An intelligent power consumption system based on photovoltaic storage and direct flexible technology

Abstract

The present invention relates to the field of energy dispatching technology, and more specifically, to an intelligent power system based on photovoltaic storage and direct flexible technology. It includes a photovoltaic power generation unit for collecting solar energy by installing solar photovoltaic panels and converting solar energy into electrical energy; an energy storage unit for storing excess electrical energy. When the photovoltaic power generation unit generates insufficient electrical energy or no energy, the electrical energy of the storage unit is used for power supply; an electricity management unit for monitoring and managing the distribution of direct current in the photovoltaic power generation unit, and then dynamically adjusting the direct current according to actual needs; the system can more comprehensively reflect the actual power generation capacity of the photovoltaic system by comprehensively considering factors such as temperature, season and system loss, thereby improving the prediction accuracy and reliability of the system; through real-time data collection and processing, the system can foresee the future supply and demand of electrical energy in advance, thereby improving the overall operation efficiency and stability of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of energy dispatching, and in particular to an intelligent power consumption system based on photovoltaic storage and direct-flexible technology. Background Art

[0002] With the continuous growth of global energy demand and the improvement of environmental protection awareness, the development of renewable energy and the improvement of energy utilization efficiency have become important strategic goals of all countries. Photovoltaic (solar) power generation, as a clean and renewable energy source, has been widely used. However, photovoltaic power generation has the problems of intermittency and instability, which poses a challenge to the stable operation of the power grid. In order to solve these problems, an intelligent power consumption system based on photovoltaic storage direct flexible technology came into being. Photovoltaic power generation technology uses solar panels to directly convert sunlight into electrical energy. The main components of a photovoltaic system include photovoltaic panels, inverters, controllers, etc. Photovoltaic power generation has the advantages of being clean, pollution-free, and renewable, but it also has the problems of intermittency and instability. For example, traditional photovoltaic system prediction methods often ignore factors such as temperature, seasonal changes, and system losses, resulting in low prediction accuracy and inability to accurately reflect the actual power generation capacity. Therefore, an intelligent power consumption system based on photovoltaic storage direct flexible technology is designed. Summary of the invention

[0003] The purpose of the present invention is to provide an intelligent power consumption system based on photovoltaic storage and direct flexible technology to solve the problem that the traditional photovoltaic system prediction method proposed in the above background technology often ignores factors such as temperature, seasonal changes and system losses, resulting in low prediction accuracy and inability to accurately reflect the actual power generation capacity.

[0004] To achieve the above object, the present invention aims to provide an intelligent power consumption system based on photovoltaic storage direct flexible technology, comprising:

[0005] Photovoltaic power generation unit, the photovoltaic power generation unit is used to collect solar energy by installing solar photovoltaic panels and convert solar energy into electrical energy, and temperature influence, system loss and seasonal factors are introduced in the process of converting solar energy into electrical energy for optimization; wherein the photovoltaic power generation unit includes a DC distribution module and several DC load systems;

[0006] An energy storage unit, wherein the energy storage unit is used to store excess electric energy. When the electric energy generated by the photovoltaic power generation unit is insufficient or there is no energy, the electric energy of the storage unit is used for power supply;

[0007] The power management unit is used to monitor and manage the distribution of direct current in the photovoltaic power generation unit, and then dynamically adjust the direct current according to actual needs.

[0008] As a further improvement of the technical solution, the electric energy in the photovoltaic power generation unit is direct current, and the direct current distribution module is responsible for distributing the direct current generated by photovoltaics to various direct current load systems, and the direct current load systems directly use the distributed direct current.

[0009] As a further improvement of the technical solution, the photovoltaic power generation unit converts solar energy into electrical energy as follows:

[0010] ;

[0011] in, is the maximum output power of the photovoltaic panel; is the short-circuit current; is the open circuit voltage; is the conversion efficiency;

[0012] ;

[0013] in, is the daily power generation; is the number of effective sunshine hours per day; For performance ratio.

