A photovoltaic capacity configuration method based on output capacity demand

Abstract

The application discloses a photovoltaic capacity configuration method based on output capacity demand, which comprises the following steps: calculating the power of a pump station under different combinations of the number of starting machines and the rotating speed of water pumps according to the data of the water lifting pump station, and sorting the power in ascending order; obtaining the daily output process of the photovoltaic power station in different time steps in a year according to the daily output coefficient of the photovoltaic power station in different time steps in a year; establishing a mathematical model of photovoltaic capacity configuration of the photovoltaic water lifting pump station system; obtaining the annual water supply of the photovoltaic water lifting pump station system of the photovoltaic power station, and calculating the corresponding annual average light rejection rate of the photovoltaic power station; screening the annual water supply of the photovoltaic water lifting pump station system of the photovoltaic power station which satisfies the upper limit value of the annual average light rejection rate of the photovoltaic power station according to the set upper limit value of the annual average light rejection rate of the photovoltaic power station; screening the maximum value of the annual water supply of the photovoltaic water lifting pump station system, and selecting the corresponding installed capacity of the photovoltaic power station as the installed capacity configuration scheme of the photovoltaic power station.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of photovoltaic configuration, and more particularly to a photovoltaic capacity configuration method based on output capacity demand. BACKGROUND

[0002] To meet the needs of agricultural irrigation, urban water supply and ecological regulation and storage, a large number of pumping stations are constructed between rivers and lakes and irrigation areas. In recent years, photovoltaic power generation has become an important option for replacing energy in pumping stations due to its clean and renewable advantages. However, photovoltaic output is intermittent and random, and if the installed capacity is not properly configured, there will be two major contradictions of insufficient water supply or serious light rejection. The current research mostly uses fixed load power balance or empirical coefficient to estimate the capacity, ignoring:

[0003] The flexibility of the pumping station itself "multiple variable speed" operation - the photovoltaic power can be matched by adjusting the number of water pumps and the speed of the pumps;

[0004] The water supply service target - the actual concern of the irrigation area is the annual water supply rather than the instantaneous power balance;

[0005] The policy light rejection constraint - the state / local government puts forward a hard target for new energy utilization rate (such as ≥ 90%), and the capacity that is too large will lead to excessive light rejection, and the capacity that is too small will also be difficult to complete the annual water supply task.

[0006] Based on the above background, under the premise of knowing the multi-pump group and variable frequency speed regulation capability of the pumping station, the time series characteristics of regional photovoltaic resources and the upper limit of the policy light rejection rate, how to determine the installed capacity of the photovoltaic power station so that the actual annual water supply reaches the maximum and the average annual light rejection rate does not exceed the specified upper limit is the core problem to be solved.

[0007] In view of the above problems, the present application provides a solution. SUMMARY

[0008] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide a photovoltaic capacity configuration method based on output capacity demand to solve the problems raised in the background art.

[0009] In order to achieve the above-mentioned purpose, the present application provides the following technical scheme:

[0010] A photovoltaic capacity configuration method based on output capacity demand, comprising the following steps:

[0011] Step 1, calculating the running power of the pumping station under different working conditions: based on the basic parameters of the pumping station, the running power under different combinations of the number of started pumps and different speeds is calculated, and the running power is arranged in ascending order to form a pumping station power list;

[0012] Step 2, obtaining photovoltaic output data: according to the annual output characteristics of regional photovoltaic power stations, a single time step is selected, the output coefficient of unit installed capacity corresponding to the time step is counted, and the annual photovoltaic power station output of each period is calculated by combining the photovoltaic installed capacity and the photovoltaic installed capacity;

[0013] Step 3, establishing an optimization decision model: a decision model with the maximum annual water supply as the target is constructed, which includes:

[0014] Objective function: maximize the total amount of water pumped by the system throughout the year;

[0015] Decision variable: photovoltaic power station installed capacity;

[0016] Constraint condition: including pump station power upper and lower limit constraint, water pump working station number range constraint, water pump speed safety range constraint, light rejection rate threshold constraint and variable non-negative constraint;

