Multi-input-source power system control method and device

Abstract

The invention relates to the technical field of energy control, in particular to a multi-input-source electric power system control method, which comprises the following steps of: connecting wind power, hydraulic power, solar energy and / or fuel gas and fuel oil power generation equipment into an energy tribe to obtain power generation data correspondingly generated by wind power, hydraulic power, solar energy and / or fuel gas and fuel oil power generation, obtaining daily electricity demand data corresponding to the energy tribe; acquiring daily extra power consumption data corresponding to the energy tribe, and determining whether the energy tribe has residual generated power or not based on the power generation data, the daily power consumption demand data and the daily extra power consumption; and if yes, the charging priority of the energy storage battery pack in the energy tribe is called, and the energy storage battery pack is charged by the residual electric energy based on the charging priority. According to the invention, the management efficiency of the multi-input-source power system can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of energy control, and in particular to a method for controlling a power system with multiple input sources. Background Art

[0002] As the global demand for sustainable energy grows and the focus on reducing carbon emissions grows, it is critical to develop efficient and reliable multi-energy access and coordination control systems, especially in the face of natural disasters, wars or remote areas of emergency, such systems can provide critical support and services.

[0003] Therefore, a power system control method that can integrate multiple renewable energy sources and new energy vehicles as distributed energy has been proposed; however, current technology faces challenges in how to effectively integrate multiple energy forms such as wind power, hydropower, solar power, and possible gas and oil power generation equipment, and how to realize intelligent controllers to achieve efficient management of electrical energy.

[0004] From the above, we can see that how to achieve efficient management of power systems with multiple input sources remains to be solved. Summary of the invention

[0005] In order to improve the management efficiency of a power system with multiple input sources, the present application provides a control method for a power system with multiple input sources.

[0006] In a first aspect, the present application provides a multi-input source power system control method, which adopts the following technical solution:

[0007] A method for controlling a power system with multiple input sources, comprising: connecting wind, water, solar and / or gas-fired oil-fired power generation equipment to an energy tribe, obtaining power generation data corresponding to the wind, water, solar and / or gas-fired oil-fired power generation, and obtaining daily power demand data corresponding to the energy tribe; obtaining daily additional power consumption data corresponding to the energy tribe, and determining whether the energy tribe has surplus power generation based on the power generation data, the daily power demand data and the daily additional power consumption; if there is surplus power, retrieving the charging priority of an energy storage battery group in the energy tribe, and charging the energy storage battery group with the remaining electric energy based on the charging priority.

[0008] By adopting the above technical solution, by collecting and analyzing power generation data, power demand data and additional power consumption data, the supply and demand situation of the power system can be accurately evaluated, and the energy dispatch strategy can be dynamically adjusted according to real-time data to ensure the effective use of power resources; in addition, by setting the charging priority, it can be ensured that the energy storage battery pack is charged first when there is surplus power generation. By charging the energy storage battery pack, it is possible to prepare for possible emergencies, so that power can be released in time when needed to ensure the power supply of key facilities. Finally, through the comprehensive analysis of power generation data and power demand data, the energy utilization efficiency can be optimized and waste can be reduced, thereby improving the management efficiency of the power system with multiple input sources.

[0009] Optionally, the method also includes: obtaining recent meteorological data corresponding to the energy tribe, wherein the recent meteorological data includes meteorological data corresponding to wind power, water power, and light; calling a pre-trained electric energy prediction model, inputting the recent meteorological data into the electric energy prediction model, and obtaining corresponding predicted power generation data; real-time monitoring of demand data of energy tribe users, and scheduling based on the predicted power generation data, the demand data, and pre-set priorities.

[0010] By adopting the above technical solutions and using the electric energy forecasting model to make predictions, intelligent power management is achieved for weather forecasting, power generation forecasting and user demand monitoring. On the one hand, it not only improves the power utilization efficiency of the energy tribe, but also enhances the flexibility and reliability of the system. On the other hand, especially in the face of large fluctuations in renewable energy, it can better meet user needs and ensure the stability of power supply.

[0011] Optionally, after obtaining recent meteorological data corresponding to the energy tribe, the method also includes: determining whether extreme weather exists based on the recent meteorological data; if extreme weather exists, generating a corresponding adjustment strategy, and adjusting the charging priority and discharging priority of the energy storage battery group based on the adjustment strategy; determining a target time period corresponding to the extreme weather, and determining the necessary basic power corresponding to the necessary facilities of the energy tribe based on the target time period; and charging the energy storage battery group of the energy tribe until the stored power corresponding to the energy storage battery group is greater than the necessary basic power.

