Photovoltaic power control method and system based on improved sparrow search algorithm and variable step size perturbation and observation method

Abstract

The invention provides a photovoltaic power control method and system based on an improved sparrow search algorithm and a variable step size perturbation and observation method.The method comprises the steps that collected voltage and current serve as input and are transmitted to the improved sparrow search algorithm, iterative training is carried out, whether the number of iterations is reached or not is judged, and if yes, the step size is changed; outputting an optimal fitness value fg and an optimal sparrow position Xbest, namely maximum power and maximum power point voltage, and terminating iterative training of the improved sparrow search algorithm at the same time; detecting the voltage and the current which are iteratively trained by the improved sparrow search algorithm, obtaining a power difference value, calculating a voltage difference value at the same time, and finally, completing the search of the maximum power point according to a variable step size perturbation and observation method. According to the method, the improved sparrow search algorithm is firstly utilized to quickly track the vicinity of the maximum power point, and then the variable step size perturbation and observation method is utilized to finely search the maximum power point, so that the tracking speed and the tracking precision are improved, and meanwhile, the requirements of the MPPT search speed and the search precision are considered.

Description

Technical Field

[0001] The invention relates to the technical field of photovoltaic power control, and in particular to a photovoltaic power control method and system based on an improved sparrow search algorithm and a variable step-size perturbation observation method. Background Art

[0002] In today's society, people pay more and more attention to environmental protection and resource conservation. The deteriorating ecological environment and gradually depleted resources have made people pay more and more attention to renewable resources. Vigorously developing clean energy represented by photovoltaics is an important means to deal with energy and environmental crises at home and abroad.

[0003] In the actual engineering application of photovoltaic power generation technology, due to reasons such as cloud cover and dust accumulation, the PU characteristic curve of the photovoltaic array presents multi-peak characteristics, with multiple local maximum power points and one global maximum power point. At this time, traditional photovoltaic power control methods, such as the perturbation observation method and the conductance increment method, cannot track the true maximum power point of the photovoltaic cell. Although the existing intelligent photovoltaic power control method can track the global maximum power point, it has problems such as slow tracking speed and large power oscillation. These drawbacks seriously affect the efficiency of the photovoltaic power generation system and restrict the development of the photovoltaic industry. To this end, a new photovoltaic power control method is needed to enable the system to quickly and accurately track the global maximum power point under local shadows and reduce power oscillation and energy loss. This can not only improve the efficiency of the photovoltaic power generation system and promote the development of the photovoltaic industry, but also play a positive role in solving the energy and environmental crises. Summary of the invention

[0004] Purpose of the invention: In order to solve the problems of the above-mentioned prior art, the present invention provides a photovoltaic power control method based on an improved sparrow search algorithm and a variable step-size perturbation observation method, which solves the problem of low control accuracy caused by poor local search ability of the sparrow search algorithm when it is applied to the field of power optimization control of power systems. The present invention also provides a photovoltaic power control system based on an improved sparrow search algorithm and a variable step-size perturbation observation method.

[0005] Technical solution: According to a first aspect of the present invention, a photovoltaic power control method based on an improved sparrow search algorithm and a variable step-size perturbation observation method is provided, the method comprising:

[0006] The collected voltage and current are used as input and transmitted to the improved sparrow search algorithm, and iterative training is performed to determine whether the iteration number is reached. If the iteration number is reached, the optimal fitness value f is output. g and the best sparrow position X best , i.e., the maximum power and the maximum power point voltage, and at the same time, terminating the iterative training of the improved sparrow search algorithm;

[0007] Detecting the voltage and current after iterative training of the improved sparrow search algorithm, and calculating the power at the previous moment and the power at the current moment respectively, obtaining the power difference dP, and calculating the voltage difference dU at the same time, and finally, completing the search for the maximum power point according to the variable step size perturbation observation method;

[0008] Among them, the improved sparrow search algorithm is to update the position of the joiner in the population based on the drunkard's walk strategy, and the variable step size perturbation observation method is used to automatically adjust the perturbation step size according to the distance between the current working point of the photovoltaic power generation system and the maximum power point. When the working point of the photovoltaic power generation system is at the maximum power point, that is, The photovoltaic power generation system will no longer apply disturbances.

[0009] Further, including:

[0010] The process of iterative training of the improved sparrow search algorithm comprises the following steps:

[0011] S1 inputs the detected voltage and current, sets the population size, maximum number of iterations, number of discoverers, and number of joiners;

[0012] S2 initializes the position of the sparrow population, and uses voltage and current as individual sparrows, calculates the fitness value of each sparrow according to the objective function, and finally sorts to determine the current global optimal solution X best and the worst solution X worst ;

[0013] S3 updates the position of the population discoverer and combines the global optimal solution X based on the drunkard's walk strategy best and the worst solution X worst Update the positions of the joiners in the population; finally, update the positions of the alerters in the population who are aware of the danger.

