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Spanish researchers have created a novel method to select, within a set of water bodies, those where investment in floating photovoltaics could be most beneficial. They have combined geographic information systems, multi-criteria analysis and intelligent optimization. The new approach reportedly improves LCOE by up to 8.4% compared to conventional methods.
A group of Spanish scientists proposes a new framework for stakeholders to evaluate and optimize floating photovoltaic (FPV) farms.
The proposed approach is targeted at investors and policy makers as it reportedly allows them to find the most beneficial water bodies for FPV installation in a specific area or country, while optimizing their tilt angle at a later stage.
Spain was chosen as the first case study for the new method, allowing researchers to identify the best locations in the country for FPV.
“Floating photovoltaics is in the early stages of implementation, so there is not much previous experience that allows for standardised decision-making,” they point out. “Furthermore, the lack of specific design tools and production calculations is an obstacle to understanding the real advantages. From an investment perspective, interested parties do not have a complete analysis of the profitability of their investment. From a technical, environmental and legislative perspective, there is not enough information to establish standards and criteria for design and selection of the most suitable bodies of water.”
The first step of the proposed method consists of integrating geographic information systems (GIS) with geolocated data from multiple sources and resolutions in a Web-GIS environment based on Javascript and Python.
Once all the GIS data on local water bodies have been collected, a multi-criteria analysis (MCDA) is performed, giving different values ??to the various parameters to be considered in decision making. These parameters are the generation capacity factor, water level variation, levelized cost of energy (LCOE), distance to the grid, greenhouse gas (GHG) emission reduction, legal water coverage rate and the number of water bodies within a 25 km radius.
«The objective of MCDA is to obtain a set of solutions ranked from the most to the least suitable. Two methods have been selected from among those used in the state of the art: COmplex PRoportional ASsessment (COPRAS) and Weighted Aggregates Sum Product Assessment (WASPAS)», the scientists explained. «The results of the sensitivity and comparative analyses carried out show that COPRAS presents a more stable classification than WASPAS. For this reason, the COPRAS method is selected as more accurate».
Since MCDA analysis yields the most beneficial water bodies in a specific area, the method runs a slope optimization artificial intelligence algorithm. Specifically, it uses genetic algorithms (GAs), which are widely used to solve optimization problems. GAs are metaheuristic methods that do not guarantee the best solution, but they work well when finding exact solutions is too difficult or impossible.
Running the novel method in Spain, the group found that the total generating potential of all the bodies surveyed is 55.8 TWh, representing 22.3% of the country’s annual demand. However, they also found that of the hundreds of potential water bodies, eleven represent around 32% of the total installed potential capacity. “This shows that those bodies of water where the impact of the investment is greatest are obtained,” the group explained.
In addition, the group took the five largest water bodies in the country and applied the GA to them to find the best tilting angel. They then compared it to six other tilt optimization methods from the literature. “For LCOE, the improvements range from 2.1% to 8.4%, or for GHG avoided, the improvements range from 0.66% to 10.3%,” they said.
The framework was presented in “ An innovative approach to assessing and optimizing floating solar panels”, published in Energy Conversion and Management. The research group involved academics from the University of Salamanca and the scientific research and development services company Pudbuq. |
