltage out-of-limit problem at present.

[0004] In addition, combined with different communication control methods, the current voltage control strategy based on photovoltaic inverters and energy storage can be divided into centralized, distributed and local control. Centralized control relies heavily on centralized control master station and expensive measurement, communication and monitoring terminal network, and requires transmission of a large amount of data on the network and high-density calculation, so the robustness and reliability of the information communication network of the system are crucial to the safe and reliable operation of the entire integrated distribution network; the local control method is generally applied to low-voltage distribution networks, and through real-time local measurement and calculation of local measurement devices, the current node is adjusted and controlled, which has the advantages of small calculation amount and is not affected by network performance, but cannot realize the coordination and optimal control between global devices; distributed control is achieved through the coordinated control of each sub-link or subsystem, and each sub-controller only transmits data and exchanges information with adjacent controllers, so it has less dependence on the communication network performance of the entire system. Some scholars have converted the nonlinear reactive power voltage regulation model into a convex quadratic optimization problem with linear constraints, and used heuristic algorithms to optimize the minimum reactive power compensation of capacitor and other reactive power regulation sources under distributed control, so that the total expected voltage fluctuation of the network is minimized. Some scholars have considered the transformer tap, switched capacitor and photovoltaic inverter voltage regulation means, established a relaxation-clustering dynamic reactive power optimization model based on probabilistic power flow, and carried out distributed reactive voltage control on the day-ahead and real-time hybrid time scale; some scholars have obtained the P-V curve by using the quadratic interpolation method to determine the DC voltage reference value of the inverter, and have improved the consensus algorithm by using Chebyshev filtering for photovoltaic distributed control.

[0005] Through the comprehensive study of previous research, it is found that although the existing control strategy can alleviate the overvoltage problem caused by high penetration rate of photovoltaic, the reactive power compensation control process of photovoltaic system is complex and the active reduction cost is high, and the control optimization of energy storage system is not strong; in addition, a single control method cannot fully utilize the regulation capacity of the voltage regulation equipment, and the communication control robustness is lacking. In view of this, based on the characteristics of distributed control of filter consensus algorithm, a local-distributed real-time voltage control strategy for distribution network photovoltaic- energy storage system considering information-physical coupling is proposed, and the voltage regulation strategy is divided into three stages: 1) local reactive power compensation of photovoltaic inverter; 2) distributed reactive power regulation of photovoltaic inverter based on filter consensus; 3) distributed active power regulation of energy storage system based on filter consensus. The strategy can fully utilize the voltage regulation resources of distributed photovoltaic- energy storage system for voltage control, reduce the total amount of photovoltaic system active power output as much as possible while solving the voltage over-limit problem, and reduce the overall voltage regulation cost of the energy storage system, and the strategy can well adapt to the normal changes of the information-physical topology of the distribution system, and has better voltage regulation effect and adaptability compared with the traditional single control method single-stage voltage regulation strategy. SUMMARY

[0006] The power distribution network light storage system multi-stage coordinated voltage optimization method of the application firstly utilizes an analytical method to construct a light storage system coordinated voltage regulation first stage, which can improve the overall voltage regulation response speed of the system and reduce the voltage regulation cost of single distributed control; if the voltage regulation process has not ended, then on this basis, the voltage regulation second stage is entered: the reactive power output of the photovoltaic inverter is selected as a consistency variable, and the photovoltaic inverter distributed reactive power regulation is carried out based on the consistency algorithm improved by Chebyshev filtering; if the reactive power resources of the whole network photovoltaic inverter are exhausted and the voltage regulation process has not ended, then the voltage regulation third stage is entered: the state of charge variation of the energy storage is selected as a consistency variable, and the energy storage system distributed active regulation is carried out based on the consistency algorithm improved by Chebyshev filtering. The consistency iterative algorithm improved by Chebyshev filtering effectively improves the response speed of the distributed control voltage regulation, and the control mode of local compensation first and then distributed regulation and the voltage regulation equipment scheduling sequence of the photovoltaic inverter first and then the energy storage system effectively reduce the real-time voltage optimization cost of the active power distribution network, expand the controllable range of real-time voltage deviation regulation, and improve the utilization rate of the whole network adjustable voltage regulation resources.