[0012] By adopting the above technical solution and analyzing recent meteorological data, it is possible to identify extreme weather conditions (such as strong winds, heavy rains, heavy snow, etc.) that may affect power generation capacity, and generate adjustment strategies to optimize the charging and discharging behavior of energy storage batteries, that is, to adjust the charging and discharging sequence of energy storage batteries, so as to ensure that the key facilities of the energy tribe can obtain sufficient power support and reduce the risk of power outages; at the same time, before the extreme weather arrives, the energy storage battery pack is fully charged as much as possible to reach the necessary basic power level. Even if the external power generation equipment is affected, the energy storage battery can provide sufficient backup power to ensure basic needs.

[0013] Optionally, the method also includes: retrieving historical electricity consumption data of the energy tribe, wherein the historical electricity consumption data associates the electricity consumption of the energy tribe with a corresponding time period; retrieving a pre-trained electricity prediction model, inputting the historical electricity consumption data into the electricity prediction model, and determining the peak electricity consumption period corresponding to the energy tribe; and scheduling the electricity transmission direction of the energy tribe based on the peak electricity consumption period.

[0014] By adopting the above technical solution, the power forecasting model can predict future power demand based on historical data, especially during peak power demand periods, and determine which time periods the energy tribe has high power demand, which can facilitate advance planning to ensure sufficient power supply during peak power demand periods. In addition, based on the prediction results of peak power demand periods, reasonable scheduling can be used to optimize power distribution during peak power demand periods to avoid power shortages and improve the operating efficiency of the power system.

[0015] Optionally, the method also includes: obtaining the battery health index corresponding to the energy storage battery pack of the energy tribe at intervals; calling a preset battery health threshold to determine whether the battery health index is greater than the battery health threshold; if not, issuing an alarm message to remind the energy storage battery pack to be inspected and replaced; if so, obtaining the health index difference between the battery health index and the battery health threshold, and if the health index difference is less than the set minimum difference, reducing the charge and discharge depth of the energy storage battery pack.

[0016] By adopting the above technical solution, by regularly monitoring the battery health index and taking corresponding maintenance measures according to the battery health status, it is helpful to improve the operating efficiency and reliability of the energy storage system; it can ensure that the battery works in the best condition, reduce unnecessary maintenance costs, and take timely measures when the battery performance declines, thereby ensuring the stable operation of the entire power system.

[0017] Optionally, the method further includes: if there is no surplus, adjusting the discharge priority corresponding to the energy tribe energy storage battery group; and supplying power to the equipment of the energy tribe based on the discharge priority.

[0018] By adopting the above technical solution, by analyzing the power supply and demand situation and adjusting the discharge priority of the energy storage battery pack according to the actual situation, power scheduling can be optimized, which will help ensure the power supply of key facilities when the power supply is insufficient and improve the operating efficiency and reliability of the entire power system.

[0019] Optionally, the energy tribe's new energy vehicles support V2G, V2L, V2V and V2H protocols, and bidirectional power flow between the new energy vehicles and the energy tribe's power grid, loads, other vehicles and homes. The method also includes: determining the power status of the target vehicle and retrieving a pre-set transmission priority; adjusting the transmission direction of the electric energy based on the power status and the transmission priority.

[0020] By adopting the above technical solutions and managing the two-way power flow of new energy vehicles, the flexibility and reliability of the power system can be improved, ensuring that in the case of an imbalance between power supply and demand, power resources can be effectively dispatched to give priority to meeting the needs of key facilities and high-priority users, thereby improving the operating efficiency of the entire power system.

[0021] In a second aspect, the present application provides a multi-input source power system control device, which adopts the following technical solution:

[0022] A multi-input source power system control device, comprising:

[0023] The power generation data acquisition module connects wind, water, solar and / or gas and oil power generation equipment to the energy tribe to obtain the power generation data corresponding to the wind, water, solar and / or gas and oil power generation, and obtains the daily electricity demand data corresponding to the energy tribe;

[0024] A power generation surplus determination module is used to obtain daily additional power consumption data corresponding to the energy tribe, and determine whether the energy tribe has power generation surplus based on the power generation data, the daily power demand data and the daily additional power consumption;

[0025] The management module, if there is any surplus, retrieves the charging priority of the energy storage battery group in the energy tribe, and charges the energy storage battery group with the remaining electric energy based on the charging priority.