[0014] Further, including:

[0015] The drunkard's walk strategy combined with the global optimal solution X best and the worst solution X worst Update the position of the joiner in the population, including:

[0016] The drunkard's walk strategy is an irregular change form, and each step in the change process is random, and its expression is:

[0017] D i =step·sin(-r4·π / 2+π / 2);

[0018] Among them, step is the drunkard's step length; r4 is a random number in [0,1];

[0019] Therefore, the update rule of the participant is improved by the drunkard's walk strategy, and the improved participant's position update formula is:

[0020]

[0021] in, The best position found for the current finder; is the position of the sparrow with the worst fitness value in the world; A is a matrix with 1 row and d columns, and its elements are randomly assigned values ​​of -1 or 1; when When , it means that the i-th participant with low fitness value gets very little food and needs to go to other areas to find food; when When , it means that the joiner jumps to the current best position, t is the current iteration number; i is the i-th sparrow; X i,j is the position information of the i-th sparrow in the j-th dimension, j = 1, 2, 3, …, d; L is a matrix with 1 row and d columns, all elements of which are 1, and Q is a random number that obeys the normal distribution.

[0022] Further, including:

[0023] The improved sparrow search algorithm also includes: using Tent chaotic mapping to initialize the position of the sparrow population.

[0024] Further, including:

[0025] The position of the warning persons who are aware of the danger in the updating population is specifically expressed as:

[0026]

[0027] in, is the position with the best global fitness at present; K is a random number in [-1,1]; β is a random number that obeys the standard normal distribution; f i is the fitness value of the current individual, and f g and f w is the current global optimal fitness value and the worst fitness value; ε is a minimum constant; when f i =f g When , it means that the sparrow is aware of the danger of being preyed on and needs to get closer to other sparrows; when f i >f g When , it means that the sparrow has poor adaptability and is more likely to be preyed upon.

[0028] Further, including:

[0029] The variable step size perturbation observation method uses the derivative of the sigmoid function to update the perturbation step size of the variable step size perturbation observation method in real time, specifically including:

[0030] Transform the derivative of the sigmoid function, and the transformed function expression is:

[0031]

[0032] The range of the transformed function value is [0,1]. When the independent variable is zero, the function value is also zero. Replace x in the above formula with dP / dU, and then set the maximum perturbation step value F according to the actual situation. max , the proposed variable step size update formula is obtained as:

[0033]

[0034] in, P (k) is the output power value of the photovoltaic panel at the current moment, P (k-1) is the output power value of the photovoltaic panel at the previous moment; U (k) is the photovoltaic panel voltage value at the current moment, U (k-1) It is the voltage value of the photovoltaic panel at the previous moment.

[0035] In a second aspect, the present invention further provides a photovoltaic control system, which includes a sampling module, a photovoltaic array, a photovoltaic power control module, a PWM drive module, a Boost module and a load module;

[0036] The input end of the sampling module is connected to the output end of the photovoltaic array, the output end of the sampling module is connected to the input end of the photovoltaic power control module, the output end of the photovoltaic power control module is connected to the input end of the PWM drive module, the output end of the PWM drive module is connected to the input end of the Boost boost module, the output end of the Boost boost module is connected to the load module, and the photovoltaic power control module is provided with the above-mentioned photovoltaic power control method based on the improved sparrow search algorithm and the variable step size perturbation observation method.

[0037] Further, including:

[0038] The sampling module includes a voltage sampling module and a current sampling module, which are respectively connected to the output end of the photovoltaic array and are used to collect the output voltage and output current of the photovoltaic array in real time and send them to the photovoltaic power control module.

[0039] In a third aspect, the present invention further provides a computer-readable storage medium having computer instructions stored thereon, which, when the computer instructions are executed, execute the photovoltaic power control method based on the improved sparrow search algorithm and the variable step-size perturbation observation method as described above.

[0040] In a fourth aspect, the present invention also provides a risk assessment device based on task indicators, characterized in that the risk assessment device comprises: a memory, a processor, and a photovoltaic power control program based on an improved sparrow search algorithm and a variable step-size perturbation observation method, which is stored in the memory and can be run on the processor. When the photovoltaic power control program based on the improved sparrow search algorithm and the variable step-size perturbation observation method is executed by the processor, the steps of the photovoltaic power control method based on the improved sparrow search algorithm and the variable step-size perturbation observation method as described above are implemented.

[0041] Beneficial effects: Compared with the prior art, the present invention has the following advantages:

[0042] Since the output characteristics of photovoltaic cells are affected by both light intensity and ambient temperature, the maximum power points of photovoltaic cells are different under different lighting conditions and temperatures. In the case of local shadows, the output power of the photovoltaic array has multiple peaks. Traditional photovoltaic power control methods are prone to fall into local extreme values ​​and cannot track the maximum power point. In response to this problem, the present invention proposes a photovoltaic power control method that improves the sparrow search algorithm and the variable step-size perturbation observation method. The tent chaotic mapping is introduced into the sparrow search algorithm to make the initial position of the population uniform, thereby improving the global search capability of the sparrow search algorithm.

[0043] The invention improves the joiner update rule through the drunkard's walk strategy, thereby improving the local search capability of the sparrow search algorithm; the variable step value of the variable step perturbation observation method is obtained based on the derivative of the sigmoid function, thereby overcoming the problems of slow search speed and oscillation of the traditional perturbation observation method.

