High-resolution site selection method for floating photovoltaic systems

Abstract

This disclosure provides a high-resolution site selection method for floating photovoltaic systems, which can be applied to the field of power system technology. The method includes: acquiring natural data for each region; selecting suitable target regions for deploying floating photovoltaic power generation by analyzing the natural data; calculating whether there is a power gap in the target region based on the power demand data and existing power generation of each target region; calculating the cost required to construct a floating photovoltaic power station under different simulation scenarios based on an objective function when there is a power gap in the target region; and determining the optimal strategy for constructing a floating photovoltaic power station in the target region based on the calculation results.

Description

Technical Field

[0001] This disclosure relates to the field of power system technology, and more specifically, to a high-resolution site selection method for floating photovoltaic systems. Background Technology

[0002] The emergence of floating solar PV offers a viable solution to the growing demand for solar PV construction and the constraints of land availability. Floating solar PV deployments are typically located in open water, thus not requiring land resources. Furthermore, compared to traditional terrestrial solar PV, floating solar PV offers better power generation efficiency. Therefore, promoting the construction of floating solar PV is of great significance to the development of the solar PV industry and helps accelerate the achievement of the "dual carbon" goal.

[0003] Currently, the site selection method for floating photovoltaic (PV) systems primarily uses deployment area as the main criterion, often neglecting factors such as solar radiation intensity, water level changes, and freezing periods. Furthermore, it lacks consideration of construction and grid connection benefits in floating PV projects. These issues lead to inaccurate site selection decisions, resulting in resource duplication and waste. Previous assessment methods are often highly subjective, lacking unified and scientific assessment standards and models, which easily leads to inaccurate site selection. Summary of the Invention

[0004] (a) Technical problems to be solved

[0005] This disclosure provides a high-resolution site selection method for floating photovoltaic systems, which at least partially solves one of the aforementioned technical problems.

[0006] (II) Technical Solution

[0007] According to a first aspect of this disclosure, a high-resolution site selection method for floating photovoltaic power generation is provided. The method includes: acquiring natural data for each region; selecting a suitable target region for deploying floating photovoltaic power generation by analyzing the natural data; calculating whether there is a power shortage in the target region based on the power demand data and existing power generation of each target region; calculating the cost required to construct a floating photovoltaic power station under different simulation scenarios based on an objective function when there is a power shortage in the target region; and determining the optimal strategy for constructing a floating photovoltaic power station in the target region based on the calculation results.

[0008] According to embodiments of this disclosure, natural data includes vector data of lakes and reservoirs, solar radiation data, wind speed and surface temperature data.

[0009] According to embodiments of this disclosure, selecting a suitable target area for floating photovoltaic power generation by analyzing natural data includes: obtaining historical changes of various lakes and reservoirs based on vector data; determining a first relationship between the vector data and the historical changes and a preset threshold; and determining the area as the target area if the first relationship satisfies a first condition.

[0010] According to embodiments of this disclosure, calculating whether there is a power shortage in a target area based on the power demand data and existing power generation of each target area includes: obtaining data on fixed power generation facilities in the target area; calculating the existing power generation of the target area based on the fixed power generation facility data; and comparing the existing power generation of the target area with the power demand data to determine the power shortage situation in the target area.

[0011] According to embodiments of this disclosure, when there is a power shortage in the target area, the cost required to construct a floating photovoltaic power station under different simulation scenarios is calculated based on an objective function. This includes: obtaining the deployment plan of the floating photovoltaic power station under each simulation scenario, wherein the deployment plan includes at least grid connection status, transmission line status, and power storage plan; and calculating the cost required to construct the floating photovoltaic power station under the deployment plan based on the objective function.

[0012] According to embodiments of this disclosure, the expression for the objective function is:

[0013] f = ∑CI + ∑PT + ∑FT + ∑TT + ∑CS + ∑VC + ∑TC + ∑CR + c

[0014] Where CI is the annualized cost of power plant installation; PT is the annualized cost of inter-provincial transmission; FT is the annualized cost of branch line transmission; TT is the annualized cost of trunk line transmission; CS is the annualized cost of power storage; VC is the annual total variable cost of generator operation; TC is the annual total cost of generator operation; CR is the annual total cost of reserve generation layer; and c is a fixed number representing the company's annual total capital cost and the variable cost at a certain time for generators.