[0026] In a third aspect, the present application provides a multi-input source power system control method, which adopts the following technical solution:

[0027] A method for controlling a power system with multiple input sources comprises a processor, wherein a program of the method for controlling a power system with multiple input sources as described above is run in the processor.

[0028] In a fourth aspect, the present application provides a storage medium, which adopts the following technical solution:

[0029] A storage medium stores a program of any one of the above-mentioned methods for controlling a power system with multiple input sources.

[0030] In summary, the present application includes at least one of the following beneficial technical effects: by collecting and analyzing power generation data, power demand data and additional power consumption data, the supply and demand situation of the power system can be accurately evaluated, and the energy scheduling strategy can be dynamically adjusted according to real-time data to ensure the effective use of power resources; in addition, by setting charging priority, it can be ensured that the energy storage battery pack is charged first when there is surplus power generation. By charging the energy storage battery pack, it is possible to prepare for possible emergencies, so that electricity can be released in time when needed to ensure the power supply of key facilities. Finally, through comprehensive analysis of power generation data and power demand data, energy utilization efficiency can be optimized and waste can be reduced, thereby improving the management efficiency of power systems with multiple input sources. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 is a flow chart of a method for controlling a power system with multiple input sources according to an exemplary embodiment;

[0032] Figure 2 It is a structural block diagram of a multi-input source power system control device according to an exemplary embodiment. DETAILED DESCRIPTION

[0033] Embodiments of the present application are described in detail below, examples of which are shown in the accompanying drawings.

[0034] In the description of this specification, the description with reference to the terms "certain embodiments", "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiments or examples are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0035] The present application discloses a method for controlling a power system with multiple input sources. Figure 1 ,include:

[0036] S100, connect wind, water, solar and / or gas and oil power generation equipment to the energy tribe, obtain the power generation data corresponding to the wind, water, solar and / or gas and oil power generation, and obtain the daily electricity demand data corresponding to the energy tribe.

[0037] First of all, it is necessary to connect wind, hydro, solar and / or gas-fired fuel-fired power generation equipment to the energy tribe. These equipment can be centrally managed and regulated through intelligent controllers; and the intelligent controllers collect the power generation data generated by wind, hydro, solar and / or gas-fired fuel-fired power generation equipment in real time, including but not limited to the real-time power generation and power generation efficiency of each energy source; at the same time, the intelligent controllers also need to collect the daily electricity demand data of the energy tribe, including basic load and peak load conditions, as well as electricity demand within a specific time period.

[0038] S110, obtaining daily additional electricity consumption data corresponding to the energy tribe, and determining whether the energy tribe has surplus electricity based on power generation data, daily electricity demand data and daily additional electricity consumption.

[0039] Among them, the intelligent controller also needs to obtain the daily additional electricity consumption data of the energy tribe, such as the additional electricity demand that may be generated in special activities or emergencies; at the same time, the intelligent controller calculates the total power generation and total power consumption based on the power generation data, daily power demand data and daily additional power consumption data. If the power generation is greater than the total power consumption, it can be determined that there is a surplus of electricity.

[0040] S120: If there is any surplus, the charging priority of the energy storage battery group in the energy tribe is retrieved, and the remaining electric energy is used to charge the energy storage battery group based on the charging priority.

[0041] Among them, when it is determined that there is surplus electricity, the intelligent controller will call the charging priority of the energy storage battery group. It should be pointed out here that the charging priority is usually determined according to the status of the energy storage battery group (such as remaining power, health status, etc.) and the priority rules defined by the user. Then the intelligent controller charges the energy storage battery group according to the charging priority, giving priority to charging batteries with less remaining power or poor health status to ensure the effective use of power resources.

[0042] In addition, if there is no surplus, the method further includes: when there is no surplus electricity, first adjust the discharge priority corresponding to the energy tribe energy storage battery group, and then power the energy tribe equipment based on the discharge priority.