[0007] The technical problem of the application is solved by adopting the following technical scheme:

[0008] The power distribution network light storage system multi-stage coordinated voltage optimization method comprises the following steps:

[0009] When it is monitored that the line voltage is out of limit, it is confirmed whether the local light storage system controller receives the distributed regulation instruction from other light storage system controllers, if yes, the second stage light storage coordinated voltage regulation is carried out, and if no, the first stage light storage coordinated voltage regulation is carried out;

[0010] It is detected whether the line voltage is restored to normal, if yes, the voltage optimization process is ended, and if no, the local light storage system controller sends the distributed control instruction of the photovoltaic inverter reactive power regulation to the adjacent light storage system controller, the instruction is diffused to the whole network light storage system controller from the adjacent light storage system controller, and the second stage light storage coordinated voltage regulation is carried out;

[0011] It is detected whether the line voltage is restored to normal, if yes, the voltage optimization process is ended, and if no, it is confirmed whether the maximum adjustable reactive power capacity is exhausted, if no, the second stage light storage coordinated voltage regulation is continuously carried out, if yes, the local light storage system controller sends the distributed control instruction of the energy storage active regulation to the adjacent light storage system controller, the instruction is diffused to the whole network light storage system controller from the adjacent light storage system controller, and the third stage light storage coordinated voltage regulation is carried out;

[0012] It is detected whether the line voltage is restored to normal, if yes, the voltage optimization process is ended, and if the voltage is still out of limit, it is confirmed whether the energy storage state of charge threshold is reached, if no, the third stage light storage coordinated voltage regulation is continuously carried out, and if yes, the voltage optimization process is ended.

[0013] Further, the method for the second stage of photovoltaic storage coordinated voltage regulation is:

[0014] The reactive power output of each photovoltaic inverter is initialized as a consistency state variable, and a voltage regulation step is set, and when the initial state variable does not satisfy the constraint condition, the voltage regulation step is changed to re-initialize, each photovoltaic inverter exchanges the iteration of the current state variable with each other according to the controller communication network, the consistency iteration of the reactive power output of the photovoltaic inverter is performed based on Chebyshev filter consistency, and finally the consistency state variable converging to a common stable value is obtained.

[0015] Further, the method for the third stage of photovoltaic storage coordinated voltage regulation is:

[0016] The state of charge change of each energy storage is initialized as a consistency state variable, and a voltage regulation step is set, and when the initial state variable does not satisfy the constraint condition, the voltage regulation step is changed to re-initialize, each energy storage exchanges the iteration of the current state variable with each other according to the controller communication network, the consistency iteration of the state of charge change of the energy storage is performed based on Chebyshev filter consistency, and finally the consistency state variable converging to a common stable value is obtained.

[0017] Further, in the second stage of photovoltaic storage coordinated voltage regulation, when the consistency iteration of the reactive power output of the photovoltaic inverter is performed based on Chebyshev filter consistency, the k-order Chebyshev polynomial introduced is:

[0018]

[0019] The recursive form is:

[0020]

[0021] The filter polynomial is constructed as:

[0022]

[0023] Wherein, τ is an acceleration factor; λ2 is the maximum eigenvalue of the modulus of the system state transition matrix W and |λ2|<1; W represents a state transition matrix composed of state transition weights of each communication link;

[0024] The consistency algorithm for filtering acceleration can be expressed as

[0025]

[0026]

[0027] Wherein, then X k Indicates the system state variable column vector after k iterations.

[0028] Further, the first-stage light-storage coordination voltage regulation method is: obtaining the current maximum adjustable reactive power capacity, and performing reactive power compensation according to the analytical method.

[0029] Further, the constraint conditions include that the output of the photovoltaic inverter is constrained by the inverter capacity, the power factor, and the power flow.

[0030] The power distribution network light-storage system multi-stage coordination voltage optimization device comprises:

[0031] The first-stage light-storage coordination voltage regulation module is configured to, when it is monitored that the line voltage is out of limit,

[0032] The second-stage light-storage coordination voltage regulation module is configured to detect whether the line voltage is restored to normal, and if so, end the voltage optimization process; if not, the local light-storage system controller sends the distributed control instruction of the photovoltaic inverter reactive power regulation to the adjacent light-storage system controller, and the instruction is diffused to the light-storage system controllers in the whole network, and the second-stage light-storage coordination voltage regulation is performed.