[0015] According to embodiments of this disclosure, the method further includes: after determining the optimal strategy for constructing a floating photovoltaic power station in a target area, calculating the potential power generation of the floating photovoltaic power station deployed according to the optimal strategy; determining whether there is a power shortage in the target area based on the potential power generation; and, if there is a power shortage in the target area, using other power generation methods to make up for the power shortage.

[0016] According to embodiments of this disclosure, calculating the potential power generation of a floating photovoltaic power station deployed according to an optimal strategy includes: collecting spatial location data of lakes and reservoirs in a target area; and determining the potential power generation of the floating photovoltaic power station based on the spatial location data and solar radiation data.

[0017] According to embodiments of this disclosure, determining the potential power generation of a floating photovoltaic power station based on spatial location data and solar radiation data includes: calculating the zenith angle of the location and the area of ​​deployable floating photovoltaic panels based on the latitude, longitude, and area of ​​the lake and reservoir, respectively; calculating the total solar radiation intensity based on the zenith angle and solar radiation data; and determining the potential power generation of the floating photovoltaic power station based on the total solar radiation intensity and the area of ​​deployable floating photovoltaic panels.

[0018] According to embodiments of this disclosure, other power generation methods include any one of terrestrial photovoltaic power generation, wind power generation, hydropower generation, and surplus thermal power generation.

[0019] (III) Beneficial Effects

[0020] The high-resolution site selection method for floating photovoltaic systems disclosed herein has at least the following advantages:

[0021] By acquiring natural data from various regions, suitable target areas for floating photovoltaic (PV) power plants can be precisely located. Considering both the power generation potential and economic benefits of floating PV, decision-makers can receive clear and intuitive site selection recommendations, facilitating the rapid and scientific planning and rational layout of floating PV power plants. The site selection optimization process also considers the construction, operation, and grid connection costs of floating PV power plants, thereby accurately selecting the most suitable areas for their construction and effectively improving the accuracy and reliability of site selection. Attached Figure Description

[0022] The above and other objects, features and advantages of this disclosure will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0023] Figure 1 A flowchart illustrating a high-resolution site selection method for floating photovoltaic systems according to embodiments of the present disclosure is shown schematically.

[0024] Figure 2 A conceptual diagram illustrating a floating photovoltaic system for compensating for power shortages, as shown in an embodiment of this disclosure, is presented schematically.

[0025] Figure 3 A schematic diagram illustrating the potential power generation of a floating photovoltaic system according to an embodiment of the present disclosure is shown. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this disclosure clearer, the following detailed description is provided in conjunction with specific embodiments and accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without inventive effort are within the scope of protection of this disclosure.

[0027] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0028] In this disclosure, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection, an electrical connection, or a connection that allows communication between them; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this disclosure according to the specific circumstances.

[0029] In the description of this disclosure, it should be understood that the terms "longitudinal", "length", "circumferential", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this disclosure and simplifying the description, and do not indicate or imply that the subsystem or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this disclosure.

[0030] Throughout the accompanying drawings, identical elements are represented by the same or similar reference numerals. Conventional structures or constructions have been omitted where they may cause confusion in understanding this disclosure. Furthermore, the shapes, dimensions, and positional relationships of the components in the drawings do not reflect actual size, scale, or actual positional relationships. Additionally, any reference numerals placed between parentheses in the claims should not be construed as limiting the claims.