[0044] Therefore, this method first uses the improved sparrow search algorithm to quickly track the maximum power point, and then uses the variable step size perturbation observation method to perform a fine search for the maximum power point, thereby improving the tracking speed and tracking accuracy, while taking into account the MPPT search speed and search accuracy requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a structural diagram of a photovoltaic control system according to an embodiment of the present invention;

[0046] Figure 2 It is a flow chart of a photovoltaic power control method based on an improved sparrow search algorithm and a variable step-size perturbation observation method according to an embodiment of the present invention;

[0047] Figure 3 is a graph of the derivative of the transformed sigmoid function according to an embodiment of the present invention;

[0048] Figure 4It is a photovoltaic array PU characteristic curve under different lighting conditions of the photovoltaic power control method based on the improved sparrow search algorithm and the variable step size perturbation observation method described in the embodiment of the present invention;

[0049] Figure 5 It is a comparison diagram of photovoltaic power control results of the photovoltaic power control method based on the improved sparrow search algorithm and the variable step size perturbation observation method (ISSA-IP&O) of the present invention and the traditional sparrow search algorithm (SSA) and the traditional perturbation observation method (P&O) under the standard condition (STC) described in the embodiment of the present invention;

[0050] Figure 6 It is a comparison diagram of photovoltaic power control results of the photovoltaic power control method based on the improved sparrow search algorithm and variable step size perturbation observation method (ISSA-IP&O) of the present invention and the traditional sparrow search algorithm (SSA) and the traditional perturbation observation method (P&O) under the partial shadow condition (PSC) described in the embodiment of the present invention;

[0051] Figure 7 It is a schematic diagram of the terminal hardware structure of each embodiment of the photovoltaic power control method based on the improved sparrow search algorithm and the variable step size perturbation observation method described in the embodiments of the present invention. DETAILED DESCRIPTION

[0052] 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.

[0053] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0054] Example 1

[0055] The present invention proposes a photovoltaic power control method based on an improved sparrow search algorithm and a variable step-size perturbation observation method, comprising: sampling the output voltage and current of a photovoltaic array; inputting the obtained voltage and current into an improved sparrow search algorithm and a variable step-size perturbation observation method photovoltaic power control module, and outputting a control signal to a switch tube of a Boost circuit.

[0056] The improved sparrow search algorithm and variable step-size perturbation observation method photovoltaic power control module include: introducing Tent chaos mapping into the sparrow search algorithm to make the initial position of the population uniform, thereby improving the global search capability of the sparrow search algorithm; improving the joiner update rule through the drunkard's walk strategy, thereby improving the local search capability of the sparrow search algorithm; and using the derivative of the sigmoid function to update the perturbation step of the variable step-size perturbation observation method in real time, thereby solving the problems of slow search speed and oscillation of the traditional perturbation observation method.

[0057] This method first uses the improved sparrow search algorithm to quickly track the maximum power point, and then uses the variable step size perturbation observation method to perform a fine search for the maximum power point, while taking into account the requirements of MPPT search speed and search accuracy.

[0058] like Figure 2 As shown, the specific steps include:

[0059] S10 uses the collected voltage and current as input, transmits them to the improved sparrow search algorithm, and iterates the training to determine whether the iteration number is reached. If the iteration number is reached, the optimal fitness value f is output. g and the best sparrow position X best , i.e., the maximum power and the maximum power point voltage, and at the same time terminate the iterative training of the improved sparrow search algorithm.

[0060] This step in the present embodiment does not limit the specific method of collecting voltage and current, but usually a collection module can be provided to perform real-time collection.

[0061] Sparrow Search Algorithm (SSA) is a new type of swarm intelligence optimization algorithm, which is mainly inspired by the foraging behavior and anti-predation behavior of sparrows. In the process of foraging, sparrows are divided into finders (explorers) and joiners (followers). Finders are responsible for finding food in the population and providing foraging areas and directions for the entire sparrow population, while joiners use finders to obtain food. In order to obtain food, sparrows can usually adopt two behavioral strategies, finders and joiners, for foraging. Individuals in the population will monitor the behavior of other individuals in the group, and attackers in the population will compete for food resources with high-intake companions to increase their own predation rate. In addition, when the sparrow population is aware of danger, it will take anti-predation behavior.

[0062] First, in this embodiment, the Tent chaotic mapping is introduced into the improved sparrow search algorithm. Since there is no local optimum in the chaotic optimization process, the Tent chaotic mapping is introduced to make the initial position of the population uniform and improve the global search ability of the sparrow algorithm. The expression is:

[0063]

[0064] Among them, x i is the population of the i-th dimension, u is a number between [0,1]. When u = 0.5, the sequence distribution is relatively uniform, and there is approximately consistent distribution density for different parameters.

[0065] Secondly, in this embodiment, the improved sparrow search algorithm also includes the introduction of a drunkard's walk strategy, which is an irregular form of change, and each step in the change process is random. Its expression is:

[0066] D i =step·sin(-r4·π / 2+π / 2) (2)

[0067] Among them, step is the drunkard's step length, which can be fixed or variable; r4 is a random number in [0,1].