[0033] The second-stage light-storage coordination voltage regulation module is configured to detect whether the line voltage is restored to normal, and if so, end the voltage optimization process; if not, the local light-storage system controller sends the distributed control instruction of the photovoltaic inverter reactive power regulation to the adjacent light-storage system controller, and the instruction is diffused to the light-storage system controllers in the whole network, and the second-stage light-storage coordination voltage regulation is performed.

[0034] The third-stage light-storage coordination voltage regulation module is configured to detect whether the line voltage is restored to normal, and if so, end the voltage optimization process; if not, it is confirmed whether the maximum adjustable reactive power capacity is exhausted, and if not, the second-stage light-storage coordination voltage regulation is continued; if so, the local light-storage system controller sends the distributed control instruction of the energy storage active power regulation to the adjacent light-storage system controller, and the instruction is diffused to the light-storage system controllers in the whole network, and the third-stage light-storage coordination voltage regulation is performed.

[0035] The final voltage optimization process judgment module is configured to detect whether the line voltage is restored to normal, and if so, end the voltage optimization process; if not, it is confirmed whether the energy storage state of charge threshold is reached, and if not, the third-stage light-storage coordination voltage regulation is continued; if so, the voltage optimization process is ended.

[0036] An electronic device comprises at least one processor and a memory connected with the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the power distribution network light-storage system multi-stage coordination voltage optimization method.

[0037] A computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the power distribution network light-storage system multi-stage coordination voltage optimization method.

[0038] The advantages and positive effects of the present application are:

[0039] The multi-stage coordinated voltage optimization method of the power distribution network optical storage system of the present application divides the voltage regulation strategy into three stages: 1) using an analytical method to perform local reactive power compensation of the photovoltaic inverter; 2) selecting the reactive power output of the photovoltaic inverter as a consistency variable based on filter consistency, and performing distributed reactive power regulation of the photovoltaic inverter; 3) selecting the state of charge variation of the energy storage system as a consistency variable based on filter consistency, and performing distributed active power regulation of the energy storage system; this strategy can fully utilize the voltage regulation resources of the distributed photovoltaic- energy storage system to perform voltage control, solve the voltage out-of-limit problem, and as much as possible reduce the total active power output of the photovoltaic system due to participation in voltage control, and reduce the overall voltage regulation cost of the energy storage system. At the same time, this strategy can well adapt to the normal changes of the information and physical topology of the power distribution system, and has better voltage regulation effect and adaptability compared with the traditional single control mode single-stage voltage regulation strategy. BRIEF DESCRIPTION OF DRAWINGS

[0040] The technical solutions of the present application will be described in further detail below in combination with the drawings and examples, but it should be understood that these drawings are designed only for explanatory purposes, and therefore do not limit the scope of the present application. In addition, unless specifically indicated, these drawings are only intended to conceptually illustrate the structural configurations described herein, and are not necessarily drawn to scale.

[0041] Figure 1 A schematic diagram of a radial line of a power distribution network with distributed power supply access is provided for the embodiments of the present application;

[0042] Figure 2 A schematic diagram of the output power relationship and constraints of the photovoltaic inverter is provided for the embodiments of the present application; wherein, Figure 2 A, B, C, and D respectively represent different operating state points of the photovoltaic inverter; P pv , Q pv respectively represent the active and reactive power of the photovoltaic inverter; P A , P B respectively represent the active power values when the photovoltaic inverter operates at operating points A and B; Q A , Q B respectively represent the reactive power values when the photovoltaic inverter operates at operating points A and B. DETAILED DESCRIPTION

[0043] First, it should be noted that the following will be specifically described in an exemplary manner the specific structure, features and advantages of the present application, however, all the description is only used for illustration, and should not be understood as forming any limitation on the present application. In addition, any single technical feature described or implied in the embodiments mentioned herein, or any single technical feature shown or implied in the drawings, can still continue to be combined or deleted between these technical features (or their equivalents), so as to obtain more other embodiments of the present application which can not be directly mentioned herein.