[0043] Wind, hydro, solar and / or gas-fired oil-fired power generation equipment are connected to the energy tribe. These equipment can be centrally managed and regulated by intelligent controllers. In addition, by collecting the power generation data generated by wind, hydro, solar and / or gas-fired oil-fired power generation equipment in real time, after collecting the daily power demand data of the energy tribe, as well as the daily additional power demand data of the energy tribe, such as the additional power demand that may be generated in special activities or emergencies, it is possible to determine whether there is surplus power generation in the first place. When it is determined that there is surplus power generation, the intelligent controller charges the energy storage battery group according to the charging priority, giving priority to charging batteries with less remaining power or poor health to ensure the effective use of power resources. At the same time, in the case of no surplus power generation, by adjusting the discharge priority, it can be ensured that key equipment is powered first, thereby giving priority to the operation of important facilities when the power supply is tight while reducing the power consumption of non-critical equipment. Based on the above process, the power supply and demand of the energy tribe can be reasonably balanced to ensure the smooth operation of the power system, thereby achieving the purpose of maximizing the overall efficiency of the power system.

[0044] In addition, in the energy tribe, the new energy vehicles of the energy tribe can support V2G, V2L, V2V and V2H protocols, thereby realizing the two-way flow of electric energy between the new energy vehicles and the power grid, loads, other vehicles and households of the energy tribe; for the energy tribe, this enables the new energy vehicles to serve not only as electricity consumers but also as temporary electricity suppliers, which helps to improve the flexibility and reliability of the entire power system, so the method also includes the following process:

[0045] S121, determine the power status of the target vehicle and retrieve the pre-set transmission priority.

[0046] Among them, by setting transmission priorities, it can be ensured that the needs of critical facilities and high-priority users are met first when power supply is tight.

[0047] S122, adjusting the transmission direction of electric energy based on the power status and the transmission priority.

[0048] Among them, by adjusting the transmission direction of electric energy through intelligent controllers, the utilization efficiency of electric energy can be optimized and ensure that power resources are reasonably allocated to the users or facilities that need them most.

[0049] Therefore, in the case of an imbalance in electricity supply and demand, by executing steps S121 to S122, it is possible to effectively dispatch electricity resources and give priority to meeting the needs of key facilities and high-priority users, thereby improving the operating efficiency of the entire power system.

[0050] At the same time, in the process of managing the energy tribe, it is also necessary to predict the recent power generation of the energy tribe in order to plan in advance. The specific process includes:

[0051] S123, obtaining recent meteorological data corresponding to the energy tribe.

[0052] Among them, recent meteorological data include meteorological data corresponding to wind power, water power and light, which can affect the power generation efficiency of wind power, water power and solar power.

[0053] S124, calling a pre-trained electric energy prediction model, inputting recent meteorological data into the electric energy prediction model, and obtaining corresponding predicted power generation data.

[0054] Among them, the training process of the electric energy prediction model is as follows: during the training process, past meteorological data are first collected as a training set, and each data is associated with the corresponding electric energy generated, and the meteorological data is preprocessed, including data cleaning, missing value processing and standardization, etc., to determine the corresponding model framework; then the meteorological data can be used to train the model, the model will learn the distribution pattern of meteorological data, and use the validation set to adjust the model's hyperparameters, such as learning rate, number of trees, etc. During this period, grid search or random search methods can be used to find the optimal hyperparameters, and an effective model can be trained. The model training process ensures that the model can accurately distinguish and predict the electric energy that can be generated by each type of meteorological data, which helps to understand the power generation potential in the future, so as to better plan electricity use.

[0055] S125, monitors the demand data of energy tribe users in real time, and performs scheduling based on predicted power generation data, demand data and pre-set priorities.

[0056] In the case of limited electricity, the integration of weather forecasts, power generation forecasts and user demand monitoring can improve the efficiency of electricity use in energy tribes, especially in the face of large fluctuations in renewable energy, which can better meet user needs and ensure the stability of electricity supply.

[0057] When predicting the production capacity of the energy tribe, it is also necessary to predict the corresponding energy consumption of the energy tribe. The specific process is as follows:

[0058] S126, retrieve the historical electricity consumption data of the energy tribe.

[0059] Among them, historical electricity consumption data associates the energy tribe’s electricity consumption with the corresponding time period.

[0060] S127, retrieve a pre-trained power forecasting model, input historical power consumption data into the power forecasting model, and determine the peak power consumption period corresponding to the energy tribe.

[0061] Among them, future electricity demand can be predicted based on historical electricity consumption data, especially during peak electricity consumption periods, so that advance planning can be carried out to ensure sufficient electricity supply during peak electricity consumption periods.

[0062] S128, dispatching the electricity transmission direction of the energy tribe based on the peak electricity consumption period.