[0014] As a further improvement of the technical solution, in the photovoltaic power generation unit, temperature influence, system loss and seasonal factors are introduced in the process of converting solar energy into electrical energy for optimization, and the optimization is as follows:

[0015] ;

[0016] in, For The maximum output power of photovoltaic panels; For The short-circuit current; For The open circuit voltage; For conversion efficiency; is the temperature of the photovoltaic panel surface;

[0017] ;

[0018] in, is the short-circuit current under standard test conditions; is the short-circuit current temperature coefficient; is the temperature under standard test conditions;

[0019] ;

[0020] in, is the open circuit voltage under standard test conditions; is the open circuit voltage temperature coefficient;

[0021] ;

[0022] in, is the conversion efficiency under standard test conditions; is the temperature coefficient;

[0023] ;

[0024] in, is the optimized daily power generation; is the seasonal adjustment factor; is the system loss coefficient.

[0025] As a further improvement of the present technical solution, the power management unit includes a data acquisition module, a controller and an execution module. The data acquisition module is used to collect data from the photovoltaic power generation unit and the energy storage unit, and transmit the data to the controller. The controller makes decisions and generates control signals based on the received data, and the execution module performs corresponding operations based on the type of the control signal.

[0026] As a further improvement of the present technical solution, the data acquisition module is used to collect data of the photovoltaic power generation unit and the energy storage unit, including photovoltaic power generation data, energy storage data and load data; wherein the photovoltaic power generation data is the daily power generation of the photovoltaic panel; the energy storage data is the power level and health status of the energy storage unit; and the load data is the power consumption of each DC load.

[0027] As a further improvement of the technical solution, the controller makes a decision and generates a control signal according to the received data, and the execution module performs a corresponding operation according to the type of the control signal. The specific steps are as follows:

[0028] S1, the controller processes the received data, calculates the current power generation and power consumption, and predicts the future power generation and power consumption through algorithms;

[0029] S2. Formulate power usage strategies and generate control signals based on current power generation and power consumption as well as future power demand and supply conditions;

[0030] S3, the execution module controls the switches in the photovoltaic power generation unit and the energy storage unit through control signals, thereby realizing the dynamic distribution of electric energy.

[0031] As a further improvement of the technical solution, S1 is specifically:

[0032] The SARIMA model is used to predict the electricity demand for the next week, and the LSTM model is used to predict the photovoltaic power generation for the next week. The prediction results of the SARIMA and LSTM models are combined and the final prediction value is obtained by weighted average.

[0033] As a further improvement of the technical solution, S2 is specifically:

[0034] When the power generation is greater than the power consumption, the controller can detect the excess power and generate a first control signal; when the power consumption is greater than the power generation, the controller can detect the energy shortage and generate a second control signal.

[0035] As a further improvement of the technical solution, S3 is specifically:

[0036] When the actuator receives the first control signal, it turns on the switch of the photovoltaic power generation unit and transmits the excess DC power of the photovoltaic power generation unit to the energy storage unit; when the actuator receives the second control signal, it turns on the switch of the energy storage unit and transmits the energy of the energy storage unit to the photovoltaic power generation unit, and then to the DC load system.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] 1. This intelligent power system based on solar-storage direct-flexible technology can more comprehensively reflect the actual power generation capacity of the photovoltaic system by comprehensively considering factors such as temperature, season and system loss, thereby improving the prediction accuracy and reliability of the system;

[0039] 2. In this intelligent power consumption system based on solar-storage direct-flexible technology, through real-time data collection and processing, the controller can accurately grasp the current state of the system and ensure the timeliness and accuracy of decision-making. The application of prediction algorithms enables the system to foresee the future power supply and demand in advance, providing a scientific basis for formulating reasonable power consumption strategies, thereby improving the overall operating efficiency and stability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is the overall flow chart of the present invention;

[0041] The meaning of each number in the figure is:

[0042] 1. Photovoltaic power generation unit; 2. Energy storage unit; 3. Power management unit. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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.

