Grid-connected cabinet suitable for intelligent micro power grid

Abstract

The invention belongs to the technical field of grid-connected cabinets, and particularly relates to a grid-connected cabinet suitable for an intelligent micro power grid. A data acquisition unit in a cabinet body acquires parameter information and operation data of the grid-connected cabinet; the data analysis unit receives the parameter information and the operation data acquired by the data acquisition unit, and calls a preset grid-connected control algorithm to perform parameter control on the electrical components according to the acquired parameter information and the operation data; the command generation unit generates a control command according to the electric energy control result generated by the data analysis unit; the power conversion module receives the control command and adjusts power conversion data in the grid-connected cabinet according to the control command; the communication module transmits the collected data and the operation state of the grid-connected cabinet to an external server, receives a control instruction transmitted by the external server and sends the control instruction to the intelligent control module. According to the invention, the defect of intelligent management of the grid-connected cabinet in the prior art can be overcome.

Description

Technical Field

[0001] The present invention belongs to the technical field of grid-connected cabinets, and in particular relates to a grid-connected cabinet suitable for a smart microgrid. Background Art

[0002] With the growth of energy demand and the pursuit of clean energy, distributed energy systems such as photovoltaic power generation systems and waste heat power generation systems are increasingly used in smart microgrids. As a key device between the power supply end and the power consumption end in these power generation systems, the grid cabinet undertakes the important functions of power control, protection and coordination.

[0003] In the existing technical field, the grid-connected cabinet has a relatively mature group of equipment components. Through reasonable layout and connection, these components can ensure the coordinated work between various devices to a certain extent and ensure the stable transmission and distribution of electric energy. For example, common circuit breakers, contactors and other equipment can cut off the circuit in time under abnormal conditions such as overload and short circuit to protect the safety of the entire power system; mutual inductors can accurately measure parameters such as current and voltage to provide data support for system monitoring and control.

[0004] However, the existing grid-connected cabinets have obvious limitations. The current research and development focuses on the improvement of the cabinet structure and the structure of the equipment components in the cabinet, such as improving the stability of equipment operation by optimizing the heat dissipation design of the cabinet, or miniaturizing and integrating the components to save space. However, there is less consideration for the intelligent control of power transmission in the grid-connected cabinet. In the operating environment of the smart microgrid, the grid-connected cabinet without intelligent control management is difficult to adapt to the complex and changeable power supply and demand conditions. For example, the power transmission strategy cannot be dynamically adjusted according to the real-time power generation power and power load, resulting in power waste or insufficient power supply; it is impossible to timely intelligently diagnose and optimize the power quality problems in the power grid, affecting the normal operation of power-consuming equipment; it is also difficult to achieve efficient collaboration with other smart grid equipment, reducing the operating efficiency and reliability of the entire smart microgrid. Summary of the invention

[0005] The technical problem solved by the present invention is to provide a grid-connected cabinet suitable for a smart microgrid, so as to solve the deficiencies in intelligent management of grid-connected cabinets in the prior art.

[0006] The basic solution provided by the present invention is: a grid-connected cabinet suitable for a smart microgrid, comprising a cabinet body, wherein the cabinet body comprises an intelligent control module, a power conversion module and a communication module, wherein the intelligent control module is used to intelligently control and manage the electric energy in the grid-connected cabinet, and the intelligent control module comprises a data acquisition unit, a data analysis unit and a command generation unit, wherein:

[0007] The data acquisition unit is used to collect parameter information and operation data of the grid-connected cabinet;

[0008] The data analysis unit is used to receive the parameter information and operation data collected by the data collection unit, and call the preset grid-connected control algorithm to perform parameter control on the electrical components according to the collected parameter information and operation data;

[0009] The command generation unit is used to generate a control command from the power control result generated by the data analysis unit;

[0010] The power conversion module is used to receive control commands and adjust the data of power conversion in the grid cabinet according to the control commands;

[0011] The communication module is connected to the intelligent control module, and is used to transmit the collected data and the operating status of the power cabinet to the external server, and receive the control instructions transmitted by the external server and send them to the intelligent control module.

