## 3 Data and Empirical Setup
### Scenario Probabilities and Expected Returns  
In policy and market contexts involving uncertainty and risk assessment, four scenarios are used, along with their associated probabilities, to understand outcomes  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Project** & **Scenario** &
\begin{tabular}{l} **Operational Cost** \\ **(USD/MW/year)** \\ \end{tabular} \\ \hline Solar A & Stable and High Price & 100,000 \\ \hline Solar A & Stable and Low Price & 100,000 \\ \hline Solar A & Adverse and High Price & 110,000 \\ \hline Solar A & Adverse and Low Price & 110,000 \\ \hline Wind B & Stable and High Price & 150,000 \\ \hline Wind B & Stable and Low Price & 150,000 \\ \hline Wind B & Adverse and High Price & 160,000 \\ \hline Wind B & Adverse and Low Price & 160,000 \\ \hline Hydro Gamma & Stable and High Price & 120,000 \\ \hline Hydro Gamma & Stable and Low Price & 120,000 \\ \hline Hydro Gamma & Adverse and High Price & 130,000 \\ \hline Hydro Gamma & Adverse and Low Price & 130,000 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Operational Costs for Each Project under Various Market Scenarios.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Project** & **Existing Capacity (MW)** & **Maximum Capacity (MW)** \\ \hline Solar A & 20 & 100 \\ \hline Wind B & 15 & 80 \\ \hline Hydro Gamma & 10 & 50 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Existing and Maximum Capacities of Renewable Energy Projects.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Project** & **Existing Capacity (MW)** & **Maximum Capacity (MW)** \\ \hline Solar A & 20 & 100 \\ \hline Wind B & 15 & 80 \\ \hline Hydro Gamma & 10 & 50 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Existing and Maximum Capacities of Renewable Energy Projects.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Project** & **Investment Cost (USD/MW)** \\ \hline Solar A & 800,00 \\ \hline Wind B & 1,200,000 \\ \hline Hydro Gamma & 900,000 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Investment Costs for Selected Renewable Energy Projects.  
and make informed decisions. The provided table outlines these scenarios and the likelihood of each occurring, while another table breaks down the expected returns for projects across five distinct periods. The study generated scenarios based on two primary factors: policy regulation and market prices. The latter accounts for incentives, subsidies, and supportive frameworks for renewable energy projects, while the former accounts for volatility and market price direction. The probabilities allocated to each scenario were established using a discrete probability distribution influenced by expert insights. Additionally, in the event of the worst-case scenario, a triangular probability distribution is employed in the optimization scheme. A proportional allocation method was employed to allocate the funding based on projected market expansion and expected policy changes.  
Table 5 is split per time stage for clarity, given the vast volume of the data across five time stages, scenarios, and projects.  
Table 6 shows how Solar A, Wind B, and Hydro Gamma each experience changing expected returns year by year, highlighting how stable versus adverse price scenarios influence their performance.  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Year** & **Scenario** & **Solar A** & **Wind B** & **Hydro Gamma** \\ \hline  
table and High Price & 0.16 & 0.18 & 0.14 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Consolidated 5-Year Expected Returns for Solar A, Wind B, and Hydro Gamma under Various Price Scenarios.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Scenario** & **Probability** \\ \hline Stable and High Price & 0.3 \\ \hline Stable and Low Price & 0.3 \\ \hline Adverse and High Price & 0.2 \\ \hline Adverse and Low Price & 0.2 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Scenario Probabilities.