System and method for regulating and controlling operation of distributed photovoltaic access power distribution network

Abstract

The invention belongs to the field of power grid regulation and control, and particularly relates to a distributed photovoltaic access power distribution network operation regulation and control system and method.The system is composed of a data acquisition module, a data transmission module, a data processing module and a control module; the data acquisition module acquires data of the monitor in real time, the data transmission module transmits the data of the data acquisition module to the data processing module in a wired or wireless mode, the data processing module processes the data through a logistic regression model, and whether the power distribution network has a fault or not is judged according to a processing result. And meanwhile, the control module performs hierarchical control on the power distribution network by adopting a chaos theory, and the hierarchy of the control module is divided into a local hierarchy and a centralized hierarchy, so that different operation requirements in the power distribution network are met. According to the invention, the equipment is monitored, the operation state of the distributed photovoltaic access power distribution network is identified, and characteristics and operation requirements of different components in the power distribution network are adapted.

Description

Technical Field

[0001] The present invention belongs to the field of power grid control, and specifically relates to a control system and method for distributed photovoltaic access to a distribution network. Background Art

[0002] With the development of economy and society, the demand for energy is growing, and the development and widespread use of new energy has become a hot spot in the development of power grid energy. For example, clean energy such as distributed photovoltaics on the distribution network side helps build a new power system from the distribution network side. In addition to the characteristics of less pollution, high reliability and energy utilization efficiency, and flexible installation locations, the flexible and decentralized location of distributed power sources also adapts well to the decentralized power demand and resource distribution. It is one of the important measures to solve the contradiction between economic development, energy production and consumption, and environmental protection. At present, the mainstream distributed photovoltaic access distribution network control technology in the market mainly relies on a centralized monitoring and management system. The system collects data from each distributed photovoltaic site through a central controller for unified scheduling and optimization.

[0003] However, this centralized control scheme has the following significant disadvantages: heavy communication burden: as the number of distributed photovoltaic sites increases, the amount of data that the central controller needs to process increases sharply, resulting in communication delays and bandwidth bottlenecks; poor system flexibility: the centralized system is highly dependent on a single control point. Once the central controller fails, the entire control system will be affected, reducing the reliability and stability of the system; slow response speed: because data needs to be transmitted and processed between different levels, the system's response speed to emergencies is limited, making it difficult to achieve real-time control; uneven resource allocation: centralized control often finds it difficult to perform refined management and optimize resource allocation based on the actual conditions of each distributed photovoltaic site.

[0004] Therefore, the present invention provides a control system and method for the operation of distributed photovoltaic access to a power distribution network, which achieves more efficient, flexible and reliable control through a distributed intelligent control strategy. Summary of the invention

[0005] The present invention provides a control system and method for distributed photovoltaic access to a power distribution network, which are used to solve the technical problems of heavy communication burden, poor system flexibility, slow response speed and uneven resource distribution of existing centralized control solutions.

[0006] In order to achieve the above-mentioned purpose, the technical scheme adopted by the present invention is as follows: a control system for the operation of distributed photovoltaic access distribution network, composed of a data acquisition module, a data transmission module, a data processing module and a control module. The data acquisition module collects the monitor data in real time through the monitor arranged at the distribution network monitoring node. The data transmission module transmits the data of the data acquisition module to the data processing module by wired or wireless means. The data processing module processes the data through a logistic regression model and determines whether the distribution network has a fault according to the processing results. At the same time, the control module uses chaos theory to perform hierarchical control on the distribution network, and divides the control module level into local level and centralized level, so as to adapt to different operation requirements in the distribution network.

[0007] Furthermore, the data collected by the data acquisition module from the monitor includes active power, voltage deviation and frequency fluctuation, and the data processing module extracts feature quantities from the data as training samples and processes them using a logistic regression model.

