Configuration optimization method of collaborative energy supply photovoltaic power generation water-saving irrigation system

Abstract

The invention relates to the technical field of agricultural irrigation, in particular to a configuration optimization method of a collaborative energy supply photovoltaic power generation water-saving irrigation system. According to water demand characteristics of local crops in the growth period, configuration is carried out by taking the minimum water demand of the crops in different growth periods as a target, and a system flow calculation model is constructed by considering change rules of photovoltaic module utilization efficiency, water pump operation efficiency and pipeline efficiency under different irradiation intensities, valve opening degrees and water lifting heights; and determining the optimal water lifting height according to the system overall efficiency and the solar energy utilization rate. The initial investment cost, the operation cost, the maintenance cost and the replacement cost of the water-saving irrigation system are used as constraints, and a system life cycle cost model is established. The optimal configuration parameters of the photovoltaic generator set, the reservoir and the storage battery are determined by adopting a crown porcupine optimization algorithm, so that the whole life cycle cost of the system is minimized, and the lowest water demand of crops is met. The system is suitable for a water-saving irrigation system composed of a photovoltaic generator set, a reservoir and a storage battery.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural irrigation, and in particular to a configuration optimization method for a collaborative energy supply photovoltaic power generation water-saving irrigation system. Background Art

[0002] Global climate change and water shortage are becoming increasingly serious problems, and traditional agricultural irrigation methods have significant deficiencies in water and energy consumption. Current agricultural irrigation systems generally have problems such as high energy consumption, waste of resources and high operating costs, especially in areas with water shortages and unstable power supply.

[0003] Traditional irrigation systems rely on power from the grid, resulting in high operating costs and environmental issues. Photovoltaic power generation, as a clean, renewable energy source, combined with reservoirs and batteries for agricultural irrigation can significantly improve the efficiency of water and energy utilization. However, how to scientifically and rationally configure the system consisting of photovoltaic generators, reservoirs and batteries to meet crop water requirements and minimize the system's full life cycle cost remains an urgent problem to be solved. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a configuration optimization method for a synergistic photovoltaic power generation water-saving irrigation system, so as to achieve the minimum water demand for crops in different growth stages and minimize the full life cycle cost of the irrigation system on this basis.

[0005] The present invention adopts the following technical scheme to achieve the above-mentioned purpose. The present invention provides a configuration optimization method of a cooperative energy supply photovoltaic power generation water-saving irrigation system, comprising:

[0006] S1. According to the water demand characteristics of local crops in different growth stages, determine the minimum water demand of crops in each growth stage, with the goal of meeting the minimum water demand of crops in different growth stages, determine the water lifting flow of solar photovoltaic water pumps, adjust the water tank capacity and the total lift of solar photovoltaic water lifting, and select the corresponding solar photovoltaic water pump units and solar photovoltaic panels;

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

[0008] S3. Ensure that the capacity of the reservoir meets the irrigation demand through the water resource balance equation;

[0009] S4. Based on the utilization efficiency of photovoltaic modules, water pump operation efficiency, pipeline efficiency and output power of photovoltaic modules per unit area under different irradiation intensities, valve openings and water lifting heights, an irrigation system flow calculation model is constructed, and the optimal water lifting height is determined according to the overall efficiency of photovoltaic water pump water lifting and the utilization rate of solar energy;

[0010] S5. Establish a life cycle cost model for the irrigation system based on the initial investment cost, operation cost, maintenance cost and replacement cost of the photovoltaic generator set;

[0011] S6. Use a multi-objective optimization algorithm to determine the optimal configuration parameters of the photovoltaic generator set, water reservoir and battery to minimize the life cycle cost of the irrigation system and meet the minimum water requirement of the crops.

