A configuration optimization method of a synergistic energy supply photovoltaic power generation water-saving irrigation system

Abstract

The present application relates to the field of agricultural irrigation technology, and particularly relates to a configuration optimization method of a cooperative energy supply photovoltaic power generation water-saving irrigation system. According to the water requirement characteristics of local crops in the growth period, the present application is configured to meet the minimum water requirement of crops in different growth periods, considers the utilization efficiency of photovoltaic modules, the operation efficiency of water pumps and the change law of pipeline efficiency under different irradiation intensities, valve opening degrees and water lifting heights, constructs a system flow calculation model, and determines the optimal water lifting height according to the overall efficiency of the system and the solar energy utilization rate. The initial investment cost, operation cost, maintenance cost and replacement cost of the water-saving irrigation system are taken as constraints to establish a system life cycle cost model. The Guanhao pig optimization algorithm is used to determine the optimal configuration parameters of the photovoltaic generator set, the water storage tank and the battery, so as to minimize the system life cycle cost and meet the minimum water requirement of crops. The present application is suitable for the water-saving irrigation system composed of a photovoltaic generator set, a water storage tank and a battery.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of agricultural irrigation technology, in particular to a configuration optimization method of a cooperative energy supply photovoltaic power generation water-saving irrigation system. BACKGROUND

[0002] Global climate change and water resource shortage problems are becoming increasingly serious, and traditional agricultural irrigation methods have significant deficiencies in water consumption and energy consumption. The current agricultural irrigation system generally has problems of high energy consumption, resource waste, and high operating cost, especially in water-deficient and unstable power supply areas.

[0003] Traditional irrigation systems rely on grid power supply, resulting in high operating costs and environmental pollution. Photovoltaic power generation, as a clean and renewable energy source, combined with water storage tanks and batteries, can be applied to agricultural irrigation to significantly improve the utilization efficiency of water resources and energy. However, how to scientifically and reasonably configure the system composed of photovoltaic generator sets, water storage tanks, and batteries to meet the water requirements of crops and minimize the life cycle cost of the irrigation system is still a problem to be solved. SUMMARY

[0004] The purpose of the present application is to overcome the shortcomings of the prior art and provide a configuration optimization method of a cooperative energy supply photovoltaic power generation water-saving irrigation system, which realizes the satisfaction of the minimum water requirement of crops in different growth periods and minimizes the life cycle cost of the irrigation system.

[0005] The present application achieves the above-mentioned purpose by adopting the following technical solutions, and provides a configuration optimization method of a cooperative energy supply photovoltaic power generation water-saving irrigation system, comprising:

[0006] S1, determining the minimum water requirement of crops in different growth periods according to the water requirement characteristics of local crops in different growth periods, taking the minimum water requirement of crops in different growth periods as the target, determining the pumping flow of solar photovoltaic water pumps, the capacity of regulating water tanks, and the total lift of solar photovoltaic pumping, and selecting corresponding solar photovoltaic water pump sets and solar photovoltaic panels;

[0007] S2, ensuring that the photovoltaic power generation capacity and the battery energy storage meet the power demand of the irrigation system through the energy balance equation;

[0008] S3, ensuring that the capacity of the water storage tank meets the irrigation demand through the water resource balance equation;

[0009] S4, based on the utilization efficiency of photovoltaic modules, the operating efficiency of water pumps, the pipeline efficiency, and the output power per unit area of photovoltaic modules under different irradiance intensities, valve openings, and pumping heights, a flow calculation model of the irrigation system is constructed, and the optimal pumping height is determined according to the overall efficiency of photovoltaic water pumping and the solar utilization rate;

[0010] S5. Establish a life-cycle cost model for the irrigation system, taking the initial investment cost, operating cost, maintenance cost and replacement cost of the photovoltaic generator set as constraints.

[0011] S6. Employ a multi-objective optimization algorithm to determine the optimal configuration parameters for the photovoltaic generator set, water storage tank, and battery, minimizing the total life-cycle cost of the irrigation system while meeting the minimum water requirements of the crops.

[0012] Furthermore, in step S1, the water pumping flow rate of the solar photovoltaic water pump is determined based on the irrigation water volume and the planned water pumping time. The specific calculation method is as follows:

[0013] The daily water lifting capacity of the solar photovoltaic water pump is Q. d =W / (ηt) ds In the formula, Q d This refers to the daily water lifting capacity of the solar photovoltaic water pump, expressed in m³. 3 W represents net irrigation water consumption, in m³. 3 η is the irrigation water utilization coefficient, t ds The number of days for water lifting is selected based on the operating conditions.