[0012] Furthermore, the data analysis unit calls a preset grid-connected control algorithm to control the electric energy of the electrical components according to the collected parameter information and operation data. Specifically:

[0013] Extract the voltage data and current data of the city grid side and the power generation side connected to the grid cabinet, and the voltage data and current data of the local load, and calculate the power value of the city grid side, the power value of the power generation side, and the power demand value at the local load;

[0014] Based on the improved ant lion optimization algorithm, a grid-connected control algorithm is constructed to determine the population size N, the maximum number of iterations T, the spatial dimension D, and the fitness function F(x) according to the power value on the municipal grid side, the power value on the power generation side, the power demand value at the local load, and the operating data;

[0015] Obtain the initial value of the grid-connected control parameter to generate a solution space, call the grid-connected control algorithm to iterate in the solution space based on the fitness function F(x) according to the maximum number of iterations, stop the iteration when the maximum number of iterations is reached, and output the global optimal ant lion position with the best fitness value as the optimal grid-connected control parameter;

[0016] Generate control commands based on optimal grid-connected control parameters.

[0017] Furthermore, the invoking of the grid-connected control algorithm for iteration is specifically as follows:

[0018] Initialize the positions of N ant lions and N ants in the solution space X = (x 1 ,x 2 ,…,x D ), calculate the fitness value corresponding to the fitness function F(x) of each individual, and select the ant lion with the best fitness as the global optimal ant lion ALbest , get its position X best And the fitness value F best ;

[0019] Each ant i selects a target antlion j in a roulette manner, and the calculation formula is:

[0020]

[0021] Among them, F(AL j ) represents the fitness value of the jth antlion; and a random number r is set from 0 to 1 to determine Then ant i chooses antlion j as the target antlion;

[0022] The trap ratio is then calculated based on the current number of iterations t; each ant then performs a random walk and selects the elite ant lion, allowing each ant to walk around the elite ant lion during random walks. The walk step length is adjusted based on the weighted sum of historical movement vectors, and the ant's walk position X is finally obtained. real ;

[0023] Calculate the fitness value of each ant at each new position, update the global optimal ant lion and the optimal fitness value, and determine whether the current number of iterations has reached the maximum number of iterations. If so, output the position of the global optimal ant lion as the optimal grid-connected control parameter; otherwise, execute the next iteration.

[0024] Further, the fitness function construction process is:

[0025] Based on the power value of the city grid side, the power value of the power generation side and the power demand value at the local load, the absolute value of the difference between the total output power of the city grid side and the power generation side and the power demand of the local load is calculated to generate a power balance error;

[0026] Generate energy utilization rate based on the sum of the ratios of actual output power on the city grid side and the power generation side to their rated power;

[0027] Obtain the fluctuation range of grid voltage and frequency under different local load conditions and generate voltage and frequency stability;

[0028] Based on power balance error, energy utilization, voltage and frequency stability, a fitness function is constructed, which is expressed as:

[0029] F(x)=ω1×|P total -P load |+ω2×(U grid +U gen )+ω3×(F grid +F gen )

[0030] P total =P grid +P gen

[0031]

[0032]

[0033] Among them, ω1, ω2, ω3 represent weight coefficients, V grid 、V gen ,I grid ,I gen Respectively represent the voltage and current on the city grid side and the power generation side, They represent power factor respectively;

[0034]

[0035] Among them, V load and I load Respectively represent the voltage and current of the local load; Indicates the local load power factor;

[0036] U grid and U gen Respectively represent the quantitative values ​​of the voltage fluctuation range of the city grid side and the power generation side, F grid and F gen They respectively represent the quantitative values ​​of the frequency fluctuation range on the grid side and the power generation side.

[0037] Further, the trap ratio is calculated according to the current iteration number t as follows:

[0038] According to the current iteration number t, the trap ratio ratio is calculated according to the improved trap ratio formula, and the expression is:

[0039]

[0040] Among them, t is the current iteration number and T is the maximum iteration number.

