Multi-bin multi-traveler problem-oriented non-rectangular photovoltaic array reconstruction method

Abstract

The invention discloses a multi-bin multi-traveling salesman problem-oriented non-rectangular photovoltaic array reconstruction method. The method comprises the steps of obtaining a parameter matrix of a photovoltaic array and weights of various parameters in the parameter matrix; converting the parameter matrix of each photovoltaic module in the photovoltaic array into a corresponding coordinate matrix; obtaining the distance between the photovoltaic modules according to the parameter matrix, the weight and the coordinate matrix; taking the preset number of series battery strings as the number of travelers in the multi-bin multi-traveler problem, and taking each photovoltaic module as a city node; and based on the number of travelers and the distance between the urban node and each photovoltaic module, adopting a multi-bin traveler problem optimization algorithm to obtain optimal photovoltaic module series and parallel configuration so as to realize dynamic reconstruction of the photovoltaic array. According to the method, the influence of non-uniform illumination and temperature on the non-rectangular photovoltaic array is considered at the same time, the performance of the non-rectangular photovoltaic array under the non-uniform illumination is improved, and the influence of the non-uniform illumination on the performance of the irregular photovoltaic array is effectively reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of solar power generation, and particularly relates to a non-rectangular photovoltaic array reconstruction method oriented to the multi-warehouse multi-traveling salesman problem. Background Art

[0002] Due to the influence of environmental factors, uneven light distribution often occurs on the surface of a photovoltaic array. The uneven light intensity will not only cause mismatch losses and hot spot problems, but may even lead to the damage of the photovoltaic array. To mitigate the negative impact of uneven light on the array performance, a reconstruction method is often adopted. Currently, the reconstruction research mainly focuses on rectangular photovoltaic arrays and assumes that each photovoltaic module contains the same number of photovoltaic cells. However, when the photovoltaic array is non-rectangular and the number of photovoltaic cells in each module is not equal, the existing methods are often inapplicable. Irregular photovoltaic arrays usually appear in mountain photovoltaic power stations and concentrating photovoltaic power generation systems, where the uneven light situation is more complex. Summary of the Invention

[0003] To solve the above problems existing in the prior art, the present invention provides a non-rectangular photovoltaic array reconstruction method oriented to the multi-warehouse multi-traveling salesman problem. The technical problems to be solved by the present invention are realized through the following technical solutions:

[0004] The present invention provides a non-rectangular photovoltaic array reconstruction method oriented to the multi-warehouse multi-traveling salesman problem, and the method includes:

[0005] Obtaining a parameter matrix of the photovoltaic array through a light intensity sensor, a temperature sensor, and relevant parameters of the photovoltaic module;

[0006] Obtaining the weights of various parameters in the parameter matrix according to the characteristics of the photovoltaic cells;

[0007] Regarding each photovoltaic module in the photovoltaic array as a point in three-dimensional space, and converting the parameter matrix of each photovoltaic module into a corresponding coordinate matrix;

[0008] Obtaining the distances between each photovoltaic module according to the parameter matrix, the weights of various parameters in the parameter matrix, and the coordinate matrix;

[0009] Determining the number of series-connected battery strings in the photovoltaic array according to a preset requirement;

[0010] Taking the number of series-connected battery strings as the number of traveling salesmen in the multi-warehouse multi-traveling salesman problem, and regarding each photovoltaic module as a city node; based on the number of traveling salesmen, the city nodes, and the distances between each photovoltaic module, adopting a multi-warehouse traveling salesman problem optimization algorithm to obtain an optimal series and parallel configuration of the photovoltaic modules to realize the dynamic reconstruction of the photovoltaic array.

[0011] In an embodiment of the present invention, the expression of the parameter matrix of the photovoltaic array is as follows:

[0012]

[0013] where i ∈ [1, M], PV i represents the parameter corresponding to the i-th photovoltaic module, G i represents the light intensity corresponding to the i-th photovoltaic module, T i represents the temperature corresponding to the i-th photovoltaic module, N si represents the number of photovoltaic cells corresponding to the i-th photovoltaic module, and M represents the total number of photovoltaic modules in the non-rectangular photovoltaic array.

[0014] In an embodiment of the present invention, according to the characteristics of the photovoltaic cells, the weights of various parameters in the parameter matrix are obtained, including:

[0015] Based on the light intensity, temperature, and number of photovoltaic cells of the photovoltaic modules in the photovoltaic array, the power of the photovoltaic module at the maximum power point is obtained;

[0016] According to the light intensity, temperature, number of photovoltaic cells, and power at the maximum power point corresponding to the photovoltaic module, the weights of various parameters in the parameter matrix are obtained.