[0031] Similarly, to simplify this disclosure and aid in understanding one or more of the various aspects of the disclosure, in the above description of exemplary embodiments of the present disclosure, various features of the present disclosure are sometimes grouped together in a single embodiment, figure, or description thereof. The use of terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refers to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the present disclosure. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0032] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this disclosure, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0033] This disclosure provides a high-resolution site selection method for floating photovoltaic power generation, including: acquiring natural data for each region; selecting suitable target regions for deploying floating photovoltaic power generation by analyzing the natural data; calculating whether there is a power shortage in each target region based on the power demand data and existing power generation; calculating the cost required to construct a floating photovoltaic power station under different simulation scenarios based on an objective function when there is a power shortage in the target region; and determining the optimal strategy for constructing a floating photovoltaic power station in the target region based on the calculation results.

[0034] Figure 1 A flowchart illustrating a high-resolution site selection method for floating photovoltaic systems according to an embodiment of the present disclosure is shown schematically.

[0035] like Figure 1 As shown, the power system optimization method based on biomass energy power generation facility site selection in this embodiment includes operations S110 to S150.

[0036] Operation S110 acquires natural data for each region.

[0037] In some embodiments, the required natural data can be obtained from open-source websites (such as geospatial data platforms, resource and environmental data platforms, etc.). Natural data may include topographic features, vector data of lakes and reservoirs (including latitude and longitude data, water area, etc. for each lake and reservoir), solar radiation data, wind speed and surface temperature data, etc.

[0038] In operation S120, target areas suitable for deploying floating photovoltaic power generation are selected by analyzing natural data.

[0039] In some embodiments, the acquired natural data is cleaned and organized, and the cleaned and organized natural data is analyzed to select a suitable target area for deploying floating photovoltaic power generation.

[0040] Detailed information about each lake and reservoir is obtained using vector data, and the historical changes of each lake / reservoir are determined based on this detailed information. This detailed information can be time-series data, including changes in the lake / reservoir's area, shape, location, and other attributes at different points in time. Through detailed analysis of the lakes / reservoirs, their historical changes are obtained, including data on annual ice cover periods, water area, and seasonal water volume variations.

[0041] The historical changes and water area of ​​the lake / reservoir are compared with preset thresholds to obtain the first relationship between the historical changes / water area and the preset conditions. Based on the first conditions, the first relationship is filtered, and the areas where the lakes / reservoirs whose first relationship meets the first conditions are identified as target areas.

[0042] Preset thresholds may include, for example, a first threshold corresponding to the annual freezing period, a second threshold corresponding to the water area, and a third threshold corresponding to seasonal water volume changes. Each preset threshold is compared with the historical changes and water area of ​​the lake / water body to obtain a first relationship (i.e., the relationship between the historical changes and water area of ​​the lake / water body and the preset threshold). When all the first relationships corresponding to the preset thresholds satisfy a first condition, the area where the lake / water body is located is determined as the target area. The first condition is: the annual freezing period of the lake / water body is less than the first threshold, the water area is greater than the second threshold, and the seasonal water volume change is less than the third threshold. When the lake / reservoir meets the first condition, it indicates that the lake / reservoir is suitable for power generation, and the area where the lake / reservoir is located is the target area.

[0043] In operation S130, the existence of a power shortage in each target area is calculated based on the power demand data and existing power generation of each target area.

[0044] In some embodiments, the electricity demand of the target area can be obtained through historical data analysis or predictive models, and data on stationary power generation facilities in the target area can be acquired. Based on this data, the current power generation capacity of the target area can be calculated. The current power generation capacity of the target area is then compared with the electricity demand data to determine the electricity gap in the target area.

[0045] Figure 2A conceptual diagram illustrating a floating photovoltaic system for compensating for power shortages is shown in an embodiment of this disclosure.

[0046] like Figure 2 As shown, stationary power generation facilities may include, for example, nuclear power, bioenergy carbon capture and storage (CFS), and coal-fired combined heat and power plants with CFS technology. Power gap data is determined using power generation data from stationary power generation facilities and electricity demand data from the target area.

[0047] In operation S140, given the existence of a power shortage in the target area, the cost required to construct a floating photovoltaic power station under different simulation scenarios is calculated based on the objective function.

