Photovoltaic power station intelligent cleaning system based on cost calculation

Abstract

The invention relates to a photovoltaic power station intelligent cleaning system based on cost calculation. A photovoltaic datum plate and a photovoltaic plate of a photovoltaic power station are arranged in parallel; the cleaning device is used for cleaning the photovoltaic datum plate once every day; whether the photovoltaic panel needs to be cleaned or not can be accurately judged, a signal is sent out, and the benefit of a power station is expected to be maximized. The method is simple in structure, easy to implement and high in practicability, the cleaning frequency of the photovoltaic power station can be scientifically and accurately formulated through the algorithm, resource waste is avoided, cost is effectively saved, and benefits are maximized.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic technology, and in particular to an intelligent cleaning system for a photovoltaic power station based on cost calculation. Background Art

[0002] At present, the installed capacity of photovoltaic power stations is growing rapidly, and the problem of photovoltaic panel cleaning is gradually exposed. At present, there are several ways to clean photovoltaic power stations: one is manual cleaning, the second is manual semi-automatic cleaning, and the third is mechanical fully automatic cleaning. The three cleaning methods have their own advantages and disadvantages, but there is no unified standard for the cleaning cycle. How to accurately judge the cleaning cycle to obtain the maximum benefit has become a key issue. Cleaning too frequently costs too much and wastes resources. Cleaning is not timely enough, resulting in reduced power generation efficiency, which in turn affects the overall benefits of the power station.

[0003] Therefore, real-time monitoring of the loss of photovoltaic panels in power stations due to dirty agents and formulating reasonable cleaning strategies based on the loss and cleaning costs of photovoltaic panels in power stations are of great significance for the economic operation of large-scale photovoltaic power stations.

[0004] For example, the patent publication number CN115860256A discloses a “method for predicting the cleaning cycle of a large photovoltaic power station based on dust accumulation condition monitoring”. The mathematical model takes into account the situation in which the cleaned photovoltaic panels continue to accumulate dust during the entire cleaning process of the large photovoltaic power station. This model is more in line with the actual situation and can more accurately predict the optimal cleaning cycle, thus bringing the greatest economic benefits to the photovoltaic power station.

[0005] For example, the "A prediction method for the cleaning cycle of photovoltaic modules" disclosed in patent publication number CN117436837A can accurately predict the power generation efficiency over time based on the various working parameters of the power station, and takes into account parameters such as cleaning costs, power generation income and electricity losses. It can accurately simulate the change curve of economic losses over time, and can easily make accurate predictions for each photovoltaic power station, ensuring that the photovoltaic power station can maintain a high power generation efficiency under the most economically adaptable conditions.

[0006] However, the mathematical model structure in the prior art is complex, which makes it difficult to accurately evaluate the relationship between the efficiency loss and cleaning cost of the photovoltaic power station in actual application. It is difficult to ensure that the loss of power generation efficiency and the cost of cleaning can be effectively balanced in actual operation to maximize economic benefits. Summary of the invention

[0007] In view of the deficiencies of the prior art, the present invention provides a photovoltaic power station intelligent cleaning system based on cost calculation to solve the above problems.

[0008] The present invention provides the following technical solutions:

[0009] Intelligent cleaning system for photovoltaic power station based on cost calculation, comprising:

[0010] Photovoltaic reference panel, arranged in parallel with the photovoltaic panels of the photovoltaic power station;

[0011] Cleaning device, used to perform a cleaning operation on the photovoltaic reference panel once a day;

[0012] Judge once a day whether a cleaning alarm signal needs to be issued through the following steps:

[0013] The dirtiness rate k of the photovoltaic panels in the station = 1 - (total power of the photovoltaic power station / number of photovoltaic panels in the station) / photovoltaic reference panel;

[0014] Reduction value W1 of the daily income of the photovoltaic power station:

[0015] W1 =

(daily power generation of the photovoltaic power station * on-grid electricity price) / (1 - k)

[0016] W2 = total cost of cleaning the photovoltaic power station;

[0017] D = number of days of the nearest rain interval in the future weather forecast;

[0018] If W1 * D >= W2, then send a cleaning alarm signal; when W1 * D < W2, no cleaning alarm signal is sent.

[0019] Preferably, a cleaning operation is performed on the photovoltaic reference panel once a day before the photovoltaic power station is connected to the grid.

[0020] Preferably, the cleaning device adopts a water spraying structure.

[0021] Preferably, the algorithm determination is performed daily after the photovoltaic power station is disconnected from the grid.

[0022] Preferably, take the weather conversion coefficient L for the current day. When it is sunny, L = 100%, when it is cloudy, L = 50%, when it is overcast, L = 20%. The weather conversion coefficient for the kth day in the future is set as L k ;

[0023] Total reduction value of the income of the D days' weather before the rainy weather

[0024] If W0 > = W2, then send a cleaning alarm signal; when W0 < W2, no cleaning alarm signal is sent.

[0025] Preferably, a = 100%, b = 50%, c = 20%.

[0026] The present invention has the following beneficial technical effects:

[0027] The present invention can accurately judge whether the photovoltaic panels need to be cleaned and send a signal, so as to maximize the income of the power station.

[0028] The invention has a simple structure, is easy to implement, and has strong practicability. Through the algorithm, the cleaning frequency of the photovoltaic power station can be scientifically and accurately formulated, thereby avoiding waste of resources, effectively saving costs, and maximizing benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a relationship diagram between the full power generation income and the cleaning cost of the first embodiment of the present invention.