[0044] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0045] As Figure 1 The power distribution network photovoltaic energy storage system multi-stage coordinated voltage optimization method based on the filter consistency algorithm improvement provided by the embodiment firstly constructs the photovoltaic energy storage system coordinated voltage regulation first stage by using the analytical method, which can improve the overall voltage regulation response speed of the system on the one hand, and reduce the voltage regulation cost of single distributed control on the other hand. If the voltage regulation process has not ended, the voltage regulation second stage is entered on this basis: the reactive power output of the photovoltaic inverter is selected as the consistency variable, and the photovoltaic inverter distributed reactive power regulation is carried out based on the Chebyshev filter improved consistency algorithm. If the voltage regulation process still has not ended until the photovoltaic inverter reactive power resource of the whole network is exhausted, the voltage regulation third stage is entered: the energy storage system state of charge change is selected as the consistency variable, and the energy storage system distributed active regulation is carried out based on the Chebyshev filter improved consistency algorithm. The Chebyshev filter improved consistency iterative algorithm effectively improves the speed of distributed control voltage regulation response, and the control mode of first local compensation and then distributed regulation and the voltage regulation equipment scheduling sequence of first photovoltaic inverter and then energy storage system effectively reduce the real-time voltage optimization cost of the active power distribution network, expand the controllable range of real-time voltage deviation regulation, and improve the utilization rate of the whole network adjustable voltage regulation resource.

[0046] The specific steps of the power distribution network photovoltaic energy storage system multi-stage coordinated voltage optimization method of the embodiment are as follows:

[0047] In the photovoltaic energy storage coordinated voltage regulation first stage, the power distribution network voltage sensor monitors that the line has a voltage out-of-limit problem, first sends the photovoltaic inverter local reactive power compensation voltage regulation instruction to the local photovoltaic energy storage system controller, the local photovoltaic energy storage system controller confirms whether the distributed regulation instruction from other photovoltaic energy storage system controllers is received, if yes, the distributed regulation is carried out, otherwise, the current maximum adjustable reactive power capacity is calculated immediately, and the reactive power compensation is executed according to the analytical method. During the voltage regulation process, the voltage regulation target value and the voltage boundary have a margin, and the photovoltaic inverter output is subject to the inverter capacity constraint, the power factor constraint and the power flow constraint.

[0048] In Figure 1The simplified distribution network radial line with distributed power access is shown as an example, and U i is the voltage amplitude of node i; P i , Q i , R i , X i are the active power, reactive power, equivalent resistance and equivalent reactance between node i-1 and node i, respectively; P DG,i , Q DG,i represent the active power and reactive power of the grid-connected distributed power of node i; P L,i , Q L,i represent the active power and reactive power of the load of node i; it is assumed that the reference voltage of the line head bus U0 remains unchanged, and the initial voltage of node i is U i,0 When the active and reactive power of the distributed power of a node k on the line is changed and the power change is represented by ΔP DG,k , ΔQ DG,k , the voltage of node i will change from the initial voltage U i,0 to U i,1 , and satisfies:

[0049]

[0050] Equation (1) represents the value of U i,1 when node k is upstream of node i (k≤i) and node k is downstream of node i (k>i), then when the line voltage exceeds the critical voltage, the local voltage controller immediately calculates the maximum adjustable reactive power capacity and performs reactive power compensation. According to equation (1), the reactive power compensation amount of the photovoltaic inverter at node i is

[0051]

[0052] Where, ΔQ pv, i,t is the reactive power compensation amount of the photovoltaic inverter at node i at time t; is the system voltage boundary; ε is the voltage regulation margin, and εU lim is the voltage regulation target value;

[0053] In this process, the constraints are as follows:

[0054] Maximum adjustable reactive power capacity constraint

[0055]

[0056]

[0057]

[0058]

[0059] in, The maximum adjustable reactive power capacity of the photovoltaic inverter installed at node i at time t, considering only capacity constraints; The maximum adjustable reactive power capacity of the photovoltaic inverter installed at node i at time t, considering only the power factor constraint; To comprehensively consider the inverter capacity constraint and power factor constraint, the maximum adjustable reactive power capacity; P pv,i,t Q pv,i,t S represents the active and reactive power outputs of the photovoltaic system installed at node i at time t; pv,i Install the rated capacity of the photovoltaic inverter at node i; ρ min γ is the minimum power factor of the photovoltaic inverter; γ is the reactive power adjustability coefficient, ranging from 0 to 1; Figure 2 For example, when the active power of the photovoltaic inverter is P A At that time, the inverter is only constrained by its capacity and is at operating point A, Q. A This is the maximum adjustable reactive power capacity at this time; when the active power of the photovoltaic inverter is P B At this time, the inverter also needs to consider the power factor limitation and operate at point B, Q. B This is the maximum adjustable reactive power capacity at this time; when the photovoltaic active power is 0, the operating point is in the OD segment, and the inverter enters the fixed reactive power operating mode. At this time, the maximum adjustable reactive power capacity is γS. pv,i ;