[0017] Step 4, calculating the annual water supply and light rejection rate under different photovoltaic capacities: input the pump station power list of step 1 and the photovoltaic power station output data corresponding to the time step selected in step 2 into the model, and iteratively calculate the annual water supply and the corresponding annual average light rejection rate under different installed capacities;

[0018] Step 5, screening feasible schemes: according to the preset upper limit of light rejection rate, screen the photovoltaic installed capacity and the corresponding annual water supply that meet the constraints;

[0019] Step 6, determining the optimal installed capacity: select the photovoltaic installed capacity corresponding to the maximum annual water supply from the feasible schemes of step 5 as the final configuration scheme.

[0020] In a preferred embodiment, the specific implementation of the objective function in step 3 is:

[0021] The system water pumping flow is determined by the photovoltaic installed capacity, the unit installed capacity output coefficient, the real-time output value and the light rejection rate;

[0022] The abandoned power output value does not exceed the difference between the total photovoltaic output and the minimum running power of the pump station;

[0023] The annual average light rejection rate is the ratio of total abandoned power to total power generation.

[0024] In a preferred embodiment, the constraint condition of step 3 includes:

[0025] The real-time power of the pump station is between the minimum running power and the maximum running power;

[0026] The number of water pump start-ups is within the range of single station to maximum working pump number;

[0027] The water pump speed is between the allowed minimum speed and the maximum speed;

[0028] The annual average light rejection rate does not exceed the set threshold.

[0029] In a preferred embodiment, the range of values of the photovoltaic installed capacity in step 4 is determined by the following method:

[0030] The minimum value is zero;

[0031] The maximum value is the maximum operating power of the pump station divided by the annual average output value of the photovoltaic unit capacity.

[0032] In a preferred embodiment, the upper limit value of the light rejection rate in step 5 does not exceed 10%.

[0033] In a preferred embodiment, the time step selection mechanism of step 2 is:

[0034] Provide a variety of time resolution options ranging from 1 / 60h to 1h;

[0035] Only one time step is actually used for calculation.

[0036] In a preferred embodiment, the pump station design parameters in step 1 include:

[0037] Net head 149.8 meters, single pump rated flow 0.34 cubic meters / second;

[0038] Rated head 158.0 meters, rated speed 1480 revolutions / minute;

[0039] Configure 4 centrifugal pumps, of which 3 are working and 1 is standby.

[0040] In a preferred embodiment, step 4 uses a fixed step increment method to traverse the photovoltaic installed capacity, with an increment step of 100 kilowatts.

[0041] The technical effects and advantages of the photovoltaic capacity configuration method based on output capacity demand:

[0042] The present application matches the "multiple variable speed" discrete power of the pump station with the photovoltaic output curve, constructs a capacity optimization model with the core of maximizing annual water supply and controlling annual average light rejection rate, fully releases the photovoltaic power generation potential, significantly improves the annual water supply, and stabilizes the light rejection rate within the policy upper limit, realizes the synchronous optimization of clean water supply, energy saving and emission reduction and investment economy, and because the algorithm parameters and scheduling rules are transparent and traceable, it is convenient for direct landing engineering design and operation practice. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 The flowchart of the photovoltaic capacity configuration method based on output capacity demand of the present application;

[0044] Figure 2This is a power ranking diagram of the pump station under different combinations of the number of units in operation and different pump speeds of the present invention;

[0045] Figure 3 This is a diagram of the hourly daily output coefficient of the photovoltaic power station of the present invention throughout the year;

[0046] Figure 4 This is a graph showing the annual water supply variation of the photovoltaic water pumping station system under different installed capacities of the photovoltaic power station of the present invention;

[0047] Figure 5 This is a graph showing the changes in the average annual abandonment rate of photovoltaic power stations under different installed capacity conditions of the photovoltaic power stations of the present invention. DETAILED DESCRIPTION