[0014] The water pumping flow rate of the solar photovoltaic water pump is q d =Q d / T t In the formula, q d For the water pumping flow rate of solar photovoltaic water pumps, T t This refers to the daily water lifting time for solar photovoltaic systems.

[0015] Furthermore, in step S1, the capacity of the regulating water tank is determined by the daily water pumping volume and daily irrigation volume of the solar photovoltaic water pump during a single irrigation period. The capacity of the regulating water tank is then obtained through water balance analysis. The specific calculation method is as follows:

[0016]

[0017] V = max(V1, V2, ..., V i )

[0018] V min =Q i -(W i T d ) / t d

[0019] In the formula, V n The water tank capacity needs to be adjusted during the irrigation period, and the unit is m. 3 Q i W represents the daily water lifting capacity of the solar photovoltaic water pump during a single irrigation period. iis the daily irrigation water volume in a irrigation period, i is the number of days in a irrigation period, V is the volume of the regulating reservoir, V min is the minimum volume of the reservoir, T d is the daily pumping time of the solar photovoltaic water pump, t d is the daily irrigation time.

[0020] Further, in step S1, the total lift of the solar photovoltaic water pump is calculated as follows:

[0021] H p =∑h ω +h0+ΔZ, where H p is the design working head of the water pump, ∑h ω is the sum of the head losses of the pipelines, h0 is the filter and other head losses at the water source, and ΔZ is the terrain elevation difference.

[0022] Further, step S1 further includes:

[0023] adjusting the output frequency in real time according to the change of the solar radiation intensity to achieve maximum power point tracking;

[0024] The maximum peak water power of the photovoltaic array of the solar photovoltaic panel is calculated according to the following formula:

[0025] where N sf is the maximum peak water power, Q max is the peak flow of the water pump, unit: m 3 / h, H is the total lift of the system, g is the acceleration of gravity, and ρ is the density of water;

[0026] The peak pumping power of the solar photovoltaic water pump is calculated according to the following formula:

[0027] where N pf is the peak pumping power, k1 is the flow correction coefficient, k2 is the correction coefficient of the pumping machine form, and k3 is the correction coefficient of the electric drive form;

[0028] According to the peak pumping power of the solar photovoltaic water pump, the corresponding photovoltaic water-lifting inverter and irrigation system control cabinet are selected.

[0029] Further, in step S2, the energy balance equation is:

[0030] EPV(t) + EST(t) ≥ EDE(t), where EPV is the photovoltaic power generation, EST is the energy storage of the battery, and EDE is the power demand of the irrigation system.

[0031] Further, in step S3, the water resource balance equation is:

[0032] VST(t)≥VDE(t), wherein VST is the water storage capacity of the reservoir, and VDE is the irrigation demand.

[0033] Further, in step S4, the calculation method of the utilization efficiency of the photovoltaic module, the operation efficiency of the water pump, the pipeline efficiency, and the output power per unit area of the photovoltaic module is as follows:

[0034]

[0035]

[0036]

[0037]

[0038] wherein η1 is the conversion efficiency of the photovoltaic module, η2 is the operation efficiency of the water pump, η3 is the pipeline efficiency, P a is the output power per unit area of the photovoltaic module, G is the solar radiation intensity, P is the total output power of the photovoltaic module, ρ is the density of water, Q is the flow rate of the water pump, H Z is the static lift of the irrigation system, i.e., the water lifting height, H S is the outlet power supply pressure of the water pump, i.e., the pump lift, h is the head loss of the water pipeline, which is composed of the frictional head loss and the local head loss, and A1 is the area of the cell panel of the photovoltaic module;

[0039] The overall efficiency of the photovoltaic water pump is calculated as follows:

[0040] η T is the overall efficiency of the photovoltaic water pump;

[0041] The pump lift H S is equal to the required lift H D in the pipeline output process, and the calculation method is as follows:

[0042]

[0043] wherein H D is the required lift in the pipeline output process, L is the pipeline length, D is the pipe diameter, A2 is the pipeline cross-sectional area, and λ and ∑ξ are the pipeline frictional resistance coefficient and the sum of various local resistance coefficients;

[0044] The sum of the local resistance coefficients ∑ξ of the pipeline is composed of the local resistance coefficients of the water lifting pipeline, which is changed by adjusting the valve opening degree, and the relationship between the two can be obtained by experiment:

[0045] wherein v is the kinematic viscosity of water;