[0063] Through the above process, according to the prediction results of the peak power consumption period, reasonable scheduling can be used to optimize power distribution during the peak power consumption period to avoid power shortages and improve the operating efficiency of the power system.

[0064] In the near-term forecasting stage of the energy tribe, we also need to focus on whether extreme weather will occur in the near future. If so, we need to store the corresponding electric energy in advance for the energy tribe, including:

[0065] S1231, determine whether there is extreme weather based on recent meteorological data;

[0066] Among them, by analyzing recent meteorological data, it is possible to identify extreme weather conditions (such as strong winds, heavy rains, heavy snow, etc.) that may affect power generation capacity.

[0067] S1232: If extreme weather occurs, a corresponding adjustment strategy is generated, and the charging priority and the discharging priority of the energy storage battery group are adjusted based on the adjustment strategy.

[0068] It can ensure that during extreme weather, the energy tribe’s key facilities have access to sufficient power support to reduce the risk of power outages, and it is necessary to ensure that priority is given to power supply for key equipment and services, such as medical facilities and communications equipment.

[0069] S1233, determining a target time period corresponding to extreme weather, and determining the necessary basic electricity volume corresponding to necessary facilities of the energy tribe based on the target time period;

[0070] By determining the target time period, it can help plan the charging and discharging cycles of the energy storage batteries and ensure stable power supply during critical periods.

[0071] S1234, charging the energy storage battery pack of the energy tribe until the storage power corresponding to the energy storage battery pack is greater than the necessary basic power.

[0072] Among them, by ensuring that the stored electricity is greater than the necessary basic electricity, electricity can be continuously supplied to critical facilities and services even in harsh environments, thereby protecting the lives of residents and maintaining basic living conditions.

[0073] Finally, in the energy tribe, the energy storage battery pack is the main device for storing the energy tribe's electricity. The batteries in the energy storage battery pack need to be monitored. The specific process includes:

[0074] S101, obtaining the battery health index corresponding to the energy storage battery group of the energy tribe at intervals.

[0075] Among them, by regularly obtaining the battery health index of the energy storage battery pack, the health status of the battery can be continuously monitored.

[0076] S102, calling a preset battery health threshold to determine whether the battery health index is greater than the battery health threshold.

[0077] Among them, by comparing the battery health index with a preset battery health threshold, it can be determined whether the battery is in a good working condition.

[0078] S103, if not, an alarm message is issued to remind the energy storage battery pack to be checked and the battery to be replaced.

[0079] When the battery health index is lower than the preset threshold, the system will issue an alarm to remind maintenance personnel to take timely action, thus avoiding system interruption caused by battery failure.

[0080] S104: If yes, then obtain the health index difference between the battery health index and the battery health threshold, and if the health index difference is less than the set minimum difference, reduce the charge and discharge depth of the energy storage battery pack.

[0081] Among them, when the battery health index is greater than the battery health threshold, but the health index difference is small (that is, the battery performance is close to the threshold), the system will reduce the charge and discharge depth of the energy storage battery pack, which can help slow down the aging process of the battery, extend the battery life, and ensure the stable operation of the system.

[0082] The present application embodiment discloses a multi-input source power system control device, referring to Figure 1 , the devices include but are not limited to:

[0083] The power generation data acquisition module 200 connects the wind, water, solar and / or gas and oil power generation equipment to the energy tribe, and is used to obtain the power generation data corresponding to the wind, water, solar and / or gas and oil power generation, and obtain the daily power demand data corresponding to the energy tribe;

[0084] The power generation surplus determination module 210 obtains the daily extra power consumption data corresponding to the energy tribe, and determines whether the energy tribe has power generation surplus based on the power generation data, the daily power demand data and the daily extra power consumption;

[0085] The management module 220 retrieves the charging priority of the energy storage battery group in the energy tribe if there is any surplus electric energy, so as to charge the energy storage battery group based on the charging priority with the surplus electric energy.

[0086] Furthermore, the device includes but is not limited to:

[0087] A recent meteorological data acquisition module is used to obtain recent meteorological data corresponding to the energy tribe, wherein the recent meteorological data includes meteorological data corresponding to wind power, water power, and light;

[0088] The electric energy prediction model retrieval module is used to retrieve the pre-trained electric energy prediction model, input the recent meteorological data into the electric energy prediction model, and obtain the corresponding predicted power generation data;

[0089] The demand data monitoring module is used to monitor the demand data of energy tribe users in real time and perform scheduling based on predicted power generation data, demand data and pre-set priorities.

