# VPP Participation in the FCR Cooperation Considering Opportunity Costs
## 4 Discussion  
In this study, it was assumed that Portugal and Spain joined the FCR Cooperation. Drawing upon a set of assumptions and historical FCR market data, we computed the revenues of a VPP that aggregated solar and wind generation with HE demand, along with the shares of revenues distributed among the VPP participants. Technical questions about the dispatch of existing sources within the VPP perimeter were left outside the scope of the study. For instance, suppose that in real time, it was required for the VPP to activate 1 MW of downward reserve; this leads to the question of where will this 1 MW come from. It is the VPP's task to decide whether this 1 MW will imply the reduction of production from one single wind turbine or from a whole solar farm. Such a problem is already faced  
Figure 14: VPP bid size components per hour (organized from highest to lowest in the series). Used data from scenario 1. Figure 13: Number of market sessions each month in which VPP did not participate and its relation to energy and FCR prices. Used data from scenario 1.  
by VPPs, such as the one in [13]; therefore, it was assumed that VPPs already possessed knowledge about the best way to solve the real-time dispatch. Note that in the present analysis, the hydrogen price was kept constant, but it was in itself a source of uncertainty. If the hydrogen price was very large, upward reserve reserve activation implies that the electrolyzers decreased their energy consumption and, therefore, hydrogen production; this led to high opportunity costs. A critical assumption about the VPP was that it participated in the market sessions as a price-taker. This implies that when the VPP chose to submit a bid, it did so with a price below the CBMP so that the bid was accepted. This limitation is noteworthy, as the CBMP is not known in advance. A comprehensive assessment would necessitate access to the strategies employed by other BSPs. Understanding their bidding strategy, encompassing both prices and volumes, is essential for forecasting CBMPs and LMPs. As mentioned by [27] regarding energy markets, due to the simplicity of model implementation, the common assumption was that producers could not impact the market-clearing price with their bids. These market agents are \"price takers\", like the VPP of the present paper, which bids at zero price to ensure it was cleared. However, if the VPP presents a large portion of the bids, it will have an impact in the market-clearing price [27]: the market-clearing price would be lower because some of the more expensive bids would not be accepted. In this case, the revenue of the VPP itself would be lower, as it is proportional to the market-clearing price, as per Equation (5). Recognizing the limitation inherent in this approach, it is essential to emphasize that the obtained results are likely more realistic when the installed capacity of hybrid energies (HEs) is minimal, exerting minimal influence on the market dynamics. Specifically, in a pessimistic scenario where only 50 MW of HEs were installed in Portugal by 2025 (scenario 1), and if these were incorporated into a VPP contracting only 3% of the total installed wind and solar power (\(VGS_{c}\)), considering a 20% share for both upward and downward reserves (\(RGS_{c}\)), the anticipated revenue for an entire year (at 2022 prices) amounted to EUR 844k. Figure 14 indicates that approximately 20% of the time, the bid size was constrained by \(PN_{c}\). A larger value for \(PN_{c}\) would allow for a higher bid size, as there was ample wind and solar power available to support an increased bid (as noted by the blue curve being above the orange curve). This underscores the assertion made in Section 2 that \(VGS_{c}\) is not just a parameter but also an outcome. In scenario 1 for Portugal, \(VGS_{c}\) was set at 3%. Importantly, increasing the value of this parameter would not impact the VPP bid size since the constraint lay on the HE side, specifically in the upward reserve.