Micro-grid multi-energy complementary collaborative optimization system and method

Abstract

The micro-grid multi-energy complementary collaborative optimization method comprises the steps of obtaining load data and meteorological data corresponding to each power generation device, and determining a power generation instruction according to the load data and the meteorological data corresponding to each power generation device; controlling a plurality of power generation devices to collect electric energy according to the power generation instruction and storing the electric energy into a power supply corresponding to each power generation device; acquiring actual power generation power corresponding to each power generation device, and determining a discharge instruction according to the load data and all the actual power generation power; and collecting and storing electric energy meeting a preset condition in all the batteries, and releasing the electric energy according to the discharging instruction. By analyzing the meteorological data, the actual power generation power of the power generation equipment is improved to the maximum extent, and power supply is more reasonable, stable, accurate and efficient.

Description

Technical Field

[0001] This invention relates to the field of new energy power generation technology, specifically to a microgrid multi-energy complementary and coordinated optimization system and method. Background Technology

[0002] Compared to traditional fossil fuels and other resources, renewable energy sources such as solar, wind, hydro, and thermal power are inexhaustible. In terms of power generation, new energy power generation methods typically include solar power, wind power, hydropower, and thermal power. Through distributed power sources in microgrids, various energy sources are used to centrally store and convert electrical energy, forming small-scale power systems.

[0003] A microgrid consists of distributed power sources, energy storage devices, energy conversion devices, and load monitoring devices. It can operate independently as a power supply system or be connected to an external power grid. When the power load in a microgrid increases and the total power stored in the distributed power sources and energy storage devices is insufficient to support the current load demand, it is necessary to purchase electricity from an external power grid company to support the load operation; otherwise, the microgrid will experience a power shortage.

[0004] However, current new energy power generation methods are overly dependent on the natural environment and have various drawbacks. For example, solar power generation depends on sunlight, while wind power generation has high requirements for climate and geographical limitations. Under the influence of a single device or weather, the stable power supply of the microgrid cannot be guaranteed. Summary of the Invention

[0005] Therefore, the present invention provides a microgrid multi-energy complementary collaborative optimization system and method, which aims to solve the problem of unstable power supply in microgrids in the prior art.

[0006] To achieve the above objectives, in a first aspect, the present invention provides a microgrid multi-energy complementary and coordinated optimization system, comprising: a power generation module, an energy storage module, and a monitoring and regulation module; The power generation module is used to control multiple power generation devices to collect electrical energy and store it in the power supply corresponding to each power generation device according to the power generation instructions issued by the monitoring and regulation module. The energy storage module is used to collect and store electrical energy that meets preset conditions from all power sources; and release electrical energy according to the discharge command issued by the monitoring and regulation module. The monitoring and regulation module is used to acquire load data and meteorological data corresponding to each power generation device, determine power generation instructions based on the load data and meteorological data corresponding to each power generation device, and control the operation of the power generation module according to the power generation instructions; it also acquires the actual power generation of each power generation device, determines the discharge instructions based on the load data and all actual power generation, and controls the energy storage module to release electrical energy according to the discharge instructions.

[0007] The beneficial effects of the microgrid multi-energy complementary and coordinated optimization system provided by this invention are as follows: Compared with the prior art, this invention integrates multiple power generation devices, enabling mutual support among energy sources to improve the stability of the microgrid's power supply capacity from a multi-energy perspective. Starting with natural conditions, by analyzing meteorological data, the actual power generation capacity of the power generation devices is maximized, saving initial hardware deployment costs and making the power supply more rational, stable, precise, and efficient. Simultaneously, under the influence of natural conditions, for power supply support that cannot be met, energy storage modules can further provide stable power support to the microgrid's load modules. Furthermore, by dynamically adjusting the power generation devices and energy storage batteries, energy waste is reduced and resource utilization is improved.

[0008] Based on the above solution, the present invention can be further improved as follows.

[0009] Furthermore, the multiple power generation devices include at least two of the following: solar power generation devices, wind power generation devices, hydropower generation devices, thermal power generation devices, tidal power generation devices, and nuclear power generation devices.