[0060] Current constraints

[0061]

[0062]

[0063] Among them: U i,t U j,t Let G be the voltage amplitudes at nodes i and j during time period t; ij B ij These represent the branch conductance and branch susceptance between nodes i and j, respectively; θ ij,t P represents the voltage phase angle difference between nodes i and j during time period t; i,t Q i,t These represent the injected active power and reactive power at node i during time period t, respectively; P PV,i,t Q PV,i,t These represent the active and reactive power output of the photovoltaic system at node i during time period t; P ES,i,t P represents the active power output of energy storage at node i during time period t; L,i,t Q L,i,t Let be the active power and reactive power of the load at node i during time period t, respectively; and Ω be the set of nodes in the distribution network.

[0064] If the line voltage returns to normal, the voltage optimization process ends; otherwise, it proceeds to the second stage of photovoltaic-storage coordinated voltage regulation. The local photovoltaic-storage system controller sends distributed control commands for reactive power regulation of photovoltaic inverters to adjacent photovoltaic-storage system controllers, thereby spreading the commands to all photovoltaic-storage system controllers in the network.

[0065] In the second stage of photovoltaic-storage coordinated voltage regulation, the reactive power output rate of each photovoltaic inverter is initialized as a consistency variable, and a certain voltage regulation step size is set. When the initial state variable does not meet the constraints, the voltage regulation step size is changed and re-initialized. Each photovoltaic inverter in the system exchanges and iterates its current state variable with each other according to the controller communication network. The consistency iteration of the reactive power output rate of the photovoltaic inverter is carried out based on Chebyshev filter consistency, and finally a consistent state variable that converges to a common stable value is obtained.

[0066] Let a directed graph G = {V, E} represent the communication network topology of distributed voltage regulation, where V = {v1, v2, ..., v...} N} represents the set of all communication nodes; E = {e ij |e ij = (i,j), i,j∈V} represents the set of all communication links; e ij This indicates that there is a communication link between node i and node j. To ensure the reliability of distributed control, the communication mode in this embodiment is full-duplex communication, i.e., e ij =e ji Distributed control based on consensus algorithms requires communication link e ij Assign state transition weights w ij Let x be the control state variable of node i in the k-th iteration of the system. i,k The consensus algorithm is then expressed as:

[0067]

[0068] Among them, V i w represents the set of all nodes that have communication links with node i; ij The possible values ​​are:

[0069]

[0070] Among them, ID i This represents the in-degree of communication node i.

[0071] Let N be the number of controllers in the entire system, then X k =[x i,k ] N×1 W represents the column vector of system state variables after k iterations; W = [w ij ] N×NThe state transition matrix composed of each communication link state transition weight, the matrix expression of the consensus algorithm is:

[0072] X k+1 = W·X k k = 1, 2, …, n (11)

[0073] The k-order (k≥0) Chebyshev polynomial is introduced, which is expressed as:

[0074]

[0075] The recursive form is:

[0076]

[0077] The filter polynomial is constructed by using formula (11) and (12):

[0078]

[0079] Where τ is the acceleration factor; λ2 is the modulus of the system state transition matrix W, and |λ2|<1;

[0080] The consensus algorithm of filter acceleration according to formula (13) and (14) can be expressed as:

[0081]

[0082]

[0083] Considering the difference of the capacity of each photovoltaic inverter, the reactive power output of each photovoltaic inverter is taken as the consensus variable, which is expressed as:

[0084]

[0085] Where Q pv,i,t represents the reactive power of photovoltaic inverter at node i at time t; From formula (5), we get:

[0086] When the voltage of photovoltaic grid-connected point i at time t is out of limit, the initial state vector X1

[0087]

[0088] Where μ is the adjustment step; V is the set of all photovoltaic storage system installation nodes, which is also the set of nodes where the controller in the information system is located, and the number of nodes is N.

