Photovoltaic energy storage assembly discharge monitoring system based on artificial intelligence

Abstract

The invention relates to the field of photovoltaic energy storage, in particular to a photovoltaic energy storage component discharge monitoring system based on artificial intelligence, and aims to solve the problem of unstable discharge during load supply caused by insufficient monitoring of discharge factors during use of a photovoltaic energy storage component. Comprising a load input unit, a load supply unit, an energy storage overall planning unit, an energy storage input unit and an energy storage sensing unit. The historical operation conditions of different energy storage assemblies are obtained, the energy storage assemblies are judged according to the historical operation conditions, and when the load supply demand exists, the load demand, the historical operation conditions of the energy storage assemblies and the current energy storage conditions of the energy storage assemblies are comprehensively judged, so that the optimal selection result of the energy storage assemblies is obtained; therefore, deep selection of the energy storage assembly is realized, and meanwhile, the operation process of the energy storage assembly is supervised, so that discharge selection of the energy storage assembly can adapt to load requirements.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic energy storage, and in particular to a photovoltaic energy storage component discharge monitoring system based on artificial intelligence. Background Art

[0002] Solar power generation is known as the most ideal energy source. Photovoltaic power generation is a power generation method that converts solar energy into electrical energy. The electrical energy generated by the photovoltaic power generation system is stored in the battery assembly, and then the battery assembly is used to charge the load. Due to factors such as weather and the characteristics of sunlight itself, photovoltaic power generation has strong volatility and randomness, resulting in poor reliability of photovoltaic power generation. Therefore, when there is sufficient solar energy, it is necessary to convert electrical energy into storage batteries through solar panels. When electricity is needed, the battery discharges to provide electrical energy. In order to control the charging and discharging operation of the battery, a charging and discharging control board is usually set between the solar panel and the battery, and the charging and discharging operation of the battery is controlled by the charging and discharging control board;

[0003] The existing patent CN106787102A discloses a technical solution, which determines the charge and discharge control of the battery according to the power of the battery, thereby improving the use effect of the battery. However, in actual use, photovoltaic equipment is generally equipped with multiple batteries. The method of dividing the batteries only according to the power of the batteries can only achieve the alternating selection of power supply and charging through different batteries during use, but cannot select the best one according to different batteries and load requirements or the combination of batteries for power supply, which leads to unstable discharge of the battery when supplying loads;

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The present invention obtains the historical operating conditions of different energy storage components and judges the energy storage components according to the historical operating conditions. When there is a load supply demand, the load demand, the historical operating conditions of the energy storage components and the current energy storage conditions of the energy storage components are comprehensively judged to obtain the optimal selection result of the energy storage components, thereby realizing in-depth selection of energy storage components. At the same time, by supervising the operation process of the energy storage components, it is ensured that the discharge selection of the energy storage components can adapt to the load demand, and solves the problem that the photovoltaic energy storage components do not monitor the discharge factors sufficiently during use, resulting in unstable discharge when the load is supplied. A photovoltaic energy storage component discharge monitoring system based on artificial intelligence is proposed.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A photovoltaic energy storage component discharge monitoring system based on artificial intelligence, comprising a load input unit, a load supply unit, an energy storage coordination unit, an energy storage input unit and an energy storage sensing unit;

[0008] The load input unit can obtain the required load conditions and send the required load conditions to the energy storage coordination unit and the load supply unit at the same time;

[0009] The energy storage coordination unit manages all energy storage components, obtains the operating conditions of all energy storage components, selects from all energy storage components according to the required load conditions, obtains the load supply component, and sends the load supply component to the load supply unit;

[0010] The load supply unit supplies the required load through the load supply component, and the load supply unit manages the operation of the load supply component to obtain the supply operation status, and sends the supply operation status to the energy storage sensing unit;

[0011] After the energy storage sensing unit obtains the supply operation status, it judges the supply operation status, and when the supply operation status reaches a preset condition, it sends the load supply component to the energy storage coordination unit, and the energy storage coordination unit replaces the load supply component.

