Browsing by Author "Faria, Pedro"
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- Reduction of the Market Splitting Occurrences: A Dynamic Line Rating Approach for the 2030 Iberian Day-ahead Market ScenariosPublication . Algarvio, Hugo; Couto, António; Estanqueiro, Ana; Carvalho, Rui; Santos, Gabriel; Faia, Ricardo; Faria, Pedro; Vale, ZitaABSTRACT: Typically, Transmission System Operators apply power flow models with Seasonal Line Rating prescriptions to compute the ampacity of power lines, in a process that enables to obtain the cross-border capacity for trading between different countries or market zones. These seasonal-dependent models rely on fixed conservative meteorological conditions throughout the year, underestimating the real-time transmission capacity of overhead lines. This can contribute to market splitting occurrences, i.e., a situation where the cleared power flow between different market zones of the coupled market is superior to the cross-border capacity, separating markets, which brings economic losses to market participants. Dynamic Line Rating analysis allows computing the overhead lines’ capacity considering the weather conditions that influence the power line's thermal dynamics. This work presents a study that applies the CIGRÉ 601 model in cross-border power lines between Portugal and Spain to quantify the reduction in market splitting occurrences in the day-ahead Iberian market considering based on the installed capacities from the 2030 national energy and climate plans. Comparing with the seasonal approach, dynamic line rating enabled to reduce the number of market splitting occurrences from 1512 to 514, reducing the electricity costs by more than 1% and the price difference from 19 to 12 €/MWh.
- The Role of Demand and Vres Flexibility in Carbon-Neutral Power Systems: Insights from Portugal and Spain in Prospective 2050 ScenariosPublication . Algarvio, Hugo; Couto, António; Lopes, Fernando; Estanqueiro, Ana; Faia, Ricardo; Santos, Gabriel; Carvalho, Rui; Faria, Pedro; Vale, ZitaABSTRACT: The goal of a carbon-neutral society by 2050 is speeding up the integration of variable renewable energy sources (vRES) in European power systems. For the expected levels of vRES, the adaptation of the demand will be crucial to manage the stochastic behaviour of these technologies. This work evaluates the impact of four prospective 2050 energy mix scenarios in the Iberian electricity market. All scenarios consider near 100% vRES shares. Scenarios that incentivize demand flexibility (S2 and S4) result in the lowest wholesale prices and costs for society. Peak load reduction using demand response occurred in the two scenarios (S1 and S3) with low demand flexibility and high share of renewable generation. S3 is the most unstable leading to the higher wholesale prices. The results highlight that an equilibrium between demand flexibility and investments in the generation side is essential for reducing costs and ensuring stability.
- Spatial flexibility options in electricity market simulation tools: Deliverable D4.3Publication . Couto, António; Silva, Cátia; Algarvio, Hugo; Faria, Pedro; Pinto, Tiago; Schimeczek, Christoph; José, Débora Regina S.; Morales-España, Germán; Helistö, Niina; Sijm, Jos; Kiviluoma, Juha; Hernandez-Serna, Ricardo; Chrysanthopoulos, Nikolaos; Strbac, Goran; Estanqueiro, AnaABSTRACT: Deliverable D4.3 addresses the spatial flexibility options that are being considered by TradeRES models. D4.3 presents a report describing the spatial flexibility-related modelling components that are already implemented and those that are being designed for integration in TradeRES agent-based models. This report includes the main definitions, concepts and terminology related to spatial flexibility, as means to support the presentation of the specific models that are being developed by the project, namely about flow based market coupling, market spliting, nodal pricing, dynamic line rating, cross border intraday market, cross border reserve market, cross border capacity market, consumer flexibility aggregation, renewable energy aggregation, storage aggregation, electric vehicle aggregation and grid capacity.