3.4.2. Stage "1"

The article is an attempt to transfer the determined dependencies diagnosed on the basis of a relatively small sample of case studies to the entire industry. Due to the fact that the aim of the study is to obtain knowledge and formulate conclusions about the analyzed groups of service enterprises, despite the relatively small number of their representatives, an analysis of the intergroup correlation was carried out, the product of which is the r-Pearson and non-linear Rho-Spearman correlation matrices for individual general case studies (Figures 13–16).


**Figure 13.** Correlation matrix with Pearson's correlation coefficients between analyzed case studies for the pre-pandemic period. Source: own study.


**Figure 14.** Correlation matrix with Spearman's correlation coefficients between analyzed case studies for pre-pandemic period. Source: own study.


**Figure 15.** Correlation matrix with Pearson's correlation coefficients between analyzed case studies for pandemic period. Source: own study.


**Figure 16.** Correlation matrix with Spearman's correlation coefficients between analyzed case studies for the pandemic period. Source: own study.

The correlation analysis of the electricity consumption profiles of the analyzed enterprises was carried out in relation to:

• The power demand profile in the National Power System to determine the impact of these groups of enterprises on the power grid stability. The partial aim of the study is to determine whether these economic sectors contribute to the electricity peak demand in the national network, still covered in Polish conditions by high-emission conventional sources. The positive correlation justifies the environmental effectiveness of PV using in case studies.

• The electricity production profiles of potential PV sources with their productivity defined in simplification only on the basis of historical insolation conditions for the considered locations.

Higher correlation coefficients between electricity consumption profiles in enterprises and insolation, and thus also the potential production of electricity from photovoltaics, result in a greater potential self-consumption coefficient of this electricity.

Therefore, in the first stage of the research process, correlation analysis was performed to avoid unnecessary in-depth self-consumption analysis. Only when the correlation analysis reveals the existence of a relationship between the variables, it is reasonable to test the degree of self-consumption of PV electricity.

The correlation matrices were organized in such a way as to investigate how the electricity generation profiles of a potential RES source fit into the electricity consumption profiles in individual research objects to cover their own energy needs. Thus, the study deals with an increase in environmental efficiency as a result of the reduction of the emissions of national energy, based mainly on fossil fuels as a result of the use of own photovoltaic sources to cover their own electricity demand. Then, the correlation matrices between the individual electricity consumption profiles in the relevant case studies at pre-pandemic and pandemic periods were determined using the "pairs.panels" function from the "psych" library of the RStudio environment. The correlation between the case studies was carried out in order to assess their representativeness, including the research results and conclusions drawn on their basis in relation to the industries they represent.