[0030] Figure 2 This is a relationship diagram between the full power generation income and the cleaning cost of the second embodiment of the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] Embodiment 1:

[0033] Intelligent cleaning system for photovoltaic power plants based on cost calculation:

[0034] A photovoltaic panel of the same model as the photovoltaic power station (hereinafter referred to as the photovoltaic reference panel) is selected and connected in parallel with other photovoltaic panels of the photovoltaic power station;

[0035] The cleaning device adopts a water spray structure, and is used for performing water spray cleaning operations on the photovoltaic reference panel.

[0036] Before the photovoltaic power station is connected to the grid every day, the photovoltaic reference panel is cleaned once. After the photovoltaic power station is connected to the grid, the photovoltaic power station operation data is collected to determine the operation efficiency. After the photovoltaic power station is disconnected every day, the algorithm determines and then outputs an alarm signal whether cleaning is needed.

[0037] The system operation algorithm is:

[0038] The dirtyness of the photovoltaic panels at the site k = 1-(total power of the photovoltaic power station / number of photovoltaic panels at the site) / photovoltaic reference panel.

[0039] Take W1 = [(the power generation of the photovoltaic power station on that day * the grid-connected electricity price) / (1-k)] * k = the reduction in the revenue of the photovoltaic power station on that day;

[0040] Take W2 = total cost of cleaning the PV power station;

[0041] Take D = the number of days between the next rainy days as predicted by the weather forecast.

[0042] If W1*D >= W2, a cleaning alarm signal is sent; when W1*D < W2, no cleaning alarm signal is sent.

[0043] As Figure 1 shown: Assume that the full-day power generation income of a photovoltaic power station on the current day is 1000 yuan, and the cost required to clean the photovoltaic power station is 400 yuan. The corresponding relationship between the dirtiness rate k of the photovoltaic panels in the station and the number of days D until the nearest rain in the weather forecast for triggering the alarm signal is as Figure 1 shown.

[0044] Embodiment 2:

[0045] It includes all the content of Embodiment 1, and the difference is:

[0046] Since the income of a photovoltaic power station is greatly affected by weather factors, when calculating the reduction value of the future income of the photovoltaic power station, it is necessary to correct the income according to the weather.

[0047] Take L as the weather conversion coefficient. When it is sunny, L = 100%; when it is cloudy, L = 50%; when it is overcast, L = 20%. Obtain the future weather conditions according to the weather forecast. The weather conversion coefficient on the kth day in the future is set as L k , where L = L1.

[0048] W1 / L is to correct the income according to the weather.

[0049] According to the weather conditions in the next few days, taking the nearest rainy weather as the node, obtain the total reduction value W0 of the income converted by the weather in the D days before the rainy weather:

[0050]

[0051] The determination algorithm is that if W0 >= W2, a cleaning alarm signal is sent; when W0 < W2, no cleaning alarm signal is sent. As Figure 2 shown is a relationship diagram of the full-day power generation income and the cleaning cost using Embodiment 2.

[0052] The above-described embodiments only represent the specific implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several deformations and improvements can still be made, and these all belong to the protection scope of the present invention.

Claims

1. The photovoltaic power station intelligent cleaning system based on cost calculation is characterized by: Including: A photovoltaic reference panel, which is connected in parallel with the photovoltaic panels of the photovoltaic power station; A cleaning device for performing a cleaning operation on the photovoltaic reference panel once a day; Judging once a day whether a cleaning alarm signal needs to be sent through the following steps: The dirtiness rate k of the photovoltaic panels at the station = 1 - (total power of the photovoltaic power station / number of photovoltaic panels at the station) / photovoltaic reference panel; The reduced value W1 of the daily income of the photovoltaic power station: W1 = 【(daily power generation of the photovoltaic power station * on-grid electricity price) / (1 - k)】 * k; W2 = total cost of cleaning the photovoltaic power station; D = the number of days of the nearest rain interval in the future weather forecast; If W1 * D >= W2, a cleaning alarm signal is sent. When W1 * D < W2, no cleaning alarm signal is sent.

2. The photovoltaic power station intelligent cleaning system based on cost calculation according to claim 1 is characterized in that: Perform a cleaning operation on the photovoltaic reference panel once a day before the photovoltaic power station is connected to the grid.

3. The photovoltaic power station intelligent cleaning system based on cost calculation according to claim 1 is characterized in that: The cleaning device adopts a water spray structure.

4. The photovoltaic power station intelligent cleaning system based on cost calculation according to claim 1 is characterized in that: Perform algorithm determination after the photovoltaic power station is disconnected from the grid every day.

5. The photovoltaic power station intelligent cleaning system based on cost calculation according to claim 1, characterized in that: Take the weather conversion coefficient of the day L, when it is sunny L = a, when it is cloudy b, when it is overcast L = c, and the weather conversion coefficient of the kth day in the future is L k ; The total benefit reduction of the D-day weather before the rainy weather If W0 > = W2, a cleaning alarm signal is sent. When W0 < W2, no cleaning alarm signal is sent.

6. The photovoltaic power station intelligent cleaning system based on cost calculation according to claim 5 is characterized in that: a = 100%, b = 50%, c = 20%.

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