[0010] Furthermore, the power generation command is determined based on the load data and the meteorological data corresponding to each power generation device. Specifically, the meteorological data includes meteorological forecast data and actual meteorological data; the meteorological correlation coefficient corresponding to each power generation device is obtained based on the meteorological forecast data and the corresponding actual meteorological data; and the power generation command is determined based on the load data and all meteorological correlation coefficients.

[0011] Furthermore, the discharge command is determined based on the load data and all actual power generation. Specifically, when the power difference between the sum of all actual power generation and the load data is less than a first preset value, the sum of the absolute value of the power difference and the first preset value is used as the power value in the discharge command.

[0012] Furthermore, the energy storage module is also used to obtain the load amplitude based on the load data, and when the load amplitude exceeds the second preset value, the voltage is adjusted through STATCOM.

[0013] The beneficial effects of adopting the above scheme are as follows: Based on load fluctuations, the power demand fluctuations of the load modules in the microgrid are determined. When power demand fluctuations are large, there may be a power source conversion between power generation equipment and energy storage equipment. Therefore, for the intermittent power conversion and rapid load changes, STATCOM dynamic reactive power compensation can significantly improve the voltage stability, reactive power compensation capability, and power quality of the microgrid.

[0014] Secondly, the present invention provides a multi-energy complementary and coordinated optimization method for microgrids, comprising: Acquire load data and meteorological data corresponding to each power generation device; determine power generation instructions based on the load data and meteorological data corresponding to each power generation device; control multiple power generation devices to collect electrical energy and store it in the power supply corresponding to each power generation device according to the power generation instructions; Obtain the actual power generation of each power generation device, and determine the discharge command based on the load data and all actual power generation. It collects and stores electrical energy from all batteries that meets preset conditions, and releases electrical energy according to discharge commands.

[0015] Based on the above solution, the present invention can be further improved as follows.

[0016] Furthermore, the multiple power generation devices include at least two of the following: solar power generation devices, wind power generation devices, hydropower generation devices, thermal power generation devices, tidal power generation devices, and nuclear power generation devices.

[0017] Furthermore, the power generation command is determined based on the load data and the meteorological data corresponding to each power generation device. Specifically, the meteorological data includes meteorological forecast data and actual meteorological data; the meteorological correlation coefficient corresponding to each power generation device is obtained based on the meteorological forecast data and the corresponding actual meteorological data; and the power generation command is determined based on the load data and all meteorological correlation coefficients.

[0018] Furthermore, the discharge command is determined based on the load data and all actual power generation. Specifically, when the power difference between the sum of all actual power generation and the load data is less than a first preset value, the sum of the absolute value of the power difference and the first preset value is used as the power value in the discharge command.

[0019] Furthermore, it also includes obtaining the load amplitude based on the load data, and adjusting the voltage via STATCOM when the load amplitude exceeds a second preset value.

[0020] It should be noted that the beneficial effects of the technical solution of the second aspect of the present invention and the corresponding possible implementation can be found in the above description of the technical effects of the first aspect and its corresponding possible implementation, and will not be repeated here. Attached Figure Description

[0021] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a system architecture diagram of a microgrid multi-energy complementary and collaborative optimization system according to the present invention. Detailed Implementation

[0022] To gain a better understanding of the technical solution and beneficial effects of the present invention, the technical solution of the present invention and its beneficial effects are described in detail below with reference to the accompanying drawings.

[0023] Example 1, Figure 1 This is a system architecture diagram of a microgrid multi-energy complementary and cooperative optimization system according to the present invention, such as... Figure 1 As shown, a microgrid multi-energy complementary and coordinated optimization system of the present invention includes: a power generation module, an energy storage module, and a monitoring and regulation module; The power generation module and energy storage module are respectively connected to the AC bus. The monitoring and regulation module is connected to both the power generation module and the energy storage module, enabling the transmission of command and data between the power generation module and the monitoring and regulation module, as well as between the energy storage module and the monitoring and regulation module. In this embodiment of a microgrid multi-energy complementary and coordinated optimization system, the load module is connected to the AC bus and obtains electrical energy from the AC bus.

[0024] The power generation module includes multiple power generation devices and corresponding DC energy storage power supplies. The DC energy storage power supplies are connected to the AC bus via inverters. Based on energy type, power generation devices can be categorized as: solar power generation devices, wind power generation devices, hydropower generation devices, thermal power generation devices, tidal power generation devices, and nuclear power generation devices. To achieve multi-energy complementarity, the power generation devices in a microgrid must include at least two of the above-mentioned types.