[0090] Furthermore, the device includes but is not limited to:

[0091] Extreme weather judgment module, which is used to judge whether there is extreme weather based on recent meteorological data;

[0092] An adjustment strategy generation module is used to generate a corresponding adjustment strategy if extreme weather occurs, and adjust the charging priority and discharging priority of the energy storage battery group based on the adjustment strategy;

[0093] The necessary basic electricity quantity determination module determines the target time period corresponding to extreme weather, and is used to determine the necessary basic electricity quantity corresponding to the necessary facilities of the energy tribe based on the target time period;

[0094] The energy storage battery pack charging module is used to charge the energy storage battery pack of the energy tribe until the storage power corresponding to the energy storage battery pack is greater than the necessary basic power.

[0095] Furthermore, the device includes but is not limited to:

[0096] A historical electricity consumption data retrieval module is used to retrieve the historical electricity consumption data of the energy tribe, wherein the historical electricity consumption data associates the electricity consumption of the energy tribe with the corresponding time period;

[0097] The module for determining the peak electricity consumption period calls the pre-trained electricity forecasting model and inputs the historical electricity consumption data into the electricity forecasting model to determine the peak electricity consumption period corresponding to the energy tribe;

[0098] The electricity transmission direction scheduling module is used to schedule the electricity transmission direction of the energy tribe based on the peak electricity consumption period.

[0099] Furthermore, the device includes but is not limited to:

[0100] The battery health index acquisition module is used to obtain the battery health index corresponding to the energy storage battery group of the energy tribe at intervals;

[0101] The battery health index judgment module retrieves a preset battery health threshold value to judge whether the battery health index is greater than the battery health threshold value;

[0102] The alarm module is used to send out an alarm message to remind the energy storage battery pack to be checked and the battery to be replaced if it is not;

[0103] The charge and discharge depth reduction module obtains the health index difference between the battery health index and the battery health threshold. If the health index difference is less than the set minimum difference, it is used to reduce the charge and discharge depth of the energy storage battery group.

[0104] Furthermore, the device includes but is not limited to:

[0105] The discharge priority control module is used to control the discharge priority corresponding to the energy tribe energy storage battery group if there is no surplus;

[0106] The priority power supply module is used to supply power to the devices in the energy tribe based on the discharge priority.

[0107] Furthermore, the device includes but is not limited to:

[0108] A power state determination module is used to determine the power state of the target vehicle and retrieve the preset transmission priority;

[0109] The transmission direction adjustment module is used to adjust the transmission direction of electric energy based on the power status and transmission priority.

[0110] By supporting V2G, V2L, V2V and V2H protocols, new energy vehicles can not only act as electricity consumers, but also as temporary electricity suppliers. This two-way power flow capability greatly improves the flexibility and reliability of the entire power system. When the power supply is tight, new energy vehicles can serve as a backup power source to provide power support for the power grid. When there is excess power, they can receive power from the power grid for charging, thereby balancing the supply and demand of electricity.

[0111] The power transmission direction is adjusted according to the power status of the target vehicle and the pre-set power transmission priority. In the case of an imbalance between power supply and demand, power resources can be effectively dispatched to ensure that power resources are reasonably allocated to the users or facilities that need them most, giving priority to meeting the needs of key facilities and high-priority users.

[0112] Scheduling the transmission of electric energy can ensure the optimal use of electricity resources. When there is excess electricity, new energy vehicles with lower power can be given priority for charging. When electricity is tight, new energy vehicles with higher power can be given priority to supply power to the power grid or key facilities, thereby maximizing the overall efficiency of the power system.

[0113] By monitoring the power status of new energy vehicles and adjusting the direction of power transmission according to actual conditions, the impact of fluctuations in power supply and demand on the entire power system can be effectively reduced and the stability of the system can be enhanced. This dynamic scheduling mechanism can ensure the smooth operation of the power system, especially in the face of emergencies or extreme weather conditions.

[0114] An embodiment of the present application further discloses a method for controlling a power system with multiple input sources, comprising a processor, wherein a program of any one of the methods for controlling a power system with multiple input sources described above is executed in the processor.

[0115] The embodiment of the present application further discloses a storage medium storing a program of any one of the above-mentioned methods for controlling a power system with multiple input sources.