[0089] The photovoltaic inverters in the system exchange iteration of their current state variables with each other according to the controller communication network, perform consistency iteration of the reactive power output of the photovoltaic inverters based on formulas (15)-(16), and finally obtain X k = [x i,k ] N×1 = [r pv,i,t,k ] N×1 . The reactive power output value of each inverter at time t in this stage is

[0090]

[0091] When the consistency iteration is started, if |x i,1 |>1 in formula (17), the step size μ should be appropriately reduced so that the reactive power output meets the constraint.

[0092] In addition, the process meets the constraints of the power flow constraints and the power factor constraints of formulas (7)-(8):

[0093]

[0094] wherein, is the power factor of the photovoltaic inverter of node i at time t.

[0095] It is detected whether the line voltage is restored to normal, and if so, the voltage optimization process is ended; if the voltage is still out of limit, it is confirmed whether the maximum adjustable reactive power capacity is exhausted, and if not, the second stage of photovoltaic and energy storage coordinated voltage regulation is returned to continue iteration; if so, the third stage of photovoltaic and energy storage coordinated voltage regulation is entered, and the local controller sends a distributed control instruction of energy storage active regulation to the adjacent voltage controller, and the instruction is diffused to the whole network voltage controller.

[0096] In the third stage of photovoltaic and energy storage coordinated voltage regulation, the state of charge change amount of each energy storage is initialized as a consistency variable, and a certain voltage regulation step size is set, and the voltage regulation step size is changed to reinitialize when the initial state variable does not meet the constraint. The energy storages in the system exchange iteration of their current state variables with each other according to the controller communication network, perform consistency iteration of the state of charge change amount of the energy storages based on Chebyshev filter consistency, and finally obtain a consistency state variable converging to a common stable value.

[0097] Considering the difference of the capacities of the energy storage batteries, the state of charge change amount of the energy storage is selected as the consistency variable, and is expressed as:

[0098] ΔS oc,i,t = P es,i,t ·Δt / S es,i (21)

[0099] wherein, P es,i,tis the active power of the energy storage at node i at time t; Δt is the energy storage adjustment charge and discharge time; S es,i is the installed energy storage capacity at node i.

[0100] When the voltage of the photovoltaic grid-connected point i at time t is out of limit, set the initial state vector X1 of the state of charge change of each energy storage;

[0101]

[0102] Based on equations (15) and (16), the consistency iteration of the state of charge change of each energy storage cell is carried out, and finally X k i,k N×1 oc,i,t,k N×1 The active output value of each energy storage at time t in this stage is:

[0103] P es,i,t,k oc,i,t,k · S es,i / Δt (23)

[0104] The process follows the power flow constraints of equations (7) and (8) and the energy storage charge constraints:

[0105]

[0106] -P es,i ≤ P es,i,t,k ≤ P es,i (25)

[0107] S oc,i,t,k is the state of charge of the energy storage at node i at time t after active adjustment; S oc are the upper and lower limits of the state of charge of the energy storage, respectively; P es,i,t,k is the active power command value of the energy storage at node i at time t; P es,i is the rated active power value of the energy storage at node i.

[0108] The active output value of each energy storage at this time is calculated, and it is detected whether the line voltage is restored to normal. If it is normal, the voltage optimization process is ended. If the voltage is still out of limit, it is confirmed whether the critical state of charge of the energy storage is reached. If not, return to the third stage of photovoltaic and energy storage coordinated voltage regulation for iteration. Otherwise, the voltage optimization process is ended, and the voltage regulation process needs to consider the active power output constraint and the state of charge constraint of the energy storage.

[0109] Embodiment 2

[0110] Based on the same inventive concept, the embodiment of the present application also provides a multi-stage coordinated voltage optimization device for a power distribution network photovoltaic and energy storage system, which comprises: ​​​​​

[0111] The first-stage light storage coordination voltage regulation module is configured to perform first-stage light storage coordination voltage regulation when it is monitored that the line voltage is out of limit,

[0112] The first-stage light storage coordination voltage regulation module is configured to perform first-stage light storage coordination voltage regulation when it is monitored that the line voltage is out of limit,

[0113] The second-stage light storage coordination voltage regulation module is configured to detect whether the line voltage is back to normal, and if yes, end the voltage optimization process; if not, the local light storage system controller sends a distributed control instruction of photovoltaic inverter reactive power regulation to the adjacent light storage system controller, and the instruction is diffused to all the light storage system controllers in the network, and the second-stage light storage coordination voltage regulation is performed.