[0025] Energy storage modules can be divided into single-mode energy storage and hybrid energy storage. Single-mode energy storage generally uses only lithium battery packs. This method is limited by the battery material, resulting in low cycle efficiency and thus low charge / discharge efficiency and slow response speed. Hybrid energy storage combines capacity-type main energy storage with power-type auxiliary energy storage, using a combination of lithium battery packs and supercapacitors to improve the response efficiency of the energy storage module. The battery pack in the energy storage module is a DC power source, similar to power generation equipment, and needs to be connected to the AC bus via an inverter.

[0026] The monitoring and regulation module is used to acquire data from various power generation devices in the microgrid, monitor the device status, and perform control and regulation.

[0027] This embodiment focuses on a specific independent residential area. The microgrid's power generation modules consist of solar photovoltaic panels on the rooftops (solar power generation), wind turbines in open spaces a certain distance from the residential area, and waste-to-energy generators (thermal power generation) near a garbage collection station a certain distance from the residential area. Energy storage modules are composed of a combination of lithium battery packs and supercapacitors. Household appliances, property facilities (streetlights, central air conditioning, etc.), and parking lot charging stations within the residential area serve as load modules in the microgrid. The microgrid's energy management system (monitoring and regulation module) regulates and controls all of the above components.

[0028] The process of obtaining load data is as follows: Specifically, at fixed time intervals, actual electricity consumption data for the previous fixed time interval is obtained from the microgrid energy management system. In this embodiment, electricity consumption data for the previous week is obtained every week, including actual electricity consumption data for each hour of each day from Monday to Sunday. It should be noted that during most of spring to summer, the overall actual electricity consumption data for each week shows an upward trend compared to the previous week. Therefore, when obtaining load data, it is necessary to consider the electricity consumption data error, that is, the load data includes actual electricity consumption data and the electricity consumption data error, which is the variation error of the actual electricity consumption data in each fixed time interval.

[0029] Meteorological data includes both forecast data and actual meteorological data. The process of obtaining meteorological data for each power generation unit is as follows: At fixed time intervals (the fixed time interval here is different from the time interval of the actual electricity consumption data mentioned above), the actual meteorological data of the current moment and the meteorological forecast data of the next interval are acquired by the sensor controllers deployed on each power generation device. In this embodiment, the actual meteorological data is acquired every hour, and the meteorological forecast data one hour later is acquired simultaneously. The advantage of doing so is that different actual meteorological data are acquired periodically for different power generation devices, and the meteorological coefficients corresponding to different devices can be more accurate and stable, thereby further improving the synergistic and complementary optimization of actual power generation. Taking a solar photovoltaic panel as an example, the process of determining the meteorological correlation coefficient of the solar photovoltaic panel based on the actual meteorological data of the current moment and the meteorological forecast data one hour later is as follows: The meteorological correlation coefficient is determined by the first formula as follows: ; Where C represents the meteorological correlation coefficient of the solar photovoltaic panel, x represents the sub-meteorological correlation coefficient, w represents the weight corresponding to the sub-meteorological correlation coefficient, and i is a number, i=1,2,3,...,n, indicating that there are n sub-meteorological correlation coefficients. Specifically, the sub-meteorological correlation coefficients are divided into temperature correlation coefficient, light intensity correlation coefficient, wind force correlation coefficient, wind direction correlation coefficient, precipitation correlation coefficient, dust obstruction correlation coefficient, water level amplitude correlation coefficient, etc. The specific correlation coefficients are added or modified according to different power generation equipment.

