CN117614035A - Power scheduling optimization method and system based on synchronous acquisition of photovoltaic grid-connected data - Google Patents

Abstract

The invention discloses a power scheduling optimization method and a system based on synchronous acquisition of photovoltaic grid-connected data, which relate to the technical field of photovoltaic grid-connected, and are characterized in that: predicting new energy power generation, power user load and charge and discharge of an energy storage module in the next scheduling period according to the historical operating power; determining initial charge and discharge power of the energy storage module in the next scheduling period by combining the output, the predicted power generation power and the predicted load power of the traditional generator set; determining the compensation charge-discharge power of the energy storage module in the next scheduling period according to the predicted power generation power, the predicted load power and the predicted charge-discharge power; and selecting one or more energy storage units from the energy storage module to realize the scheduling control of initial charge and discharge power and compensation charge and discharge power. The invention can make the power regulation and control of distributed energy storage more accurate and reliable, effectively reduce the unbalanced supply and demand problem of the power grid caused by the predicted power error, and enhance the running stability of the power grid.

Description

Power dispatch optimization method and system based on synchronous collection of photovoltaic grid-connected data

Technical field

The present invention relates to the technical field of photovoltaic grid connection, and more specifically, it relates to a power scheduling optimization method and system based on synchronous collection of photovoltaic grid connection data.

Background technique

As distributed photovoltaic power generation accounts for an increasing proportion of the power system, the power of distributed photovoltaic power generation is affected by factors such as distribution location and weather conditions in various places. It has greater randomness and volatility, so it is very important for photovoltaic power generation. Power regulation is a necessary measure to ensure the stable operation of the power system.

At present, in the process of distributed photovoltaic grid connection, the power regulation of distributed energy storage is realized based on the long-term or short-term predicted power of electricity user load and new energy generation. As more and more new energy sources are connected to the grid, The entire new energy generation is more volatile and random, and the error in predicted power is greater. This results in the power regulation of distributed energy storage based only on the long-term or short-term predicted power of electricity user loads and new energy generation being unable to meet the needs of the power grid. It is more difficult to meet the stability requirements of the power grid, especially when the prediction errors of electricity user loads are superimposed. For this reason, the existing technology records the technology of realizing unbalanced power regulation by re-scheduling part of the flexible load. However, this process will affect the normal power consumption of electricity users to a certain extent, and the impact of power grid dispatching has a wide coverage.

Therefore, how to research and design a power scheduling optimization method and system based on synchronous collection of photovoltaic grid-connected data that can overcome the above shortcomings is an issue we urgently need to solve.

Contents of the invention

In order to solve the deficiencies in the existing technology, the purpose of the present invention is to provide a power dispatch optimization method and system based on synchronous collection of photovoltaic grid-connected data, and determine the next energy storage module based on the output of the traditional generating unit, predicted power generation and predicted load power. On the basis of the initial charge and discharge power of the dispatch cycle, by analyzing the relative prediction errors of the predicted generation power, predicted load power and predicted charge and discharge power, the compensation charge and discharge power for secondary regulation of the energy storage module is determined, which can make the distribution The power control of energy storage is more accurate and reliable, effectively reducing the imbalance of power grid supply and demand caused by predicted power errors, and enhancing the stability of power grid operation.

The above technical objectives of the present invention are achieved through the following technical solutions:

In the first aspect, a power scheduling optimization method based on synchronous collection of photovoltaic grid-connected data is provided, including the following steps:

Use time stamps to synchronously collect power data of distributed photovoltaic grid-connected devices to obtain the historical operating power of photovoltaic grid-connected devices;

According to the historical operating power, the new energy generation, power user load and charge and discharge of the energy storage module are predicted in the next dispatch cycle, and the corresponding predicted power generation, predicted load power and predicted charge and discharge power are obtained;

The initial charge and discharge power of the energy storage module in the next dispatch cycle is determined based on the output of the traditional generator set, the predicted power generation and the predicted load power;

Determine the compensated charge and discharge power of the energy storage module in the next dispatch cycle based on the predicted generation power, predicted load power and predicted charge and discharge power;

Select one or more energy storage units from the energy storage module to implement scheduling control of initial charge and discharge power and compensation charge and discharge power.