[0012] As a preferred embodiment of the present invention, the load input unit can obtain the load demand through the power supply network and record the load demand as the initial load power, and the load input unit sends the initial load power to the energy storage coordination unit;

[0013] The energy storage coordination unit obtains the operating conditions of all energy storage components, the operating conditions of the energy storage components including the maximum output power of the energy storage components, the current energy storage margin of the energy storage components and the energy storage component operation evaluation coefficient;

[0014] The energy storage coordination unit compares the initial load power with the maximum output power, records the part of the maximum output power that is greater than the initial load power as the buffer power PH, and obtains the buffer ratio BH through formula analysis. Where Pmax is the maximum output power, θ is the operation evaluation coefficient, and the energy storage coordination unit selects all energy storage components whose buffer ratio is greater than the preset threshold and records them as the first component set;

[0015] The energy storage coordination unit screens the current energy storage margins of all energy storage components in the first component set, screens all energy storage components whose current energy storage margins are greater than a preset percentage, and counts them as a second component set;

[0016] The energy storage coordination unit selects the energy storage component with the largest current energy storage margin from the second component set, records it as the load supply component, and sends the identity code corresponding to the load supply component to the load supply unit;

[0017] After the load supply unit obtains the identity code, the corresponding energy storage component is connected to the load network, and the required load is supplied through the corresponding energy storage component.

[0018] As a preferred embodiment of the present invention, the method for the energy storage coordination unit to obtain the operation evaluation coefficient of the energy storage component is: for the total operation time, the degree of fit of the output curve and the load curve, and the energy storage efficiency of the energy storage component in the historical operation process, the energy storage coordination unit assigns different weight values ​​to the total operation time, the degree of fit and the energy storage efficiency, and calculates them by weighted average to obtain the operation evaluation coefficient of the energy storage component.

[0019] As a preferred embodiment of the present invention, the method for the energy storage coordination unit to obtain the degree of fit between the output curve and the load curve is:

[0020] The energy storage coordination unit obtains the load power and output power during the historical operation of the energy storage component, and obtains the output curve and the load curve. The energy storage coordination unit calculates the ratio between the load curve area and the output curve area to obtain the degree of fitting between the output curve and the load curve.

[0021] As a preferred embodiment of the present invention, the load input unit continuously monitors the load demand, records it as the real-time load and sends the real-time load to the load supply unit, the load supply unit calculates the ratio of the real-time load to the maximum output power, obtains the load share, and compares the maximum value of the load share with the preset share peak value, and generates a load overload signal if the maximum value of the load share is greater than the preset share peak value;

[0022] The load supply unit performs arithmetic averaging on the load proportions to obtain an average load proportion, and compares the average load proportion with a preset proportion mean value. If the average load proportion is greater than the preset proportion mean value, a high load signal is generated.

[0023] As a preferred embodiment of the present invention, after the load supply unit generates an overload signal, the energy storage coordination unit selects a group of energy storage components with the largest current energy storage margin from the second component set as supplementary supply components.

[0024] As a preferred embodiment of the present invention, the load supply unit monitors the energy storage margin of the energy storage component in real time during the operation of the load supply component or the supplementary supply component, and generates an energy storage component replacement signal when the energy storage margin of the energy storage component is lower than a preset margin warning value;

[0025] During operation, the load supply unit collects the operating parameters of the energy storage component in real time, compares the collected operating parameters with the set operating range, obtains the operating time of different operating parameters within the set operating range and the operating time outside the set operating range, generates a judgment result of the operating parameter according to the ratio, obtains the operating status of the energy storage component through weighted calculation of multiple operating parameter judgment results, and sends the operating status to the energy storage sensing unit.

[0026] As a preferred implementation manner of the present invention, the energy storage sensing unit compares the operating status with a set lower limit of the operating status, and generates an alarm reminder when the operating status does not meet the set lower limit of the operating status.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] 1. In the present invention, by comprehensively managing the energy storage components, the historical operating conditions of different energy storage components are obtained, and the energy storage components are judged according to the historical operating conditions. When there is a load supply demand, the load demand, the historical operating conditions of the energy storage components and the current energy storage conditions of the energy storage components are comprehensively judged to obtain the optimal result of the energy storage components, thereby realizing the in-depth selection of the energy storage components and ensuring the output effect on the load.

