## 3 Bibliometric Analysis
### Evolution of Publications and Research Areas
While climate change and renewable energy have been dominant topics since 2005, there has been a notable rise in studies on specific technologies such as solar and wind energy [28; 29; 30; 31; 32; 33; 34; 35; 36]. Solar energy in particular has gained prominence after 2020, highlighting its potential for integration into energy matrices affected by megadroughs and its competitiveness compared to other renewable sources [37; 38; 39; 40; 41; 42; 43; 44]. Simultaneously, a decline in fossil fuel-related publications indicates a shift toward sustainability, aligning with global decarbonization goals. Research on drought impacts on energy generation, mainly hydropower, has remained steady, emphasizing the vulnerability of water-dependent energy systems. This is particularly relevant for countries like Chile, where prolonged megadroughs have significantly reduced water availability. These trends highlight the increasing role of non-conventional renewable energy sources in mitigating climate change and the need for continuous optimization to enhance energy security in extreme climatic conditions[PERSON]  
Analyzing keyword co-occurrence helps identify research strengths and future directions, making it a crucial aspect of bibliometric analysis. Two primary keyword types are examined: (1) author keywords, selected by researchers to define study themes, and (2) index keywords, assigned by databases like Scopus based on standardized taxonomies. While there is some overlap, author keywords provide a researcher-centric view, whereas index keywords reflect database classification systems. Figure 3 presents a science mapping of author keywords, illustrating the terms most frequently used by researchers. In this visualization, node size represents keyword frequency, and arc thickness indicates the strength of co-occurrence relationships[PERSON] Larger nodes correspond to frequently used keywords, while thicker arcs highlight strong associations between terms, revealing dominant topics and emerging research clusters. \begin{table}
\begin{tabular}{l l l l} \hline _Classification_ & _Authors_ & _Number_ & \% 1  \\ \hline
1 & [PERSON] & 3 & 3.66 \\
2 & [PERSON] & 2 & 2.44 \\
3 & JR & 2 & 2.44 \\
4 & [PERSON] & 2 & 2.44 \\
5 & [PERSON] & 2 & 2.44 \\
6 & [PERSON] & 2 & 2.44 \\
7 & [PERSON] & 1 & 1.22 \\
8 & [PERSON] & 1 & 1.22 \\
9 & [PERSON] & 1 & 1.22 \\
10 & [PERSON] & 1 & 1.22 \\ \hline \end{tabular}
\end{table} 
Table 1: _Cont._Figure 3: Clustering of the 35 most frequent author keywords used in the dataset: (**a**) Term map based on different groupings; (**b**) Term map by average year; (**c**) Density visualization map. Node size represents keyword frequency (i.e., the number of times a keyword appears in the dataset), and arc thickness indicates the strength of co-occurrence relationships between keywords. A larger node signifies a more frequently used keyword, while thicker connecting lines indicate stronger associations between terms. Figure 3a depicts the 35 most frequently used keywords over the past 19 years, grouped into five thematic clusters (Table 2). Keywords with at least five occurrences are included. Cluster sizes correspond to total link strength, and proximity between terms reflects their interconnection. The most frequent keywords identified were \"Solar energy\", \"Renewable energy\", \"Climate change\", and \"Wind power\". Renewable energy is the central term, frequently co-occurring with other keywords. Variations of this term, such as \"Renewable energies\", also appear, reinforcing its prominence in keyword mapping. Figure 3b shows the most relevant keywords in recent years (2022-2024), indicating a growing focus on energy utilization and storage, critical areas for achieving decarbonization and energy transition goals [45]. Figure 3c further illustrates keyword density analysis, grouping the 35 most used keywords into five interdisciplinary research clusters, demonstrating this field's complex and interconnected nature.