## 3 Bibliometric Analysis
### Evolution of Publications and Research Areas
An additional aspect to consider in the density map is the intensity of the color associated with the keywords in each cluster, indicating the main critical points in the research field. These critical points are closely linked to the most relevant keywords in this scientific domain. Five clusters are identified, with the first three being the most predominant (Table 2). The red cluster, which contains the most significant number of terms, includes keywords such as \"Economic analysis\", \"Energy\", \"Reservoirs (water)\", \"Solar energy\", and \"Solar power generation\", centered around the term \"Climate change\". The blue cluster, centered on the primary term \"Wind power\", is surrounded by parameters such as \"Energy efficiency\", \"Energy utilization\", \"Renewable energy resources\", and \"Water scarcity\". Similarly, the purple cluster has \"Alternative energy\" as its central term, with surrounding parameters such as \"Drought\", \"Hydroelectric power\", and \"Power generation\". The yellow cluster includes parameters like \"Electricity generation\", \"Energy planning\", and \"Photovoltaic system\", centered around the term \"Optimization\". Finally, the green cluster contains terms such as \"Biomass\" and \"Renewable energy sources\", revolving around the central term \"Fossil fuels\". Another significant aspect is the thematic map of keywords based on their relevance and degree of development within the research fields, as shown in Figure 4. This map is divided into four quadrants: (i) motor themes, (ii) basic themes, (iii) emerging or declining themes, and (iv) highly specialized or niche themes. The motor themes quadrant exhibits high density and centrality, indicating that these themes are well developed and highly relevant to the research field. Keywords in this quadrant include \"Renewable energies\", \"Wind power\", and \"Alternative energy\" [29; 46; 47; 48; 49; 50]. These well-structured themes are \begin{table}
\begin{tabular}{c c c} \hline _Cluster_ & _Number of Keywords_ & _Keywords in the VOSviewer Network_ \\ \hline \multirow{4}{*}{1.5} & \multirow{4}{*}{1.5} & Climate change, semantic analysis, change, photovoltaic systems, Renewable energy, reservoir management, and land use. \\  & & & Cost, Digital storage, electric power transmission networks, Energy efficiency, Energy Utilization, Renewable energy resources, Water scarcity, and Wind power. \\  & & & Alternative energy, Drought, Energy storage, Hydroelectric power plants, Power generation, Solar power. \\  & & & Electric power generation, Energy planning, Optimization, Photovoltaic cells, Photovoltaic systems. \\ \hline \multirow{4}{*}{4} & \multirow{4}{*}{6} & \multirow{4}{*}{3.5} & Blomass, Fossil fuels, Renewable energy sources. \\  & & & \\ \end{tabular}
\end{table} 
Table 2: Cluster of keywords obtained using VOSviewer software. expected to remain fundamental for advancing technologies that ensure energy transition and sustainability. On the other hand, the quadrant of fundamental themes, composed of keywords such as \"Solar energy\", \"Climate change\", and \"Solar power generation\", demonstrates high centrality but low density. While highly relevant, this indicates that these areas are foundational to the field [51; 52; 53; 54; 55; 56]. This suggests that they constitute the groundwork for future research, and the scientific community must continue exploring and optimizing these themes, given their significant potential to impact the transition to clean energy. The emerging or declining themes quadrant, which includes keywords like \"Renewable energy resources\", \"Fossil fuels\", and \"Energy efficiency\", shows low centrality and development. This could indicate either a decline in interest or insufficient exploration, suggesting that these topics are in the early stages of development or are losing momentum [30; 57; 58]. Energy efficiency in particular requires more attention due to its critical importance for sustainability.