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0049] In this example, a water pumping station (installed 4 centrifugal pumps, 3 working and 1 standby, with a designed net head of 149.8m and a rated flow of 0.34m 3 / s, rated lift is 158.0m, rated speed is 1480r / min) as an example. Figure 1 As shown in FIG, a photovoltaic capacity configuration method based on output capacity demand is implemented in the following specific steps:

[0050] Step 1: Calculate the operating power of the water pump station under different operating conditions: Based on the basic parameters of the pump station, calculate the operating power of the water pump station under different operating pump numbers (1 to 3) and different speed conditions. The water pump station power can be obtained by using the pump station test curve based on the water pump flow-head characteristics and electrical efficiency. Arrange the water pump station power under each operating condition in ascending order (such as Figure 2 The power list obtained in step 1 provides the pump station load conditions for subsequent configuration calculations.

[0051] Step 2: Obtain photovoltaic output data: According to the annual output characteristics of the photovoltaic power stations built in the study area, select a single time step (take 1 / 60h, 1 / 12h, 1 / 6h, 1 / 4h, 1 / 3h, 1 / 2h, 1h, etc.), and calculate the unit installed capacity output coefficient (unit installed capacity output coefficient) corresponding to the time step (such as Figure 3 Multiply the output per unit installed capacity by the photovoltaic installed capacity to obtain the output of the photovoltaic power station in each time period of the year under different installed capacity conditions.

[0052] Step 3: Establishing the mathematical model of the capacity configuration of the photovoltaic water pumping station system: constructing a mathematical optimization model with the maximization of annual water supply as the objective. The mathematical model of the capacity configuration of the photovoltaic water pumping station system considering annual water supply is composed of an objective function, decision variables, and constraint conditions, and is specifically as follows:

[0053] a. Objective function

[0054] The mathematical model established in step 3 is a mathematical model with the maximization of the annual water supply of the photovoltaic water pumping station system as the objective.

[0055] Objective function F: maximization of the annual water supply of the photovoltaic water pumping station system. The specific form is as follows:

[0056] ;

[0057] ;

[0058] ;

[0059] ;

[0060] In the formula:

[0061] is the water pumping flow rate of the photovoltaic water pumping station system on the dth day and jth time period within a year, with the unit of m3 / s;

[0062] D is the total number of days in a year, with the unit of days;

[0063] J is the number of time periods according to the time step , the daily output process of the photovoltaic power station is divided into J time periods, where ;

[0064] is the minimum power of the water pumping station running at the start time, with the unit of kW;

[0065] is the relationship function between the output of the photovoltaic power station and the water pumping flow rate of the photovoltaic water pumping station system;

[0066] A is the installed capacity of the photovoltaic power station, with the unit of kW;

[0067] is the output of the photovoltaic power station A on the dth day and jth time period within a year, with the unit of kW;

[0068] is the output coefficient of the photovoltaic power station on the dth day and jth time period within a year under the installed capacity of the photovoltaic power station A;

[0069] is the annual average light rejection rate of the photovoltaic power station;

[0070] is the abandoned power output of photovoltaic power station A at the installed capacity of the whole year on the dth day and the jth period, in kW;

[0071] is the time step, in h.

[0072] b. Decision variables

[0073] Photovoltaic installed capacity of photovoltaic water pumping station system is the decision variable.

[0074] c. Constraints, which include five categories, as follows:

[0075] ①Power constraints of water pumping stations ;

[0076] ② Constraints on the number of water pumps in operation: ;

[0077] ③Pump speed constraint: ;

[0078] ④ Constraints on the average annual abandonment rate of photovoltaic power stations: ;

[0079] ⑤ Non-negative constraint: All the variables involved above are non-negative values.

[0080] Where:

[0081] The maximum power of the water pumping station when it is started, in kW;

[0082] is the power of the water pumping station at the dth day and the jth period of the whole year, in kW;

[0083] is the number of pumps in operation at the pumping station on the dth day and the jth period of the year, in units;

[0084] N is the difference between the total number of installed units and the number of standby units in the water pumping station, in units;

[0085] The pump speed of the water pumping station at the dth day and the jth period of the whole year, in r / min;

[0086] The minimum speed of the water pump in the water pumping station, in r / min;

[0087] The maximum speed of the water pump in the water pumping station, in r / min;

[0088] The upper limit value of the annual average light rejection rate of the photovoltaic power station.