[0008] Furthermore, the process of processing data by the logistic regression model is:

[0009] A method for controlling a distributed photovoltaic system connected to a distribution network includes the following steps:

[0010] (1) Data acquisition: The data acquisition module collects the monitor data in real time through the monitors arranged at the monitoring nodes of the distribution network. The data includes active power, voltage deviation and frequency fluctuation;

[0011] (2) Data processing: The data transmission module transmits the data from the data acquisition module to the data processing module via wired or wireless means. The data processing module extracts feature quantities from the data as training samples and processes them using a logistic regression model;

[0012] (3) Hierarchical control: The distribution network is judged to be faulty based on the processing results. At the same time, the control module uses chaos theory to perform hierarchical control on the distribution network, dividing the control module level into local level and centralized level to adapt to different operating requirements in the distribution network.

[0013] Furthermore, a multi-level coordinated control model can be constructed in the hierarchical control process, and the MPPT maximum power point tracking algorithm parameters can be used to control the charging and discharging of the photovoltaic energy storage system.

[0014] Compared with the prior art, the present invention has the following beneficial effects:

[0015] (1) The present invention obtains the operating data of distributed photovoltaic access to the distribution network, extracts the power balance, voltage stability, and frequency fluctuation characteristics, and identifies the operating status of the distributed photovoltaic access to the distribution network. Using the characteristics of chaos theory, the control level is divided into a local level and a centralized level to adapt to the characteristics and operating requirements of different components in the distribution network. The control sensitivity between each control level is further calculated to ensure efficient transmission and accurate response of information between levels.

[0016] (2) The multi-level coordinated control strategy of the power grid of the present invention realizes the coordinated work among the photovoltaic power source, energy storage system, load and other components. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a diagram of the control method for accessing the distributed photovoltaic power distribution network according to the present invention. DETAILED DESCRIPTION

[0018] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0019] like Figure 1 As shown, a control system for distributed photovoltaic access to a distribution network is composed of a data acquisition module, a data transmission module, a data processing module and a control module. The data acquisition module collects the monitor data in real time through the monitor arranged at the distribution network monitoring node. The data transmission module transmits the data of the data acquisition module to the data processing module by wire or wireless means. The data processing module processes the data through a logistic regression model and determines whether the distribution network has a fault according to the processing result. At the same time, the control module uses chaos theory to perform hierarchical control on the distribution network, and divides the control module level into a local level and a centralized level, so as to adapt to different operation requirements in the distribution network.

[0020] The data collected by the data acquisition module includes active power, voltage deviation and frequency fluctuation. w =P w1 +P w2 -P w3 , P w1 is the distributed photovoltaic output power, P w2 is the charging and discharging power of the energy storage system, P w3 is the load power; voltage deviation V=V1-V2, V1 is the actual voltage, V2 is the reference voltage; frequency fluctuation f=f1-f2, f1 is the actual frequency value, f2 is the reference frequency value.

[0021] The data processing module extracts feature quantities from the data and uses them as training samples, which are processed using a logistic regression model. The process of the logistic regression model processing data is as follows:

[0022] (1) Suppose there are n feature quantities [x1, x2,..., x n , 1 bias term b, and corresponding weights [ω1, ω2,..., ω n . The model representation of logistic regression is: In the formula, logSigmoid is the logarithmic domain activation function, which is used to convert the output into a probability value; σ is the dot product of the weight vector and the feature vector;

[0023] (2) Set a threshold K. The function maps the output of the operating state feature quantity to the interval [0, 1], and identifies whether a fault occurs in the distribution network with distributed photovoltaic access according to a specific value. If H > K, it is identified that a fault occurs in the distribution network with distributed photovoltaic access; if H < K, it is identified that the distribution network with distributed photovoltaic access is operating normally.

[0024] Based on the above power grid operating state monitoring system, judge the operating state of the distribution network, and use chaos theory to conduct hierarchical control on the entire distribution network. The control levels of the distribution network are divided into local levels and centralized levels, and the control index is mainly based on droop control.