[0030] Taking temperature as an example, the temperature correlation coefficient is determined by the second formula as follows: ; Where x is the temperature correlation coefficient, μ is the coefficient relating meteorological conditions and electric current (here, the coefficient relating temperature and electric current); T c T represents the temperature in actual meteorological data. p T represents the temperature in meteorological forecast data. stcThis is the standard test temperature. Similarly, substituting μ into the coefficient relating wind force and current, T... c Substituting the wind force from the actual meteorological data, T p Substitute the wind force from the meteorological forecast data, T stc By substituting the wind force from the standard test, the wind force correlation coefficient can also be calculated. Other sub-meteorological correlation coefficients can be calculated using the second formula based on standard meteorological data, actual meteorological data, and meteorological forecast data. Similarly, by substituting the sub-meteorological correlation coefficients corresponding to the wind turbine cluster and their corresponding weights into the first formula, the meteorological correlation coefficients corresponding to the wind turbine cluster can also be obtained. Likewise, the meteorological correlation coefficients corresponding to other power generation equipment can be calculated using both the first and second formulas.

[0031] The process of determining the power generation command based on the load data and the meteorological data corresponding to each of the above-mentioned power generation devices is as follows: Actual power generation of solar photovoltaic panels = Rated power generation of solar photovoltaic panels The meteorological correlation coefficient C for solar photovoltaic panels. Similarly, the actual power generation of a wind turbine cluster equals the rated power generation of the wind turbine unit. The meteorological correlation coefficient C of the wind turbine cluster; the actual power generation of the waste generator = the rated power generation of the waste generator. Meteorological correlation coefficient C for garbage generators.

[0032] The difference between the sum of the actual power generated by the solar photovoltaic panels and the wind turbine generator group and the load data is compared. If there is a difference between the total actual power generated and the load data (or the total actual power generated is less than the load data), it indicates that the sum of the power generated by the solar photovoltaic panels and the wind turbine generator group is insufficient to maintain the stable operation of the load module's power consumption. In this case, it is necessary to issue power generation commands to the solar photovoltaic panels and the wind turbine generator group, and also to issue power generation commands to the waste generator at the waste station to compensate for the difference between the actual power generated and the load data. It should be noted that although incinerating waste through waste generators can reduce the contamination of bacteria and viruses in the waste and the emission of harmful gases, the technical cost of waste generators is relatively high. Therefore, in this embodiment, solar photovoltaic panels and wind turbine generator groups are used as the main power generation source, and waste generators are used as an auxiliary power generation source to form a "solar wind-waste recycling" system. Through the regulation of the energy management system, the power output efficiency can be improved while maximizing the stability of the load module's operation in the microgrid.

[0033] The process of controlling multiple power generation devices to collect electrical energy and store it in the power source corresponding to each power generation device according to the power generation command issued by the monitoring and adjustment module is as follows.

[0034] like Figure 1Each power generation device also includes a DC energy storage power source (corresponding to Power Source 1, Power Source 2, ..., etc. in the diagram) to collect excess electrical energy from the power generation device. When the electrical energy in the DC energy storage power source of the power generation device exceeds a certain proportion, the electrical energy in the DC energy storage power source can be stored in the energy storage module according to the energy storage module. Generally speaking, the capacity of the DC energy storage power source of the power generation device is relatively small compared to the power capacity in the energy storage module. When the capacity of the DC energy storage power source of the power generation device exceeds 50%, the remaining electrical energy is stored in the battery of the energy storage module.

[0035] The actual power generation of solar photovoltaic panels, wind turbine generator groups, and waste generators is obtained. If the power generation of all actual power generation cannot meet the requirements of the load data, that is, when the power difference between the sum of all actual power generation and the load data is less than the first preset value, the sum of the absolute value of the power difference and the first preset value is used as the power value in the discharge command.

[0036] Generally, to improve system stability, a power generation error value, i.e., a first preset value, is set. This first preset value can be adjusted according to actual production and daily life needs, or it can be dynamically adjusted by dynamically updating the total actual power generation and load data. For example: The actual electricity consumption data of the residential area from 2 PM to 3 PM the previous day was 1000 kW. Considering a data error of 100 kW, the load data of the residential area from 2 PM to 3 PM the current day is 1100 kW, and the first preset value is set to 100 kW. During this period, the actual power generation of the solar photovoltaic panels, affected by meteorological data, is 750 kW, and the actual power generation of the wind turbine group, affected by meteorological data, is 350 kW. The garbage generator did not generate any power due to insufficient garbage that day, so its actual power generation is recorded as 0 kW. The total actual power generation of all power generation equipment is 1100 kW. The absolute value of the difference between the total actual power generation (1100 kW) and the load data (1100 kW) (0 kW) is less than the first preset value (100 kW). Therefore, the power value in the discharge command is 100 kW. Based on the power value of the discharge command, the energy management system controls the energy storage module to release 100 kW of power.