[0044] Example

[0045] See also Figure 1 As shown, a smart power consumption system based on photovoltaic storage direct flexible technology is provided, including a photovoltaic power generation unit 1, an energy storage unit 2 and a power consumption management unit 3;

[0046] The photovoltaic power generation unit 1 is used to collect solar energy by installing solar photovoltaic panels and convert the solar energy into electrical energy, which can be directly used for power supply. In the process of converting solar energy into electrical energy, temperature influence, system loss and seasonal factors are introduced for optimization;

[0047] Wherein, the photovoltaic power generation unit 1 includes a DC power distribution module and several DC load systems;

[0048] The electric energy in the photovoltaic power generation unit 1 is direct current. The direct current distribution module is responsible for distributing the direct current generated by photovoltaics to various direct current load systems, and the direct current load systems directly use the distributed direct current. DC loads include all devices that can directly use direct current, such as LED lights, DC motors, DC air conditioners, DC chargers, etc. These devices directly receive direct current from the photovoltaic power generation unit 1 without being converted into alternating current through an inverter. The direct current distribution module usually includes components such as a direct current distribution box, a direct current circuit breaker, and a direct current cable. The direct current distribution box is used to centrally manage and distribute direct current, the direct current circuit breaker is used to protect the circuit from overload and short circuit, and the direct current cable is used to transmit direct current.

[0049] The photovoltaic power generation unit 1 converts solar energy into electrical energy as follows:

[0050] ;

[0051] in, is the maximum output power of the photovoltaic panel; is the short-circuit current; is the open circuit voltage; is the conversion efficiency;

[0052] ;

[0053] in, is the daily power generation; is the number of effective sunshine hours per day; is the performance ratio, which reflects the ratio of the actual power generation of the system to the theoretical maximum power generation;

[0054] In the photovoltaic power generation unit 1, the temperature effect, system loss and seasonal factors are introduced in the process of converting solar energy into electrical energy for optimization. After optimization, the specific results are as follows:

[0055] ;

[0056] in, For The maximum output power of photovoltaic panels; For The short-circuit current; For The open circuit voltage; For conversion efficiency; is the temperature of the photovoltaic panel surface;

[0057] By introducing the influence of temperature, the calculation of the maximum output power is made more accurate. Temperature changes have a significant impact on the performance of photovoltaic panels, especially in high temperature environments, where the efficiency of photovoltaic panels will decrease. This formula takes into account the impact of temperature on short-circuit current, open-circuit voltage, and conversion efficiency, thereby more realistically reflecting the maximum output power under actual working conditions and improving the prediction accuracy and reliability of the system.

[0058] ;

[0059] in, is the short-circuit current under standard test conditions; is the short-circuit current temperature coefficient; is the temperature under standard test conditions;

[0060] The short-circuit current changes with temperature, and generally an increase in temperature will cause a slight increase in the short-circuit current. , the formula can more accurately reflect the effect of temperature on short-circuit current. This helps to more accurately calculate the performance of photovoltaic panels under different temperature conditions and improve the overall efficiency of the system.

[0061] ;

[0062] in, is the open circuit voltage under standard test conditions; is the open circuit voltage temperature coefficient;

[0063] The open circuit voltage decreases with increasing temperature, which is an important characteristic of photovoltaic panels. , this formula can more accurately reflect the effect of temperature on open circuit voltage. This helps to more accurately calculate the performance of photovoltaic panels under different temperature conditions and ensure the stable operation of the system.

[0064] ;

[0065] in, is the conversion efficiency under standard test conditions; is the temperature coefficient;

[0066] The conversion efficiency decreases with increasing temperature, which is a key parameter of photovoltaic panels. , the formula can more accurately reflect the effect of temperature on conversion efficiency. This helps to more accurately calculate the performance of photovoltaic panels under different temperature conditions and improve the overall efficiency and reliability of the system.