[0041] Furthermore, the power conversion module includes a rectifier, an inverter and a transformer, the rectifier is used to convert AC power into DC power, the inverter is used to convert DC power into AC power, and the transformer is used to adjust the voltage level.

[0042] Furthermore, it also includes a protection module, which is connected to the intelligent control module. The protection module is used to respond to the instructions of the intelligent control module to protect the internal components of the power cabinet when an abnormality occurs.

[0043] The principle and advantage of the present invention are as follows: In this application, compared with the existing grid-connected cabinets, the equipment and devices are improved. This application achieves accurate transmission and control of grid data and better coordination of operation between equipment by intelligently controlling the grid data of the grid-connected cabinet, specifically:

[0044] First, the parameter information and operation data of the electrical components in the grid-connected cabinet are collected, and the preset grid-connected control algorithm is called to control the parameters of the electrical components according to the collected parameter information and operation data. Among them, the preset grid-connected control algorithm is implemented in this scheme according to the improved antlion optimization algorithm. In the improvement process, for the power supply end of the grid-connected cabinet including the power generation side and the city grid side, in order to achieve grid connection without access to the grid, a fitness function based on power balance error, energy utilization rate, and voltage and frequency stability is constructed. At the same time, for the design of the trap ratio in the antlion optimization algorithm, an adaptive trap ratio adjustment strategy is proposed, so that in the early stage of iteration, the growth rate of the trap ratio is appropriately slowed down, so that ants can explore the solution space more widely and increase the probability of finding the global optimal solution. In the later stage of iteration, the growth of the trap ratio is accelerated, while converging to the optimal solution faster.

[0045] Finally, the optimal solution is obtained, which can be used as the optimal grid-connected control parameter to further improve the accuracy of the grid-connected cabinet in power control. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a functional block diagram of an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The following is further described in detail through specific implementation methods:

[0048] The embodiment is basically as shown in the attached Figure 1 As shown: a grid-connected cabinet suitable for a smart microgrid, comprising a cabinet body, in which an intelligent control module, a power conversion module, a communication module and a protection module are arranged, wherein the intelligent control module is used to intelligently control and manage the electric energy in the grid-connected cabinet, and the grid-connected cabinet is provided with a variety of electrical components for coordinating and controlling the power supply end and the power consumption end, such as circuit breakers, contactors, fuses, current transformers, voltage transformers, measurement and control protection devices, disconnectors, surge protectors, etc.;

[0049] The power conversion module is used to receive the control command generated by the intelligent control module when the intelligent control module performs intelligent control and management of electric energy, and adjust the power conversion data in the grid-connected cabinet according to the control command; in this solution, the power conversion module and the intelligent control module are connected through a communication module. The power conversion module includes a rectifier, an inverter and a transformer. The rectifier is used to convert AC power into DC power, the inverter is used to convert DC power into AC power, and the transformer is used to adjust the voltage level. Specifically, for example, if the control command received by the power conversion module requires reducing the generated power, the conduction time or modulation mode of the switching device in the grid-connected cabinet is changed through the inverter to reduce the output current, thereby reducing the output power, and vice versa. Increase the output current.

[0050] As for the generation of control commands, in order to realize the intelligent microgrid in the grid-connected cabinet and improve the management and control of the grid, the intelligent control module includes a data acquisition unit, a data analysis unit, and a command generation unit. The data acquisition unit is used to collect parameter information and operation data of the grid-connected cabinet and transmit it to the data analysis unit. The data analysis unit first pre-processes the collected data, such as data cleaning and data conversion. Then, the data analysis unit calls the preset grid-connected control algorithm to analyze the pre-processed data and generate parameter control of the electrical components in the grid-connected cabinet. In this solution, the preset grid-connected control algorithm analysis and processing logic is:

[0051] Step 1: Extract the voltage data and current data of the city grid side and the power generation side connected to the grid cabinet, and the voltage data and current data of the local load, and calculate the power value of the city grid side, the power value of the power generation side, and the power demand value at the local load;