Further, the historical operating power includes the historical power generation of new energy power generation, the historical load power of electricity users, and the historical charging and discharging power of energy storage modules in distributed new energy systems;

Based on the historical power generation prediction analysis of new energy power generation, the predicted power generation for the next dispatch cycle is obtained;

Based on the historical load power prediction analysis of electricity users, the predicted load power of the next dispatch period is obtained;

And, based on the historical charge and discharge power prediction analysis of the energy storage module in the distributed new energy system, the predicted charge and discharge power of the next dispatch cycle is obtained.

Further, the calculation formula for the initial charge and discharge power of the energy storage module in the next scheduling cycle is specifically:

in, Indicates the initial charging and discharging power of the energy storage module in the next scheduling period T+1. The negative value is the charging power, and the positive value is the discharging power;/> Represents the predicted load power of electricity users in the next dispatch period T+1; P _G represents the output of traditional generating units;/> Indicates the predicted power generation of new energy power generation in the next dispatch period T+1.

Further, the calculation formula for the compensated charge and discharge power of the energy storage module in the next scheduling period is specifically:

in, Represents the compensated charge and discharge power of the energy storage module in the next scheduling period T+1; K represents the compensation coefficient, the value range is (0,1); α represents the predicted balance deviation rate;/> Indicates the predicted charge and discharge power of the energy storage module in the next scheduling period T+1;/> Indicates the initial charging and discharging power of the energy storage module in the next scheduling period T+1. The negative value is the charging power, and the positive value is the discharging power;/> Represents the predicted load power of electricity users in the next dispatch period T+1; P _G represents the output of traditional generating units;/> Indicates the predicted power generation of new energy power generation in the next dispatch period T+1.

Further, the process of selecting one or more energy storage units from the energy storage module to implement scheduling control of the initial charge and discharge power and the compensation charge and discharge power is specifically as follows:

Select at least one first energy storage unit from the energy storage module to implement scheduling control of initial charge and discharge power;

And, selecting at least one second energy storage unit from the energy storage module to implement scheduling control to compensate for charging and discharging power.

Further, the process of selecting one or more energy storage units from the energy storage module to implement scheduling control of the initial charge and discharge power and the compensation charge and discharge power is specifically as follows:

The vector sum of the initial charge and discharge power and the compensation charge and discharge power is used as the total charge and discharge power of the energy storage module;

Select one or more energy storage units from the energy storage module to implement scheduling control of the total charge and discharge power.

Further, the duration of the scheduling period ranges from 0.25h to 2h.

In the second aspect, a power scheduling optimization system based on synchronous collection of photovoltaic grid-connected data is provided, including:

The data acquisition module is used to synchronously collect the power data of distributed photovoltaic grid-connected devices using time stamps to obtain the historical operating power of photovoltaic grid-connected devices;

The power prediction module is used to predict the new energy generation, electricity user load and the charge and discharge of the energy storage module in the next dispatch cycle based on the historical operating power, and obtain the corresponding predicted power generation, predicted load power and predicted charge and discharge power. ;

The power calculation module is used to determine the initial charge and discharge power of the energy storage module in the next dispatch cycle based on the output of the traditional generator set, predicted power generation and predicted load power;

The compensation analysis module is used to determine the compensated charge and discharge power of the energy storage module in the next dispatch cycle based on the predicted power generation, predicted load power and predicted charge and discharge power;

The scheduling control module is used to select one or more energy storage units from the energy storage module to implement scheduling control of initial charge and discharge power and compensation charge and discharge power.

In a third aspect, a computer terminal is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements any one of the first aspects. The power dispatch optimization method based on the synchronous collection of photovoltaic grid-connected data is described.