[0017] In an embodiment of the present invention, based on the light intensity, temperature, and number of photovoltaic cells of the photovoltaic modules in the photovoltaic array, obtaining the power of the photovoltaic module at the maximum power point includes:

[0018] According to the light intensity and temperature of the photovoltaic modules in the photovoltaic array, the corresponding short-circuit current is obtained;

[0019] According to the short-circuit current and the number of photovoltaic cells, the open-circuit voltage of the photovoltaic module is obtained;

[0020] Based on the open-circuit voltage, the fill factor of the photovoltaic module is obtained;

[0021] According to the short-circuit current, open-circuit voltage, and fill factor, the power of the photovoltaic module at the maximum power point is obtained. In an embodiment of the present invention, the expression of the power of the photovoltaic module at the maximum power point is as follows:

[0022] P m =I sc_mod ×V oc_mod ×FF;

[0023] where, I sc_mod represents the short-circuit current of the photovoltaic module, V oc_mod represents the open-circuit voltage of the photovoltaic module, and FF represents the fill factor of the photovoltaic module.

[0024] In one embodiment of the present invention, the expression for the weights of various parameters in the parameter matrix is as follows:

[0025]

[0026] where α represents the first weight, β represents the second weight, γ represents the third weight, and P m represents the power of the photovoltaic module at the maximum power point, represents taking the partial derivative, G represents the light intensity corresponding to the photovoltaic module, T represents the temperature corresponding to the photovoltaic module, and N s represents the number of photovoltaic cells corresponding to the photovoltaic module.

[0027] In one embodiment of the present invention, the expression for the distance between photovoltaic modules is as follows:

[0028]

[0029] where i and j respectively represent any two photovoltaic modules in the photovoltaic array, α represents the first weight, β represents the second weight, γ represents the third weight, and G i represents the light intensity corresponding to the i-th photovoltaic module in the photovoltaic array, and T i represents the temperature corresponding to the i-th photovoltaic module in the photovoltaic array, and N si represents the number of photovoltaic cells corresponding to the i-th photovoltaic module in the photovoltaic array, and G j represents the light intensity corresponding to the j-th photovoltaic module in the photovoltaic array, and T j represents the temperature corresponding to the j-th photovoltaic module in the photovoltaic array, and N sj represents the number of photovoltaic cells corresponding to the j-th photovoltaic module in the photovoltaic array.

[0030] In one embodiment of the present invention, the mathematical model of the multi-warehouse traveling salesman problem optimization algorithm is as follows:

[0031] min f = f1(1 + χ·f2);

[0032] where f1 represents the sum of the driving costs of all traveling salesmen, χ represents the weight, and f2 represents the standard deviation of the driving distances between traveling salesmen.

[0033] In one embodiment of the present invention, the expression for the sum of the driving costs of all traveling salesmen f1 is as follows:

[0034]

[0035] where α represents the first weight, β represents the second weight, γ represents the third weight, i and j respectively represent any two photovoltaic modules in the photovoltaic array, n represents the total number of traveling salesmen, M represents the total number of photovoltaic modules in the non-rectangular photovoltaic array, and x ijkIndicate whether the traveling salesman k travels from city i to city j. If so, take the value of 1; otherwise, take the value of 0, G i Indicate the light intensity corresponding to the i-th photovoltaic module in the photovoltaic array, T i Indicate the temperature corresponding to the i-th photovoltaic module in the photovoltaic array, N si Indicate the number of photovoltaic cells corresponding to the i-th photovoltaic module in the photovoltaic array, G j Indicate the light intensity corresponding to the j-th photovoltaic module in the photovoltaic array, T j Indicate the temperature corresponding to the j-th photovoltaic module in the photovoltaic array, N sj Indicate the number of photovoltaic cells corresponding to the j-th photovoltaic module in the photovoltaic array.

[0036] In one embodiment of the present invention, the expression of the standard deviation f2 of the driving distances between traveling salesmen is as follows:

[0037] f2 = var(Q1, Q2,..., Q k );

[0038] where k ∈ [1, n], n represents the total number of traveling salesmen, and Q k represents the path length of the k-th traveling salesman.