[0068] S20 detects the voltage and current after iterative training of the improved sparrow search algorithm, and respectively calculates the power at the previous moment and the power at the current moment to obtain the power difference dP, and simultaneously calculates the voltage difference dU, and finally, completes the search for the maximum power point according to the variable step size perturbation observation method;

[0069] Among them, the improved sparrow search algorithm is to update the position of the joiner in the population based on the drunkard's walk strategy, and the variable step size perturbation observation method is used to automatically adjust the perturbation step size according to the distance between the current working point of the photovoltaic power generation system and the maximum power point. When the working point of the photovoltaic power generation system is at the maximum power point, that is, The photovoltaic power generation system will no longer apply disturbance. This embodiment does not limit the specific structure of the photovoltaic power generation system, and can be based on a conventional photovoltaic power generation system, and corresponding related functions can also be increased or decreased based on the photovoltaic power generation system.

[0070] like Figure 2 As shown, combined with S10 and S20, it can be seen that the photovoltaic power control method based on the improved sparrow search algorithm and the variable step size perturbation observation method specifically includes the following steps:

[0071] Step 1: Set the population size, maximum number of iterations, number of discoverers, and number of joiners of the sparrow algorithm.

[0072] Step 2: Detect the voltage and current of the photovoltaic panel. Initialize the population based on the Tent chaotic map, calculate the fitness value, and sort to obtain the global optimal solution X best and the worst solution X worst .

[0073] Step 3: Update the position of the population discoverer, calculate the fitness value to obtain the current global optimal solution; update the position of the joiner in the population based on the drunkard's walk strategy; update the position of the warning person in the population who is aware of the danger.

[0074] Step 4: Determine whether the number of iterations has been reached. If the number of iterations has been reached, output the optimal fitness value f g and the best sparrow position X best , that is, the maximum power and the maximum power point voltage, and terminate the sparrow algorithm at the same time and enter the variable step size perturbation observation method; otherwise, repeat steps 1 to 3.

[0075] Step 5: Detect the voltage and current obtained by the sparrow algorithm, calculate the power at the previous moment and the power at the current moment according to the power calculation formula P=UI, and obtain the power difference dP, and calculate the voltage difference dU at the same time. Calculate the perturbation step length according to formula (9), and then complete the search for the maximum power point according to the perturbation observation method perturbation rule.

[0076] Step 6: Determine whether the algorithm restart condition is met. If so, restart the algorithm; otherwise, output the maximum power point voltage.

[0077] In the above step 3, the position of the population discoverer is updated, and the fitness value is calculated to obtain the current global optimal solution. This embodiment specifically includes:

[0078] In the sparrow algorithm, discoverers with better fitness values ​​will find food first in the process of searching for food, and provide foraging directions for other participants. Some individuals in the population conduct reconnaissance and early warning, and are called early warning detectors.

[0079] The finder's position update formula is:

[0080]

[0081] Among them, t is the current iteration number; i is the i-th sparrow; X i,j is the position information of the i-th sparrow in the j-th dimension, j = 1, 2, 3, …, d; α is a random number in (0, 1]; R2∈(0, 1] is the warning value; S∈(0.5, 1] ​​is the safety value; M is the maximum number of iterations, Q is a random number that obeys the normal distribution; L is a matrix with 1 row and d columns, all elements of which are 1.

[0082] When R2<S, the sparrow population is in a safe area and can conduct extensive searches; when R2≥S, the sparrows in the population have discovered predators, and the sparrow population needs to go elsewhere to find food.

[0083] The joiner update formula in the prior art is as follows:

[0084]

[0085] in, The best position found for the current finder; is the position of the sparrow with the worst fitness value in the world; A is a matrix with 1 row and d columns, and its elements are randomly assigned values ​​of -1 or 1; when When , it means that the i-th participant with low fitness value gets very little food and needs to go to other areas to find food; when , it means that the joiner jumps to the vicinity of the current best position.

[0086] In this embodiment, the position of the joiner in the population is updated based on the drunkard's walk strategy; the position of the early warning person who is aware of the danger in the population is updated, specifically including:

[0087] The drunkard's walk is an irregular form of change, and each step in the change process is random. Its expression is shown in formula (2).

[0088] The drunkard's walk has strong randomness and uncertain direction. The local search ability of the sparrow algorithm is enhanced by improving the participant update rule through the drunkard's walk strategy. The improved participant position update formula is:

[0089]

[0090] The position update formula of the alerter is:

[0091]

[0092] in, is the position with the best global fitness at present; K is a random number in [-1,1]; β is a random number that obeys the standard normal distribution; f i is the fitness value of the current individual, and f g and f w is the current global optimal fitness value and the worst fitness value; ε is a minimum constant; when f i =f g When , it means that the sparrow is aware of the danger of being preyed on and needs to get closer to other sparrows; when f i >f g When , it means that the sparrow has poor adaptability and is more likely to be preyed upon.

[0093] In this embodiment, the perturbation step length is calculated according to formula (9), and then the maximum power point search is completed according to the perturbation rule of the perturbation observation method, which specifically includes:

[0094] The variable step-size perturbation observation method utilizes the derivative of the sigmoid function to update the perturbation step size of the variable step-size perturbation observation method in real time, thereby solving the problems of slow search speed and oscillation of the traditional perturbation observation method.