[0067] ;

[0068] in, is the optimized daily power generation; The seasonal adjustment factor can be determined using historical meteorological data to take into account the change in solar radiation in different seasons. For example, solar radiation is higher in summer and lower in winter; For the system loss coefficient, taking into account factors such as cable loss, inverter efficiency, and dust shielding, intelligent algorithms (such as machine learning) can be used to predict and optimize system losses and improve the overall performance of the system;

[0069] By introducing the temperature effect, the calculation of power generation is more accurate, reflecting the performance changes under actual working conditions, and the seasonal adjustment coefficient Taking into account the changes in solar radiation in different seasons, the prediction of power generation is more in line with the actual situation, improving the adaptability and reliability of the system, and the system loss coefficient It takes into account factors such as cable loss, inverter efficiency, and dust shielding, optimizes system performance through intelligent algorithms (such as machine learning), and improves the overall efficiency of the system. By comprehensively considering factors such as temperature, season, and system loss, the formula can more comprehensively reflect the actual power generation capacity of the photovoltaic system and provide a scientific basis for system planning and optimization.

[0070] The energy storage unit 2 is used to store excess electric energy. When the electric energy generated by the photovoltaic power generation unit 1 is insufficient or there is no energy, the electric energy of the storage unit 2 is used for power supply;

[0071] In the intelligent power consumption system based on the photovoltaic storage direct flexible technology, the energy storage unit 2 plays a key buffering and regulating role. When the photovoltaic power generation unit 1 generates excess electricity, the energy storage unit 2 stores the excess electricity; when the photovoltaic power generation unit 1 has insufficient electricity or no electricity output, the energy storage unit 2 releases the stored electricity to ensure the continuous and stable power supply of the system. In this way, the energy storage unit 2 not only smoothes the output of electricity, improves the reliability and power quality of the system, but also realizes the peak shaving and valley filling of the power grid, optimizes the energy utilization efficiency, and supports the flexible operation of the system and the energy conservation and emission reduction goals.

[0072] The power management unit 3 is used to monitor and manage the distribution of DC power in the photovoltaic power generation unit 1, and then dynamically adjust the DC power according to actual needs; it can decide which DC loads use the DC power generated by photovoltaics first, and which can switch to the energy storage unit or other power sources when the photovoltaic power is insufficient.

[0073] The power management unit 3 includes a data acquisition module, a controller and an execution module. The data acquisition module is used to collect data from the photovoltaic power generation unit 1 and the energy storage unit 2 and transmit them to the controller. The controller makes decisions and generates control signals based on the received data. The execution module performs corresponding operations based on the type of control signal.

[0074] The data acquisition module can monitor the working status of photovoltaic power generation unit 1 and energy storage unit 2 in real time, including key parameters such as current, voltage, and temperature. This enables the system to detect abnormal conditions in a timely manner, warn of potential failures in advance, and improve the reliability and safety of the system. At the same time, by collecting and analyzing these data, the system's operating strategy can be optimized and energy utilization efficiency can be improved;

[0075] As the core of the power management unit, the controller is responsible for processing the data transmitted by the data acquisition module and making decisions based on preset logic and algorithms. It can dynamically adjust the distribution of DC power to ensure that high-priority loads use the DC power generated by photovoltaics first, while low-priority loads switch to energy storage unit 2 or other power sources when photovoltaic power is insufficient. This intelligent management method not only improves the flexibility and response speed of the system, but also maximizes the use of renewable energy, reduces dependence on traditional power grids, and achieves the goal of energy conservation and emission reduction.

[0076] The execution module performs specific operations according to the control signals generated by the controller, such as switching circuits, adjusting load power, etc. Through precise execution operations, it ensures that all parts of the system work together to achieve optimal energy utilization. The efficient operation of the execution module can also extend the service life of the equipment, reduce maintenance costs, and improve the overall performance of the system.

[0077] The data acquisition module is used to collect data of the photovoltaic power generation unit 1 and the energy storage unit 2, including photovoltaic power generation data, energy storage data and load data; wherein the photovoltaic power generation data is the daily power generation of the photovoltaic panel; the energy storage data is the power level and health status of the energy storage unit 2; the load data is the power consumption of each DC load;

[0078] The controller makes decisions based on the received data and generates control signals. The execution module performs corresponding operations based on the type of control signal. The specific steps are as follows:

[0079] S1, the controller processes the received data, calculates the current power generation and power consumption, and predicts the future power generation and power consumption through algorithms;

[0080] Through real-time data collection and processing, the controller can accurately grasp the current state of the system and ensure the timeliness and accuracy of decision-making. The application of prediction algorithms enables the system to foresee the future power supply and demand in advance, providing a scientific basis for formulating reasonable power consumption strategies, thereby improving the overall operating efficiency and stability of the system.