[0114] The third-stage light storage coordination voltage regulation module is configured to detect whether the line voltage is back to normal, and if yes, end the voltage optimization process; if not, it is confirmed whether the maximum adjustable reactive power capacity is exhausted, if not, the second-stage light storage coordination voltage regulation is continued; if yes, the local light storage system controller sends a distributed control instruction of energy storage active power regulation to the adjacent light storage system controller, and the instruction is diffused to all the light storage system controllers in the network, and the third-stage light storage coordination voltage regulation is performed.

[0115] The final voltage optimization process judgment module is configured to detect whether the line voltage is back to normal, and if yes, end the voltage optimization process; if not, it is confirmed whether the energy storage state of charge threshold is reached, if not, the third-stage light storage coordination voltage regulation is continued, if yes, the voltage optimization process is ended.

[0116] Based on the same inventive concept, the embodiment of the present application further provides an electronic device, comprising: at least one processor; and a memory in communication connection with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the power distribution network light storage system multi-stage coordination voltage optimization method described above; it should be noted that the electronic device can include but is not limited to a processing unit and a storage unit; those skilled in the art can understand that the electronic device including the processing unit and the storage unit does not constitute a limitation to the computing device, and can include more components, or combine certain components, or different components, for example, the electronic device can also include an input / output device, a network access device, a bus, etc.

[0117] A computer readable storage medium, storing a computer program, the computer program being executed by a processor to implement the power distribution network optical storage system multi-stage coordinated voltage optimization method described above; it should be noted that the readable storage medium may, for example, be, but is not limited to, an electric, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination of the above; the program contained on the readable medium can be transmitted by any suitable medium, including, but not limited to, wireless, wired, optical cable, RF, etc., or any suitable combination of the above. For example, the program code for performing the operations of the present application can be written in any combination of one or more programming languages, including an object-oriented programming language, such as Java, C++, etc., and a conventional procedural programming language, such as C language or similar programming languages. The program code can be executed entirely on a user computing device, partially on a user device, as a separate software package, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, through the Internet by connecting to an Internet service provider).

[0118] The above embodiments have been described in detail, but the above content is only the preferred embodiments of the present application, and cannot be considered as limiting the scope of the present application. Any equivalent changes and improvements made in the scope of the present application should still belong to the scope of the present application.

Claims

1. A multi-stage coordinated voltage optimization method for photovoltaic-storage systems in distribution networks, characterized in that, Includes the following steps: When a voltage over-limit is detected on the line, it is confirmed whether the local photovoltaic-storage system controller has received a distributed regulation command from other photovoltaic-storage system controllers. If so, the second stage of photovoltaic-storage coordinated voltage regulation is carried out; otherwise, the first stage of photovoltaic-storage coordinated voltage regulation is carried out. The first stage of photovoltaic-storage coordinated voltage regulation is local reactive power compensation of the photovoltaic inverter. The system checks whether the line voltage has returned to normal. If it is normal, the voltage optimization process ends. Otherwise, the local photovoltaic-storage system controller sends a distributed control command for reactive power regulation of the photovoltaic inverter to the adjacent photovoltaic-storage system controller, and then spreads the command to the entire grid photovoltaic-storage system controller, and performs the second stage of photovoltaic-storage coordinated voltage regulation. If the line voltage returns to normal, the voltage optimization process ends; otherwise, it is confirmed whether the maximum adjustable reactive power capacity has been exhausted. If it has not been exhausted, the second stage of photovoltaic-storage coordinated voltage regulation continues; if it has been exhausted, the local photovoltaic-storage system controller sends a distributed control command for energy storage active power regulation to the adjacent photovoltaic-storage system controller, and thereby spreads the command to the entire network photovoltaic-storage system controller, and performs the third stage of photovoltaic-storage coordinated voltage regulation. Check if the line voltage has returned to normal. If it is normal, end the voltage optimization process. If the voltage is still out of limit, check if the energy storage charge state threshold has been reached. If not, continue with the third stage of photovoltaic-energy storage coordinated voltage regulation. Otherwise, end the voltage optimization process. The second-stage method for coordinated voltage regulation of photovoltaic and energy storage is as follows: The reactive power output rate of each photovoltaic inverter is initialized as a consistent state variable, and the voltage regulation step size is set. When the initial state variable does not meet the constraints, the voltage regulation step size is changed and re-initialized. Each photovoltaic inverter exchanges and iterates its current state variable with each other according to the controller communication network. The consistency iteration of the reactive power output rate of the photovoltaic inverter is carried out based on Chebyshev filter consistency, and finally a consistent state variable that converges to a common stable value is obtained. The third-stage method for coordinated voltage regulation of photovoltaic and energy storage is as follows: The state of charge change of each energy storage is initialized as a consistent state variable, and the voltage regulation step size is set. When the initial state variable does not meet the constraints, the voltage regulation step size is changed and re-initialized. Each energy storage exchanges and iterates its current state variable with each other according to the controller communication network. The consistency iteration of the state of charge change of the energy storage is carried out based on Chebyshev filter consistency, and finally a consistent state variable that converges to a common stable value is obtained. In the second stage of photovoltaic-storage coordinated voltage regulation, when iterating the consistency of the reactive power output rate of the photovoltaic inverter based on the Chebyshev filter consistency, the introduced k-th order Chebyshev polynomial is: ； Its recursive form is: ； Construct the filter polynomial: ； in, As an acceleration factor; The system state transition matrix The modulus of the largest eigenvalue is not 1 and ; W This represents the state transition matrix composed of the state transition weights of each communication link; The consensus algorithm for filtering acceleration can be expressed as follows: ； ； Among them, then X k express k The system state variable column vector after the iteration.