[0048] In some embodiments, if a power shortage exists in the target area, floating photovoltaic (PV) power stations can be deployed in that area to compensate for the power gap left by the fixed power generation layer. Considering different natural factors such as sunlight conditions, water temperature, wind speed, and water level changes, as well as the installation and operation and maintenance costs of floating PV power stations, multiple simulation scenarios are set up. The deployment plans for floating PV power stations differ under different simulation scenarios, and each simulation scenario includes a deployment plan for at least one floating PV power station. The deployment plan includes at least the construction status, grid connection status, transmission line status, and power storage plan for the floating PV power station. The cost required to construct a floating PV power station under each deployment plan is calculated based on an objective function.

[0049] The costs of constructing a floating photovoltaic (PV) power plant include construction, transportation, and storage costs. The objective function encompasses the power generation cost of the floating PV system, grid connection costs for newly deployed power plants, inter-provincial transmission line costs, fuel costs outside of necessary operating time, changes in fixed capacity costs, reserve capacity costs, and electricity storage costs. Based on the function results, potential locations with lower total costs for floating PV power plant construction and grid connection can be prioritized. The expression for the objective function is:

[0050] f = ∑CI + ∑PT + ∑FT + ∑TT + ∑CS + ∑VC + ∑TC + ∑CR + c

[0051] Where f is the cost required to construct a floating photovoltaic power station, CI is the annualized cost of power station installation; PT is the annualized cost of inter-provincial transmission; FT is the annualized cost of branch line transmission; TT is the annualized cost of trunk line transmission; CS is the annualized cost of power storage; VC is the total annual variable cost of generator operation; TC is the total annual cost of generator operation; CR is the total annual cost of the power generation reserve layer; and c is a fixed number representing the company's total annual capital cost and variable cost over time for generators.

[0052] In practice, the construction cost, power generation cost, energy storage cost, and levelized cost of electricity (LCOE) of each floating photovoltaic (PV) power station can be estimated based on the capacity factor and response cost of each PV unit. Construction, operation, and maintenance costs are crucial parameters for calculating the LCOE. However, with technological advancements, the LCOE of PV power generation is expected to continue decreasing, thus the LCOE will also be subject to continuous change.

[0053] Power transmission costs primarily include transmission costs between different regions (e.g., between provinces), trunk line transmission costs, and branch line transmission costs. In practical applications, many floating photovoltaic (PV) systems may be located in remote areas far from load centers, requiring the transmission of electricity from the PV power plant to the nearest substation via branch lines, and then the substation's electricity to the main nodes via trunk lines. Therefore, when calculating transmission costs, it is necessary to calculate the costs of transmitting electricity via both branch lines and trunk lines.

[0054] Load centers and key nodes are geographically related, typically with prefecture-level cities or above designated as load centers, and provincial capitals or major regional cities designated as key nodes at a higher level. In the deployment plan of the simulated scenario, each photovoltaic power station can be assigned to the nearest load center, and then the load center can be matched to the key node at the provincial level to ensure that the overall transmission distance from the floating photovoltaic power station to the key node is minimized.

[0055] The construction costs of branch lines and trunk lines are calculated based on the required transmission capacity, and these costs are incorporated into the objective function of the optimization model. For branch lines connecting batteries and substations, their capacity can be obtained by multiplying the total selected capacity of that unit by the battery's maximum hourly capacity factor. For trunk lines connecting substations and main nodes, their capacity depends on the peak output of the total capacity of all units connected to that substation.

[0056] In operation S150, the optimal strategy for constructing a floating photovoltaic power station in the target area is determined based on the calculation results.

[0057] In some embodiments, the optimal strategy for deploying floating photovoltaic power plants is determined based on the calculation results of the objective function, thereby achieving high-resolution site selection for floating photovoltaic power plants. Floating photovoltaic power plants deployed based on the optimal strategy exhibit beneficial performance in terms of both power generation potential and economic benefits, and can provide a valid reference for the construction of floating photovoltaic power plants in practical scenarios.

[0058] The high-resolution site selection method for floating photovoltaic systems provided in this disclosure may further include operations S160 to S180.

[0059] In operation S160, after determining the optimal strategy for constructing a floating photovoltaic power station in the target area, the potential power generation of the floating photovoltaic power station deployed according to the optimal strategy is calculated.