[0089] Step 4: Calculate the annual water supply and light rejection rate under different photovoltaic capacities: combine the pump station power obtained in step 1 under different numbers of starting units and different water pump speeds with the daily output process of the photovoltaic power station obtained in step 2 under different installed capacities of the photovoltaic power station throughout the year as input variables of the mathematical model of the photovoltaic water pumping station system photovoltaic capacity configuration established in step 3 to obtain the annual water supply of the photovoltaic water pumping station system under different installed capacities of the photovoltaic power station (see Figure 4 ), and calculate the corresponding annual average light rejection rate of the photovoltaic power station (see Figure 5 ).

[0090] Among them, the daily output process of the photovoltaic power station under different installed capacities as input variables, the minimum value of the installed capacity of the photovoltaic power station is zero, the maximum value of the installed capacity of the photovoltaic power station is the ratio of the maximum power of the water pumping station running when the pump station starts to the annual average output per unit installed capacity of the photovoltaic power station, and the corresponding photovoltaic water pumping station system annual water supply under different installed capacities of the photovoltaic power station is obtained in an equivalent incremental manner, and the corresponding annual average light rejection rate of the photovoltaic power station is calculated. For example: the annual average output per unit installed capacity of the photovoltaic power station is 0.195kW, the maximum power of the water pumping station running when the pump station starts is 2123.662kW, so the maximum installed capacity of the photovoltaic power station is 10900kW.

[0091] Step 5: Select a scheme that meets the light rejection rate requirement: according to the annual water supply of the photovoltaic water pumping station system under different installed capacities of the photovoltaic power station and the annual average light rejection rate of the photovoltaic power station obtained in step 4, and the set upper limit value of the annual average light rejection rate of the photovoltaic power station, select the different installed capacities of the photovoltaic power station and the corresponding annual water supply of the photovoltaic water pumping station system that meet the upper limit value of the annual average light rejection rate of the photovoltaic power station (see Table 1).

[0092] Among them, the upper limit value of the annual average light rejection rate of the photovoltaic power station needs to be set according to local policy requirements or actual conditions. For example: The National Development and Reform Commission and the National Energy Administration recently issued the "Optimization of Power System Regulation Capacity Special Action Implementation Plan (2025-2027)", which proposes that the national new energy utilization rate will not be less than 90%. Therefore, 10% is selected as the upper limit value of the annual average light rejection rate of the photovoltaic power station.

[0093] Table 1 Annual water supply of photovoltaic water pumping station system under different installed capacities of photovoltaic power station and annual average light rejection rate of photovoltaic power station

[0094]

[0095] Step 6: Determine the optimal installed capacity: according to the upper limit value of the annual average light rejection rate of the photovoltaic power station obtained in step 5, the different installed capacities of the photovoltaic power station and the corresponding annual water supply of the photovoltaic water pumping station system are obtained, the maximum value of the annual water supply of the photovoltaic water pumping station system is selected, and the corresponding installed capacity of the photovoltaic power station is selected as the final photovoltaic water pumping station system photovoltaic power station installed capacity configuration scheme. For example: select 10% as the upper limit value of the annual average light rejection rate of the photovoltaic power station, and the maximum value of the annual water supply of the photovoltaic water pumping station system is 791.75 million m 3 The corresponding photovoltaic power station installed capacity is 2900kW, so the final photovoltaic water pumping station system photovoltaic power station installed capacity is 2900kW.

[0096] The above formulas are all dimensionless numerical calculations, and the formulas are obtained by software simulation of a large amount of data to obtain a formula of the latest real situation, and the preset parameters in the formula are set by a person skilled in the art according to the actual situation.

[0097] The above embodiments can be realized wholly or partially by software, hardware, firmware or any combination thereof. When realized by software, the above embodiments can be realized in the form of a computer program product wholly or partially.

