Viability of DVPPs

H. Nemati, L.J. Fernández, A. Ortega, P. Sánchez, L. Sigrist

Resumen:

In Task 5.2, a tool to optimize the bidding strategy of DynamicVirtual Power Plants (DVPPs) when engaging in European energy and ancillary service markets was developed. The operation and performance of the proposed tool were discussed in Deliverable D5.2 through a comprehensive set of illustrative examples, demonstrating its effectiveness and applicability. Preliminary results showcased the flexibility of the robust DVPP optimization model, empowering users to define the uncertain range boundaries based on their preferred strategy, be it optimistic, neutral, or conservationist.
This report, which is the result of Task T5.5, presents and discusses more comprehensive economic viability studies of DVPPs for different synthetic, yet realistic, case studies defined in Task T5.4.
The aim is twofold. On the one hand, the model’s simplicity and computational efficiency are demonstrated, showcasing its potential to scale effortlessly to systems of varying sizes, characteristics and complexities. On the other hand, a thorough evaluation of a diverse array of realistic scenarios, derived from actual European electricity market situations, is conducted using the proposed DVPP model. The DVPP model’s versatility
allows it to be readily applied to virtually any European country. However, to illustrate its effectiveness in specific regional contexts, two main examples are discussed in the document, namely a Southern-Europe region (Spain) and a Northern-Europe region (Denmark). By showcasing these contrasting scenarios, we demonstrate how the DVPP model can be tailored to diverse energy market conditions across Europe.
Through this comprehensive evaluation, valuable insights for potential DVPP operators to optimize their profits while participating in distinct electricity markets are proposed. The DVPP model’s versatility enables users to make informed decisions based on their specific strategies, optimizing returns in both standard and novel market conditions. For instance, in the case of the Spanish scenarios, the results obtained from simulations indicate that properly configured and operated DVPPs can be economically more efficient than other solutions based on, e.g., electrochemical Battery Energy Storages (BESs) of several tens of megawatt-hour capacity. For instance, without coordinating the DVPP units, a 8 MW/16 MWh BESneeds tobe installed to achieve a similar performance than a non dispatchable source-based DVPPwith an installed capacity of 200MW.These promising findings provide valuable insights for DVPP operators, suggesting that the optimized DVPP configuration can outperform battery storage solutions in the contexts analyzed. Different scenarios of uncertainties on weather conditions are analyzed, for example sunny and cloudy days for the Southern-Europe region and windy and no-windy days for the Northern-Europe region.
The DVPP optimization tool proposed in D5.2 was primarily focused on optimizing daily bidding in electricity markets. It considered a fixed DVPP portfolio, where a predetermined set of units was aggregated as a single market participation entity. The model relied on short-term data and forecasting for daily operations, making it suitable for immediate market responses. While this approach provides valuable insights into the DVPP’s performance and capabilities, it had some limitations. One major constraint was the lack of consideration for longer-term planning and strategic decision-making, i.e., the optimal configuration of a DVPP.

Proyecto del IIT: H2020POSYTYF (H2020POSYTYF)

Entidad financiadora: Comisión Europea. H2020

Fecha de publicación: 31-jul-2023