[0046] η1 and solar irradiance G inverse proportional piecewise function relationship as shown below:

[0047]

[0048] In the valve opening is 0 ~ 100%, to establish the opening range under the valve opening k and local resistance coefficient ∑ξ relationship as follows:

[0049]

[0050] The water pump flow Q formula as follows:

[0051]

[0052] Then calculate the maximum pumping capacity under each solar irradiance, respectively, pumping height H Z The value, the corresponding water pump start minimum irradiance, solar utilization rate, photovoltaic module weighted average efficiency, water pump weighted average efficiency, pipeline weighted average efficiency and photovoltaic water pump pumping the overall average efficiency, so as to determine the optimal photovoltaic water pump pumping height.

[0053] Further, in step S5, the objective function expression of the life cycle cost model is as follows:

[0054] C = C pv + C B + C C + C D + C BnPW + C DnPW + C Isnt + C MPW

[0055] In the formula, C pv is the purchase cost of photovoltaic cells, C B is the purchase cost of the battery, C C is the purchase cost of the controller, C D is the purchase cost of the reservoir, C BnPW is the present value of the replacement procurement funds of the battery, C DnPW is the present value of the replacement procurement funds of the reservoir, C Isnt is the installation cost of the system, C MPW The system operation and maintenance cost is converted to the present value at the initial investment;

[0056] The present value of the replacement cost of the battery and the battery after n years:

[0057]

[0058]

[0059] Wherein, i is the inflation rate, d is the bank interest rate, and n is the annual sequence number.

[0060] The present value of the maintenance cost is a.

[0061]

[0062] Wherein, a is the annual maintenance cost, and N is the service life of the photovoltaic system.

[0063] Further, in step S6, the multi-objective optimization algorithm is the Crown Hyrax optimization algorithm.

[0064] The beneficial effects of the present application are:

[0065] The present application determines the minimum water requirement of crops in different growth periods according to the water requirement characteristics of local crops in different growth periods, determines the pumping flow of the solar photovoltaic water pump, the capacity of the regulating water tank, and the total lift of the solar photovoltaic water pump, with the goal of meeting the minimum water requirement of crops in different growth periods. Through the energy balance equation, it ensures that the photovoltaic power generation capacity and the battery energy storage meet the power demand of the irrigation system; through the water resource balance equation, it ensures that the capacity of the water storage tank meets the irrigation demand; based on the utilization efficiency of photovoltaic modules, the operating efficiency of the water pump, the pipeline efficiency, and the output power per unit area of photovoltaic modules under different irradiance intensities, valve openings, and pumping heights, an irrigation system flow calculation model is constructed, and the optimal pumping height is determined according to the overall efficiency of the photovoltaic water pump and the solar utilization rate; the initial investment cost, operating cost, maintenance cost, and replacement cost of the photovoltaic generator set are used as constraints to establish a life cycle cost model of the irrigation system; a multi-objective optimization algorithm is used to determine the optimal configuration parameters of the photovoltaic generator set, the water storage tank, and the battery, so that the life cycle cost of the irrigation system is minimized and the minimum water requirement of crops is met.

[0066] By determining the optimal configuration parameters of the photovoltaic generator set, the water storage tank, and the battery through the above-mentioned method, the minimum water requirement of crops in different growth periods is met, and the life cycle cost of the system is minimized on this basis. BRIEF DESCRIPTION OF DRAWINGS

[0067] Figure 1 is a configuration optimization method flow chart of a collaborative energy supply photovoltaic power generation water-saving irrigation system provided by an embodiment of the present application. DETAILED DESCRIPTION

[0068] To make the purpose, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application.

[0069] The application provides a configuration optimization method of a cooperative energy supply photovoltaic power generation water-saving irrigation system, which comprises a solar cell panel, a support, a foundation, a battery pack, a control system, a photovoltaic water pump, a water intake building, a water delivery pipeline, a water storage tank, a water terminal, a safety protection net and the like.