[0060] In operation S170, it is determined whether there is a power shortage in the target area based on the potential power generation.

[0061] When operating S180, if there is a power shortage in the target area, other power generation methods are used to make up for the power shortage.

[0062] In some embodiments, after determining the optimal strategy for floating photovoltaic power stations in a target area, the potential power generation of the floating photovoltaic power stations under the simulated scenario can be further calculated to determine whether there is a power gap in the target area.

[0063] In the specific implementation process, calculating the potential power generation of a floating photovoltaic power station includes: collecting spatial location data of lakes and reservoirs in the target area; and determining the potential power generation of the floating photovoltaic power station based on the spatial location data and solar radiation data.

[0064] Figure 3 A schematic diagram illustrating the potential power generation of a floating photovoltaic system according to an embodiment of the present disclosure is shown.

[0065] like Figure 3 As shown, for example, Python software can be used to extract spatial location data of lakes and reservoirs (e.g., including the latitude, longitude, and area of ​​the lakes and reservoirs) and solar radiation data. The solar radiation data includes direct solar radiation data and diffuse solar radiation data. The zenith angle of the location is calculated based on the latitude and longitude of the lake / reservoir, and the area where floating photovoltaic panels can be deployed is calculated based on the area of ​​the lake / reservoir. The total solar radiation intensity (GHI) is calculated using the solar zenith angle, direct solar radiation data, and diffuse solar radiation data. The formula for calculating the total solar radiation intensity is:

[0066] GHI = DHI + DNI * cosθ

[0067] Where DHI represents direct solar radiation data, DNI represents diffuse solar radiation data, and θ represents the solar zenith angle.

[0068] After obtaining the total solar radiation intensity, the potential power generation (Power) of the floating photovoltaic power station is determined based on the total solar radiation intensity and the area of ​​deployable floating photovoltaic panels. The expression for the potential power generation (Power) is:

[0069] Power = GHI * Area * Component Conversion Rate * Overall Conversion Efficiency

[0070] Among them, area refers to the area of ​​photovoltaic panels deployed, module conversion rate is the efficiency of converting solar radiation into electrical energy, and comprehensive conversion rate is the overall output efficiency.

[0071] Based on the potential power generation of floating photovoltaic power plants, it can be determined whether there is a power gap in the target area. If a power gap exists, other power generation methods can be used to make up for it. These other power generation methods may include, for example, terrestrial photovoltaic power generation, wind power generation, hydropower generation, and surplus thermal power generation. When making up for the power gap, the power gap can be made up in the order preset in the power concept model.

[0072] The conceptual model of electricity is shown in Table 1:

[0073]

[0074] In the power concept model, nuclear energy, carbon capture and storage (CCS) of bioenergy, and coal-fired power plants with CCS technology are designated as the first layer, the stationary generation layer, where electricity generated will be prioritized. However, the power generation in this layer cannot meet the electricity demand of most regions. Therefore, other power generation methods are used to compensate for the power gap left by the stationary generation layer. Floating photovoltaic (PV) systems are placed in the second layer of the model, also known as the variable energy generation layer, to fill the power gap left by the stationary generation layer. The potential power generation of floating PV systems is calculated using the optimal deployment strategy and integrated into the overall grid, while the remaining power gap is calculated. Subsequently, the power generation from the third, fourth, and fifth layers of the model is used to fill the power gap data after grid connection calculations in the previous layer. Finally, the remaining power gap is entirely filled by thermal power generation in the fifth layer.

[0075] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Without departing from the scope of this disclosure, those skilled in the art can make various substitutions and modifications, all of which should be included within the protection scope of this disclosure.