[0052] Step 2: Build a grid-connected control algorithm based on the improved ant lion optimization algorithm, determine the population size N, the maximum number of iterations T, the spatial dimension D, and determine the fitness function F(x) according to the power value on the municipal grid side, the power value on the power generation side, the power demand value at the local load, and the operating data;

[0053] Step 3: Obtain the initial value of the grid-connected control parameter to generate a solution space, call the grid-connected control algorithm to iterate in the solution space based on the fitness function F(x) according to the maximum number of iterations, stop the iteration when the maximum number of iterations is reached, and output the global optimal antlion position with the best fitness value as the optimal grid-connected control parameter;

[0054] Step 4: Generate control commands based on optimal grid-connected control parameters.

[0055] In the above steps, the grid-connected control algorithm constructed based on the improved ant lion optimization algorithm first generates a solution space for all initial values ​​of the grid-connected cabinet when controlling the power parameters, and the grid-connected control algorithm selects the optimal solution in the solution space, that is, the screening process of the optimal grid-connected control parameters is:

[0056] First, the parameters are set to determine the population size N, the maximum number of iterations T, and the spatial dimension D. In this embodiment, the control parameters of the grid-connected control algorithm include the power adjustment step and the power threshold, and the initial value range is an interval determined based on the rated capacity of the grid-connected cabinet and the maximum demand of the local load.

[0057] Then initialize the positions X=(x 1 ,x 2 ,…,x D ), determine the fitness function F(x) according to the power value on the city grid side, the power value on the power generation side, the power demand value at the local load and the operating data; calculate the fitness value of each individual, and the fitness function construction process is:

[0058] Based on the power value of the city grid side, the power value of the power generation side and the power demand value at the local load, the absolute value of the difference between the total output power of the city grid side and the power generation side and the power demand of the local load is calculated to generate a power balance error;

[0059] Generate energy utilization rate based on the sum of the ratios of actual output power on the city grid side and the power generation side to their rated power;

[0060] Obtain the fluctuation range of grid voltage and frequency under different local load conditions and generate voltage and frequency stability;

[0061] Based on power balance error, energy utilization, voltage and frequency stability, a fitness function is constructed, which is expressed as:

[0062] F(x)=ω1×|P total -P load |+ω2×(U grid +U gen )+ω3×(F grid +F gen )

[0063] P total =P grid +P gen

[0064]

[0065]

[0066] Among them, V grid、V gen ,I grid ,I gen Respectively represent the voltage and current on the city grid side and the power generation side, They represent power factor respectively;

[0067]

[0068] Among them, V load and I load Respectively represent the voltage and current of the local load; Indicates the local load power factor; the power factor is obtained by measuring with a power factor meter;

[0069] U grid and U gen Respectively represent the quantitative values ​​of the voltage fluctuation range of the city grid side and the power generation side, F grid and F gen They respectively represent the quantitative values ​​of the frequency fluctuation range on the grid side and the power generation side.

[0070] Then, according to each ant, each ant i selects a target ant lion j in a roulette manner, and the calculation formula is:

[0071]

[0072] Among them, F(AL j ) represents the fitness value of the jth antlion; and a random number r is set from 0 to 1 to determine Then ant i chooses antlion j as the target antlion;

[0073] Then calculate the trap ratio according to the current iteration number t, specifically:

[0074] According to the current iteration number t, the trap ratio ratio is calculated according to the improved trap ratio formula, and the expression is:

[0075]

[0076] Among them, t is the current iteration number and T is the maximum iteration number.

[0077] Each ant then performs a random walk, and the random walk calculation formula is:

[0078] X i (t)=[0,cumsum(2r(t1)-1),cumsum(2r(t2)-1),…,cumsum(2r(t) D )-1)]

[0079] in:

[0080]

[0081] r is a uniform random number between 0 and 1;

[0082] Elite ant lions are selected to make each ant tend to walk around the elite ant lions when walking randomly. In this scheme, the top 10% (0.1N) of the best ant lions are selected as the elite ant lion set. For each ant i, with probability p elite When walking randomly, it tends to walk around elite ant lions;