In a fourth aspect, a computer-readable medium is provided with a computer program stored thereon. The computer program is executed by a processor and can realize the power synchronous collection based on photovoltaic grid-connected data as described in any one of the first aspects. Scheduling optimization methods.

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

1. The power dispatch optimization method provided by the present invention based on the synchronous collection of photovoltaic grid-connected data determines the initial charge and discharge power of the energy storage module in the next dispatch cycle based on the traditional generator unit output, predicted power generation and predicted load power. By analyzing the relative prediction errors of predicted power generation, predicted load power and predicted charge and discharge power, the compensation charge and discharge power for secondary regulation of energy storage modules is determined, which can make the power regulation of distributed energy storage more accurate and reliable. , effectively reducing the imbalance between supply and demand in the power grid caused by predicted power errors, and enhancing the stability of the power grid operation;

2. This invention is based on the consistency of the prediction error ranges of predicted power generation, predicted load power and predicted charge and discharge power, and obtains a solution that can make the predicted power generation, predicted load power, predicted charge and discharge power and the output of traditional generator sets meet the supply and demand of the power grid. Balance the predicted balance deviation rate, and calculate the charge and discharge power that is more consistent with the real situation based on the predicted balance deviation rate, and finally realize the secondary power control based on the charge and discharge power and initial charge and discharge power that are more consistent with the real situation, effectively reducing Scheduling of flexible loads for power grid operation;

3. The present invention uses the vector sum of the initial charge and discharge power and the compensation charge and discharge power for unified scheduling, which can avoid the waste of energy storage resources and extend the service life of the energy storage module;

4. The present invention performs independent dispatch control on the initial charge and discharge power and the compensation charge and discharge power, which can enhance the flexibility of the power grid dispatch operation and reduce the failure rate of the energy storage module.

Description of drawings

The drawings described here are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation to the embodiments of the present invention. In the attached picture:

Figure 1 is a flow chart in Embodiment 1 of the present invention;

Figure 2 is a system block diagram in Embodiment 2 of the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples and drawings. The schematic embodiments of the present invention and their descriptions are only used to explain the present invention and do not as a limitation of the invention.

Embodiment 1: Power scheduling optimization method based on synchronous collection of photovoltaic grid-connected data, as shown in Figure 1, including the following steps:

S1: Use time stamps to synchronously collect distributed photovoltaic grid-connected power data to obtain the historical operating power of photovoltaic grid-connected;

S2: Predict the new energy generation, electricity user load and charge and discharge of the energy storage module in the next dispatch cycle based on the historical operating power, and obtain the corresponding predicted power generation, predicted load power and predicted charge and discharge power;

S3: Determine the initial charge and discharge power of the energy storage module in the next dispatch cycle based on the output of the traditional generator set, predicted power generation and predicted load power;

S4: Determine the compensated charge and discharge power of the energy storage module in the next dispatch cycle based on the predicted generation power, predicted load power and predicted charge and discharge power;

S5: Select one or more energy storage units from the energy storage module to implement scheduling control of initial charge and discharge power and compensation charge and discharge power.

It should be noted that since there are differences in the locations of each distributed photovoltaic area and each photovoltaic module within a single area, when collecting distributed photovoltaic grid-connected data for centralized processing, the data may be out of sync due to time delays. Therefore, the present invention Timestamps are used to mark data everywhere in the process of distributed photovoltaic grid connection, and the historical data of distributed photovoltaic grid connection is synchronized by correcting the timestamps in the data center.

The historical operating power includes the historical power generation of new energy power generation, the historical load power of electricity users, and the historical charge and discharge power of energy storage modules in distributed new energy systems. In the power prediction process, the predicted power generation of the next dispatch period is obtained based on the historical power generation prediction analysis of new energy power generation; the predicted load power of the next dispatch period is obtained based on the historical load power prediction analysis of power users; and, based on the distribution The historical charge and discharge power prediction analysis of the energy storage module in the new energy system is used to obtain the predicted charge and discharge power of the next dispatch cycle.