[0116] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in the field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for controlling a power system with multiple input sources, characterized in that: include: Connect wind, water, solar and / or gas-fired oil-fired power generation equipment to the energy tribe, obtain the corresponding power generation data of wind, water, solar and / or gas-fired oil-fired power generation, and obtain the corresponding daily electricity demand data of the energy tribe; Obtaining daily extra electricity consumption data corresponding to the energy tribe, and determining whether the energy tribe has surplus electricity generation based on the power generation data, the daily electricity demand data and the daily extra electricity consumption; If there is any surplus, the charging priority of the energy storage battery group in the energy tribe is retrieved, and the remaining electric energy is used to charge the energy storage battery group based on the charging priority.

2. The multi-input source power system control method according to claim 1, characterized in that: The method further comprises: Obtain the recent meteorological data corresponding to the energy tribe, where the recent meteorological data includes meteorological data corresponding to wind power, water power, and light; Retrieving a pre-trained electric energy prediction model, inputting the recent meteorological data into the electric energy prediction model, and obtaining corresponding predicted power generation data; The demand data of energy tribe users is monitored in real time, and scheduling is performed based on the predicted power generation data, the demand data and pre-set priorities.

3. The multi-input source power system control method according to claim 1, characterized in that: After obtaining recent meteorological data corresponding to the energy tribe, the method further includes: Determine whether there is extreme weather based on the recent meteorological data; If extreme weather occurs, a corresponding adjustment strategy is generated, and the charging priority and the discharging priority of the energy storage battery group are adjusted based on the adjustment strategy; Determine a target time period corresponding to extreme weather, and determine the necessary basic electricity consumption corresponding to necessary facilities of the energy tribe based on the target time period; The energy storage battery pack of the energy tribe is charged until the storage power corresponding to the energy storage battery pack is greater than the necessary basic power.

4. The multi-input source power system control method according to claim 1, characterized in that: The method further comprises: Retrieving the historical electricity consumption data of the energy tribe, wherein the historical electricity consumption data associates the electricity consumption of the energy tribe with the corresponding time period; Retrieving a pre-trained electric energy prediction model, inputting the historical electricity consumption data into the electric energy prediction model, and determining the peak electricity consumption period corresponding to the energy tribe; The electricity transmission direction of the energy tribe is dispatched based on the peak electricity consumption period.

5. The multi-input source power system control method according to claim 1, characterized in that: The method further comprises: Get the battery health index of the energy storage battery group of the energy tribe at intervals; Retrieving a preset battery health threshold and determining whether the battery health index is greater than the battery health threshold; If not, an alarm message is issued to remind the energy storage battery pack to be checked and the battery to be replaced; If so, the health index difference between the battery health index and the battery health threshold is obtained, and if the health index difference is less than the set minimum difference, the charge and discharge depth of the energy storage battery pack is reduced.

6. The multi-input source power system control method according to claim 1, characterized in that: The method further comprises: If there is no surplus, adjust the discharge priority of the corresponding energy storage battery group of the Energy Tribe; The devices of the energy tribe are powered based on the discharge priority.

7. The multi-input source power system control method according to claim 1, characterized in that: The new energy vehicles of the energy tribe support V2G, V2L, V2V and V2H protocols, and the two-way power flow between the new energy vehicles and the power grid, loads, other vehicles and homes of the energy tribe. The method also includes: Determine the target vehicle's power status and call up the pre-set transmission priority; The transmission direction of the electric energy is adjusted based on the power status and the transmission priority.

8. A power system control device with multiple input sources, characterized in that: include: The power generation data acquisition module connects wind, water, solar and / or gas and oil power generation equipment to the energy tribe to obtain the power generation data corresponding to the wind, water, solar and / or gas and oil power generation, and obtains the daily electricity demand data corresponding to the energy tribe; A power generation surplus determination module is used to obtain daily additional power consumption data corresponding to the energy tribe, and determine whether the energy tribe has power generation surplus based on the power generation data, the daily power demand data and the daily additional power consumption; The management module, if there is any surplus, retrieves the charging priority of the energy storage battery group in the energy tribe, and charges the energy storage battery group with the remaining electric energy based on the charging priority.

9. A method for controlling a power system with multiple input sources, characterized in that: The method comprises a processor in which a program of the method for controlling a power system with multiple input sources as claimed in any one of claims 1 to 7 is executed.

10. A storage medium, characterized in that: A program storing the method for controlling a power system with multiple input sources according to any one of claims 1 to 7 is provided.

Images