[0039] Advantages of the present invention:

[0040] In the solution provided by the present invention, the non-rectangular photovoltaic array reconstruction method proposed by the present invention is applicable to photovoltaic arrays with irregular shapes and is also applicable when the output voltages of each photovoltaic module are not equal. The present invention simultaneously considers the effects of non-uniform illumination and temperature on non-rectangular photovoltaic arrays, and proposes a new reconstruction method oriented to the multi-bin multi-traveling salesman problem, which improves the performance of non-rectangular photovoltaic arrays under non-uniform illumination and effectively reduces the influence of non-uniform illumination on the performance of irregular photovoltaic arrays. Description of the drawings

[0041] Figure 1 It is a schematic diagram of the steps of a non-rectangular photovoltaic array reconstruction method oriented to the multi-bin multi-traveling salesman problem provided by an embodiment of the present invention;

[0042] Figure 2a It is a conceptual diagram of the application of an embodiment of the present invention to the concentrating space solar power station SSPS-OMEGA;

[0043] Figure 2b It is a ground demonstration verification diagram of the application of an embodiment of the present invention to the concentrating space solar power station SSPS-OMEGA;

[0044] Figure 2c It is a schematic structural diagram of the solar receiver in the application of an embodiment of the present invention to the concentrating space solar power station SSPS-OMEGA;

[0045] Figure 2d It is a schematic structural diagram of a photovoltaic module on a single photovoltaic array in an embodiment of the present invention;

[0046] Figure 3 It is a schematic diagram of the position of a photovoltaic module in a three-dimensional space in a multi-warehouse multi-traveling salesman problem-oriented non-rectangular photovoltaic array reconstruction method provided by an embodiment of the present invention;

[0047] Figure 4a It is a schematic diagram of a photovoltaic array obtained by a multi-warehouse multi-traveling salesman problem-oriented non-rectangular photovoltaic array reconstruction method provided by an embodiment of the present invention;

[0048] Figure 4b It is a schematic diagram of a traditional SP topology photovoltaic array;

[0049] Figure 4c It is a schematic diagram of a traditional TCT topology photovoltaic array;

[0050] Figure 4d It is a schematic diagram of a traditional photovoltaic array obtained by optimizing only the open-circuit voltage in the TCT topology;

[0051] Figure 4e It is a schematic diagram of a traditional photovoltaic array obtained by optimizing only the light intensity in the TCT topology;

[0052] Figure 5 It is a current-voltage curve graph of photovoltaic arrays with different topologies;

[0053] Figure 6 It is a power-voltage curve graph of photovoltaic arrays with different topologies. Detailed implementation manners

[0054] The following further describes the present invention in detail with reference to specific embodiments, but the implementation manners of the present invention are not limited thereto.

[0055] An embodiment of the present invention provides a multi-warehouse multi-traveling salesman problem-oriented non-rectangular photovoltaic array reconstruction method, as Figure 1 shown, which may include:

[0056] S1. Obtain a parameter matrix of the photovoltaic array through a light intensity sensor, a temperature sensor, and relevant parameters of the photovoltaic module; wherein, the expression of the parameter matrix of the photovoltaic array is as follows:

[0057]

[0058] wherein, i ∈ [1, M], PV i represents the parameter corresponding to the i-th photovoltaic module, G i represents the light intensity corresponding to the i-th photovoltaic module, T idenotes the temperature corresponding to the i-th photovoltaic module, N si denotes the number of photovoltaic cells corresponding to the i-th photovoltaic module, and M denotes the total number of photovoltaic modules in the non-rectangular photovoltaic array.

[0059] The conceptual diagram to which the embodiment of the present invention is applied to the concentrating space solar power station SSPS-OMEGA, please refer to Figure 2a As shown, in the SSPS-OMEGA scheme of the concentrating space solar power station, sunlight is concentrated by a spherical concentrator on the photovoltaic array at the bottom of the spherical crown. The ground demonstration verification diagram of the embodiment of the present invention applied to the concentrating space solar power station SSPS-OMEGA, please refer to Figure 2b , in Figure 2b In the shown scheme, the solar receiver is a Figure 2c rotor of the gyroscope shown. The solar receiver is axially divided into 8 equal parts on average, and 1 / 8 of the solar receiver is a photovoltaic array. After unfolding the photovoltaic array, there are 4 substrates as shown in Figure 2d As shown. Multiple rows of photovoltaic cells are laid on each substrate, and the photovoltaic cells in the same row are connected in series to form a photovoltaic module. It can be seen that there are 26 rows of photovoltaic cells, constituting 26 photovoltaic modules.

