## 3 Methodology
After the April amendment to the RES Act, new prosumers make their settlements in the net-billing system. The generated electricity is sold to the grid, and its shortage is purchased by the prosumer at market prices. The proposed changes will have a significant impact on the reduction of prosumer investments in photovoltaics in the coming months. The issue of wind-energy development is different, as it has been significantly limited since May 2016 due to the introduction of the so-called \"10H\" rule. Pursuant to the Act, a wind farm could not be built at a distance less than 10 times the height of the turbine (including raised blades) from residential buildings, forms of nature protection and forest complexes. Currently (June 2022), there are works on new regulations, according to which the Local Development Plan will be able to define a distance of a wind farm from a residential building, other than that determined by the \"10H\" rule, but with an absolute minimum distance of 500 m.  
For the purposes of the forecast for the development of photovoltaic sources, it was assumed that by the end of the year, photovoltaics will grow by a constant volume (estimated on the basis of the average increase in installed capacity after the introduced changes to the RES Act). According to a report by the U.S. Department of Energy, the investment time in a new onshore wind farm ranges from 2 to 4 years [61]. Therefore, it was assumed that the changes will not translate into an increase in investments in this segment by the end of the year; an increase of 5.1% estimated based on data from the last 6 months was assumed for the calculation. The proposed forecast of the installed capacity is presented in the table below (Table 3). The utilization factor for the installed capacity in the following months, based on historical data, and the auto-consumption ratio (36% for PV and 0% for wind energy), was also assumed. To determine the impact of photovoltaic sources on the reduction of generation in conventional sources (hard-coal and lignite power plants), the Replacement Indicator-REP was formulated. The algorithm of its creation is presented in the figure below (Figure 6). For its estimation, data on energy production according to generation technology from 2021 and the first half of 2022 were analyzed. The main assumption of its occurrence is the simultaneous hourly decrease in generation in coal-fired and lignite-fired units with an increase in production in PV installations. All hours of the day were analyzed, although over 96% of the above conditions were met between 8 am and 2 pm; it was expected due to the increase in production in PV installations, and it also coincides with the morning peak \begin{table}
\begin{tabular}{c c c} \hline \hline
**Month/Year** & **IPpv (MWp)** & **IPWind (MWp)** \\ \hline
01/2022 & 8147 & 7118 \\
02/2022 & 8768 & 7185 \\
03/2022 & 9401 & 7212 \\
04/2022 & 9998 & 7242 \\
05/2022 & 10,222 & 7277 \\
06/2022 & 10,364 & 7483 \\
07/2022 & **10,505** & **7547** \\
08/2022 & **10,647** & **7611** \\
09/2022 & **10,788** & 7676 \\
10/2022 & **10,930** & **7742** \\
11/2022 & **11,071** & **7808** \\
12/2022 & **11,213** & **7875** \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Installed capacity forecast (from July 2022) for selected renewable energy sources in Poland (red color–predictive value). in electricity demand. The hourly replacement rate (REP) was then aggregated into daily, monthly (3) and annual (4) values. \[REP(m)=\sum_{i=1}^{nd}REP(d) \tag{3}\]  
where:  
\(REP(m)\)--monthly replacement factor, GWh;  
\(REP(d)\)--daily replacement factor, GWh;  
\(nd\)--number of days in the month. \[REP(y)=\sum_{i=1}^{12}REP(m) \tag{4}\]  
where:  
\(REP(y)\)--yearly replacement factor, GWh;  
\(REP(m)\)--daily replacement factor, GWh.