[0070] The configuration optimization method is as shown in the figure, and the specific steps are as follows: Figure 1

[0071] S1, according to the water requirement characteristics of different growth periods of local crops, the minimum water requirement of each growth period is determined, the irrigation system of crops is designed to meet the minimum water requirement of different growth periods of crops, the water pumping flow of the solar photovoltaic water pump, the capacity of the regulating water tank and the total lift of the solar photovoltaic water pumping are determined to select reasonable solar photovoltaic water pump units and solar photovoltaic panels;

[0072] S2, through the energy balance equation, the photovoltaic power generation capacity and the battery energy storage capacity are ensured to meet the power demand of the irrigation system;

[0073] S3, through the water resource balance equation, the capacity of the water storage tank is ensured to meet the irrigation demand;

[0074] S4, based on the change rules of the utilization efficiency of the photovoltaic module, the operation efficiency of the water pump, the pipeline efficiency and the output power per unit area of the photovoltaic module under different irradiation intensities, valve opening degrees and water pumping heights, a system flow calculation model is constructed, the optimal water pumping height is determined according to the overall efficiency of the irrigation system and the solar utilization rate, and on this basis, the water pumping system cost is reduced and the solar utilization rate is improved by increasing the area of the photovoltaic module and the number of the water storage tanks;

[0075] S5, taking the initial investment cost, operation cost, maintenance cost and replacement cost of the photovoltaic generator set as constraints, a system life cycle cost LCC model is established;

[0076] S6, a multi-objective optimization algorithm is adopted to determine the optimal configuration parameters of the photovoltaic generator set, the water storage tank and the battery, so that the system life cycle cost is minimized and the minimum water requirement of crops is met.

[0077] Specifically, in step S1, the water pumping flow of the solar photovoltaic water pump is determined according to the irrigation water quantity and the planned water pumping time:

[0078] The daily water pumping quantity of the solar photovoltaic water pump is Q d = W / (ηt ds ), wherein Q d is the daily water pumping quantity of the photovoltaic solar energy (m 3 ), W is the net irrigation water quantity (m 3 ), η is the irrigation water utilization coefficient, t ds is the water pumping days (d), and the setting working condition is selected. ​

[0079] The water pumping flow rate of the solar photovoltaic water pump is q d =Q d / T t In the formula, q d Photovoltaic solar water lifting flow rate (m 3 ), T t The daily water lifting time (h) is for solar photovoltaic systems.

[0080] Specifically, in step S1, the capacity of the regulating pool needs to be determined by the daily water extraction volume of solar photovoltaic power and the daily irrigation water volume during a single irrigation period. The capacity of the regulating pool can be obtained through water balance analysis.

[0081]

[0082] V = max(V1, V2, ..., V i )

[0083] V min =Q i -(W i T d ) / t d

[0084] In the formula, V n The water tank capacity (m³) needs to be adjusted during the irrigation period. 3 ), Q i The daily water lifting capacity of solar photovoltaic power during a single irrigation period (m³) 3 ), W i Daily irrigation water consumption (m³) during a single irrigation period 3 ), where i is the number of days in a single irrigation period, and V is the volume of the regulating pool (m³). 3 V min Minimum volume of the pool (m³) 3 ), T d The daily water lifting time (h) for solar photovoltaic systems is t. d The daily irrigation time (h) is the irrigation water usage period.

[0085] Specifically, in step S1, the total head of the solar photovoltaic water lifting system is calculated as follows:

[0086] H p =∑h ω +h0+ΔZ, where H p The working head for the water pump is ∑h ω ΔZ is the sum of head losses in each level of pipeline, h0 is the head loss from filters and other sources at the water source, and ΔZ is the elevation difference.

[0087] Specifically, step S1 also includes:

[0088] The solar energy conversion control system controls and adjusts the operation, converts the direct current generated by the solar cell array into alternating current, drives the water pump, and adjusts the output frequency in real time according to the change of the sunshine intensity, realizes the maximum power point tracking, and maximally utilizes the solar energy.

[0089] The maximum peak water power of the photovoltaic array of the solar photovoltaic panel is calculated according to the following formula:

[0090] In the formula, N sf is the peak water power (W) ; Q max is the peak flow of the water pump (m 3 / h) ; H is the total lift of the system (m) ; g is the gravity acceleration (m / s 2 ) ; and p is the density of water (kg / m 3 ).

[0091] The peak water-lifting power of the solar photovoltaic water pump is calculated according to the following formula:

[0092] In the formula, N pf is the peak water power of the water-lifting system (W) ; k1 is the flow correction coefficient; k2 is the water-lifting machine form correction coefficient; and k3 is the electric power transmission form correction coefficient.

[0093] The present application can also control and adjust the operation of the system through the photovoltaic water-lifting inverter, adjust the output frequency in real time according to the change of the sunshine intensity, realize the maximum power point tracking, and reasonably select the photovoltaic water-lifting inverter and the system control cabinet according to the power of the photovoltaic water pump.

[0094] Specifically, in step S2, the energy balance equation is:

[0095] In the formula, EPV is the photovoltaic power generation amount, EST is the energy storage amount of the battery, and EDE is the power demand of the irrigation system.