[0060] The light intensity G of the photovoltaic module is obtained through the light intensity sensor on each photovoltaic module, and the temperature T of the photovoltaic module is obtained through the temperature sensor. At the same time, the number of photovoltaic cells N included in the photovoltaic module itself s is a known quantity. When the photovoltaic array includes 26 photovoltaic cells, the parameter matrix PV of the photovoltaic array is obtained; the specific values in the parameter matrix PV are shown in Table 1.

[0061] Table 1

[0062]

[0063]

[0064] S2. According to the characteristics of the photovoltaic cells, the weights of various parameters in the parameter matrix can be obtained, including:

[0065] S21. Based on the light intensity, temperature, and number of photovoltaic cells of the photovoltaic modules in the photovoltaic array, the power of the photovoltaic module at the maximum power point can be obtained, including:

[0066] S211. According to the light intensity and temperature of the photovoltaic modules in the photovoltaic array, the corresponding short-circuit current is obtained.

[0067] Specifically, the expression of the photocurrent of the photovoltaic module is as follows:

[0068]

[0069] In the formula, G represents the light intensity of the photovoltaic module, and G STC represents the light intensity under standard conditions, T represents the temperature of the photovoltaic module, and T STC represents the temperature under standard conditions, which can be 173.15K. I ph,STC represents the photocurrent under standard conditions. The value of this photocurrent can be obtained from the photovoltaic cell parameter manual as 1.0712A. α sc represents the short - circuit current temperature coefficient. The short - circuit current temperature coefficient can be obtained from the photovoltaic cell parameter manual as 0.0008.

[0070] The photocurrent of the photovoltaic module is approximately equal to the short - circuit current. Therefore, the expression for the short - circuit current of the photovoltaic module is as follows:

[0071]

[0072] Through the above process, it can be obtained that the short - circuit current of the photovoltaic module is a function of G and T, that is:

[0073] I sc_mod = f I (G,T).

[0074] S212. According to the short - circuit current and the number of photovoltaic cells, the open - circuit voltage of the photovoltaic module is obtained; among them, the expression for the open - circuit voltage of the photovoltaic module is as follows:

[0075]

[0076] In the formula, N s represents the number of photovoltaic cells included in the module, n represents the ideality factor, k represents the Boltzmann constant, equal to 1.3806504×10 -23 J / K, q represents the electron charge constant, equal to 1.602176487×10 -19 C, I0 represents the reverse saturation current of the diode. The expression for the reverse saturation current of the diode is as follows:

[0077]

[0078] Among them, I 0,STC represents the saturation current under standard test conditions, and E g represents the energy band width of the semiconductor. The empirical formula for the energy band width of a gallium arsenide cell is as follows:

[0079]

[0080] Combining the above description, the expression for the open - circuit voltage of the photovoltaic module with respect to G, T, and N s is as follows:

[0081] Voc_mod = f V (G, T, N s ).

[0082] S213. Obtain the fill factor of the photovoltaic module based on the open-circuit voltage. Among them, the empirical formula for the fill factor of the photovoltaic module is as follows:

[0083]

[0084] v oc_mod,STC represents the open-circuit voltage of the normalized photovoltaic module, and its expression is as follows:

[0085]

[0086] V oc_mod,STC represents the open-circuit voltage of the photovoltaic module under standard conditions, and its expression is as follows:

[0087] V oc_mod,STC = N s × V oc_cell,STC ;

[0088] Among them, V oc_cell,STC represents the open-circuit voltage of the photovoltaic cell in the photovoltaic module under standard conditions, and this value can be obtained from the photovoltaic cell manual.

[0089] Combined with the above description, it can be obtained that the fill factor of the photovoltaic module is an expression about T and N s as follows:

[0090] FF = f FF (T, N s ).

[0091] S214. Obtain the power of the photovoltaic module at the maximum power point according to the short-circuit current, open-circuit voltage and fill factor.

[0092] The expression for the power of the photovoltaic module at the maximum power point is as follows:

[0093] P m = I sc_mod × V oc_mod × FF;

[0094] Among them, I sc_mod represents the short-circuit current of the photovoltaic module, V oc_mod represents the open-circuit voltage of the photovoltaic module, and FF represents the fill factor of the photovoltaic module.

[0095] P m = I sc_mod × V oc_mod × FF = f(G, T, N s ).

[0096] S22. Obtain the weights of various parameters in the parameter matrix according to the light intensity, temperature, number of photovoltaic cells, and power at the maximum power point corresponding to the photovoltaic module.