[0037] Furthermore, when the energy management system controls the power generation equipment to generate electricity or controls the energy storage module to discharge, voltage fluctuations may occur due to power fluctuations in the power generation equipment, or voltage instability may result from abnormal circuitry. To further stabilize the power supply in the microgrid, optionally, in this embodiment, the STATCOM and energy storage module coordinate with each other to quickly and continuously adjust reactive power with a response time in the millisecond range, effectively responding to rapid changes in the system. Figure 1As shown, the STATCOM is connected in parallel with the energy storage module.

[0038] The following is the definition of STATCOM: STATCOM stands for Static Synchronous Compensator, which is a parallel reactive power compensation device that can generate or absorb reactive power, and its output can be varied to control specific parameters in the power system.

[0039] Specifically, the load amplitude is determined based on the fluctuation of the load data. The load amplitude can be a numerical amplitude or a percentage amplitude. The data amplitude is determined by the difference between the load data before and after the change, and the percentage amplitude is determined by the ratio of the difference in load data to the load data before the change. In this embodiment, for the load amplitude in a residential area, the second preset value is set to 10%. When the load amplitude exceeds 10%, the voltage is adjusted via STATCOM.

[0040] The beneficial effects of the microgrid multi-energy complementary and coordinated optimization system provided by this invention are as follows: Compared with the prior art, this invention integrates multiple power generation devices, enabling mutual support among energy sources from a multi-energy perspective to improve the stability of the microgrid's power supply capacity. Starting with natural conditions, by analyzing meteorological data, the actual power generation capacity of each power generation device is accurately determined, making the power supply more rational, stable, precise, and efficient. Simultaneously, under the influence of natural conditions, for power supply support that cannot be met, energy storage modules can further provide stable power support to the microgrid's load modules. Furthermore, by dynamically adjusting the power generation devices and energy storage batteries, energy waste is reduced and resource utilization is improved.

[0041] Example 2: This invention provides a multi-energy complementary and coordinated optimization method for microgrids, comprising: Acquire load data and meteorological data corresponding to each power generation device; determine power generation instructions based on the load data and meteorological data corresponding to each power generation device; control multiple power generation devices to collect electrical energy and store it in the power supply corresponding to each power generation device according to the power generation instructions; Obtain the actual power generation of each power generation device, and determine the discharge command based on the load data and all actual power generation. It collects and stores electrical energy from all batteries that meets preset conditions, and releases electrical energy according to discharge commands.

[0042] Based on the above solution, the present invention can be further improved as follows.

[0043] Furthermore, the multiple power generation devices include at least two of the following: solar power generation devices, wind power generation devices, hydropower generation devices, thermal power generation devices, tidal power generation devices, and nuclear power generation devices.

[0044] Furthermore, the power generation command is determined based on the load data and the meteorological data corresponding to each power generation device. Specifically, the meteorological data includes meteorological forecast data and actual meteorological data; the meteorological correlation coefficient corresponding to each power generation device is obtained based on the meteorological forecast data and the corresponding actual meteorological data; and the power generation command is determined based on the load data and all meteorological correlation coefficients.

[0045] Furthermore, the discharge command is determined based on the load data and all actual power generation. Specifically, when the power difference between the sum of all actual power generation and the load data is less than a first preset value, the sum of the absolute value of the power difference and the first preset value is used as the power value in the discharge command.

[0046] Furthermore, it also includes obtaining the load amplitude based on the load data, and adjusting the voltage via STATCOM when the load amplitude exceeds a second preset value.

[0047] The present invention proposes a microgrid multi-energy complementary and coordinated optimization method, which can realize a microgrid multi-energy complementary and coordinated optimization system as described in the above embodiments, and has the same technical effects as the above embodiments.

[0048] It should be noted that the terms "first," "second," etc., used in the specification of this application are used to distinguish similar objects and do not imply a specific order or sequence. Where appropriate, the order of use of similar objects may be interchanged so that the embodiments of this application described herein can be implemented in an order other than that shown or described.