[0081] S1 is specifically:

[0082] The SARIMA model is used to predict the electricity demand for the next week, and the LSTM model is used to predict the photovoltaic power generation for the next week. The prediction results of the SARIMA and LSTM models are combined and the final prediction value is obtained by weighted average.

[0083] The SARIMA model is an extended ARIMA model that is specifically designed to process time series data with seasonal patterns. The SARIMA model can capture trends, seasonality, and random fluctuations in time series. The LSTM model is a special recurrent neural network (RNN) that is particularly suitable for processing long sequence data. By introducing memory units and gating mechanisms, LSTM can effectively solve the gradient vanishing and gradient exploding problems in RNN.

[0084] The SARIMA model is good at handling seasonal and trend components, while the LSTM model is good at handling long dependencies and nonlinear relationships. Combining the prediction results of the two can give full play to their respective advantages and improve the accuracy of predictions. Combining the prediction results of multiple models by weighted average method can reduce the error of a single model and improve the robustness of predictions.

[0085] S2. Formulate power usage strategies and generate control signals based on current power generation and power consumption as well as future power demand and supply conditions;

[0086] S2 is specifically:

[0087] When the power generation is greater than the power consumption, the controller can detect the excess power and generate a first control signal; when the power consumption is greater than the power generation, the controller can detect the energy shortage and generate a second control signal.

[0088] The first control signal can instruct the execution module to store excess electrical energy in the energy storage unit 2, or to give priority to supplying high-priority loads, so as to avoid wasting electrical energy and improve energy utilization; the second control signal can instruct the execution module to call for electrical energy from the energy storage unit 2 or other backup power sources to ensure the normal operation of important loads and improve the reliability and stability of the system.

[0089] S3, the execution module controls the switches in the photovoltaic power generation unit 1 and the energy storage unit 2 through the control signal, thereby realizing the dynamic distribution of electric energy;

[0090] S3 is specifically:

[0091] When the actuator receives the first control signal, it turns on the switch of the photovoltaic power generation unit 1 and transmits the excess DC power of the photovoltaic power generation unit 1 to the energy storage unit 2; when the actuator receives the second control signal, it turns on the switch of the energy storage unit 2 and transmits the energy of the energy storage unit 2 to the photovoltaic power generation unit 1, and then to the DC load system.

[0092] By dynamically adjusting the distribution of electric energy, the system can ensure efficient operation under different working conditions, maximize the use of renewable energy, and reduce dependence on traditional power grids. The rapid response capability of the execution module enables the system to quickly adapt to changes in the supply and demand of electric energy, improve the flexibility and response speed of the system, and through reasonable distribution of electric energy, reduce equipment overload and frequent start and stop, extend the service life of equipment, reduce maintenance costs, ensure the normal operation of important loads when electric energy is scarce, and improve the reliability and safety of the system.