[0097] The weights of various parameters in the parameter matrix are defined as the power P at the maximum power point of the photovoltaic module m Under standard conditions (G = 1000 W / m 2 , T = 25 °C, N s = 1) with respect to the partial derivatives of G, T, and N s , and the expressions for the weights of various parameters in the parameter matrix are obtained by solving as follows:

[0098]

[0099] where α represents the first weight, β represents the second weight, γ represents the third weight, and P m represents the power of the photovoltaic module at the maximum power point, represents taking the partial derivative, G represents the light intensity corresponding to the photovoltaic module, T represents the temperature corresponding to the photovoltaic module, and N s represents the number of photovoltaic cells corresponding to the photovoltaic module.

[0100] It can be understood that the first weight α represents the weight corresponding to the light intensity in the parameter matrix, the second weight β represents the weight corresponding to the temperature in the parameter matrix, and the third weight γ represents the weight corresponding to the number of photovoltaic cells in the parameter matrix.

[0101] S3. Regard each photovoltaic module in the photovoltaic array as a point in three-dimensional space, and convert the parameter matrix of each photovoltaic module into a corresponding coordinate matrix.

[0102] Specifically, as Figure 3 shown, the photovoltaic module is equivalent to 26 points, G is used as the x-axis coordinate of the coordinate matrix, T is used as the y-axis coordinate of the coordinate matrix, and N s is used as the z-axis coordinate of the coordinate matrix.

[0103] S4. Obtain the distances between each photovoltaic module according to the parameter matrix, the weights of various parameters in the parameter matrix, and the coordinate matrix; among them, the expression for the distance between photovoltaic modules is as follows:

[0104]

[0105] where i and j respectively represent any two photovoltaic modules in the photovoltaic array, α represents the first weight, β represents the second weight, γ represents the third weight, G i represents the light intensity corresponding to the i-th photovoltaic module in the photovoltaic array, T i represents the temperature corresponding to the i-th photovoltaic module in the photovoltaic array, and N sirepresents the number of photovoltaic cells corresponding to the \(i\)-th photovoltaic module in the photovoltaic array, \(G\) j represents the light intensity corresponding to the \(j\)-th photovoltaic module in the photovoltaic array, \(T\) j represents the temperature corresponding to the \(j\)-th photovoltaic module in the photovoltaic array, \(N\) sj represents the number of photovoltaic cells corresponding to the \(j\)-th photovoltaic module in the photovoltaic array.

[0106] The expression for the distance between any two modules \(i\) and \(j\) is as follows:

[0107]

[0108] Furthermore, the expression for the distance matrix of the photovoltaic modules is obtained as follows:

[0109]

[0110] Due to the large amount of data in the distance matrix, the matrix is written as 4 sub-matrices of \(7\times13\) and 2 sub-matrices of \(5\times13\), and its expression is as follows:

[0111]

[0112] Among them, the specific forms of each sub-matrix are as follows:

[0113]

[0114]

[0115]

[0116]

[0117]

[0118]

[0119]

[0120]

[0121] S5. Determine the number of series-connected cell strings in the photovoltaic array according to the preset requirements;

[0122] Specifically, the preset requirements can be set according to the actual situation. In the embodiments of the present invention, the number of series-connected cell strings in the photovoltaic array can be set to 4.

[0123] S6. Take the number of series-connected battery strings as the number of traveling salesmen in the multi-warehouse multi-traveling salesman problem, and take each photovoltaic module as a city node. Based on the number of traveling salesmen, city nodes, and the distances between photovoltaic modules, use the multi-warehouse traveling salesman problem optimization algorithm to obtain the optimal series and parallel configurations of photovoltaic modules to achieve the dynamic reconfiguration of the photovoltaic array.

[0124] Specifically, the specific process of step S6 is as follows:

[0125] S61. Take the number of series-connected battery strings as the number of traveling salesmen in the multi-warehouse multi-traveling salesman problem.

[0126] From S5, it can be obtained that the number of traveling salesmen is 4.

[0127] S62. Take each photovoltaic module as a city node.

[0128] It can be determined that there are a total of 26 city nodes, and the coordinate matrix of the city nodes is the parameter matrix of the photovoltaic array.

[0129] S63. Based on the number of traveling salesmen, city nodes, and the distances between photovoltaic modules, use the multi-warehouse traveling salesman problem optimization algorithm to obtain the optimal series and parallel configurations of photovoltaic modules to achieve the dynamic reconfiguration of the photovoltaic array, which may include:

[0130] Four salesmen start from four different cities without setting a fixed starting point. Visit a certain number of cities and each city can only be visited by one salesman once, and finally return to the cities where they started.