[0049] Although the present invention has been described using the above preferred embodiments, it is not intended to limit the scope of protection of the present invention. Any changes and modifications made by those skilled in the art to the above embodiments without departing from the spirit and scope of the present invention shall still fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be defined by the claims.

Claims

1. A microgrid multi-energy complementary and coordinated optimization system, characterized in that, include: Power generation module, energy storage module, and monitoring and control module; The power generation module is used to control multiple power generation devices to collect electrical energy and store it in the power supply corresponding to each power generation device according to the power generation instructions issued by the monitoring and regulation module. The energy storage module is used to collect and store electrical energy from all power sources that meets preset conditions; The electrical energy is released according to the discharge command issued by the monitoring and adjustment module; The monitoring and regulation module is used to acquire load data and meteorological data corresponding to each power generation device, determine power generation instructions based on the load data and meteorological data corresponding to each power generation device, and control the operation of the power generation module according to the power generation instructions; it also acquires the actual power generation of each power generation device, determines the discharge instructions based on the load data and all actual power generation, and controls the energy storage module to release electrical energy according to the discharge instructions.

2. The microgrid multi-energy complementary and coordinated optimization system as described in claim 1, characterized in that, Multiple power generation devices include: At least two of the following: solar power generation equipment, wind power generation equipment, hydropower generation equipment, thermal power generation equipment, tidal power generation equipment, and nuclear power generation equipment.

3. The microgrid multi-energy complementary and coordinated optimization system as described in claim 1, characterized in that, The power generation command is determined based on the load data and the meteorological data corresponding to each power generation unit, specifically as follows: Meteorological data includes both forecast data and actual meteorological data. The meteorological correlation coefficient for each power generation device is obtained based on the meteorological forecast data and the corresponding actual meteorological data. The power generation command is then determined based on the load data and all meteorological correlation coefficients.

4. The microgrid multi-energy complementary and coordinated optimization system as described in claim 1, characterized in that, The discharge command is determined based on the load data and all actual power generation, specifically as follows: When the sum of all actual generated power and the power difference of the load data are less than the first preset value, the sum of the absolute value of the power difference and the first preset value is used as the power value in the discharge command.

5. A microgrid multi-energy complementary and coordinated optimization system as described in claim 1, characterized in that, The energy storage module is also used to obtain the load amplitude based on the load data. When the load amplitude exceeds the second preset value, the voltage is adjusted through STATCOM.

6. A multi-energy complementary and coordinated optimization method for microgrids, characterized in that, include: Acquire load data and meteorological data corresponding to each power generation device, and determine the power generation command based on the load data and meteorological data corresponding to each power generation device; According to the power generation command, control multiple power generation devices to collect electrical energy and store it into the power source corresponding to each power generation device; Obtain the actual power generation of each power generation device, and determine the discharge command based on the load data and all actual power generation. It collects and stores electrical energy from all batteries that meets preset conditions, and releases electrical energy according to discharge commands.

7. The microgrid multi-energy complementary and coordinated optimization method as described in claim 6, characterized in that, Multiple power generation devices include: At least two of the following: solar power generation equipment, wind power generation equipment, hydropower generation equipment, thermal power generation equipment, tidal power generation equipment, and nuclear power generation equipment.

8. The microgrid multi-energy complementary and coordinated optimization method as described in claim 6, characterized in that, The power generation command is determined based on the load data and the meteorological data corresponding to each power generation unit, specifically as follows: Meteorological data includes both forecast data and actual meteorological data. The meteorological correlation coefficient for each power generation device is obtained based on the meteorological forecast data and the corresponding actual meteorological data. The power generation command is then determined based on the load data and all meteorological correlation coefficients.

9. The microgrid multi-energy complementary and coordinated optimization method as described in claim 6, characterized in that, The discharge command is determined based on the load data and all actual power generation, specifically as follows: When the sum of all actual generated power and the power difference of the load data are less than the first preset value, the sum of the absolute value of the power difference and the first preset value is used as the power value in the discharge command.

10. The microgrid multi-energy complementary and coordinated optimization method as described in claim 6, characterized in that, It also includes obtaining the load amplitude based on the load data, and adjusting the voltage via STATCOM when the load amplitude exceeds the second preset value.

Images