[0096] Specifically, in step S3, the water resource balance equation is:

[0097] In the formula, VST is the water storage capacity of the water storage pool (m 3 ) ; and VDE is the irrigation demand (m 3 ).

[0098] The solar energy is converted into electric energy through the photovoltaic panel, the electric energy is converted into mechanical energy through the water pump, and the water is lifted from a low-lying place to a high place. Therefore, in step S4 of the present application, the calculation mode of the photovoltaic module utilization efficiency, the water pump operation efficiency, the pipeline efficiency and the output power per unit area of the photovoltaic module is as follows:

[0099]

[0100]

[0101]

[0102] In the formula, η1 is the photovoltaic module conversion efficiency, mainly depends on the material of photovoltaic module, and is affected by environmental factors, dimensionless, same below; η2 is the photovoltaic water pump operating efficiency; η3 is the pipeline efficiency, when the water lifting height difference is a constant value, increases with the decrease of pipeline water head loss; P a is the output power of photovoltaic module per unit area (W / m 2 ); G is the solar radiation intensity (W / m 2 ); P is the total output power of photovoltaic module (W); ρ is the density of water, 1×10 3 kg / m 3 ; g is the acceleration of gravity, 9.8 m 2 / s; Q is the water pump flow (L / h); H Z is the system static lift, i.e. water lifting height (m); H S is the water pump outlet energy supply pressure, i.e. water pump lift (m); h is the water head loss of water pipeline, composed of along-path water head loss and local water head loss (m); A1 is the cell panel area of photovoltaic module (m 2 ).

[0103] The overall efficiency of photovoltaic water pump water lifting is calculated as follows:

[0104] η T is the overall efficiency of photovoltaic water pump water lifting;

[0105] The water pump lift H S is equal to the required lift H D in the pipeline output process, and the calculation method is as follows:

[0106]

[0107] In the formula, H D is the required lift of water lifting pipeline (m), L is the pipeline length (m), D is the pipe diameter (m), A2 is the pipeline cross-sectional area (m 2 ), λ and ∑ξ are the along-path resistance coefficient of pipeline and the sum of various local resistance coefficients.

[0108] The sum of local resistance coefficients of pipeline ∑ξ is composed of various local resistance coefficients of water lifting pipeline, which is changed by adjusting the valve opening degree, and the relationship can be obtained by test:

[0109] In the formula, v is the kinematic viscosity coefficient of water, 0.899×10 -2cm 2 / s.

[0110] η1 and solar irradiance G inverse proportional piecewise function relationship as shown below:

[0111]

[0112] In the valve opening is 0-100%, the opening range of the valve opening k and local resistance coefficient ∑ξ relationship as follows:

[0113]

[0114] The water pump flow Q calculation formula as follows:

[0115]

[0116] The photovoltaic module area, pipe size and other parameters into the water pump flow Q calculation formula, can be calculated under each irradiance maximum pumping capacity; respectively, pumping height H Z The value, the system's water pump start minimum irradiance, solar utilization rate, photovoltaic module weighted average efficiency, water pump weighted average efficiency, pipe weighted average efficiency, the overall average efficiency of the system, so as to determine the optimal photovoltaic water pump pumping height; on the basis of the optimal pumping height, the influence of increasing the area of photovoltaic panels or the number of reservoirs on the solar utilization rate and pumping cost is analyzed, and the optimal photovoltaic panel area and the number of reservoirs are determined.

[0117] Specifically, in step S5, the LCC target function expression is as follows:

[0118] C=C pv +C B +C C +C D +C BnPW +C DnPW +C Isnt +C MPW

[0119] In the formula, C pv is the purchase cost of photovoltaic cells (yuan); C B is the purchase cost of the battery (yuan); C C is the purchase cost of the controller (yuan); C D is the purchase cost of the reservoir (yuan); C BnPW is the present value of the replacement procurement fund of the battery (yuan); C DnPW is the present value of the replacement procurement fund of the reservoir (yuan); C Isnt is the installation cost of the system (yuan); C MPW is the present value of the system operation and maintenance cost converted to the initial investment (yuan).

[0120] The present value of the replacement cost of the battery after n years:

[0121]

[0122]

[0123] In the formula, i is the inflation rate, the reference value is 3%; d is the bank interest rate, the reference value is 5%; n is the annual number, for example, if the battery is replaced every 5 years, n=5, and if the battery is replaced every 20 years, n=20.