[0029] 2. In the present invention, the operation process of the energy storage component is continuously monitored, so that the energy storage component is selected and operated according to the real-time changes of the load, ensuring that the energy storage component can meet the load demand during the discharge process, while at the same time, the energy storage component will not be discharged too much, thereby preventing the operation of the energy storage component from being damaged, thereby ensuring the service life of the energy storage component.

[0030] 3. In the present invention, the energy storage components are automatically replaced and adjusted so that the energy storage components can automatically switch between charge and discharge, thereby ensuring the intelligent operation of the energy storage components. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0032] Figure 1 is a system block diagram of the present invention;

[0033] Figure 2 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0034] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] Embodiment 1:

[0036] See also Figure 1 - Figure 2 As shown, a photovoltaic energy storage component discharge monitoring system based on artificial intelligence includes a load input unit, a load supply unit, an energy storage coordination unit, an energy storage input unit and an energy storage sensing unit. The load input unit can obtain the load demand through the power supply network and record the load demand as the initial load power;

[0037] The load input unit sends the initial load power to the energy storage coordination unit;

[0038] The energy storage coordination unit obtains the operating status of all energy storage components, where the operating status of the energy storage components includes the maximum output power of the energy storage components, the current energy storage surplus of the energy storage components, and the energy storage component operation evaluation coefficient;

[0039] The method for the energy storage coordination unit to obtain the maximum output power of the energy storage component is manual input;

[0040] The method by which the energy storage coordination unit obtains the current remaining energy storage amount of the energy storage component is detection by the power sensor;

[0041] The method for the energy storage coordination unit to obtain the operation evaluation coefficient of the energy storage component is: to collect statistics on the historical operation of the energy storage component, to obtain the total operation time, the degree of fit of the output curve and the load curve, and the energy storage efficiency of the energy storage component during the historical operation process, the energy storage coordination unit assigns different weight values ​​to the total operation time, the degree of fit, and the energy storage efficiency, and calculates by weighted average to obtain the operation evaluation coefficient of the energy storage component;

[0042] The energy storage coordination unit compares the initial load power and the maximum output power, and records the part of the maximum output power that is greater than the initial load power as the buffer power PH. The buffer ratio BH is obtained through formula analysis. Where Pmax is the maximum output power, θ is the operation evaluation coefficient, and the energy storage coordination unit selects all energy storage components whose buffer ratio is greater than the preset threshold and records them as the first component set;

[0043] The energy storage coordination unit screens the current energy storage margins of all energy storage components in the first component set, screens all energy storage components whose current energy storage margins are greater than a preset percentage, and counts them as a second component set;

[0044] The energy storage coordination unit selects the energy storage component with the largest current energy storage margin from the second component set, records it as the load supply component, and sends the identity code corresponding to the load supply component to the load supply unit;

[0045] After the load supply unit obtains the identity code, it connects the corresponding energy storage component to the load network and supplies the required load through the corresponding energy storage component.

[0046] The method for the energy storage coordination unit to obtain the degree of fitting of the output curve and the load curve is as follows: during the historical operation of the energy storage component, the energy storage coordination unit obtains the load power through the load input unit, obtains the output power of the energy storage component through the load supply unit, and draws curves of the load power and the output power in the coordinate system respectively to obtain the output curve and the load curve. The energy storage coordination unit records the area enclosed by the output curve and the X-axis as the output area, and the area enclosed by the load curve and the X-axis as the load area. The energy storage coordination unit calculates the ratio between the load area and the output area to obtain the degree of fitting of the output curve and the load curve.

[0047] The method for the energy storage coordination unit to obtain the energy storage efficiency is: during the charging process of the energy storage component, the charging time of the energy storage component is recorded, and the energy storage efficiency is obtained by calculating based on the charging time of the energy storage component and the increased power.