[0098] Those skilled in the art can realize that the modules and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application of the technical solution and the constraints of the invention. A person skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0099] In addition, the functional modules in each embodiment of the present application can be integrated in one processing module, or each module can be physically present alone, or two or more modules can be integrated in one module.

[0100] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0101] Finally: the above is only a preferred embodiment of the present application, and is not used to limit the present application, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A photovoltaic capacity configuration method based on output capacity demand, characterized by, Comprising the following steps: Step 1, calculate the operating power of the pump station under different conditions: based on the basic parameters of the water pumping station, calculate the operating power under different combinations of the number of operating pumps and different rotating speeds, and arrange them in ascending order to form a pump station power list; Step 2, obtain photovoltaic output data: according to the annual output characteristics of regional photovoltaic power stations, select a single time step, calculate the unit installed capacity output coefficient corresponding to the time step, and calculate the annual photovoltaic power station output of each period combined with the photovoltaic installed capacity; Step 3, establish an optimization decision model: build a decision model with the maximum annual water supply as the target, which includes: Objective function: maximize the total water supply of the system in a year; Decision variable: photovoltaic power station installed capacity; Constraint conditions: including pump station power upper and lower limit constraint, water pump operating station number range constraint, water pump rotating speed safety range constraint, light rejection rate threshold constraint and variable non-negative constraint; Step 4, calculate the annual water supply and light rejection rate under different photovoltaic capacities: input the pump station power list of step 1 and the photovoltaic power station output data corresponding to the time step selected in step 2 into the model, and iteratively calculate the annual water supply and the corresponding annual average light rejection rate under different installed capacities; Step 5, screen feasible solutions: according to the preset upper limit of light rejection rate, screen the photovoltaic installed capacity and the corresponding annual water supply that meet the constraints; Step 6, determine the optimal installed capacity: select the photovoltaic installed capacity corresponding to the maximum annual water supply from the feasible solutions in step 5 as the final configuration scheme.

2. The photovoltaic capacity configuration method based on output capacity demand according to claim 1, wherein: The specific implementation method of the objective function in step 3 is: The system water pumping flow is determined by the photovoltaic installed capacity, the unit installed capacity output coefficient, the real-time output value and the light rejection rate; The abandoned power output value does not exceed the difference between the total photovoltaic output and the minimum operating power of the pump station; The annual average light rejection rate is the ratio of the total abandoned power to the total power generation.

3. The photovoltaic capacity configuration method based on output capacity demand according to claim 2, characterized in that: The constraint conditions of step 3 include: The real-time power of the pump station is between the minimum operating power and the maximum operating power; The number of water pump operating stations is within the range of single station to maximum working pump number; The rotating speed of the water pump is between the minimum and maximum rotating speeds allowed; The annual average light rejection rate does not exceed the set threshold.

4. The photovoltaic capacity configuration method based on output capacity demand according to claim 1, characterized in that ； The value range of the photovoltaic installed capacity in step 4 is determined by the following methods: The minimum value is zero; The maximum value is the maximum operating power of the pump station divided by the annual average output value of the unit capacity.

5. The photovoltaic capacity configuration method based on output capacity demand according to claim 1, wherein: The upper limit of light rejection rate in step 5 does not exceed 10%.

6. The photovoltaic capacity configuration method based on output capacity demand according to claim 1, characterized in that, The time step selection mechanism of step 2 is: Provide multiple time resolution options within the range of 1 / 60h to 1h; Only one time step is actually used for calculation.

7. The photovoltaic capacity configuration method based on output capacity demand according to claim 1, characterized in that, The pump station design parameters in step 1 include: Net head 149.8 meters, single pump rated flow 0.34 cubic meters / second; Rated head 158.0 meters, rated rotating speed 1480 revolutions / minute; Configure 4 centrifugal pumps, of which 3 are working and 1 is standby.

8. The photovoltaic capacity configuration method based on output capacity demand according to claim 1, characterized in that, Step 4 uses a fixed step increment method to traverse the photovoltaic installed capacity, and the increment step is 100 kilowatts.

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