[0093] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and the above embodiments and descriptions are only preferred examples of the present invention, and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. An intelligent power system based on solar-storage direct-flexible technology, characterized in that: include: A photovoltaic power generation unit (1), wherein the photovoltaic power generation unit (1) is used to collect solar energy by installing solar photovoltaic panels and convert the solar energy into electrical energy, and in the process of converting the solar energy into electrical energy, temperature influence, system loss and seasonal factors are introduced for optimization; wherein the photovoltaic power generation unit (1) comprises a DC power distribution module and a plurality of DC load systems; An energy storage unit (2), the energy storage unit (2) being used to store excess electric energy, and when the electric energy generated by the photovoltaic power generation unit (1) is insufficient or there is no energy, the electric energy of the energy storage unit (2) is used to supply power; A power management unit (3), the power management unit (3) being used to monitor and manage the distribution of direct current in the photovoltaic power generation unit (1), and dynamically adjust the direct current according to actual demand; The photovoltaic power generation unit (1) converts solar energy into electrical energy as follows: ； in, is the maximum output power of the photovoltaic panel; is the short-circuit current; is the open circuit voltage; is the conversion efficiency; ； in, is the daily power generation; is the number of effective sunshine hours per day; is the performance ratio; In the photovoltaic power generation unit (1), temperature influence, system loss and seasonal factors are introduced to optimize the process of converting solar energy into electrical energy. After optimization, the specific results are as follows: ； in, For The maximum output power of photovoltaic panels; For The short-circuit current; For The open circuit voltage; For conversion efficiency; is the temperature of the photovoltaic panel surface; ； in, is the short-circuit current under standard test conditions; is the short-circuit current temperature coefficient; is the temperature under standard test conditions; ； in, is the open circuit voltage under standard test conditions; is the open circuit voltage temperature coefficient; ； in, is the conversion efficiency under standard test conditions; is the temperature coefficient; ； in, is the optimized daily power generation; is the seasonal adjustment factor; is the system loss coefficient.

2. According to claim 1, the intelligent power system based on solar-storage direct-flexible technology is characterized by: The electric energy in the photovoltaic power generation unit (1) is direct current, and the direct current distribution module is responsible for distributing the direct current generated by photovoltaic power generation to various direct current load systems, and the direct current load systems directly use the distributed direct current.

3. According to claim 2, the intelligent power system based on solar-storage direct-flexible technology is characterized by: The power management unit (3) comprises a data acquisition module, a controller and an execution module. The data acquisition module is used to collect data of the photovoltaic power generation unit (1) and the energy storage unit (2) and transmit the data to the controller. The controller makes a decision and generates a control signal based on the received data. The execution module performs a corresponding operation based on the type of the control signal.

4. According to claim 3, the intelligent power system based on solar-storage direct-flexible technology is characterized by: The data acquisition module is used to collect data of the photovoltaic power generation unit (1) and the energy storage unit (2), including photovoltaic power generation data, energy storage data and load data; wherein the photovoltaic power generation data is the daily power generation of the photovoltaic panel; the energy storage data is the power level and health status of the energy storage unit (2); and the load data is the power consumption of each DC load.

5. According to claim 4, the intelligent power system based on solar-storage direct-flexible technology is characterized by: The controller makes a decision based on the received data and generates a control signal. The execution module performs corresponding operations based on the type of the control signal. The specific steps are as follows: S1, the controller processes the received data, calculates the current power generation and power consumption, and predicts the future power generation and power consumption through algorithms; S2. Formulate power usage strategies and generate control signals based on current power generation and power consumption as well as future power demand and supply conditions; S3, the execution module controls the switches in the photovoltaic power generation unit (1) and the energy storage unit (2) through control signals, thereby realizing dynamic distribution of electric energy.

6. According to claim 5, the intelligent power system based on solar-storage direct-flexible technology is characterized by: The S1 is specifically: The SARIMA model is used to predict the electricity demand for the next week, and the LSTM model is used to predict the photovoltaic power generation for the next week. The prediction results of the SARIMA and LSTM models are combined and the final prediction value is obtained by weighted average.

7. According to claim 6, the intelligent power system based on solar-storage direct-flexible technology is characterized by: The S2 is specifically: When the power generation is greater than the power consumption, the controller can detect the excess power and generate a first control signal; when the power consumption is greater than the power generation, the controller can detect the energy shortage and generate a second control signal.

8. According to claim 7, the intelligent power system based on solar-storage direct-flexible technology is characterized by: The S3 is specifically: When the actuator receives a first control signal, it turns on the switch of the photovoltaic power generation unit (1), and transmits excess direct current of the photovoltaic power generation unit (1) to the energy storage unit (2); when the actuator receives a second control signal, it turns on the switch of the energy storage unit (2), and transmits energy of the energy storage unit (2) to the photovoltaic power generation unit (1), and then to the direct current load system.

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