[0095] When the derivative of the sigmoid function approaches infinity, the dependent variable can be limited to [0,0.25], and its function expression is:

[0096]

[0097] However, the derivative of the sigmoid function is not zero when the independent variable is 0, and the function value is zero when the independent variable approaches infinity. Therefore, the derivative of the sigmoid function is transformed, and the function expression after the transformation is:

[0098]

[0099] like Figure 3 As shown, the range of the transformed function value is [0,1]. When the independent variable is zero, the function value is also zero. Replace x in equation (8) with dP / dU, and then set the maximum perturbation step value F according to the actual situation. max , the proposed variable step size update formula is:

[0100]

[0101] in, P (k) is the output power value of the photovoltaic panel at the current moment, P (k-1) is the output power value of the photovoltaic panel at the previous moment; U (k) is the photovoltaic panel voltage value at the current moment, U (k-1) It is the voltage value of the photovoltaic panel at the previous moment.

[0102] The variable step size perturbation observation method can automatically adjust the perturbation step size according to the distance between the system operating point and the maximum power point. When the system is working at the maximum power point, The system will no longer be disturbed.

[0103] like Figure 2 As shown, in this embodiment, after calculating the adaptive compensation F, it is determined whether there is P (k) =P (k-1) , if they are equal, then continue to judge U (k) =U (k-1) , otherwise, if P (k) <P (k-1) , then judge U (k) >U (k-1) , if U (k) >U (k-1) , then set U (k+1) =U (k) -F, otherwise, if U (k) ≤U (k-1) , then U (k+1) =U (k) +F;

[0104] If P (k) ≥P (k-1) , then determine whether there is U (k) >U (k-1) , if so, then U (k+1) =U (k) +F, otherwise, U (k+1) =U (k) -F;

[0105] Determine whether the restart condition is met. If so, re-adopt the improved sparrow algorithm for iterative training. Otherwise, maintain the current voltage output and end.

[0106] Example 2

[0107] On the basis of Example 1, Figure 1 As shown, the present invention proposes a system structure corresponding to a photovoltaic power control method based on an improved sparrow algorithm and a variable step-size perturbation observation method, including: a photovoltaic array, a sampling module, a photovoltaic power control module, a PWM drive module, a Boost boost module and a load module. The input end of the sampling module is connected to the output end of the photovoltaic array, the output end of the sampling module is connected to the input end of the photovoltaic power control module, the output end of the photovoltaic power control module is connected to the input end of the PWM drive module, the output end of the PWM drive module is connected to the input end of the Boost boost module, and the output end of the Boost boost module is connected to the load module.

[0108] The sampling module includes a voltage sampling module and a current sampling module. The voltage sampling module and the current sampling module are respectively connected to the output end of the photovoltaic array to collect the output voltage and output current of the photovoltaic array in real time and send them to the photovoltaic power control module.

[0109] This embodiment does not limit the specific components of the PWM drive module and the Boost boost module, which are customized according to the specific needs of the inventor.

[0110] The photovoltaic power control module in this embodiment integrates the improved sparrow search algorithm and the variable step size perturbation observation photovoltaic power control method described in the embodiment, including:

[0111] Step 10: Set the population size, maximum number of iterations, number of discoverers, and number of joiners of the sparrow algorithm.

[0112] Step 20: Detect the voltage and current of the photovoltaic panel. Initialize the population based on the Tent chaotic map, calculate the fitness value, and sort to obtain the global optimal solution X best and the worst solution X worst .

[0113] Step 30: Update the position of the population discoverer, calculate the fitness value to obtain the current global optimal solution; update the position of the joiner in the population based on the drunkard's walk strategy; update the position of the warning person in the population who is aware of the danger.

[0114] Step 40: Determine whether the number of iterations has been reached. If the number of iterations has been reached, output the optimal fitness value f g and the best sparrow position X best , that is, the maximum power and the maximum power point voltage, and at the same time terminate the sparrow algorithm and enter the variable step size perturbation observation method; otherwise, repeat steps 1 to 3.

[0115] Step 50: Detect the voltage and current obtained by the sparrow algorithm, calculate the power at the previous moment and the power at the current moment according to the power calculation formula P=UI, obtain the power difference dP, and calculate the voltage difference dU at the same time. Calculate the perturbation step length according to formula (9), and then complete the search for the maximum power point according to the perturbation observation method perturbation rule.

[0116] Step 60: Determine whether the algorithm restart condition is met, if so, restart the algorithm, otherwise output the maximum power point voltage.

[0117] Other technical features of the photovoltaic power control system based on the improved sparrow algorithm and the variable step-size perturbation observation method described in the present invention are similar to the corresponding photovoltaic power control method based on the improved sparrow algorithm and the variable step-size perturbation observation method, and will not be repeated here.

[0118] In order to verify the effectiveness of this application, the following examples are provided.