[0124] The present value of the maintenance cost is:

[0125]

[0126] In the formula, a is the annual maintenance cost (yuan); N is the operating life of the photovoltaic system, and the reference value is 20 years.

[0127] Specifically, the load power shortage rate LPSP and the energy overflow ratio EXC can be used as the power supply reliability indicators of the photovoltaic driving system, so that the photovoltaic power supply system can meet the load power supply guarantee rate and improve the renewable energy utilization rate.

[0128] The load power shortage rate represents the probability that the power generation capacity of the photovoltaic power supply system cannot meet the load power requirement within a certain time. In an independent power generation system, the calculation formula of LPSP is:

[0129]

[0130] In the formula, P load (t) is the load power at time t (W), P PV (t) is the output power of the photovoltaic array at time t (W), P store (t) is the output power of the battery at time t (W), η in is the input conversion rate of the photovoltaic cell array to the battery, and the reference value is 0.9, η out is the output efficiency of the battery to the load, and the reference value is 0.85; the value range of LPSP is [0, 1], and LPSP=0 and 1 respectively represent that the power supply guarantee rate of the photovoltaic power supply system is 100% and 0%.

[0131] The energy overflow ratio EXC represents the ratio of the overflow energy of the photovoltaic power supply system to the total power generation capacity within a certain time. In the EXC engineering, 5% to 30% is generally taken, and the calculation formula is:

[0132]

[0133] Specifically, in step S6, the multi-objective optimization algorithm adopts the Crown-Hoar optimization algorithm, and the Crown-Hoar optimization algorithm specifically includes the following steps:

[0134] (1) Initialize the population, set the population size and the number of iterations;

[0135]

[0136] where N' is the number of individuals (population size N'); is the i-th candidate solution in the search space; and are the lower and upper limits of the search range, respectively; is a randomly initialized vector between 0 and 1.

[0137] The initial population can be represented as follows:

[0138]

[0139] where x i,j represents the j-th position of the i-th solution, and d is the dimension size of the given problem.

[0140] (2) Cycle Population Reduction Technique (CPR), to accelerate the convergence speed and maintain population diversity;

[0141]

[0142] where T is a variable that determines the number of cycles; t is the current function evaluation; T max is the maximum number of function evaluations; % represents the remainder or modulus operator; N min is the smallest number of individuals in the newly generated population, so that the population size cannot be less than N min .

[0143] (3) Exploration phase, including the first defense strategy and the second defense strategy, the relevant formulas are as follows:

[0144]

[0145]

[0146]

[0147] where is the optimal solution of function estimate t; is the vector generated between the current Crown Hyrax (CP) and the randomly selected CP from the population, representing the position of the predator at iteration t; τ1 is a random number based on normal distribution; τ2 is a random value in the interval [0, 1]; r is a random number between [1, N]; is a binary vector containing 0 and 1 randomly generated to cover all possible probabilities; represents the position of the predator, between the current CP and a randomly selected CP solution from the population.

[0148] (4) Development stage, including the third defense strategy and the fourth defense strategy, the relevant formula is as follows:

[0149]

[0150]

[0151]

[0152]

[0153]

[0154]

[0155]

[0156]

[0157]

[0158]

[0159]

[0160]

[0161]

[0162]

[0163] In the formula, r3 is a random number between [1, N]; δ is a parameter used to control the search direction; is the position of the ith individual at iteration t; γ t is the defined defense factor; τ3 is a random value in the interval [0, 1]; is the odor diffusion factor; is the objective function value of the ith individual at iteration t; ε is a small value to avoid division by zero; is a vector containing a randomly generated number between 0 and 1; rand is a variable containing a randomly generated number between 0 and 1; N is the population size; t is the number of current iterations; t max is the maximum number of iterations; is to simulate the three possible situations of this strategy: (1) when equal to 0, the movement stops due to the fear of the predator to the CP, the CP will stop spreading the odor, thus the distance between the predator and the CP remains unchanged, (2) when equal to 1, the CP will significantly spread the odor due to the close distance of the predator, (3) when is a combination of 0 and 1, the predator keeps a certain safe distance from the CP, thus there is no need to release a large amount of its odor; is the optimal solution, representing the CP; is the position of the ith individual at iteration t, representing the predator of the position; a is a convergence speed factor discussed later in the parameter setting section; τ4 is a random value in the interval [0, 1]; is the average force of the CP on the ith predator, which is provided by the inelastic collision law; is the mass of the ith individual (predator) at iteration t; f(·) is the objective function; is the final speed of the ith individual at the next iteration t+1; is the initial speed of the ith individual at iteration t+1; Δt is the current iteration number; is a vector containing random numbers generated between 0 and 1; τ6, τ7, τ8, τ9 and τ 10 is a randomly generated number between 0 and 1, in each generation, is evaluated using an objective function, which needs to be minimized or maximized to achieve the desired result; and respectively represent the estimated solution to be processed; J represents the number of equality constraints; K represents the number of inequality constraints.