In addition, the prediction method can use the least squares method for curve fitting to achieve prediction, or it can use machine learning algorithms for prediction, which is not limited here.

In this embodiment, the duration of the scheduling cycle ranges from 0.25h to 2h.

In this embodiment, the calculation formula for the initial charge and discharge power of the energy storage module in the next scheduling cycle is specifically:

in, Indicates the initial charging and discharging power of the energy storage module in the next scheduling period T+1. The negative value is the charging power, and the positive value is the discharging power;/> Represents the predicted load power of electricity users in the next dispatch period T+1; P _G represents the output of traditional generating units;/> Indicates the predicted power generation of new energy power generation in the next dispatch period T+1.

Taking the output of a traditional generator set as 800KW and the dispatching period as 1 hour as an example, the predicted charging and discharging power is 60KW, the predicted generating power is 360KW, and the predicted load power is 1280KW.

The calculated initial charge and discharge power is: 1280KW-800KW-360KW=120KW.

The specific calculation formula for the compensation charge and discharge power of the energy storage module in the next dispatch cycle is:

in, Represents the compensated charge and discharge power of the energy storage module in the next scheduling period T+1; K represents the compensation coefficient, the value range is (0,1); α represents the predicted balance deviation rate;/> Indicates the predicted charge and discharge power of the energy storage module in the next scheduling period T+1;/> Indicates the initial charging and discharging power of the energy storage module in the next scheduling period T+1. The negative value is the charging power, and the positive value is the discharging power;/> Represents the predicted load power of electricity users in the next dispatch period T+1; P _G represents the output of traditional generating units;/> Indicates the predicted power generation of new energy power generation in the next dispatch period T+1.

According to 60(1+α)+360(1+α)+800=1280(1-α), it can be calculated that the value of α is approximately 0.0353.

Taking the value of K as 0.5 as an example, the calculated compensation charge and discharge power is -28.9412KW, indicating that the initial charge and discharge power of the first control is in the discharge state, while the compensated charge and discharge power of the second control is in the charge state.

As an optional implementation, in order to enhance the flexibility of power grid dispatching operation and reduce the failure rate of energy storage modules, one or more energy storage units are selected from the energy storage module to realize the scheduling of initial charge and discharge power and compensation charge and discharge power. The specific control process is: selecting at least one first energy storage unit from the energy storage module to implement scheduling control of initial charge and discharge power; and selecting at least one second energy storage unit from the energy storage module to implement scheduling of compensation charge and discharge power. control.

As another optional implementation, in order to avoid the waste of energy storage resources and extend the service life of the energy storage module, one or more energy storage units are selected from the energy storage module to realize the scheduling of the initial charge and discharge power and the compensation charge and discharge power. The specific control process is as follows: taking the vector sum of the initial charge and discharge power and the compensation charge and discharge power as the total charge and discharge power of the energy storage module; selecting one or more energy storage units from the energy storage module to implement scheduling control of the total charge and discharge power.

Taking the above-mentioned initial charge and discharge power and compensation charge and discharge power as an example, the final total charge and discharge power is 91.0588KW. According to the actual situation of new energy power generation and electricity user load, the energy storage unit requires 102KW to achieve supply and demand balance, and the 91.0588KW in the present invention is significantly closer to the real situation than the previous 120KW.

Embodiment 2: A power scheduling optimization system based on synchronous collection of photovoltaic grid-connected data. This system is used to implement the power scheduling optimization method based on synchronous collection of photovoltaic grid-connected data recorded in Embodiment 1. As shown in Figure 2, it includes data. Acquisition module, power prediction module, power calculation module, compensation analysis module and dispatch control module.