[0012] Furthermore, in step S1, the water extraction flow rate of the solar photovoltaic water pump is determined according to the irrigation water consumption and the planned water extraction time, and the specific calculation method is as follows:

[0013] The daily water lifting capacity of solar photovoltaic water pump is Q d =W / (ηt ds ), where Q d is the daily water extraction capacity of the solar photovoltaic water pump, in m 3 , W is the net irrigation water consumption, unit is m 3 , η is the irrigation water utilization coefficient, t ds The number of days for water extraction is selected according to the set working conditions;

[0014] The water flow rate of the solar photovoltaic water pump is q d =Q d / T t , where q d is the water lifting flow of the solar photovoltaic water pump, T t The water extraction time for solar photovoltaic day.

[0015] Furthermore, in step S1, the capacity of the regulating pool is determined by the daily water extraction of the solar photovoltaic water pump and the daily irrigation water volume during one irrigation period, and then the capacity of the regulating pool is 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] Where V n The capacity of the water tank to be regulated during the irrigation period, in m 3 , Q i is the daily water extraction capacity of the solar photovoltaic water pump during one irrigation period, W iis the daily irrigation water consumption in one irrigation period, i is the number of days in one irrigation period, V is the volume of the regulating pool, V min is the minimum volume of the pool, T d is the daily water extraction time of the solar photovoltaic water pump, t d It refers to the irrigation time of the day.

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

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

[0022] Furthermore, step S1 further includes:

[0023] Adjust the output frequency in real time according to the change of sunshine 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 rate of the pump, in m 3 / h, H is the total head of the system, g is the acceleration of gravity, and ρ is the density of water;

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

[0027] Where N pf is the peak power of water lifting, k1 is the flow correction factor, k2 is the water lifting equipment form correction factor, k3 is the electric transmission form correction factor;

[0028] Select the corresponding photovoltaic pumping inverter and irrigation system control cabinet according to the peak water lifting power of the solar photovoltaic water pump.

[0029] Furthermore, 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 battery storage energy, and EDE is the electricity demand of the irrigation system.

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

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

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

[0034]

[0035]

[0036]

[0037]

[0038] In the formula, 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 of photovoltaic modules per unit area, G is the solar radiation intensity, P is the total output power of photovoltaic modules, ρ is the density of water, Q is the flow rate of water pump, H Z H is the static head of the irrigation system, i.e. the water lifting height. S is the outlet supply pressure of the water pump, i.e., the head of the water pump; h is the head loss of the water pipeline, which is composed of the head loss along the pipeline and the local head loss; A1 is the panel area of ​​the photovoltaic module;

[0039] The overall efficiency calculation formula of photovoltaic water pump water extraction is as follows:

[0040] η T The overall efficiency of photovoltaic water pumps in lifting water;

[0041] Pump head H S The required head H during pipeline output D Equal, calculated as follows:

[0042]

[0043] 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 and ∑ξ are the sum of the pipeline resistance coefficient and various local resistance coefficients;

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

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

[0046] The inverse proportional piecewise function relationship between η1 and solar radiation intensity G is as follows:

[0047]

[0048] When the valve opening is 0-100%, the relationship between the valve opening k and the local resistance coefficient ∑ξ in this opening range is as follows:

[0049]

[0050] The calculation formula of the water pump flow Q is as follows:

[0051]

[0052] Then calculate the maximum water lifting capacity under different solar radiation intensities, and calculate the water lifting height H Z Take the value and calculate the corresponding minimum irradiation intensity for water pump startup, solar energy utilization rate, weighted average efficiency of photovoltaic modules, weighted average efficiency of water pumps, weighted average efficiency of pipelines and the overall average efficiency of photovoltaic water pump water lifting, so as to determine the optimal water lifting height of photovoltaic water pump.

[0053] Furthermore, 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 funds for purchasing battery replacement, C DnPW is the present value of the purchase funds for the replacement of the reservoir, C Isnt is the installation cost of the system, C MPW The system operation and maintenance costs are converted to the present value at the initial stage of investment;

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

[0057]

[0058]

[0059] In the formula, i is the inflation rate, d is the bank interest rate, and n is the year number;

[0060] The present value of maintenance cost is:

[0061]

[0062] Where a is the annual maintenance cost and N is the operating life of the PV system.

[0063] Furthermore, in step S6, the multi-objective optimization algorithm is a crested porcupine optimization algorithm.

