## 4 Use Case in the Energy Wholesale Market
### A Standard Retail Contract in the Greek Energy Market for a Comparative Analysis  
In the Greek market, there is an offering of a specific standard contract (7), which follows the Spot Market and could be used as a reference for comparative analysis [40]:  
\[\text{\it Standard Contract\leavevmode\
obreak\ Revenue}=\sum_{i=1}^{N}1.159 \times(\text{\it TEA}\times(1+\text{\it Losses}))\times E_{i} \tag{7}\]  
where \(\text{\it TEA}\) is the scaled-out price from the Spot Market to Low/Medium Voltage (\(\sim\)11% increase from the DAM price, annual estimation for 2023 based on IPTO data) and the _Losses_ factor equals 0.01357 of the low voltage, publication from the Greek DSO. The \(\text{\it TEA}\) is not included in the calculation for the added value of this contract in comparison to the DAM price since it contains the disaggregation from the high to the low-medium voltage; this is why, based on (7), it will be a fixed cost at the final billing price, which is why it is excluded. Therefore, the added value results in 17.4% from the wholesale market. The hypothesis is that the retailer responsible for (7) buys all the energy from the DAM price without diversification of other markets. **Scenario 1**  
The first strategy involves purchasing an additional 12.89% of energy based on the resulting MAPE of our automated machine learning model to mitigate the risk of penalties due to under-supply. The portfolio participates only in the Spot Market, and there are no hedging techniques during procurement. Additionally, an assumption is that the excess of the bought energy will be sold in the Real-Time Market, for the minimization of energy deviations (\(S_{t}=0\)), at a zero price as well as the factor a being set to zero. \[\text{\it Total\leavevmode\
obreak\ Revenue}=\sum_{i=1}^{N}P_{t}^{D}\times E_{t} ^{D}-P_{t}^{R}\times E_{t}^{R}, \tag{8}\]  
where \(P_{t}^{D}\): day-ahead price for the \(i-th\) time slot of the trading day and \(i\
i\{1,2\dots 24\}\); and \(E_{t}^{D}\) is the overbought amount of energy for each time slot based on the MAPE, here it is 12.89% more than the predicted one, so \(E_{t}^{D}=(1+\text{MAPE})\times F(t)\). This scenario assumes that the excess energy would be resold to the real-time Market for zero price (\(P_{t}^{R}=0\)), so the market absorbs the excess and minimizes the shortfall to zero. Moreover, the risk-aversion factor is \(b=0\). This simplified approach was compared against a standard contract commonly used in the Greek market, which was consistently 17.4% more expensive than the Day-Ahead market prices. The worst-case scenario using this approach is that during the overbought condition of the market, less energy than forecasted will be used, and this is why an energy shortfall of twice the MAPE will occur. This results in 25.78% more expensive energy and there is a negative margin in comparison with (6) at 8.38%. **Scenario 2**  
In this scenario, the strategy aims to minimize costs without minimization of the risk, using Futures contracts. These financial assets offer the securing of energy quantities at a fixed price for a dedicated amount of market time slots. The energy retailer buys an amount of energy in the Futures Market, \(E_{t}^{F}\), and the remaining amount is exposed to the volatile Spot Market as \(E_{t}^{D}\). The total energy demand for hour \(t\) is \(F(t)=E_{t}^{D}+E_{t}^{F}\). Each market is cleared at price \(P_{t}^{D}\) and \(P_{t}^{F}\) for hour \(t\) for the wholesale and Futures markets, respectively. For the definition of an equilibrium between this energy aggregation strategy and the standard contract of (7), Equation (9) sets an increase of 17.4% to the DAM price and compares it with the total revenue accordingly. \[\sum_{t=1}^{N}P_{t}^{D}\times E_{t}^{D}+P_{t}^{F}\times E_{t}^{F}=\sum_{t=1}^{ N}P_{t}^{D}\times 1.174 \tag{9}\]  
The revenue of the Real-Time Market is always set to zero due to \((P_{t}^{R}=0)\) to minimize the energy shortfalls (\(S_{t}=0\)).