Among them, the data acquisition module is used to synchronously collect the power data of distributed photovoltaic grid-connected using time stamps to obtain the historical operating power of photovoltaic grid-connected; the power prediction module is used to predict the new energy sources in the next dispatch cycle based on the historical operating power. The power generation, user load and charge and discharge of the energy storage module are predicted to obtain the corresponding predicted power generation, predicted load power and predicted charge and discharge power; the power calculation module is used to combine the output of traditional generator sets, predicted power generation and predicted load. The power determines the initial charge and discharge power of the energy storage module in the next dispatch cycle; the compensation analysis module is used to determine the compensated charge and discharge power of the energy storage module in the next dispatch cycle based on the predicted power generation, predicted load power and predicted charge and discharge power; dispatch control Module, used to select one or more energy storage units from the energy storage module to implement scheduling control of initial charge and discharge power and compensation charge and discharge power.

Working principle: This invention determines the initial charge and discharge power of the energy storage module in the next dispatch cycle based on the output of the traditional generator set, predicted power generation and predicted load power, and analyzes and predicts the generated power, predicted load power and predicted charge and discharge power. The relative prediction error situation determines the compensation charge and discharge power for secondary regulation of energy storage modules, which can make the power regulation of distributed energy storage more accurate and reliable, and effectively reduce the imbalance of power grid supply and demand caused by prediction power errors. problem, which enhances the stability of power grid operation; in addition, the present invention is based on the consistency of the prediction error ranges of predicted power generation, predicted load power and predicted charging and discharging power, and obtains a solution that can make the predicted power generation, predicted load power, predicted charging and discharging power consistent. The discharge power and traditional generator output meet the predicted balance deviation rate of the grid supply and demand balance, and based on the predicted balance deviation rate, the charge and discharge power is calculated more in line with the real situation, and finally based on the charge and discharge power and initial charge and discharge power that are more in line with the real situation. Achieving secondary power regulation effectively reduces the dispatch of flexible loads in power grid operations.

Those skilled in the art will understand that embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment that combines software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable power processing device to produce a machine, such that the instructions executed by the processor of the computer or other programmable power processing device produce a use A device for realizing the functions specified in one process or multiple processes of the flowchart and/or one block or multiple blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory that causes a computer or other programmable power processing device to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction means, the instructions The device implements the functions specified in a process or processes of the flowchart and/or a block or blocks of the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable power processing device, causing a series of operating steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby executing on the computer or other programmable device. Instructions provide steps for implementing the functions specified in a process or processes of a flowchart diagram and/or a block or blocks of a block diagram.

The above specific embodiments further describe the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Within the spirit and principles of the present invention, any modifications, equivalent substitutions, improvements, etc. shall be included in the protection scope of the present invention.

Claims (10)