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

[0065] The present invention determines the minimum water requirement of crops in different growth stages according to the water requirement characteristics of local crops in different growth stages, and determines the water lifting flow rate of solar photovoltaic water pumps, the capacity of regulating water tanks and the total lift of solar photovoltaic water lifting with the goal of meeting the minimum water requirement of crops in different growth stages. Through the energy balance equation, it is ensured that the photovoltaic power generation and battery energy storage meet the electricity demand of the irrigation system; through the water resource balance equation, it is ensured that the capacity of the water reservoir meets the irrigation demand; based on the utilization efficiency of photovoltaic modules, water pump operation efficiency, pipeline efficiency and output power of photovoltaic modules per unit area under different irradiation intensities, valve openings and water lifting heights, an irrigation system flow calculation model is constructed, and the optimal water lifting height is determined according to the overall efficiency of photovoltaic water pump water lifting and the utilization rate of solar energy; with the initial investment cost, operation cost, maintenance cost and replacement cost of photovoltaic generator sets as constraints, an irrigation system full life cycle cost model is established; a multi-objective optimization algorithm is used to determine the optimal configuration parameters of photovoltaic generator sets, water reservoirs and batteries, so that the full life cycle cost of the irrigation system is minimized and the minimum water requirement of crops is met.

[0066] The above method is used to determine the optimal configuration parameters for the coordinated energy supply of photovoltaic generators, reservoirs and batteries to meet the minimum water requirements of crops in different growth stages and minimize the full life cycle cost of the system on this basis. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0068] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0069] The present invention provides a configuration optimization method for a collaborative energy-supply photovoltaic power generation water-saving irrigation system, wherein the irrigation system comprises: solar panels, brackets, foundations, battery packs, control systems, photovoltaic water pumps, water intake buildings, water pipelines, water reservoirs, water use terminals, safety protection nets, etc.

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

[0071] S1. According to the water demand characteristics of local crops at different growth stages, determine the minimum water demand of each growth stage, with the goal of meeting the minimum water demand of crops at different growth stages, design the crop irrigation system, determine the water flow of the solar photovoltaic water pump, adjust the water tank capacity and the total lift of the solar photovoltaic water pump to select reasonable solar photovoltaic water pump units and solar photovoltaic panels;

[0072] S2. Ensure that the photovoltaic power generation and battery energy storage meet the power demand of the irrigation system through the energy balance equation;

[0073] S3. Ensure that the capacity of the reservoir meets the irrigation demand through the water resource balance equation;

[0074] S4. Based on the changing rules of photovoltaic module utilization efficiency, water pump operation efficiency, pipeline efficiency, and output power per unit area of ​​photovoltaic modules under different irradiation intensities, valve openings, and water lifting heights, a system flow calculation model is constructed. The optimal water lifting height is determined according to the overall efficiency of the irrigation system and the utilization rate of solar energy. On this basis, the water lifting cost of the water lifting system is reduced and the utilization rate of solar energy is improved by increasing the area of ​​photovoltaic modules and the number of water storage tanks.

[0075] S5. Taking the initial investment cost, operation cost, maintenance cost and replacement cost of the photovoltaic power generation unit as constraints, establish the system life cycle cost LCC model;

[0076] S6. Use a multi-objective optimization algorithm to determine the optimal configuration parameters of the photovoltaic generator set, water reservoir and battery to minimize the system's life cycle cost and meet the minimum water requirement of crops.

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

[0078] The daily water lifting capacity of solar photovoltaic water pump is Q d =W / (ηt ds ), where Q d is the daily water extraction capacity of photovoltaic solar energy (m 3 ), W is the net irrigation water consumption (m 3 ), η is the irrigation water utilization coefficient, t ds is the number of days for water extraction (d), which is selected according to the set working conditions.

[0079] Then the water pumping flow rate of the solar photovoltaic water pump is q d =Q d / T t , where q d The water pumping flow rate of photovoltaic solar energy (m 3 ), T t is the daily water extraction time of solar photovoltaic (h).