[0083] Then, the historical information is used to adjust the walking step length. Specifically, the historical movement vector of ant i in the dth dimension (the corresponding control parameter in the spatial dimension D) is set to (k represents the moving vector from the k-1th iteration to the kth iteration), then the step size adjustment factor β at the tth iteration is d The calculation formula of (t) is:

[0084]

[0085] Among them, ω(k) represents the weighting coefficient. This scheme sets The more recent the iteration, the greater the impact on the step size adjustment;

[0086] Then in the antlion optimization algorithm, the ants are trapped by the antlion and the antlion throws sand. The scaling ratio of the trap gradually decreases with the number of iterations, so the random walk range of the ants will also gradually decrease. The relative value of the ant's random walk is calculated as follows:

[0087]

[0088] a i represents the minimum value of the random walk of the ith variable, d i represents the maximum value of the random walk in the ith variable, is the minimum value of the ith variable at the tth iteration, Represents the maximum value of the i-th variable at the t-th iteration.

[0089] Next, the antlion trap range is calculated. The ant selects the jth antlion as its target antlion. According to the above trap ratio, the antlion’s trap range in round t is calculated as:

[0090]

[0091] Among them, d min and d max represents the lower and upper bounds of the solution space of the tth round, which is determined by the value range of the control parameters of the grid-connected cabinet. Indicates the position of the j-th antlion in round t.

[0092] Finally, calculate the final position of the ant:

[0093]

[0094] X real represents the position of the ant in this round of the algorithm, ave() represents the average function, that is, the average value of all parameters in ave(), X best represents the position of the ant's random walk around the global optimal ant lion, X random Indicates the position of the ant's random walk around the antlion selected in this round;

[0095] After this round of iterative random walk is completed, normalization is performed according to the set upper and lower bounds to prevent out-of-bounds. Before the optimization target or the number of iterations is reached, the above steps are repeated. Finally, when the optimization target is reached or the number of iterations T is reached, the position of the global optimal ant lion is output as the optimal grid-connected control parameter.

[0096] Therefore, in this scheme, the improved antlion optimization algorithm can continuously find the optimal control parameters in the grid-connected control algorithm to realize the functions of grid-connected and non-grid-connected in the grid-connected cabinet and optimize the system performance, which is different from the existing improvements on components in the grid-connected cabinet.

[0097] The above are only embodiments of the present invention. Common knowledge such as the known specific structures and characteristics in the scheme is not described in detail here. Ordinary technicians in the relevant field know all the common technical knowledge in the technical field to which the invention belongs before the application date or priority date, can obtain all the existing technologies in the field, and have the ability to apply conventional experimental means before that date. Ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the scope of protection of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A grid-connected cabinet suitable for a smart microgrid, characterized in that: The cabinet includes an intelligent control module, a power conversion module and a communication module. The intelligent control module is used to intelligently control and manage the electric energy in the grid-connected cabinet. The intelligent control module includes a data acquisition unit, a data analysis unit and a command generation unit, wherein: The data acquisition unit is used to collect parameter information and operation data of the grid-connected cabinet; The data analysis unit is used to receive the parameter information and operation data collected by the data collection unit, and call the preset grid-connected control algorithm to perform parameter control on the electrical components according to the collected parameter information and operation data; The command generation unit is used to generate a control command from the power control result generated by the data analysis unit; The power conversion module is used to receive control commands and adjust the data of power conversion in the grid cabinet according to the control commands; The communication module is connected to the intelligent control module, and is used to transmit the collected data and the operating status of the power cabinet to the external server, and receive the control instructions transmitted by the external server and send them to the intelligent control module.