[0131] Solve with the goal of minimizing the sum of the driving costs of all traveling salesmen and balancing the driving distances between traveling salesmen. Among them, the mathematical model of the multi-warehouse traveling salesman problem optimization algorithm is as follows:

[0132] minf = f1(1 + χ·f2);

[0133] Among them, f1 represents the sum of the driving costs of all traveling salesmen, χ represents the weight, and f2 represents the standard deviation of the driving distances between traveling salesmen. χ represents the weight, and this weight can take 0.1.

[0134] The expression of the sum of the driving costs of all traveling salesmen f1 is as follows:

[0135]

[0136] Among them, α represents the first weight, β represents the second weight, γ represents the third weight, i and j respectively represent any two photovoltaic modules in the photovoltaic array, n represents the total number of traveling salesmen, M represents the total number of photovoltaic modules in the non-rectangular photovoltaic array, x ijkIndicate whether the traveling salesman k travels from city i to city j. If so, take the value of 1; otherwise, take the value of 0, G i Indicate the light intensity corresponding to the i-th photovoltaic module in the photovoltaic array, T i Indicate the temperature corresponding to the i-th photovoltaic module in the photovoltaic array, N si Indicate the number of photovoltaic cells corresponding to the i-th photovoltaic module in the photovoltaic array, G j Indicate the light intensity corresponding to the j-th photovoltaic module in the photovoltaic array, T j Indicate the temperature corresponding to the j-th photovoltaic module in the photovoltaic array, N sj Indicate the number of photovoltaic cells corresponding to the j-th photovoltaic module in the photovoltaic array.

[0137] x ijk The expression of is as follows:

[0138]

[0139] x ijk Indicate whether the traveling salesman k travels from city i to city j. If so, take the value of 1; otherwise, take the value of 0.

[0140] The constraint conditions are as follows:

[0141]

[0142] The constraint conditions indicate that the out-degree and in-degree of all cities are both 1, that is, each city can and can only be visited by one person among the traveling salesmen.

[0143] The expression of the standard deviation f2 of the driving distances between the traveling salesmen is as follows:

[0144] f2 = var(Q1, Q2,..., Q n );

[0145] Among them, k ∈ n, n represents the total number of traveling salesmen, Q k Indicates the path length of the k-th traveling salesman.

[0146]

[0147] Through the multi-warehouse multi-traveling salesman problem optimization algorithm, the sequence numbers of the city nodes passed by each traveling salesman and their visiting order are obtained as follows:

[0148] Traveling salesman 1: Node 4 → Node 5 → Node 3 → Node 12 → Node 7 → Node 8;

[0149] Traveling salesman 2: Node 9 → Node 10 → Node 19 → Node 20 → Node 21 → Node 23 → Node 25;

[0150] Traveling Salesman 3: Node 22 → Node 17 → Node 6 → Node 14 → Node 13 → Node 2;

[0151] Traveling Salesman 4: Node 1 → Node 24 → Node 26 → Node 18 → Node 11 → Node 16 → Node 15.

[0152] According to the above access order, the optimal series and parallel configurations of photovoltaic modules are obtained to achieve the dynamic reconfiguration of the photovoltaic array. The optimized photovoltaic array is as Figure 4a shown. To verify the beneficial effects of the multi-bin multi-traveling salesman problem-oriented non-rectangular photovoltaic array reconfiguration method proposed in the embodiments of the present invention, a traditional method is selected as the control group for comparative verification with the embodiments of the present invention. For the schematic diagram of the traditional SP topology photovoltaic array, please refer to Figure 4b shown. For the schematic diagram of the traditional TCT topology photovoltaic array, please refer to Figure 4c shown. For the schematic diagram of the photovoltaic array obtained by only optimizing the open-circuit voltage in the TCT topology, please refer to Figure 4d shown. For the schematic diagram of the photovoltaic array obtained by only optimizing the light intensity in the TCT topology, please refer to Figure 4e shown. The optimized photovoltaic array provided by the present invention and the selected control group are respectively subjected to simulation analysis to obtain the current-voltage curve of different topology photovoltaic arrays as shown in Figure 5 shown and the power-voltage curve of different topology photovoltaic arrays as shown in Figure 6 shown.