[0119] Considering that the PU output characteristic curve of the photovoltaic array under PSC will have multiple local maximum power points, the traditional photovoltaic power control method cannot accurately identify the local extreme value and the global maximum value, and is prone to failure when tracking the maximum power point, resulting in reduced tracking efficiency. The introduction of intelligent algorithms solves the defect that traditional photovoltaic power control methods are prone to fall into local optimality. Although intelligent algorithms can solve the disadvantages of traditional algorithms falling into local peaks under multi-peak conditions, there is still room for improvement in tracking speed, accuracy and stability. In order to further verify that the output characteristic curve of the photovoltaic array under different conditions presents a multi-peak phenomenon, a simulation model of the photovoltaic array is established, and different lighting conditions are set to prepare for the verification of the photovoltaic power control method. S1, S2, and S3 represent the light intensity on photovoltaic cells PV1, PV2, and PV3, respectively. Table 1 shows the different environmental parameters set in the photovoltaic power control method example based on the improved sparrow algorithm and the variable step size perturbation observation method of the present invention, which are divided into STC and PSC.

[0120] Table 1 Irradiance under different lighting conditions

[0121]

[0122] Figure 4 The photovoltaic array PU characteristic curve under different lighting conditions is obtained by the photovoltaic power control method based on the improved sparrow algorithm and the variable step size perturbation observation method of the present invention. In STC, the PU curve of the photovoltaic array has only one peak, and in PSC, the PU curve of the photovoltaic array has multiple peaks. The more complex the lighting conditions, the more complex the output characteristic curve, and the more likely the traditional photovoltaic power control method will fall into a local solution.

[0123] Figure 5 It is a comparison chart of photovoltaic power control results of the improved sparrow algorithm and variable step size perturbation observation method (ISSA-IP&O) of the present invention and the traditional sparrow algorithm (SSA) and the traditional perturbation observation method (P&O) under STC; Figure 6 This is a comparison chart of the photovoltaic power control results of the method proposed in the present invention under PSC, SSA and P&O. The results show that under STC and PSC, the method proposed in the present invention has a faster tracking speed and higher tracking efficiency than other methods, avoiding the system from falling into the local maximum power point, and effectively improving the photovoltaic power generation efficiency.

[0124] Example 3

[0125] Reference Figure 7 , Figure 7 The figure is a schematic diagram of the terminal structure of the hardware operating environment involved in the embodiment of the present invention.

[0126] like Figure 7 As shown, the terminal may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a network interface 1003, and a memory 1004. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The network interface 1003 may optionally include a standard wired interface, a wireless interface (such as a wireless fidelity (WIreless-FIdelity, WI-FI) interface). The memory 1004 may be a high-speed RAM memory (Random Access Memory, RAM) or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk memory. The memory 1004 may optionally be a storage device independent of the aforementioned processor 1001.

[0127] Those skilled in the art will understand that Figure 7 The terminal structure shown in the figure does not constitute a limitation on the terminal, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0128] like Figure 7 As shown, the memory 1004 as a computer storage medium may include an operating system, a data storage module, a network communication module, and a photovoltaic power control program based on an improved sparrow algorithm and a variable step size disturbance observation method.

[0129] exist Figure 7 In the terminal shown, the network interface 1003 is mainly used to connect to the backend server and perform data communication with the backend server; the processor 1001 can call the photovoltaic power control program based on the improved sparrow algorithm and the variable step size perturbation observation method stored in the memory 1004, and perform the following operations:

[0130] The collected voltage and current are used as input and transmitted to the improved sparrow search algorithm, and iterative training is performed to determine whether the iteration number is reached. If the iteration number is reached, the optimal fitness value f is output. g and the best sparrow position X best , i.e., the maximum power and the maximum power point voltage, and at the same time, terminating the iterative training of the improved sparrow search algorithm;

[0131] Detecting the voltage and current after iterative training of the improved sparrow search algorithm, and calculating the power at the previous moment and the power at the current moment respectively, obtaining the power difference dP, and calculating the voltage difference dU at the same time, and finally, completing the search for the maximum power point according to the variable step size perturbation observation method;

[0132] Among them, the improved sparrow search algorithm is to update the position of the joiner in the population based on the drunkard's walk strategy, and the variable step size perturbation observation method is used to automatically adjust the perturbation step size according to the distance between the current working point of the photovoltaic power generation system and the maximum power point. When the working point of the photovoltaic power generation system is at the maximum power point, that is, The photovoltaic power generation system will no longer apply disturbances.

[0133] Further, the processor 1001 may call the photovoltaic power control program based on the improved sparrow algorithm and the variable step size perturbation observation method stored in the memory 1004, and further perform the following operations:

[0134] The process of iterative training of the improved sparrow search algorithm comprises the following steps:

[0135] S1 inputs the detected voltage and current, sets the population size, maximum number of iterations, number of discoverers, and number of joiners;

[0136] S2 initializes the position of the sparrow population, and uses voltage and current as individual sparrows, calculates the fitness value of each sparrow according to the objective function, and finally sorts to determine the current global optimal solution X best and the worst solution X worst ;

[0137] S3 updates the position of the population discoverer and combines the global optimal solution X based on the drunkard's walk strategy best and the worst solution X worst Update the positions of the joiners in the population; finally, update the positions of the alerters in the population who are aware of the danger.