[0164] The above only describes the preferred embodiments of the present application, and it should be understood that the present application is not limited to the forms disclosed herein, and should not be considered as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the concepts described herein, by the above teachings or related art or knowledge. Any modification and change made by those skilled in the art without departing from the spirit and scope of the present application shall be within the protection scope of the claims of the present application.

Claims

1. A configuration optimization method of a synergistic energy-provided photovoltaic power generation water-saving irrigation system, characterized in that, Comprise: S1, according to the different growth stages of local crops water requirement characteristics, determine the minimum water requirement of crops in different growth stages, to meet the minimum water requirement of crops in different growth stages as the goal, determine the solar photovoltaic water pump pumping flow, regulating pool capacity and solar photovoltaic pumping total head, and select the corresponding solar photovoltaic water pump unit and solar photovoltaic panel; S2, through the energy balance equation, ensure that the photovoltaic power generation and battery energy storage meet the power demand of irrigation system; S3, through the water resources balance equation, ensure that the capacity of the reservoir meet the irrigation demand; S4, based on different irradiance, valve opening, pumping height under the utilization efficiency of photovoltaic module, pump operating efficiency, pipeline efficiency and unit area photovoltaic module output power, build irrigation system flow calculation model, according to the overall efficiency of photovoltaic water pump pumping and solar utilization rate to determine the optimal pumping height; S5, the initial investment cost, operation cost, maintenance cost and replacement cost of photovoltaic water-saving irrigation system as constraint, establish the life cycle cost model of irrigation system; S6, using multi-objective optimization algorithm, determine the optimal configuration parameters of photovoltaic generator set, reservoir and battery, make the life cycle cost of irrigation system minimum, and meet the minimum water requirement of crops; In step S4, the calculation method of photovoltaic module utilization efficiency, pump operating efficiency, pipeline efficiency and unit area photovoltaic module output power is as follows: wherein η1 is the conversion efficiency of the photovoltaic module, η2 is the operating efficiency of the water pump, η3 is the pipeline efficiency, P a is the output power per unit area of the photovoltaic module, G is the solar irradiance, P is the total output power of the photovoltaic module, ρ is the density of water, g is the acceleration of gravity, Q is the flow rate of the water pump, H Z is the static lift of the irrigation system, i.e. the water lifting height, H S is the outlet energy supply pressure of the water pump, i.e. the water lifting height of the water pump, h is the head loss of the water pipeline, which is composed of the frictional head loss and the local head loss, and A1 is the area of the cell panel of the photovoltaic module. The overall efficiency of photovoltaic water pump pumping is calculated as follows: η T ηoverall is the overall efficiency of the photovoltaic water pumping Pump head H S The required head H during pipeline output D They are equal, and the calculation method is as follows: In the formula, H D is the required head during pipeline output, L is the pipeline length, D is the pipe diameter, A2 is the pipeline cross-sectional area, λ,∑ ξ is the pipeline resistance coefficient and the sum of various local resistance coefficients; The sum of local resistance coefficient ∑ξ is composed of each local resistance coefficient of pumping pipeline, which is changed by adjusting the valve opening, and the relationship between them can be obtained by test: where v is the kinematic viscosity of water; The inverse proportional segmented function relationship between η1 and solar irradiance G is as follows: When the valve opening is 0-100%, the relationship between valve opening k and local resistance coefficient ∑ξ in this opening range is as follows: Then the calculation formula of pump flow Q is as follows: Then the maximum water lifting capacity under each solar radiation intensity is calculated, and the water lifting height H Z The minimum radiation intensity for starting the water pump, solar energy utilization rate, weighted average efficiency of photovoltaic module, weighted average efficiency of water pump, weighted average efficiency of pipeline, and overall average efficiency of photovoltaic water pump water lifting are calculated according to the values, so as to determine the optimal water lifting height of the photovoltaic water pump.