2. A grid-connected cabinet suitable for a smart microgrid according to claim 1, characterized in that: The data analysis unit calls the preset grid-connected control algorithm to control the electric energy of the electrical components according to the collected parameter information and operation data. Specifically: Extract the voltage data and current data of the city grid side and the power generation side connected to the grid cabinet, and the voltage data and current data of the local load, and calculate the power value of the city grid side, the power value of the power generation side, and the power demand value at the local load; Based on the improved ant lion optimization algorithm, a grid-connected control algorithm is constructed to determine the population size N, the maximum number of iterations T, the spatial dimension D, and the fitness function F(x) according to the power value on the municipal grid side, the power value on the power generation side, the power demand value at the local load, and the operating data; Obtain the initial value of the grid-connected control parameter to generate a solution space, call the grid-connected control algorithm to iterate in the solution space based on the fitness function F(x) according to the maximum number of iterations, stop the iteration when the maximum number of iterations is reached, and output the global optimal ant lion position with the best fitness value as the optimal grid-connected control parameter; Generate control commands based on optimal grid-connected control parameters.

3. A grid-connected cabinet suitable for a smart microgrid according to claim 2, characterized in that: The specific process of calling the grid-connected control algorithm for iteration is as follows: Initialize the positions of N ant lions and N ants in the solution space X = (x 1 , x 2 , ..., x D ), calculate the fitness value corresponding to the fitness function F(x) of each individual, and select the ant lion with the best fitness as the global optimal ant lion AL best , get its position X best And the fitness value F best ; Each ant i selects a target antlion j in a roulette manner, and the calculation formula is: Among them, F(AL j ) represents the fitness value of the jth antlion; and a random number r is set from 0 to 1 to determine Then ant i chooses antlion j as the target antlion; The trap ratio is then calculated based on the current number of iterations t; each ant then performs a random walk and selects the elite ant lion, allowing each ant to walk around the elite ant lion during random walks. The walk step length is adjusted based on the weighted sum of historical movement vectors, and the ant's walk position X is finally obtained. real ; Calculate the fitness value of each ant at each new position, update the global optimal ant lion and the optimal fitness value, and determine whether the current number of iterations has reached the maximum number of iterations. If so, output the position of the global optimal ant lion as the optimal grid-connected control parameter; otherwise, execute the next iteration.

4. A grid-connected cabinet suitable for a smart microgrid according to claim 3, characterized in that: The fitness function construction process is: Based on the power value of the city grid side, the power value of the power generation side and the power demand value at the local load, the absolute value of the difference between the total output power of the city grid side and the power generation side and the power demand of the local load is calculated to generate a power balance error; Generate energy utilization rate based on the sum of the ratios of actual output power on the city grid side and the power generation side to their rated power; Obtain the fluctuation range of grid voltage and frequency under different local load conditions and generate voltage and frequency stability; Based on power balance error, energy utilization, voltage and frequency stability, a fitness function is constructed, which is expressed as: F(x)=ω1×|P total -P load |+ω2×(U grid +U gen )+ω3×(F grid +F gen ) P total =P grid +P gen Among them, ω1, ω2, ω3 represent weight coefficients, V grid 、V gen ,I grid、 I gen Respectively represent the voltage and current on the city grid side and the power generation side, They represent power factor respectively; Among them, V load and I load Respectively represent the voltage and current of the local load; Indicates the local load power factor; U grid and U gen Respectively represent the quantitative values ​​of the voltage fluctuation range of the city grid side and the power generation side, F grid and F gen They respectively represent the quantitative values ​​of the frequency fluctuation range on the grid side and the power generation side.

5. A grid-connected cabinet suitable for a smart microgrid according to claim 4, characterized in that: The calculation of the trap ratio according to the current iteration number t is specifically as follows: According to the current iteration number t, the trap ratio ratio is calculated according to the improved trap ratio formula, and the expression is: Among them, t is the current iteration number and T is the maximum iteration number.

6. The grid-connected cabinet suitable for a smart microgrid according to claim 1, characterized in that: The power conversion module includes a rectifier, an inverter and a transformer. The rectifier is used to convert AC power into DC power, the inverter is used to convert DC power into AC power, and the transformer is used to adjust the voltage level.

7. The grid-connected cabinet suitable for a smart microgrid according to claim 1, characterized in that: It also includes a protection module, which is connected to the intelligent control module. The protection module is used to respond to the instructions of the intelligent control module to protect the internal components of the grid-connected cabinet when an abnormality occurs.

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