1. A power scheduling optimization method based on synchronous collection of photovoltaic grid-connected data, which is characterized by including the following steps: Use time stamps to synchronously collect power data of distributed photovoltaic grid-connected devices to obtain the historical operating power of photovoltaic grid-connected devices; According to the historical operating power, the new energy generation, power user load and charge and discharge of the energy storage module are predicted in the next dispatch cycle, and the corresponding predicted power generation, predicted load power and predicted charge and discharge power are obtained; The initial charge and discharge power of the energy storage module in the next dispatch cycle is determined based on the output of the traditional generator set, the predicted power generation and the predicted load power; Determine the compensated charge and discharge power of the energy storage module in the next dispatch cycle based on the predicted generation power, predicted load power and predicted charge and discharge power; Select one or more energy storage units from the energy storage module to implement scheduling control of initial charge and discharge power and compensation charge and discharge power. 2. The power scheduling optimization method based on synchronous collection of photovoltaic grid-connected data according to claim 1, characterized in that the historical operating power includes historical power generation of new energy power generation, historical load power of power users and distributed power. Historical charge and discharge power of energy storage modules in new energy systems; Based on the historical power generation prediction analysis of new energy power generation, the predicted power generation for the next dispatch cycle is obtained; Based on the historical load power prediction analysis of electricity users, the predicted load power of the next dispatch period is obtained; And, based on the historical charge and discharge power prediction analysis of the energy storage module in the distributed new energy system, the predicted charge and discharge power of the next dispatch cycle is obtained. 3. The power scheduling optimization method based on synchronous collection of photovoltaic grid-connected data according to claim 1, characterized in that the calculation formula of the initial charge and discharge power of the energy storage module in the next scheduling cycle is specifically: in, Indicates the initial charging and discharging power of the energy storage module in the next scheduling period T+1. The negative value is the charging power, and the positive value is the discharging power;/> Represents the predicted load power of electricity users in the next dispatch period T+1; P _G represents the output of traditional generating units;/> Indicates the predicted power generation of new energy power generation in the next dispatch period T+1. 4. The power scheduling optimization method based on synchronous collection of photovoltaic grid-connected data according to claim 1, characterized in that the compensation charge and discharge power calculation formula of the energy storage module in the next scheduling cycle is specifically: in, Represents the compensated charge and discharge power of the energy storage module in the next scheduling period T+1; K represents the compensation coefficient, the value range is (0,1); α represents the predicted balance deviation rate;/> Indicates the predicted charge and discharge power of the energy storage module in the next scheduling period T+1;/> Indicates the initial charging and discharging power of the energy storage module in the next scheduling period T+1. The negative value is the charging power, and the positive value is the discharging power;/> Represents the predicted load power of electricity users in the next dispatch period T+1; P _G represents the output of traditional generating units;/> Indicates the predicted power generation of new energy power generation in the next dispatch period T+1. 5. The power scheduling optimization method based on synchronous collection of photovoltaic grid-connected data according to claim 1, characterized in that, one or more energy storage units are selected from the energy storage module to realize initial charge and discharge power and compensation charge and discharge power. The specific process of scheduling control is: Select at least one first energy storage unit from the energy storage module to implement scheduling control of initial charge and discharge power; And, selecting at least one second energy storage unit from the energy storage module to implement scheduling control to compensate for charging and discharging power. 6. The power scheduling optimization method based on synchronous collection of photovoltaic grid-connected data according to claim 1, characterized in that, one or more energy storage units are selected from the energy storage module to realize initial charge and discharge power and compensation charge and discharge power. The specific process of scheduling control is: The vector sum of the initial charge and discharge power and the compensation charge and discharge power is used as the total charge and discharge power of the energy storage module; Select one or more energy storage units from the energy storage module to implement scheduling control of the total charge and discharge power. 7. The power scheduling optimization method based on synchronous collection of photovoltaic grid-connected data according to claim 1, characterized in that the duration of the scheduling cycle ranges from 0.25h to 2h. 8. A power scheduling optimization system based on synchronous collection of photovoltaic grid-connected data, which is characterized by: The data acquisition module is used to synchronously collect the power data of distributed photovoltaic grid-connected devices using time stamps to obtain the historical operating power of photovoltaic grid-connected devices; The power prediction module is used to predict the new energy generation, electricity user load and the charge and discharge of the energy storage module in the next dispatch cycle based on the historical operating power, and obtain the corresponding predicted power generation, predicted load power and predicted charge and discharge power. ; The power calculation module is used to determine the initial charge and discharge power of the energy storage module in the next dispatch cycle based on the output of the traditional generator set, predicted power generation and predicted load power; The compensation analysis module is used to determine the compensated charge and discharge power of the energy storage module in the next dispatch cycle based on the predicted power generation, predicted load power and predicted charge and discharge power; The scheduling control module is used to select one or more energy storage units from the energy storage module to implement scheduling control of initial charge and discharge power and compensation charge and discharge power. 9. A computer terminal, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that when the processor executes the program, any one of claims 1-7 is implemented. The power scheduling optimization method based on the synchronous collection of photovoltaic grid-connected data described in the item. 10. A computer-readable medium with a computer program stored thereon, characterized in that, when the computer program is executed by a processor, the synchronous collection of photovoltaic grid-connected data as described in any one of claims 1-7 can be realized Power scheduling optimization method.