[0080] Specifically, in step S1, the capacity of the regulating pool needs to be determined by the daily water extraction of solar photovoltaic power and the daily irrigation water volume during one 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] Where V n The capacity of the water tank to be adjusted during the irrigation period (m 3 ), Q i is the daily water extraction of solar photovoltaic in one irrigation period (m 3 ), W i is the daily irrigation water consumption in one irrigation period (m 3 ), i is the number of days in an irrigation period, V is the volume of the regulating pool (m 3 ), V min is the minimum volume of the pool (m 3 ), T d is the solar photovoltaic daily water extraction time (h), t d is the daily irrigation time of irrigation water (h).

[0085] Specifically, in step S1, the total lift of solar photovoltaic water pumping is calculated as follows:

[0086] H p =∑h ω +h0+ΔZ, where H p Design working head for the pump, ∑h ω is the sum of the head losses of pipelines at all levels, h0 is the filter and other head losses at the water source, and ΔZ is the terrain height difference.

[0087] Specifically, step S1 also includes:

[0088] The operation is controlled and regulated through the solar energy conversion control system, which converts the direct current generated by the solar cell array into alternating current to drive the water pump. The output frequency is adjusted in real time according to the changes in sunlight intensity to achieve maximum power point tracking and maximize the use of 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] Where N sf is the peak water power (W); Q max is the peak flow rate of the pump (m 3 / h); H is the total head of the system (m); g is the acceleration due to gravity (m / s 2 );ρ 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] Where N pf is the peak water power of the water lifting system (W); k1 is the flow correction coefficient; k2 is the water lifting equipment form correction coefficient; k3 is the electric transmission form correction coefficient.

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

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

[0095] EPV(t)+EST(t)≥EDE(t), where EPV is the photovoltaic power generation, EST is the battery storage energy, and EDE is the electricity demand of the irrigation system.

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

[0097] VST(t)≥VDE(t), where VST is the water storage capacity of the reservoir (m 3 ); VDE is irrigation demand (m 3 ).

[0098] Solar energy is converted into electrical energy through photovoltaic panels, and electrical energy is converted into mechanical energy through water pumps to pump water from low-lying areas to high-lying areas. Therefore, in step S4 of the present invention, the calculation method of photovoltaic module utilization efficiency, water pump operation efficiency, pipeline efficiency and photovoltaic module output power per unit area is as follows:

[0099]

[0100]

[0101]

[0102] Wherein, η1 is the conversion efficiency of photovoltaic modules, which is mainly determined by the material of photovoltaic modules and is also affected by environmental factors. It is dimensionless and the same below; η2 is the operation efficiency of photovoltaic water pump; η3 is the pipeline efficiency, which increases with the decrease of pipeline head loss when the water lifting height difference is a constant value; P a is the output power of photovoltaic modules per unit area (W / m 2 ); G is the solar radiation intensity (W / m 2 ), P is the total output power of the photovoltaic module (W), ρ is the density of water, which is 1×10 3 kg / m 3 ; g is the acceleration due to gravity, the value is 9.8m 2 / s; Q is the pump flow rate (L / h); H Z H is the static head of the system, i.e. the water lifting height (m); S is the pump outlet supply pressure, i.e., the pump head (m); h is the head loss of the water pipeline, which consists of the head loss along the pipeline and the local head loss (m); A1 is the panel area of ​​the photovoltaic module (m 2 ).

[0103] The overall efficiency calculation formula of photovoltaic water pump water extraction is as follows:

[0104] η T The overall efficiency of photovoltaic water pumps in lifting water;

[0105] Pump head H S The required head H during pipeline output D Equal, calculated as follows:

[0106]

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

[0108] The sum of the local resistance coefficients of the pipeline ∑ξ is composed of the local resistance coefficients of the water pumping pipeline, which can be changed by adjusting the valve opening. The relationship between the two can be obtained from the experiment:

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

[0110] The inverse proportional piecewise function relationship between η1 and solar radiation intensity G is as follows:

[0111]

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

[0113]

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

[0115]

