Cost calculation-based intelligent cleaning system for photovoltaic power station

Abstract

The present invention relates to a cost calculation-based intelligent cleaning system for a photovoltaic power station. A photovoltaic reference panel is connected in parallel to a photovoltaic panel of the photovoltaic power station; a cleaning device is configured to perform a cleaning operation on the photovoltaic reference panel once per day. In the present invention, whether a photovoltaic panel requires cleaning can be accurately determined and a signal is issued, thereby maximizing the economic benefits of power stations. The present invention has a simple structure, is easy to implement, and has strong practicability; by means of the algorithm, the cleaning frequency of photovoltaic power stations can be scientifically and accurately determined, thereby avoiding resource waste and effectively reducing costs, and maximizing economic benefits.

Description

Cost-based intelligent cleaning system for photovoltaic power plants Technical Field

[0001] This invention relates to the field of photovoltaic technology, specifically to a cost-based intelligent cleaning system for photovoltaic power plants. Background Technology

[0002] With the rapid growth of installed photovoltaic (PV) power plant capacity, the issue of PV panel cleaning has gradually become apparent. Currently, there are several cleaning methods for PV power plants: manual cleaning, semi-automatic manual cleaning, and fully automatic mechanical cleaning. Each method has its advantages and disadvantages, but there is no unified standard for the cleaning cycle. Accurately determining the cleaning cycle to maximize benefits has become a key issue. Cleaning too frequently incurs excessive costs and wastes resources. Insufficient cleaning leads to reduced power generation efficiency, which in turn affects the overall profitability of the power plant.

[0003] Therefore, real-time monitoring of the damage to photovoltaic panels caused by dirt and grime, and the development of reasonable cleaning strategies based on the damage and cleaning costs of the photovoltaic panels, are of great significance for the economical operation of large-scale photovoltaic power plants.

[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 monitoring". The mathematical model that considers the situation where the photovoltaic panels that have been cleaned continue to accumulate dust during the entire cleaning process of a large photovoltaic power station is more in line with the actual situation. Therefore, it can more accurately predict the optimal cleaning cycle and bring the maximum economic benefits to the photovoltaic power station.

[0005] For example, the patent publication number CN117436837A discloses "A method for predicting the cleaning cycle of photovoltaic modules", which can accurately predict the power generation efficiency over time based on various operating parameters of the power station. It also considers parameters such as cleaning costs, power generation revenue, and power loss, and accurately simulates the change curve of economic losses over time. It can easily make accurate predictions for each photovoltaic power station, ensuring that the photovoltaic power station can maintain high power generation efficiency under the most economically suitable conditions.

[0006] However, the complex mathematical models in existing technologies make it difficult to accurately assess the relationship between the efficiency loss of photovoltaic power plants and the cleaning cost in practical applications. This makes it challenging to ensure an effective balance between the loss of power generation efficiency and the cost of a single cleaning cycle in actual operation, thereby maximizing economic benefits. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides a cost-based intelligent cleaning system for photovoltaic power plants to solve the aforementioned problems.

[0008] This invention provides the following technical solution:

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

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

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

[0012] Judge once a day whether it is necessary to send a cleaning alarm signal through the following steps:

[0013] 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;

[0014] The 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 = the 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, then do not send a cleaning alarm signal.

[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 daily L as the weather conversion coefficient. When it is sunny, L = 100%; when it is cloudy, L = 50%; when it is overcast, L = 20%. The weather conversion coefficient of the kth day in the future is set as L k ;

[0023] The total reduction value of the income of the D-day weather before the rainy weather

[0024] If W0 > = W2, then send a cleaning alarm signal; when W0 < W2, then do not send a cleaning alarm signal.

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

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

[0027] This invention can accurately determine whether photovoltaic panels need cleaning and send a signal in order to maximize the benefits of the power plant.

[0028] This invention has a simple structure, is easy to implement, and is highly practical. Through this algorithm, the cleaning frequency of photovoltaic power plants can be scientifically and accurately determined, avoiding resource waste, effectively saving costs, and maximizing benefits. Attached Figure Description

[0029] Figure 1 is a graph showing the relationship between the total power generation revenue and the cleaning cost in Embodiments 1 and 2 of the present invention.

[0030] Figure 1 is a graph showing the relationship between the total power generation revenue and the cleaning cost in Embodiment 2 of the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] Example 1:

[0033] Cost-based intelligent clean photovoltaic power plant system:

[0034] Select a photovoltaic panel of the same model as the photovoltaic power station (hereinafter referred to as the photovoltaic reference panel) and connect it in parallel with the other photovoltaic panels in the photovoltaic power station;

[0035] The cleaning device adopts a water spray structure and is used to perform water spray cleaning operations on photovoltaic reference panels.

[0036] Before the photovoltaic power station is connected to the grid each day, the photovoltaic reference panels are cleaned once. After the photovoltaic power station is connected to the grid, the operating data of the photovoltaic power station is collected to determine the operating efficiency. After the photovoltaic power station is disconnected from the grid each day, the algorithm determines whether cleaning is required and outputs an alarm signal.

[0037] The system operating algorithm is as follows:

[0038] The amount of dirt on the photovoltaic panels at the power station is k = 1 - (total power of the photovoltaic power station / number of photovoltaic panels at the power station) / photovoltaic reference panel.

[0039] Take W1 = [(Daily photovoltaic power plant power generation * grid connection price) / (1 - k)] * k = Daily reduction in photovoltaic power plant revenue;

[0040] Let W2 = the total cost of cleaning the photovoltaic power station;

[0041] Let D = the number of days until the next rainy day in 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 shown in Figure 1: Assume that the full-power generation income of the 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 at the station and the number of days D until the nearest rain in the future weather forecast for triggering the alarm signal is shown in Figure 1.

[0044] Embodiment 2:

[0045] It includes all the content of Embodiment 1, with the difference that:

[0046] Since the income of the photovoltaic power station is greatly affected by weather factors, when calculating the future income reduction value 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 a node, obtain the total income reduction value W0 of the weather conversion in the D days before the rainy weather:

[0050] The determination algorithm is that when W0 >= W2, a cleaning alarm signal is sent; when W0 < W2, no cleaning alarm signal is sent. As shown in Figure 2 is a relationship diagram of the full-power generation income and the cleaning cost using Embodiment 2.

[0051] The above-described embodiments only represent the specific implementation manners of the present invention. Their descriptions are relatively specific and detailed, but they should not be construed as limiting 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 modifications and improvements can still be made, and these all belong to the protection scope of the present invention.

Claims

1. A cost-based intelligent cleaning system for photovoltaic power plants, characterized in that, Comprising: A photovoltaic reference panel, which is arranged in parallel with the photovoltaic panels of a photovoltaic power station; A cleaning device, which is used to perform 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, then send a cleaning alarm signal, and if W1 * D < W2, then do not send a cleaning alarm signal.

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

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

5. The intelligent clean photovoltaic power station system based on cost calculation according to claim 1, characterized in that, Let L be the weather conversion factor for the current day: L = a for sunny days, b for cloudy days, and c for overcast days. Let L be the weather conversion factor for the kth future day. k ; The total reduction in revenue on day D before the rainy weather. If W0 >= W2, then send a cleaning alarm signal, and if W0 < W2, then do not send a cleaning alarm signal.

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

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