CPES - Indexed Articles in Conferences
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ItemGDBN, a Customer-centric Digital Platform to Support the Value Chain of Flexibility Provision( 2024)This paper proposes an original framework for a flexibility-centric value chain and describes the pre-specification of the Grid Data and Business Network (GDBN), a digital platform to provide support to the flexibility value chain activities. First, it outlines the structure of the value chain with the most important tasks and actors in each activity. Next, it describes the GDBN concept, including stakeholders' engagement and conceptual architecture. It presents the main GDBN services to support the flexibility value chain, including, matching consumers and assets and service providers, assets installation and operationalization to provide flexibility, services for energy communities and services, for consumers, aggregators, and distribution systems operators, to participate in flexibility markets. At last, it details the workflow and life cycle management of this platform and discusses candidate business models that could support its implementation in real-life scenarios.
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ItemReview of commercial flexibility products and market platforms( 2024)The European Union is pushing its members states to implement regulations that incentivize distribution system operators to procure flexibility to enhance grid operation and planning. Since flexibility should be obtained using market-based solutions, when possible, flexibility market platforms become essential tools to harness consumer-side flexibility, supporting its procurement, trading, dispatch, and settlement. These reasons have led to the appearance of multiple flexibility market platforms with different structure and functionalities. This work provides a comprehensive description of the main flexibility platforms operating in Europe and provides a concise review of the platform main characteristics and functionalities, including their user segment, flexibility trading procedures, settlement processes, and flexibility products supported.
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ItemA New Adaptive Lead-Lag Control Scheme for High Current PEM Hydrogen Electrolyzers( 2023)This paper aims at researching the design of a current controller for an interleaved Buck converter used to feed a high current 5 kW Polymer electrolyte membrane (PEM) electrolyzer representing a module stack level. The main challenge is to design a robust controller that ensures operation over a wide range of electrolyzer operating points while guaranteeing control requirements and current sharing between the converters. The developed control scheme ensures responsiveness to the requirements of the grid's ancillary services and control over the dynamics of the electrolyzer. MATLAB/Simulink simulation results with dSPACE compatible models are presented to validate the lead-lag controller, designed using root locus, achieving a ripple current of 0.1 A, a 0.3% steady-state error, and a settling time of 50 ms for a step response.
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ItemPV Inverter Fault Classification using Machine Learning and Clarke Transformation( 2023)In a photovoltaic power plant (PVPP), the DC-AC converter (inverter) is one of the components most prone to faults. Even though they are key equipment in such installations, their fault detection techniques are not as much explored as PV module-related issues, for instance. In that sense, this paper is motivated to find novel tools for detection focused on the inverter, employing machine learning (ML) algorithms trained using a hybrid dataset. The hybrid dataset is composed of real and synthetic data for fault-free and faulty conditions. A dataset is built based on fault-free data from the PVPP and faulty data generated by a digital twin (DT). The combination DT and ML is employed using a Clarke/space vector representation of the inverter electrical variables, thus resulting in a novel feature engineering method to extract the most relevant features that can properly represent the operating condition of the PVPP. The solution that was developed can classify multiple operation conditions of the inverter with high accuracy. © 2023 IEEE.
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ItemEvaluation of the uncertainties used to perform flow security assessment: A real case study( 2019)In this paper, a validation framework is proposed to evaluate the quality of uncertainty forecasts, when used to perform branch flow security assessment. The consistency between probabilistic forecasts and observations and the sharpness of the uncertainty forecasts is verified with advanced metrics widely used in weather prediction. The evaluation is completed by assessing the added value of exploiting uncertainty forecasts over the TSO current practices of using deterministic forecasts. For electric power industry, this proposed validation framework provides a way to compare the performance among alternative uncertainty models, when used to perform security assessment in power systems. The quality of the proposed metrics is illustrated and validated on historical data of the French transmission system. © 2019 IEEE.