2. The configuration optimization method of a synergistic energy-supplied photovoltaic power generation water-saving irrigation system according to claim 1, characterized in that, In step S1, the pumping flow of solar photovoltaic water pump is determined according to the irrigation water quantity and the proposed pumping time, and the specific calculation method is as follows: Solar photovoltaic water pump daily water lifting quantity Q d = W / (ηt ds ), wherein Q d is a solar photovoltaic water pump daily water lifting quantity, unit is m 3 , W is net irrigation water quantity, unit is m 3 , η is irrigation water use coefficient, t ds is water lifting days, selected according to setting working condition; The water pumping flow of the solar photovoltaic water pump is q d = Q d / T t , wherein q d is the water pumping flow of the solar photovoltaic water pump, and T t is the daily water pumping time of the solar photovoltaic water pump.

3. The configuration optimization method of a synergistic energy-supplied photovoltaic power generation water-saving irrigation system according to claim 2, characterized in that, In step S1, the regulating pool capacity is determined by the daily pumping quantity of solar photovoltaic water pump and the daily irrigation water quantity in the first irrigation period, and the capacity of the regulating pool is obtained by water balance analysis, and the specific calculation method is as follows: V = max(V1, V2,..., V i ) V min = Q i - (W i T d ) / t d In the formula, V n is the required regulating pool capacity during the irrigation period, in m 3 , i is the daily water pumping capacity of the solar photovoltaic water pump during the irrigation period, in W i is the daily irrigation water volume during the irrigation period, i is the number of days in the irrigation period, V is the regulating pool volume, V min is the minimum pool volume, T d is the daily water pumping time of the solar photovoltaic water pump, t d is the daily irrigation time.

4. The configuration optimization method of a synergistic energy-supplied photovoltaic power generation water-saving irrigation system according to claim 1, characterized in that, In step S1, the calculation method of solar photovoltaic pumping total head is as follows: H p =∑h ω +h0+ΔZ, where H p is the design working head of the water pump, ∑h ω is the sum of the head losses in the pipes, h0 is the filter and other head losses at the water source, and ΔZ is the terrain elevation difference.

5. The configuration optimization method of a synergistic energy-supplied photovoltaic power generation water-saving irrigation system according to claim 4, characterized in that, Step S1 also includes: Adjust the output frequency in real time according to the change of solar intensity, realize the maximum power point tracking; The maximum peak water power of solar photovoltaic panel is calculated as follows: where N sf is the maximum peak water power, Q max is the peak flow rate of the water pump, in m 3 / h, H is the total head of the system, and p is the density of water. The pumping peak power of solar photovoltaic water pump is calculated as follows: where N pf is the peak pumping power, k1 is the flow correction coefficient, k2 is the pumping machine type correction coefficient, and k3 is the electric drive type correction coefficient. According to the pumping peak power of solar photovoltaic water pump, select the corresponding photovoltaic water pumping inverter and irrigation system control cabinet.

6. The configuration optimization method of a synergistic energy-supplied photovoltaic power generation water-saving irrigation system according to claim 1, characterized in that, In step S2, the energy balance equation is: EPV(t)+EST(t)≥EDE(t), wherein EPV is photovoltaic power generation, EST is battery energy storage, and EDE is the power demand of irrigation system.

7. The configuration optimization method of a synergistic energy-supplied photovoltaic power generation water-saving irrigation system according to claim 1, characterized in that, In step S3, the water resources balance equation is: VST(t)≥VDE(t), wherein VST is the storage capacity of the reservoir, and VDE is the irrigation demand.

8. The configuration optimization method of a synergistic energy-supplied photovoltaic power generation water-saving irrigation system according to claim 1, characterized in that, In step S5, the objective function expression of the life cycle cost model is as follows: C=C pv +C B +C C +C D +C BnPW +C DnPW +C Isnt +C MPW wherein C pv is the purchase cost of the photovoltaic cell, C B is the purchase cost of the battery, C C is the purchase cost of the controller, C D is the purchase cost of the water reservoir, C BnPW is the present value of the replacement purchase of the battery, C DnPW is the present value of the replacement purchase of the water reservoir, C Isnt is the installation cost of the system, C MPW is the present value of the system operation and maintenance costs converted to the initial investment period; The present value of the battery and the replacement cost of the battery after n years: In the formula, i is the inflation rate, d is the bank interest rate, and n is the annual number; The present value of the maintenance cost is: In the formula, a is the annual maintenance cost, and N is the operating life of the photovoltaic system.

9. The method of claim 1, wherein the configuration optimization method of a synergistic energy-provided photovoltaic power generation water-saving irrigation system is characterized in that, In step S6, the multi-objective optimization algorithm is the Crown-hoar optimization algorithm.

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