[0116] Substituting the photovoltaic module area, pipeline size and other parameters into the calculation formula of the water pump flow Q, the maximum water lifting capacity under each irradiation intensity can be calculated; Z Take values, calculate the system's minimum irradiation intensity for starting the water pump, solar energy utilization rate, weighted average efficiency of photovoltaic modules, weighted average efficiency of water pumps, weighted average efficiency of pipelines, and overall average efficiency, so as to determine the optimal water lifting height of the photovoltaic water pump; on the basis of the optimal water lifting height, analyze the impact of increasing the area of ​​photovoltaic panels or the number of water reservoirs on the solar energy utilization rate and water lifting cost, and determine the optimal area of ​​photovoltaic panels and number of water reservoirs respectively.

[0117] Specifically, in step S5, the LCC objective 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 funds for battery replacement (yuan); C DnPW is the present value of the purchase funds for the replacement of the reservoir (yuan); C Isnt is the installation cost of the system (yuan); C MPW The system operation and maintenance costs are converted to the present value (yuan) at the initial investment stage.

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

[0121]

[0122]

[0123] In the formula, i is the inflation rate, with a reference value of 3%; d is the bank interest rate, with a reference value of 5%; n is the year number, such as if the battery is replaced every 5 years, then n=5; if the water tank is replaced every 20 years, then n=20.

[0124] The present value of maintenance cost is:

[0125]

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

[0127] Specifically, the present invention can also use the load power shortage rate LPSP and the energy overflow ratio EXC as power supply reliability indicators of the photovoltaic drive system, so that the photovoltaic power supply system can not only meet the load power supply guarantee rate but also improve the utilization rate of renewable energy.

[0128] The load shortfall rate indicates the probability that the power generation of the photovoltaic power supply system cannot meet the load power consumption requirements within a certain period of time. In an independent power generation system, the LPSP calculation formula is:

[0129]

[0130] Where P load (t) is the load power consumption 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 from the photovoltaic cell array to the battery, with a reference value of 0.9, η out is the output efficiency from the battery to the load, with a reference value of 0.85; the LPSP value range is [0,1], where LPSP=0 and 1 represent the power supply guarantee rate of the photovoltaic power supply system of 100% and 0%, respectively.

[0131] The energy overflow ratio EXC indicates the ratio of the energy overflowed by the photovoltaic power supply system to the total power generation within a certain period of time. In EXC projects, it is generally 5% to 30%, and the calculation formula is:

[0132]

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

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

[0135]

[0136] In the formula, 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; A vector randomly initialized from 0 to 1.

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

[0138]

[0139] In the formula, x i,j represents the jth position of the ith solution, and d is the dimension of the given problem.

[0140] (2) Cyclic population reduction (CPR) technology, which accelerates convergence and maintains population diversity;

[0141]

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

[0143] (3) The survey phase includes the first defense strategy and the second defense strategy. The relevant formula is as follows:

[0144]

[0145]

[0146]

[0147] In the formula, Estimate the optimal solution for the function t; is the vector generated between the current crested porcupine (CP) and a randomly selected CP from the population, representing the position of the predator at iteration t; τ1 is a random number based on a normal distribution; τ2 is a random value in the interval [0, 1]; r is a random number between [1, N]; The randomly generated binary values ​​of 0 and 1 always cover all possible probabilities; represents the position of the predator, which is between the current CP and a CP solution randomly selected from the population.

[0148] (4) Development phase, 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] Where 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 that avoids division by zero; is a vector containing randomly generated values ​​between 0 and 1; rand is a variable containing randomly generated numbers between 0 and 1; N is the population size; t is the number of current iterations; t max is the maximum number of iterations; To simulate the three possible situations of this strategy: (1) When is equal to 0, the predator stops moving due to fear of CP, and CP stops spreading its scent, so the distance between the predator and CP remains unchanged. (2) When it is equal to 1, the CP will emit a significant odor due to the close distance of the predator. (3) When it is a combination of 0 and 1, the predator maintains a certain safe distance from the CP, so there is no need to release its scent in large quantities; is the optimal solution, representing CP; is the position of the i-th individual at iteration t, representing the predator at that position; α is the convergence speed factor discussed later in the parameter setting section; τ4 is a random value in the interval [0,1]; is the average force exerted by CP on the i-th predator, which is provided by the law of inelastic collision; is the mass of the ith individual (predator) at iteration t; f(·) is the objective function; is the final velocity of the i-th individual at the next iteration t+1; is the initial velocity of the i-th 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 value between 0 and 1. In each generation, The evaluation uses an objective function that needs to be minimized or maximized to achieve the desired result; and They represent the estimated solutions The constraints to be processed; J represents the number of equality constraints; K represents the number of inequality constraints.