[0153] In Figure 5 and Figure 6 , (a) represents the simulation curve corresponding to the multi-bin multi-traveling salesman problem-oriented non-rectangular photovoltaic array reconfiguration method proposed in the embodiments of the present invention, (b) represents the simulation curve corresponding to the traditional SP topology photovoltaic array, (c) represents the simulation curve corresponding to the traditional TCT topology photovoltaic array, (d) represents the simulation curve corresponding to the photovoltaic array obtained by only optimizing the open-circuit voltage in the TCT topology, and (e) represents the simulation curve corresponding to the photovoltaic array obtained by only optimizing the light intensity in the TCT topology. From Figure 5 and Figure 6 , it can be concluded that the maximum power point corresponding to the multi-bin multi-traveling salesman problem-oriented non-rectangular photovoltaic array reconfiguration method proposed in the embodiments of the present invention can reach 1942W, showing different improvements compared with the other traditional methods. The multi-bin multi-traveling salesman problem-oriented non-rectangular photovoltaic array reconfiguration method proposed in the embodiments of the present invention performs better in terms of fill factor FF and efficiency ratio ER, while maintaining a lower power loss PL and maximum power loss ML. Its performance efficiency PE reaches 42.6%. It can be seen that the overall performance of the optimized photovoltaic array in the embodiments of the present invention has been significantly improved compared with the traditional technology.

[0154] The non-rectangular photovoltaic array reconstruction method proposed in the embodiments of the present invention is applicable to photovoltaic arrays with irregular shapes and is also applicable when the output voltages of each photovoltaic module are not equal. The present invention simultaneously considers the effects of non-uniform illumination and temperature on non-rectangular photovoltaic arrays, and proposes a new reconstruction method oriented towards the multi-depot multi-traveling salesman problem, which improves the performance of non-rectangular photovoltaic arrays under non-uniform illumination and effectively reduces the impact of non-uniform illumination on the performance of irregular photovoltaic arrays.

[0155] It should be noted that in the description of the present invention, it should be understood that the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "a plurality" means two or more unless otherwise specifically defined.

[0156] The above are only the preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A multi-bin multi-traveling salesman problem-oriented non-rectangular photovoltaic array reconstruction method, characterized in that: include: The parameter matrix of the photovoltaic array is obtained through the light intensity sensor, temperature sensor and related parameters of the photovoltaic module; According to the characteristics of the photovoltaic cell, the weights of various parameters in the parameter matrix are obtained; Consider each photovoltaic module in the photovoltaic array as a point in three-dimensional space, and convert the parameter matrix of each photovoltaic module into a corresponding coordinate matrix; Obtaining the distance between each photovoltaic module according to the parameter matrix, the weights of various parameters in the parameter matrix and the coordinate matrix; Determine the number of series-connected battery strings in the photovoltaic array according to preset requirements; The number of series-connected battery strings is taken as the number of traveling salesmen in the multi-warehouse multi-traveling salesman problem, and each photovoltaic module is taken as a city node. Based on the number of traveling salesmen, the distances between city nodes and each photovoltaic module, the multi-warehouse traveling salesman problem optimization algorithm is adopted to obtain the optimal series and parallel configuration of photovoltaic modules to achieve dynamic reconstruction of the photovoltaic array.

2. According to the multi-warehouse multi-traveling salesman problem-oriented non-rectangular photovoltaic array reconstruction method of claim 1, it is characterized in that: The expression of the parameter matrix of the photovoltaic array is as follows: Among them, i∈[1,M], PV i represents the parameters corresponding to the i-th photovoltaic module, G i represents the light intensity corresponding to the i-th photovoltaic module, T i represents the temperature corresponding to the i-th photovoltaic module, N si represents the number of photovoltaic cells corresponding to the i-th photovoltaic module, and M represents the total number of photovoltaic modules in the non-rectangular photovoltaic array.

3. The method for reconfiguring a non-rectangular photovoltaic array guided by a multi-warehouse multi-traveling salesman problem according to claim 2 is characterized in that: According to the characteristics of the photovoltaic cell, the weights of various parameters in the parameter matrix are obtained, including: Based on the light intensity, temperature and number of photovoltaic cells in the photovoltaic module in the photovoltaic array, the power of the photovoltaic module at the maximum power point is obtained; The weights of various parameters in the parameter matrix are obtained according to the light intensity, temperature, number of photovoltaic cells and power at the maximum power point corresponding to the photovoltaic module.