[0138] Further, the processor 1001 may call the photovoltaic power control program based on the improved sparrow algorithm and the variable step size perturbation observation method stored in the memory 1004, and further perform the following operations:

[0139] The drunkard's walk strategy combined with the global optimal solution X best and the worst solution X worst Update the position of the joiner in the population, including:

[0140] The drunkard's walk strategy is an irregular change form, and each step in the change process is random, and its expression is:

[0141] D i =step·sin(-r4·π / 2+π / 2);

[0142] Among them, step is the drunkard's step length; r4 is a random number in [0,1];

[0143] Therefore, the update rule of the participant is improved by the drunkard's walk strategy, and the improved participant's position update formula is:

[0144]

[0145] in, The best position found for the current finder; is the position of the sparrow with the worst fitness value in the world; A is a matrix with 1 row and d columns, and its elements are randomly assigned values ​​of -1 or 1; when When , it means that the i-th participant with low fitness value gets very little food and needs to go to other areas to find food; when When , it means that the joiner jumps to the current best position, t is the current iteration number; i is the i-th sparrow; X i,j is the position information of the i-th sparrow in the j-th dimension, j = 1, 2, 3, …, d; L is a matrix with 1 row and d columns, all elements of which are 1, and Q is a random number that obeys the normal distribution.

[0146] Further, the processor 1001 may call the photovoltaic power control program based on the improved sparrow algorithm and the variable step size perturbation observation method stored in the memory 1004, and further perform the following operations:

[0147] The improved sparrow search algorithm also includes: using Tent chaotic mapping to initialize the position of the sparrow population.

[0148] Further, the processor 1001 may call the photovoltaic power control program based on the improved sparrow algorithm and the variable step size perturbation observation method stored in the memory 1004, and further perform the following operations:

[0149] The position of the warning persons who are aware of the danger in the updating population is specifically expressed as:

[0150]

[0151] in, is the position with the best global fitness at present; K is a random number in [-1,1]; β is a random number that obeys the standard normal distribution; f i is the fitness value of the current individual, and f g and f w is the current global optimal fitness value and the worst fitness value; ε is a minimum constant; when f i =f g When , it means that the sparrow is aware of the danger of being preyed on and needs to get closer to other sparrows; when f i >f g When , it means that the sparrow has poor adaptability and is more likely to be preyed upon.

[0152] Further, the processor 1001 may call the photovoltaic power control program based on the improved sparrow algorithm and the variable step size perturbation observation method stored in the memory 1004, and further perform the following operations:

[0153] The variable step size perturbation observation method uses the derivative of the sigmoid function to update the perturbation step size of the variable step size perturbation observation method in real time, specifically including:

[0154] Transform the derivative of the sigmoid function, and the transformed function expression is:

[0155]

[0156] The range of the transformed function value is [0,1]. When the independent variable is zero, the function value is also zero. Replace x in the above formula with dP / dU, and then set the maximum perturbation step value F according to the actual situation. max , the proposed variable step size update formula is obtained as:

[0157]

[0158] in, P (k) is the output power value of the photovoltaic panel at the current moment, P (k-1) is the output power value of the photovoltaic panel at the previous moment; U (k) is the photovoltaic panel voltage value at the current moment, U (k-1)It is the voltage value of the photovoltaic panel at the previous moment.

[0159] In addition, it can be understood by a person skilled in the art that all or part of the processes in the method for implementing the above embodiment can be completed by instructing the relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the control terminal to implement the process steps of the embodiment of the above method.

[0160] Therefore, the present invention also provides a computer-readable storage medium, which stores a photovoltaic power control program based on an improved sparrow algorithm and a variable step-size perturbation observation method. When the photovoltaic power control program based on the improved sparrow algorithm and the variable step-size perturbation observation method is executed by a processor, the various steps of the photovoltaic power control method based on the improved sparrow algorithm and the variable step-size perturbation observation method described in the above embodiment are implemented.

[0161] It should be noted that since the storage medium provided in the embodiment of the present application is the storage medium used to implement the method of the embodiment of the present application, based on the method introduced in the embodiment of the present application, the person skilled in the art can understand the specific structure and deformation of the storage medium, so it is not repeated here. All storage media used in the method of the embodiment of the present application belong to the scope of protection of this application.

[0162] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0163] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0164] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0165] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0166] It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claim. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention may be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names.

[0167] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0168] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

[0169] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A photovoltaic power control method based on an improved sparrow search algorithm and a variable step size perturbation observation method, characterized in that: The method includes: The collected voltage and current are used as input and transmitted to the improved sparrow search algorithm, and iterative training is performed to determine whether the iteration number is reached. If the iteration number is reached, the optimal fitness value f is output. g and the best sparrow position X best , i.e., the maximum power and the maximum power point voltage, and at the same time, terminating the iterative training of the improved sparrow search algorithm; Detecting the voltage and current after iterative training of the improved sparrow search algorithm, and calculating the power at the previous moment and the power at the current moment respectively, obtaining the power difference dP, and calculating the voltage difference dU at the same time, and finally, completing the search for the maximum power point according to the variable step size perturbation observation method; Among them, the improved sparrow search algorithm is to update the position of the joiner in the population based on the drunkard's walk strategy, and the variable step size perturbation observation method is used to automatically adjust the perturbation step size according to the distance between the current working point of the photovoltaic power generation system and the maximum power point. When the working point of the photovoltaic power generation system is at the maximum power point, that is, The photovoltaic power generation system will no longer apply disturbances.