[0164] The above is only a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art shall not deviate from the spirit and scope of the present invention, and shall be within the scope of protection of the claims attached to the present invention.

Claims

1. A configuration optimization method for a collaborative energy supply photovoltaic power generation water-saving irrigation system, characterized in that: include: S1. According to the water demand characteristics of local crops at different growth stages, determine the minimum water demand of crops at different growth stages, with the goal of meeting the minimum water demand of crops at different growth stages, determine the water lifting flow of solar photovoltaic water pumps, the capacity of regulating water tanks and the total lift of solar photovoltaic water lifting, and select the corresponding solar photovoltaic water pump units and solar photovoltaic panels; S2. Ensure that the photovoltaic power generation and battery energy storage meet the power demand of the irrigation system through the energy balance equation; S3. Ensure that the capacity of the reservoir meets the irrigation demand through the water resource balance equation; S4. Based on the utilization efficiency of photovoltaic modules, water pump operation efficiency, pipeline efficiency and output power of photovoltaic modules per unit area under different irradiation intensities, valve openings and water lifting heights, an irrigation system flow calculation model is constructed, and the optimal water lifting height is determined according to the overall efficiency of photovoltaic water pump water lifting and the utilization rate of solar energy; S5. Taking the initial investment cost, operation cost, maintenance cost and replacement cost of the photovoltaic water-saving irrigation system as constraints, establish a full life cycle cost model for the irrigation system; S6. Use a multi-objective optimization algorithm to determine the optimal configuration parameters of the photovoltaic generator set, water reservoir and battery to minimize the life cycle cost of the irrigation system and meet the minimum water requirement of the crops.

2. The configuration optimization method of a cooperative energy supply photovoltaic power generation water-saving irrigation system according to claim 1 is characterized in that: In step S1, the water extraction flow rate of the solar photovoltaic water pump is determined according to the irrigation water consumption and the planned water extraction time. The specific calculation method is as follows: The daily water lifting capacity of solar photovoltaic water pump is Q d =W / (ηt ds ), where Q d is the daily water extraction capacity of the solar photovoltaic water pump, in m 3 , W is the net irrigation water consumption, unit is m 3 , η is the irrigation water utilization coefficient, t ds The number of days for water extraction is selected according to the set working conditions; Then the water pumping flow rate of the solar photovoltaic water pump is q d =Q d / T t , where q d is the water pumping flow of the solar photovoltaic water pump, T t The water extraction time for solar photovoltaic day.

3. The configuration optimization method of the cooperative energy supply photovoltaic power generation water-saving irrigation system according to claim 2 is characterized in that: In step S1, the capacity of the regulating pool is determined by the daily water extraction of the solar photovoltaic water pump and the daily irrigation water volume during one irrigation period, and then the capacity of the regulating pool is obtained through water balance analysis. The specific calculation method is as follows: V=max(V1,V2,…,V i ) V min =Q i -(W i T d ) / t d Where V n The capacity of the water tank to be regulated during the irrigation period, in m 3 , Q i is the daily water extraction capacity of the solar photovoltaic water pump during one irrigation period, W i is the daily irrigation water consumption in one irrigation period, i is the number of days in one irrigation period, V is the volume of the regulating pool, V min is the minimum volume of the pool, T d is the daily water extraction time of the solar photovoltaic water pump, t d It refers to the irrigation time of the day.