2. The multi-stage coordinated voltage optimization method for a photovoltaic-storage system in a distribution network according to claim 1, characterized in that: The first-stage method for coordinated voltage regulation of photovoltaic and energy storage is to obtain the current maximum adjustable reactive power capacity and perform reactive power compensation based on the analytical method.

3. The multi-stage coordinated voltage optimization method for a photovoltaic-storage system in a distribution network according to claim 1, characterized in that: The constraints include inverter output being constrained by inverter capacity, power factor, and power flow.

4. A multi-stage coordinated voltage optimization device for a distribution network photovoltaic-storage system, comprising performing multi-stage coordinated voltage optimization of a distribution network photovoltaic-storage system using the method described in any one of claims 1-3, characterized in that, include: The first-stage photovoltaic-storage coordinated voltage regulation module is used to confirm whether the local photovoltaic-storage system controller has received a distributed regulation command from other photovoltaic-storage system controllers when the voltage of the line exceeds the limit. If yes, the second-stage photovoltaic-storage coordinated voltage regulation is performed; otherwise, the first-stage photovoltaic-storage coordinated voltage regulation is performed. The second-stage photovoltaic-storage coordinated voltage regulation module is used to detect whether the line voltage has returned to normal. If it is normal, the voltage optimization process ends; otherwise, the local photovoltaic-storage system controller sends a distributed control command for reactive power regulation of the photovoltaic inverter to the adjacent photovoltaic-storage system controller, and then spreads the command to the entire grid photovoltaic-storage system controller, and performs the second-stage photovoltaic-storage coordinated voltage regulation. The third-stage photovoltaic-storage coordinated voltage regulation module is used to detect whether the line voltage has returned to normal. If it is normal, the voltage optimization process ends; otherwise, it checks whether the maximum adjustable reactive power capacity has been exhausted. If it has not been exhausted, the second-stage photovoltaic-storage coordinated voltage regulation continues; if it has been exhausted, the local photovoltaic-storage system controller sends a distributed control command for energy storage active power regulation to the adjacent photovoltaic-storage system controller, and thereby spreads the command to the entire network photovoltaic-storage system controller, and performs the third-stage photovoltaic-storage coordinated voltage regulation. The final voltage optimization process judgment module is used to detect whether the line voltage has returned to normal. If it is normal, the voltage optimization process ends. If the voltage still exceeds the limit, check whether the energy storage state of charge has been reached. If not, continue with the third stage of photovoltaic-energy storage coordinated voltage regulation. Otherwise, the voltage optimization process ends.

5. An electronic device, characterized in that, include: At least one processor; And a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 3.

6. A computer-readable storage medium storing a computer program that, when executed by a processor, implements the method of any one of claims 1 to 3.

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