# Determining Signatures for Energy Mix Produced by Photovoltaic Systems and Wind Turbines
## 5 Conclusions  
The clustering method, known for over 20 years, has been practically used to determine the signatures of the photovoltaic-wind energy mix. The article presents the entire computational algorithm related to the acquisition of measurement data, their processing using innovative tools, and expert validation of the obtained results indicating their practical importance in balancing energy produced by various renewable sources. In the preliminary studies, a traditional statistical analysis of the time series of generated power was performed. Histograms and box plots were made to provide the necessary knowledge about the analyzed processes. In this way, the characteristics of each of the energy sources were better known, which is necessary for the effective construction of energy mixes. In this way, it was proven that it is possible to create energy mixes with specific signatures intended for supplying dedicated green energy receivers. The article uses an analysis of special cases based on real measurement data. This analysis concerns the exceptionally favorable conditions for energy production from photovoltaic systems and wind turbines on a national scale, which takes place in the Lublin region in Poland. Research results support investment processes in the construction of new generating capacities in a specific region of a European country. The authors carried out a series of analyses in the area of power generation by two renewable energy sources: photovoltaic systems and wind turbines. All analyses and data processing methods were accompanied by expert commentary precisely describing the physical meaning of the obtained results. The following general and specific conclusions can be drawn from the research conducted in the article:  
1. Renewable Energy Sources in the form of photovoltaic systems and wind turbines are characterized by high cyclicality and seasonality of the generated power. This requires balancing the power grid with many energy sources and using storage. 2. Statistical analysis, including the creation of box plots and histograms for the power generated by the photovoltaic and wind sources, provided important information on the characteristics of the power generated by each RES separately. This knowledge can be used by RES designers and developers to create effective photovoltaic-wind energy mixes. The analysis of each of the presented RES indicates that the Lublin region in Poland has a large potential for generating energy from the sun and wind. 3. Cluster analysis with unsupervised clustering is an effective tool for describing the power generation processes from photovoltaic systems and wind turbines. Analysis of a two-time series of generated power from the same month allowed for the creation of a signature of the power generated by the photovoltaic-wind energy mix. Clustering monthly power courses into 10 classes without labeling allowed for the selection and physical validation of the power levels generated by both energy sources. 4. Division into 10 classes of the multidimensional space of power generation by RES allows for the location in time (especially during the day) of the process in individual clusters. This allows for the description of the processes of complementation of individual energy sources in the mix and their complete replacement. The signature of the power generation process from the energy mix presented in the article takes into account the construction data and the geographical context related to the devices used and their location. 5. The authors performed detailed expert validation in the field of power generation by photovoltaic and wind systems and provided the possibilities of its practical application in energy management in the energy mix. The presented algorithm for data analysis and processing using the KNIME platform has universal application and can be used to analyze systems with different capacities and consisting of many RES.