2. The photovoltaic power control method based on the improved sparrow search algorithm and the variable step size perturbation observation method as claimed in claim 1, characterized in that: The process of iterative training of the improved sparrow search algorithm comprises the following steps: S1 inputs the detected voltage and current, sets the population size, maximum number of iterations, number of discoverers, and number of joiners; S2 initializes the position of the sparrow population, and uses voltage and current as individual sparrows, calculates the fitness value of each sparrow according to the objective function, and finally sorts to determine the current global optimal solution X best and the worst solution X worst ; S3 updates the position of the population discoverer and combines the global optimal solution X based on the drunkard's walk strategy best and the worst solution X worst Update the positions of the joiners in the population; finally, update the positions of the alerters in the population who are aware of the danger.

3. The photovoltaic power control method based on the improved sparrow search algorithm and the variable step size perturbation observation method as claimed in claim 2, characterized in that: The drunkard's walk strategy combined with the global optimal solution X best and the worst solution X worst Update the position of the joiner in the population, including: The drunkard's walk strategy is an irregular change form, and each step in the change process is random, and its expression is: D i =step·sin(-r4·π / 2+π / 2); Among them, step is the drunkard's step length; r4 is a random number in [0,1]; Therefore, the update rule of the participant is improved by the drunkard's walk strategy, and the improved participant's position update formula is: in, The best position found for the current finder; is the position of the sparrow with the worst fitness value in the world; A is a matrix with 1 row and d columns, and its elements are randomly assigned values ​​of -1 or 1; when When , it means that the i-th participant with low fitness value gets very little food and needs to go to other areas to find food; when When , it means that the joiner jumps to the current best position, t is the current iteration number; i is the i-th sparrow; X i,j is the position information of the i-th sparrow in the j-th dimension, j = 1, 2, 3, …, d; L is a matrix with 1 row and d columns, all elements of which are 1, and Q is a random number that obeys the normal distribution.

4. The photovoltaic power control method based on the improved sparrow search algorithm and the variable step size perturbation observation method according to claim 1, characterized in that: The improved sparrow search algorithm also includes: using Tent chaotic mapping to initialize the position of the sparrow population.

5. The photovoltaic power control method based on the improved sparrow search algorithm and the variable step size perturbation observation method according to claim 1, characterized in that: The position of the warning persons who are aware of the danger in the updating population is specifically expressed as: in, is the position with the best global fitness at present; K is a random number in [-1,1]; β is a random number that obeys the standard normal distribution; f i is the fitness value of the current individual, and f g and f w is the current global optimal fitness value and the worst fitness value; ε is a minimum constant; when f i =f g When , it means that the sparrow is aware of the danger of being preyed on and needs to get closer to other sparrows; when f i >f g When , it means that the sparrow has poor adaptability and is more likely to be preyed upon.

6. The photovoltaic power control method based on the improved sparrow search algorithm and the variable step size perturbation observation method according to claim 1, characterized in that: The variable step size perturbation observation method uses the derivative of the sigmoid function to update the perturbation step size of the variable step size perturbation observation method in real time, specifically including: Transform the derivative of the sigmoid function, and the transformed function expression is: The range of the transformed function value is [0,1]. When the independent variable is zero, the function value is also zero. Replace x in the above formula with dP / dU, and then set the maximum perturbation step value F according to the actual situation. max , the proposed variable step size update formula is obtained as: in, P (k) is the output power value of the photovoltaic panel at the current moment, P (k-1) is the output power value of the photovoltaic panel at the previous moment; U (k) is the photovoltaic panel voltage value at the current moment, U (k-1) It is the voltage value of the photovoltaic panel at the previous moment.

7. A photovoltaic control system, characterized in that: The system includes a sampling module, a photovoltaic array, a photovoltaic power control module, a PWM drive module, a Boost module and a load module; The input end of the sampling module is connected to the output end of the photovoltaic array, the output end of the sampling module is connected to the input end of the photovoltaic power control module, the output end of the photovoltaic power control module is connected to the input end of the PWM drive module, the output end of the PWM drive module is connected to the input end of the Boost boost module, and the output end of the Boost boost module is connected to the load module. The photovoltaic power control module is provided with the photovoltaic power control method based on the improved sparrow search algorithm and the variable step size perturbation observation method as described in any one of claims 1 to 6.

8. The photovoltaic control system according to claim 7, characterized in that: The sampling module includes a voltage sampling module and a current sampling module, which are respectively connected to the output end of the photovoltaic array and are used to collect the output voltage and output current of the photovoltaic array in real time and send them to the photovoltaic power control module.

9. A computer-readable storage medium having computer instructions stored thereon, which, when the computer instructions are executed, execute the photovoltaic power control method based on the improved sparrow search algorithm and the variable step-size perturbation observation method as described in any one of claims 1 to 6.

10. A risk assessment device based on task indicators, characterized in that: The risk assessment device includes: a memory, a processor, and a photovoltaic power control program based on an improved sparrow search algorithm and a variable step-size perturbation observation method, which is stored in the memory and can be run on the processor. When the photovoltaic power control assessment program based on the improved sparrow search algorithm and the variable step-size perturbation observation method is executed by the processor, the steps of the photovoltaic power control method based on the improved sparrow search algorithm and the variable step-size perturbation observation method as described in any one of claims 1 to 6 are implemented.

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