## 2 Methods
The share of non-renewable energy (\(f_{\text{non-RES}}\)) includes fossil and nuclear energy and is determined as the remaining share after subtracting the share of renewable energy, as follows:  
\[f_{\text{non-RES}}=100\%-f_{\text{RES}} \tag{7}\]  
A sub-category of non-renewable generation is the share of fossil generation (\(f_{\text{ fossil}}\)), calculated as the ratio between the sum of net energy produced in gas- (\(E_{\text{gas}}\)), oil- (\(E_{\text{oil}}\)), and coal-fired (\(E_{\text{coal}}\)) units and the net electricity demand (\(E_{\text{demand}}\)), as follows:  
\[f_{\text{fossil}}=\frac{\sum\limits_{j=1}^{t}\bigl{(}E_{\text{coal}}+E_{\text{ oil}}+E_{\text{gas}}\bigr{)}_{j}}{\sum\limits_{j=1}^{t}E_{\text{demand},j}} \cdot 100\% \tag{8}\]  
The share of variable energy (\(f_{\text{VRE}}\)) is calculated as the ratio between net variable renewable energy (\(E_{\text{VRE}}\)) and total electricity demand (\(E_{\text{demand}}\)), as follows:  
\[f_{\text{VRE}}=\frac{\sum\limits_{j=1}^{t}E_{\text{VRE},j}}{\sum\limits_{j=1} ^{t}E_{\text{demand},j}}\cdot 100\%=\frac{\sum\limits_{j=1}^{t}(E_{\text{PV}}+E_{ \text{wind}})_{j}}{\sum\limits_{j=1}^{t}E_{\text{demand},j}}\cdot 100\% \tag{9}\]  
The share of import dependency (\(f_{\text{import}}\)) is the ratio between net electricity import and net electricity demand, where the net electricity import is the missing energy demand, calculated as the difference between electricity demand (\(E_{\text{demand}}\)) and total energy generation (\(E_{\text{VRE}}+E_{\text{residual}}\)), as follows:  
\[f_{\text{import}}=\frac{\sum\limits_{j=1}^{t}\left[E_{\text{demand}}-\left(E_ {\text{VRE}}+E_{\text{residual}}\right)\right]_{j}}{\sum\limits_{j=1}^{t}E_{ \text{demand},j}}\cdot 100\% \tag{10}\]The share of renewable energy oversupply (\(f_{\text{OS}}\)) is the ratio between VRE energy surplus (\(\Delta E_{\text{VRE}}\)) and net electricity demand (\(E_{\text{demand}}\)), as follows:  
\[f_{\text{OS}}=\frac{\sum\limits_{j=1}^{t}\Delta E_{\text{VRE},j}}{\sum\limits_{ j=1}^{t}E_{\text{demand},j}}\cdot 100\%=\frac{\sum\limits_{j=1}^{t}\left[E_{\text{VRE}}- \left(E_{\text{load}}-E_{\text{residual}}\right)\right]_{j}}{\sum\limits_{j=1}^{ t}E_{\text{demand},j}}\cdot 100\% \tag{11}\]  
Renewable energy oversupply occurs when total generation exceeds electricity consumption, and the VRE surplus needs to be exported, stored, or curtailed. The main assumptions of the power system model arise from the following principles of the merit order and the announced near-future projects in the power sector in Croatia:  
1. Power load and electricity generation profiles were modelled on a 15-minute interval basis. Present load and net generation data was retrieved from the Energy Charts website, available also on the ENTSO-E database. 2. Future power load profiles were built from historical data using scaling factors. 3. Assuming that the wind sector is mature in Croatia, future wind generation profiles were estimated from historical wind generation data using scaling factors. 4. Solar data for the exact locations of the announced utility-scale solar PV power plants was unavailable. Therefore, hourly solar data was estimated using the sky diffuse model developed by PVWatts [45]. Comparison against measurements of solar energy quantities in the major cities [46] revealed that the PVWatts tool is able to predict within 4% error on the annual scale. Subsequently, the hourly data was reduced to 15-min interval data using spline interpolation. 5. Solar PV for self-consumption is disregarded because it is not available to the public grid. ENTSO-E reports data for net power loads and net generation, which are measured when entering the public grid, while solar PV for self-consumption is generated and consumed locally. Estimation of energy generation from solar PV self-consumption units is avoided due to uncertainties such as shading factors, installation angles, PV panel type and age, system losses, power purchase schemes. 6.