Claims

1. A high-resolution site selection method for floating photovoltaic systems, characterized in that, The method includes: Acquire natural data for each region; the natural data includes vector data of lakes and reservoirs, solar radiation data, wind speed and surface temperature data; By analyzing the aforementioned natural data, suitable target areas for deploying floating photovoltaic power generation are selected; Based on the electricity demand data and existing power generation of each target area, calculate whether there is a power shortage in the target area; Given the existence of a power shortage in the target area, the cost required to construct a floating photovoltaic power station under different simulation scenarios is calculated based on the objective function. The optimal strategy for constructing a floating photovoltaic power station in the target area was determined based on the calculation results. The step of selecting a suitable target area for floating photovoltaic power generation by analyzing the natural data includes: obtaining historical changes of each lake and reservoir based on the vector data; determining a first relationship between the vector data, the historical changes, and preset thresholds; and determining the area as the target area when the first relationship satisfies a first condition. The historical changes include annual freezing period data, water area, and seasonal water volume change data. The preset thresholds include a first threshold corresponding to the annual freezing period, a second threshold corresponding to the water area, and a third threshold corresponding to the seasonal water volume change. The first relationship reflects the historical changes of the lake / water area and the relationship between the water area and the preset thresholds. The first condition includes: the annual freezing period of the lake / water area is less than the first threshold, the water area is greater than the second threshold, and the seasonal water volume change is less than the third threshold. The expression for the objective function is: f=∑CI+∑PT+∑FT+∑TT+∑CS+∑VC+∑TC+∑CR+c Where CI is the annualized cost of power plant installation; PT is the annualized cost of inter-provincial transmission; FT is the annualized cost of branch line transmission; TT is the annualized cost of trunk line transmission; CS is the annualized cost of power storage; VC is the annual total variable cost of generator operation; TC is the annual total cost of generator operation; CR is the annual total cost of reserve generation layer; and c is a fixed number representing the company's annual total capital cost and the variable cost at a certain time for generators.

2. The high-resolution site selection method for floating photovoltaic systems according to claim 1, characterized in that, The step of calculating whether there is a power shortage in each target area based on the power demand data and existing power generation data of each target area includes: Acquire data on fixed power generation facilities in the target area; Calculate the current power generation capacity of the target area based on the data from the fixed power generation facilities; The existing power generation in the target area is compared with the power demand data to determine the power shortage situation in the target area.

3. The high-resolution site selection method for floating photovoltaic systems according to claim 1, characterized in that, In the case of a power shortage in the target area, the cost required to construct a floating photovoltaic power station under different simulation scenarios is calculated based on the objective function, including: Obtain the deployment plan of the floating photovoltaic power station under each simulated scenario, wherein the deployment plan includes grid connection status, transmission line status and power storage plan; The cost required to construct a floating photovoltaic power station under this deployment plan is calculated based on the objective function.

4. The high-resolution site selection method for floating photovoltaic systems according to claim 1, characterized in that, The method further includes: After determining the optimal strategy for constructing a floating photovoltaic power station in the target area, the potential power generation of the floating photovoltaic power station deployed according to the optimal strategy is calculated. Determine whether there is a power shortage in the target area based on the potential power generation; In the event of a power shortage in the target area, other power generation methods will be used to make up for the power shortage.

5. The high-resolution site selection method for floating photovoltaic systems according to claim 4, characterized in that, The calculation of the potential power generation of a floating photovoltaic power station deployed according to the optimal strategy includes: Collect spatial location data of lakes and reservoirs in the target area; The potential power generation of the floating photovoltaic power station is determined based on the spatial location data and the solar radiation data.

6. The high-resolution site selection method for floating photovoltaic systems according to claim 5, characterized in that, Determining the potential power generation of the floating photovoltaic power station based on the spatial location data and the solar radiation data includes: Calculate the zenith angle and the area where floating photovoltaic panels can be deployed at the location based on the latitude, longitude, and area of ​​the lake and reservoir, respectively. Calculate the total solar radiation intensity based on the zenith angle and the solar radiation data; The potential power generation of the floating photovoltaic power station is determined based on the total solar radiation intensity and the area of ​​the deployable floating photovoltaic panels.

7. The high-resolution site selection method for floating photovoltaic systems according to claim 4, characterized in that, The other power generation methods include any one of terrestrial photovoltaic power generation, wind power generation, hydropower generation, and surplus thermal power generation.

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