[0025] The process of the control system performing hierarchical control on the distribution network is as follows:

[0026] (1) Set chaos characteristic indicators: active power, voltage deviation, and frequency;

[0027] (2) The dynamic behavior index of the chaos system is represented by Lyapunov Lv: In the formula: f(x) is the mapping function describing the dynamic behavior of the system; x i is the signal node of the distribution network; d is the signal length of the distributed photovoltaic access to the distribution network; ξ is the influencing factor other than photovoltaic in the chaos system;

[0028] (3) When Lv > 0, it means that the distribution network is in a chaotic state. At this time, local level control is used; when Lv < 0, it means that the distribution network is in a stable state. At this time, centralized level control is used.

[0029] Chaotic state: When Lv > 0, it means that the distribution network is in a chaotic state. At this time, local level control is used, and the droop control parameters are selected according to the operating state of the distribution network. That is, if d is 0, the distribution network selects the droop control parameters after centralized level decision-making; if d is 1, the distribution network selects the preset conservative droop control parameters. The corresponding expression is:

[0030]

[0031] Dd is the droop coefficient determined by the centralized level; f d is the frequency reduction rate decided by the centralized level; f0 is the preset conservative frequency reduction rate. V0 is the reference voltage decided by the centralized level. Droop parameter preset principle:

[0032]

[0033] is the control gain; λ is the communication branch element of the distribution network. To ensure that the voltage of the distributed photovoltaic access user-side distribution network is always within the normal range, V is set to the midpoint of the normal voltage range. D is the signal length of the distributed photovoltaic access distribution network.

[0034] Stable state: Lv<0, it means that the distribution network is in a stable state. At this time, the centralized level is used for control, considering the network loss and deviation objective function: m=Wm l +W v m v ; Where W, W v are the weight coefficients of network active power loss, voltage, and frequency deviation respectively; m l , m v They are network loss term, voltage, and frequency deviation term. When dividing the control level, the overall performance and local characteristics of the power grid need to be considered comprehensively to coordinate the control strategies among multiple levels.

[0035] When the distribution network is in a stable state, the control module can also construct a multi-level coordinated control model, the specific process of which is as follows:

[0036] (1) Setting the distribution network model: Where l is the distribution network state variable; is the control variable;

[0037] (2) Calculation of distribution network control sensitivity R: When the distribution network adopts a multi-level coordination mode, Calculated: Control sensitivity Obtain the control sensitivity calculation result;

[0038] (3) The multi-level coordinated control model is set to C = (1-∑Q / P)R, where P is the energy consumption of the distributed photovoltaic access distribution network. The control sensitivity R is introduced into the multi-level coordinated control model, and the MPPT maximum power point tracking algorithm parameters are used to control the charging and discharging of the photovoltaic energy storage system.

[0039] A method for controlling a distributed photovoltaic system connected to a distribution network includes the following steps:

[0040] (1) Data acquisition: The data acquisition module collects the monitor data in real time through the monitors arranged at the monitoring nodes of the distribution network. The data includes active power, voltage deviation and frequency fluctuation;

[0041] (2) Data processing: The data transmission module transmits the data from the data acquisition module to the data processing module via wired or wireless means. The data processing module extracts feature quantities from the data as training samples and processes them using a logistic regression model;

[0042] (3) Hierarchical control: The distribution network is judged to be faulty based on the processing results. At the same time, the control module uses chaos theory to perform hierarchical control on the distribution network, dividing the control module level into local level and centralized level to adapt to different operating requirements in the distribution network.

[0043] In the hierarchical control process, a multi-level coordinated control model can also be constructed, and the MPPT maximum power point tracking algorithm parameters can be used to control the charging and discharging of the photovoltaic energy storage system.