[0048] Embodiment 2:

[0049] See also Figure 1 - Figure 2 As shown, the load input unit continuously monitors the load demand, records it as the real-time load and sends the real-time load to the load supply unit, the load supply unit calculates the ratio of the real-time load to the maximum output power of the energy storage supply component, obtains the load share, and compares the maximum value of the load share with the preset share peak value. If the maximum value of the load share is greater than the preset share peak value, a load overload signal is generated. If the maximum value of the load share is not greater than the preset share peak value, a load normal signal is generated.

[0050] The load supply unit performs arithmetic averaging on the load proportions to obtain an average load proportion, and compares the average load proportion with a preset proportion average value. If the average load proportion is greater than the preset proportion average value, a load overload signal is generated; if the average load proportion is not greater than the preset proportion average value, a load normal signal is generated;

[0051] After generating the overload signal, the load supply unit sends the overload signal to the energy storage coordination unit. After receiving the overload signal, the energy storage coordination unit again selects a group of energy storage components with the largest current energy storage margin from the second component set as supplementary supply components, and sends the supplementary supply components to the load supply unit. The load supply unit supplies the required load jointly through the supplementary supply components and the load supply components.

[0052] Embodiment three:

[0053] See also Figure 1 - Figure 2 As shown, during the operation of the load supply component or the supplementary supply component, the load supply unit monitors the energy storage margin of the energy storage component in real time, and obtains a preset margin warning value at the same time. When the energy storage margin of the energy storage component is lower than the preset margin warning value, an energy storage component replacement signal is generated. When the energy storage margin of the energy storage component is greater than the preset margin warning value, no response is made.

[0054] During the operation of the load supply component or the supplementary supply component, the load supply unit collects the operating parameters of the energy storage component in real time, compares the collected operating parameters with the set operating range, marks the operating parameters that exceed the set operating range, and records the operating time of different operating parameters within the set operating range and the operating time outside the set operating range, thereby generating a judgment result of the operating parameter according to the ratio of the time within the range to the time outside the range, and obtains the operating status of the energy storage component through weighted calculation of multiple operating parameter judgment results, and sends the operating status to the energy storage sensing unit;

[0055] The energy storage sensing unit compares the operating status with the set operating status lower limit. When the operating status does not meet the set operating status lower limit, an alarm reminder is generated and sent to the energy storage coordination unit. The energy storage coordination unit selects a new energy storage component from the second component set for replacement. When the operating conditions meet the set operating status upper limit, no response is made.

[0056] Embodiment 4:

[0057] See also Figure 1 - Figure 2 As shown, the energy storage coordination unit determines the remaining power of the energy storage component, selects the energy storage receiving component in order from small to large according to the remaining power of the energy storage component, and stores the electric energy generated by photovoltaic power generation through the energy storage receiving component;

[0058] The energy storage input unit monitors the charging process of the energy storage receiving component, obtains the charging data and sends it to the energy storage coordination unit for evaluation and analysis of the energy storage component. At the same time, it monitors the charging amount of the energy storage component. When the charging amount reaches the preset standard, charging is stopped and other energy storage receiving components are replaced.

[0059] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A photovoltaic energy storage component discharge monitoring system based on artificial intelligence, characterized in that: It includes a load input unit, a load supply unit, an energy storage coordination unit, an energy storage input unit and an energy storage sensing unit; The load input unit can obtain the required load conditions and send the required load conditions to the energy storage coordination unit and the load supply unit at the same time; The energy storage coordination unit manages all energy storage components, obtains the operating conditions of all energy storage components, selects from all energy storage components according to the required load conditions, obtains the load supply component, and sends the load supply component to the load supply unit; The load supply unit supplies the required load through the load supply component, and the load supply unit manages the operation of the load supply component to obtain the supply operation status, and sends the supply operation status to the energy storage sensing unit; After the energy storage sensing unit obtains the supply operation status, it judges the supply operation status, and when the supply operation status reaches a preset condition, it sends the load supply component to the energy storage coordination unit, and the energy storage coordination unit replaces the load supply component.

