CPES

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http://localhost:4000/handle/123456789/40
This service focuses its activities in areas such as regulation and electricity markets, integration of dispersed independent producers, technical and economic management of distribution systems, use of information technologies in regional energy planning, uncertainty and risk management.

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Browsing CPES by Author "4882"
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    Active Distribution Grid Management based on Robust AC Optimal Power Flow
    ( 2018) Ricardo Jorge Bessa ; Tiago André Soares ; Pinson,P ; Morais,H ; 4882 ; 6611
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    The challenges of estimating the impact of distributed energy resources flexibility on the TSO/DSO boundary node operating points
    ( 2018) Luís Seca ; Vladimiro Miranda ; Manuel Matos ; João Vieira Silva ; Jean Sumaili ; Ricardo Jorge Bessa ; 4417 ; 208 ; 214 ; 4882 ; 6299 ; 5164
    The increasing penetration of renewable energy sources characterized by a high degree of variability and uncertainty is a complex challenge for network operators that are obligated to ensure their connection while keeping the quality and security of supply. In order to deal with this variable behavior and forecast uncertainty, the distribution networks are equipped with flexible distributed energy resources capable of adjusting their operating point to avoid technical issues (voltage problems, congestion, etc.). Within this paradigm, the flexibility that, in fact, can be provided by such resources, needs to be estimated/forecasted up to the transmission network node (primary substation) and requires new tools for TSO/DSO coordination. This paper addresses this topic by developing a methodology capable of finding the flexibility area while taking into account the technical grid constraints. The proposed approach is based on the formulation of a single optimization problem which is run several times, according with the expected precision for the flexibility area estimation. To each optimization problem run, a different objective function belonging to a family of straight lines is assigned. This allows exploring the active and reactive power flow limits at the TSO/DSO boundary nodes - which define the flexibility area. The effectiveness of the proposed model has been evaluated on two test networks and the results suggest a step forward in the TSO/DSO coordination field. Nevertheless, further investigations to study the effect of assets with discrete control nature (e.g., on load tap changers - OLTC, capacitor banks) on the occurrence of disjoint flexibility areas should be carried. © 2017 Elsevier Ltd.
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    Data-driven Anomaly Detection and Event Log Profiling of scada Alarms
    ( 2022) José Ricardo Andrade ; Conceição Nunes Rocha ; Ricardo Silva ; Viana,JP ; Ricardo Jorge Bessa ; Clara Sofia Gouveia ; Almeida,B ; Santos,RJ ; Louro,M ; Santos,PM ; Ribeiro,AF ; 4882 ; 5524 ; 6121 ; 6801 ; 7343
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    Estimating the Active and Reactive Power Flexibility Area at the TSO-DSO Interface
    ( 2018) João Vieira Silva ; Sebastian Viana,M ; Goncer,B ; Caujolle,M ; Vladimiro Miranda ; Manuel Matos ; Seca,L ; Ricardo Jorge Bessa ; Sumaili,J ; 6299 ; 4882 ; 208 ; 214
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    Proactive management of distribution grids with chance-constrained linearized AC OPF
    ( 2019) Tiago André Soares ; Ricardo Jorge Bessa ; 4882 ; 6611
    Distribution system operators (DSO) are currently moving towards active distribution grid management. One goal is the development of tools for operational planning of flexibility from distributed energy resources (DER) in order to solve potential (predicted) congestion and voltage problems. This work proposes an innovative flexibility management function based on stochastic and chance-constrained optimization that copes with forecast uncertainty from renewable energy sources (RES). Furthermore, the model allows the decision-maker to integrate its attitude towards risk by considering a trade-off between operating costs and system reliability. RES forecast uncertainty is modeled through spatial-temporal trajectories or ensembles. An AC-OPF linearization that approximates the actual behavior of the system is included, ensuring complete convexity of the problem. McCormick and big-M relaxation methods are compared to reformulate the chance-constrained optimization problem. The discussion and comparison of the proposed models is carried out through a case study based on actual generation data, where operating costs, system reliability and computer performance are evaluated.
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    PV Inverter Fault Classification using Machine Learning and Clarke Transformation
    ( 2023) Ricardo Jorge Bessa ; Ana Silva ; 4882 ; 9079
    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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    Reactive power provision by the DSO to the TSO considering renewable energy sources uncertainty
    ( 2020) Tiago André Soares ; Leonel Magalhães Carvalho ; Moris,H ; Ricardo Jorge Bessa ; Tiago João Abreu ; Lambert,E ; 4882 ; 4971 ; 6611 ; 7440
    The current coordination between the transmission system operator (TSO) and the distribution system operator (DSO) is changing mainly due to the continuous integration of distributed energy resources (DER) in the distribution system. The DER technologies are able to provide reactive power services helping the DSOs and TSOs in the network operation. This paper follows this trend by proposing a methodology for the reactive power management by the DSO under renewable energy sources (RES) forecast uncertainty, allowing the DSO to coordinate and supply reactive power services to the TSO. The proposed methodology entails the use of a stochastic AC-OPF, ensuring reliable solutions for the DSO. RES forecast uncertainty is modeled by a set of probabilistic spatiotemporal trajectories. A 37-bus distribution grid considering realistic generation and consumption data is used to validate the proposed methodology. An important conclusion is that the methodology allows the DSO to leverage the DER full capabilities to provide a new service to the TSO.
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    A review on the decarbonization of high-performance computing centers
    ( 2024) Carlos Silva ; André Martins Pereira ; Ricardo Jorge Bessa ; 8560 ; 9080 ; 4882
    High-performance computing relies on performance-oriented infrastructures with access to powerful computing resources to complete tasks that contribute to solve complex problems in society. The intensive use of resources and the increase in service demand due to emerging fields of science, combined with the exascale paradigm, climate change concerns, and rising energy costs, ultimately means that the decarbonization of these centers is key to improve their environmental and financial performance. Therefore, a review on the main opportunities and challenges for the decarbonization of high-performance computing centers is essential to help decision-makers, operators and users contribute to a more sustainable computing ecosystem. It was found that state-of-the-art supercomputers are growing in computing power, but are combining different measures to meet sustainability concerns, namely going beyond energy efficiency measures and evolving simultaneously in terms of energy and information technology infrastructure. It was also shown that policy and multiple entities are now targeting specifically HPC, and that identifying synergies with the energy sector can reveal new revenue streams, but also enable a smoother integration of these centers in energy systems. Computing-intensive users can continue to pursue their scientific research, but participating more actively in the decarbonization process, in cooperation with computing service providers. Overall, many opportunities, but also challenges, were identified, to decrease carbon emissions in a sector mostly concerned with improving hardware performance.