[0044] By acquiring the operating data of distributed photovoltaic access to the distribution network, extracting characteristic quantities such as power balance, voltage stability, and frequency fluctuation, the operating status of the distributed photovoltaic access to the distribution network can be identified. Using the characteristics of chaos theory, the control level is divided into local level and centralized level to adapt to the characteristics and operating requirements of different components in the distribution network. The control sensitivity between each control level is further calculated to ensure efficient transmission and accurate response of information between levels. Finally, by implementing a multi-level coordinated control strategy for the distribution network, the coordinated work between photovoltaic power sources, energy storage systems, loads and other components can be achieved, which can achieve the technical effects of fast response speed and uniform resource distribution.

[0045] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A control system for distributed photovoltaic access to a distribution network, characterized in that: It consists of a data acquisition module, a data transmission module, a data processing module and a control module. The data acquisition module collects the monitor data in real time through the monitor arranged at the distribution network monitoring node. The data transmission module transmits the data of the data acquisition module to the data processing module by wired or wireless means. The data processing module processes the data through a logistic regression model and determines whether the distribution network has a fault according to the processing result. At the same time, the control module adopts chaos theory to perform hierarchical control on the distribution network and divides the control module level into a local level and a centralized level, so as to adapt to different operation requirements in the distribution network.

2. A control system for distributed photovoltaic access to a distribution network according to claim 1, characterized in that: The data acquisition module collects data from the monitor including active power, voltage deviation and frequency fluctuation. The data processing module extracts feature quantities from the data as training samples and processes them using a logistic regression model.

3. A control system for distributed photovoltaic access to a distribution network according to claim 1, characterized in that: The control system uses chaos theory to perform hierarchical control on the entire distribution network, and the control index is droop control.

4. A control system for distributed photovoltaic access to a distribution network according to claim 3, characterized in that: The process of hierarchical control of the distribution network by the control system is as follows: (1) Setting chaos characteristic indicators: active power, voltage deviation and frequency; (2) The dynamic behavior index of the chaotic system is expressed by Lyapunov Lv; (3) When Lv>0, it means that the distribution network is in a chaotic state, and local level control is used at this time; Lv<0, it means that the distribution network is in a stable state, and centralized level control is used at this time.

5. A control system for distributed photovoltaic access to a distribution network according to claim 4, characterized in that: When the distribution network is in a chaotic state, the local hierarchical control is used to select the control droop parameters according to the operating state of the distribution network. That is, if d is 0, the distribution network uses the droop parameters after centralized hierarchical decision-making. If d is 1, the distribution network uses the preset conservative droop parameters.

6. A control system for distributed photovoltaic access to a distribution network according to claim 5, characterized in that: When the distribution network is in a stable state, it is controlled at a centralized level, and the network loss and deviation objective functions are used to control the active power, voltage and frequency of the distribution network.

7. A control system for distributed photovoltaic access to a distribution network according to claim 1, characterized in that: When the distribution network is in a stable state, the control module can also construct a multi-level coordinated control model, the specific process of which is as follows: (1) Set up the distribution network model; (2) Calculate the control sensitivity R of the distribution network; (3) Set up a multi-level coordinated control model.

8. A method for implementing a control system for distributed photovoltaic access to a distribution network as described in any one of claims 1 to 7, characterized in that: The following steps are involved: (1) Data acquisition: The data acquisition module collects the monitor data in real time through the monitors arranged at the monitoring nodes of the distribution network. The data includes active power, voltage deviation and frequency fluctuation; (2) Data processing: The data transmission module transmits the data from the data acquisition module to the data processing module via wired or wireless means. The data processing module extracts feature quantities from the data as training samples and processes them using a logistic regression model; (3) Hierarchical control: The distribution network is judged to be faulty based on the processing results. At the same time, the control module uses chaos theory to perform hierarchical control on the distribution network, dividing the control module level into local level and centralized level to adapt to different operating requirements in the distribution network.

9. A method for controlling the operation of distributed photovoltaic access to a distribution network according to claim 8, characterized in that: In the hierarchical control process, a multi-level coordinated control model can also be constructed, and the MPPT maximum power point tracking algorithm parameters can be used to control the charging and discharging of the photovoltaic energy storage system.

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