2. According to claim 1, a photovoltaic energy storage component discharge monitoring system based on artificial intelligence is characterized in that: The load input unit can obtain the load demand through the power supply network and record the load demand as the initial load power. The load input unit sends the initial load power to the energy storage coordination unit; The energy storage coordination unit obtains the operating conditions of all energy storage components, the operating conditions of the energy storage components including the maximum output power of the energy storage components, the current energy storage margin of the energy storage components and the energy storage component operation evaluation coefficient; The energy storage coordination unit compares the initial load power with the maximum output power, records the part of the maximum output power that is greater than the initial load power as the buffer power PH, and obtains the buffer ratio BH through formula analysis. Where Pmax is the maximum output power, θ is the operation evaluation coefficient, and the energy storage coordination unit selects all energy storage components whose buffer ratio is greater than the preset threshold and records them as the first component set; The energy storage coordination unit screens the current energy storage margins of all energy storage components in the first component set, screens all energy storage components whose current energy storage margins are greater than a preset percentage, and counts them as a second component set; The energy storage coordination unit selects the energy storage component with the largest current energy storage margin from the second component set, records it as the load supply component, and sends the identity code corresponding to the load supply component to the load supply unit; After the load supply unit obtains the identity code, the corresponding energy storage component is connected to the load network, and the required load is supplied through the corresponding energy storage component.

3. According to claim 2, a photovoltaic energy storage component discharge monitoring system based on artificial intelligence is characterized in that: The method for the energy storage coordination unit to obtain the operation evaluation coefficient of the energy storage component is: for the total operation time, the degree of fit of the output curve and the load curve, and the energy storage efficiency of the energy storage component in the historical operation process, the energy storage coordination unit assigns different weight values ​​to the total operation time, the degree of fit and the energy storage efficiency, and calculates them by weighted average to obtain the operation evaluation coefficient of the energy storage component.

4. The photovoltaic energy storage component discharge monitoring system based on artificial intelligence according to claim 3 is characterized in that: The method for the energy storage coordination unit to obtain the degree of fit between the output curve and the load curve is: The energy storage coordination unit obtains the load power and output power during the historical operation of the energy storage component, and obtains the output curve and the load curve. The energy storage coordination unit calculates the ratio between the load curve area and the output curve area to obtain the degree of fitting between the output curve and the load curve.

5. The photovoltaic energy storage component discharge monitoring system based on artificial intelligence according to claim 4 is characterized in that: The load input unit continuously monitors the load demand, records it as the real-time load and sends it to the load supply unit. The load supply unit calculates the ratio of the real-time load to the maximum output power to obtain the load share, and compares the maximum value of the load share with the preset share peak value. If the maximum value of the load share is greater than the preset share peak value, a load overload signal is generated. The load supply unit performs arithmetic averaging on the load proportions to obtain an average load proportion, and compares the average load proportion with a preset proportion mean value. If the average load proportion is greater than the preset proportion mean value, a high load signal is generated.

6. The photovoltaic energy storage component discharge monitoring system based on artificial intelligence according to claim 1 is characterized in that: After the load supply unit generates the overload signal, the energy storage coordination unit selects a group of energy storage components with the largest current energy storage margin from the second component set again as supplementary supply components.

7. The photovoltaic energy storage component discharge monitoring system based on artificial intelligence according to claim 1 is characterized in that: The load supply unit monitors the energy storage margin of the energy storage component in real time during the operation of the load supply component or the supplementary supply component, and generates an energy storage component replacement signal when the energy storage margin of the energy storage component is lower than a preset margin warning value; During operation, the load supply unit collects the operating parameters of the energy storage component in real time, compares the collected operating parameters with the set operating range, obtains the operating time of different operating parameters within the set operating range and the operating time outside the set operating range, generates a judgment result of the operating parameter according to the ratio, obtains the operating status of the energy storage component through weighted calculation of multiple operating parameter judgment results, and sends the operating status to the energy storage sensing unit.

8. The photovoltaic energy storage component discharge monitoring system based on artificial intelligence according to claim 1 is characterized in that: The energy storage sensing unit compares the operating status with a set lower limit of the operating status, and generates an alarm reminder when the operating status does not meet the set lower limit of the operating status.

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