4. The method for reconfiguring a non-rectangular photovoltaic array guided by a multi-warehouse multi-traveling salesman problem according to claim 3 is characterized in that: The method of obtaining the power of the photovoltaic module at the maximum power point based on the light intensity, temperature and number of photovoltaic cells of the photovoltaic module in the photovoltaic array includes: According to the light intensity and temperature of the photovoltaic modules in the photovoltaic array, the corresponding short-circuit current is obtained; According to the short-circuit current and the number of photovoltaic cells, the open-circuit voltage of the photovoltaic module is obtained; The fill factor of the photovoltaic module is obtained based on the open circuit voltage; The power of the photovoltaic module at the maximum power point is obtained based on the short-circuit current, open-circuit voltage and fill factor.

5. The method for reconfiguring a non-rectangular photovoltaic array guided by a multi-warehouse multi-traveling salesman problem according to claim 4, characterized in that: The expression of the power of the photovoltaic module at the maximum power point is as follows: P m =I sc_mod ×V oc_mod ×FF; Among them, I sc_mod Represents the short-circuit current of the photovoltaic module, V oc_mod represents the open circuit voltage of the photovoltaic module, and FF represents the fill factor of the photovoltaic module.

6. The method for reconfiguring a non-rectangular photovoltaic array guided by a multi-warehouse multi-traveling salesman problem according to claim 3, characterized in that: The expressions of the weights of various parameters in the parameter matrix are as follows: Among them, α represents the first weight, β represents the second weight, γ represents the third weight, P m Indicates the power of the photovoltaic module at the maximum power point, Indicates partial derivative, G represents the light intensity corresponding to the photovoltaic module, T represents the temperature corresponding to the photovoltaic module, N s Indicates the number of photovoltaic cells corresponding to the photovoltaic module.

7. The method for reconfiguring a non-rectangular photovoltaic array guided by a multi-warehouse multi-traveling salesman problem according to claim 6, characterized in that: The expression for the distance between the photovoltaic modules is as follows: Where i and j represent any two photovoltaic modules in the photovoltaic array, α represents the first weight, β represents the second weight, γ represents the third weight, G i represents the light intensity corresponding to the i-th photovoltaic module in the photovoltaic array, T i represents the temperature corresponding to the i-th photovoltaic module in the photovoltaic array, N si represents the number of photovoltaic cells corresponding to the i-th photovoltaic module in the photovoltaic array, G j represents the light intensity corresponding to the jth photovoltaic module in the photovoltaic array, T j represents the temperature corresponding to the jth photovoltaic module in the photovoltaic array, N sj Indicates the number of photovoltaic cells corresponding to the jth photovoltaic module in the photovoltaic array.

8. The method for reconfiguring a non-rectangular photovoltaic array guided by a multi-warehouse multi-traveling salesman problem according to claim 1, characterized in that: The mathematical model of the multi-warehouse traveling salesman problem optimization algorithm is as follows: minf=f1(1+χ·f2); Among them, f1 represents the sum of the travel costs of all traveling salesmen, χ represents the weight, and f2 represents the standard deviation of the travel distance between each traveling salesman.

9. The method for reconfiguring a non-rectangular photovoltaic array guided by a multi-warehouse multi-traveling salesman problem according to claim 8, characterized in that: The expression of the sum of the travel costs of all traveling salesmen f1 is as follows: Where α represents the first weight, β represents the second weight, γ represents the third weight, i and j represent any two photovoltaic modules in the photovoltaic array, n represents the total number of traveling salesmen, M represents the total number of photovoltaic modules in the non-rectangular photovoltaic array, and x ijk Indicates whether the traveling salesman k reaches city j from city i. If yes, the value is 1, otherwise, the value is 0. i represents the light intensity corresponding to the i-th photovoltaic module in the photovoltaic array, T i represents the temperature corresponding to the i-th photovoltaic module in the photovoltaic array, N si represents the number of photovoltaic cells corresponding to the i-th photovoltaic module in the photovoltaic array, G j represents the light intensity corresponding to the jth photovoltaic module in the photovoltaic array, T j represents the temperature corresponding to the jth photovoltaic module in the photovoltaic array, N sj Indicates the number of photovoltaic cells corresponding to the jth photovoltaic module in the photovoltaic array.

10. The method for reconfiguring a non-rectangular photovoltaic array guided by a multi-warehouse multi-traveling salesman problem according to claim 8, characterized in that: The expression of the standard deviation f2 of the travel distance between the traveling salesmen is as follows: f2=var(Q1,Q2,...,Q k ); Among them, k∈[1,n], n represents the total number of traveling salesmen, Q k represents the path length of the kth traveling salesman.

Images