4. The configuration optimization method of a cooperative energy supply photovoltaic power generation water-saving irrigation system according to claim 1, characterized in that: In step S1, the total lift of solar photovoltaic water pumping is calculated as follows: H p =∑h ω +h0+ΔZ, where H p Design working head for the pump, ∑h ω is the sum of the head losses of pipelines at all levels, h0 is the filter and other head losses at the water source, and ΔZ is the terrain height difference.

5. The configuration optimization method of the cooperative energy supply photovoltaic power generation water-saving irrigation system according to claim 4 is characterized in that: Step S1 also includes: Adjust the output frequency in real time according to the change of sunshine intensity to achieve maximum power point tracking; The maximum peak water power of the photovoltaic array of the solar photovoltaic panel is calculated according to the following formula: Where N sf is the maximum peak water power, Q max is the peak flow rate of the pump, in m 3 / h, H is the total head of the system, g is the acceleration of gravity, and ρ is the density of water; The peak water-lifting power of the solar photovoltaic water pump is calculated according to the following formula: Where N pf is the peak power of water lifting, k1 is the flow correction factor, k2 is the water lifting equipment form correction factor, k3 is the electric transmission form correction factor; Select the corresponding photovoltaic pumping inverter and irrigation system control cabinet according to the peak water lifting power of the solar photovoltaic water pump.

6. The configuration optimization method of a cooperative energy supply 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), where EPV is the photovoltaic power generation, EST is the battery storage energy, and EDE is the electricity demand of the irrigation system.

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

8. The configuration optimization method of the cooperative energy supply photovoltaic power generation water-saving irrigation system according to claim 1 is characterized in that: In step S4, the calculation method of photovoltaic module utilization efficiency, water pump operation efficiency, pipeline efficiency and photovoltaic module output power per unit area is as follows: In the formula, 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 of photovoltaic modules per unit area, G is the solar radiation intensity, P is the total output power of photovoltaic modules, ρ is the density of water, Q is the flow rate of water pump, H Z H is the static head of the irrigation system, i.e. the water lifting height. S is the outlet supply pressure of the water pump, i.e., the head of the water pump; h is the head loss of the water pipeline, which is composed of the head loss along the pipeline and the local head loss; A1 is the panel area of ​​the photovoltaic module; The overall efficiency calculation formula of photovoltaic water pump water extraction is as follows: η T The overall efficiency of photovoltaic water pumps in lifting water; Pump head H S The required head H during pipeline output D Equal, calculated 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 and ∑ξ are the sum of the pipeline resistance coefficient and various local resistance coefficients; The sum of the local resistance coefficients of the pipeline ∑ξ is composed of the local resistance coefficients of the water pumping pipeline, which can be changed by adjusting the valve opening. The relationship between the two can be obtained from the experiment: Where v is the kinematic viscosity of water; The inverse proportional piecewise function relationship between η1 and solar radiation intensity G is as follows: When the valve opening is 0-100%, the relationship between the valve opening k and the local resistance coefficient ∑ξ in this opening range is as follows: The calculation formula of the water pump flow Q is as follows: Then calculate the maximum water lifting capacity under different solar radiation intensities, and calculate the water lifting height H Z Take the value and calculate the corresponding minimum irradiation intensity for water pump startup, solar energy utilization rate, weighted average efficiency of photovoltaic modules, weighted average efficiency of water pumps, weighted average efficiency of pipelines and the overall average efficiency of photovoltaic water pump water lifting, so as to determine the optimal water lifting height of photovoltaic water pump.

9. The configuration optimization method of the cooperative energy supply 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 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 funds for purchasing battery replacement, C DnPW is the present value of the purchase funds for the replacement of the reservoir, C Isnt is the installation cost of the system, C MPW The system operation and maintenance costs are converted to the present value at the initial stage of investment; 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 year number; The present value of maintenance cost is: Where a is the annual maintenance cost and N is the operating life of the PV system.

10. The configuration optimization method of the cooperative energy supply photovoltaic power generation water-saving irrigation system according to claim 1, characterized in that: In step S6, the multi-objective optimization algorithm is a crested porcupine optimization algorithm.

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