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Publications

Publications by Jean Sumaili

2017

Mitigation in the Very Short-term of Risk from Wind Ramps with Unforeseen Severity

Authors
Pinto, M; Miranda, V; Saavedra, O; Carvalho, L; Sumaili, J;

Publication
JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS

Abstract
This paper addresses a critical analysis of the impact of the wind ramp events with unforeseen magnitude in power systems at the very short term, modeling the response of the operational reserve against this type of phenomenon. A multi-objective approach is adopted, and the properties of the Pareto-optimal fronts are analyzed in cost versus risk, represented by a worst scenario of load curtailment. To complete this critical analysis, a study about the usage of the reserve in the event of wind power ramps is performed. A case study is used to compare the numerical results of the models based on stochastic programming and models that take a risk analysis view in the system with high level of wind power. Wind power uncertainty is represented by scenarios qualified by probabilities. The results show that the reliability reserve may not be adequate to accommodate unforeseen wind ramps and therefore the system may be at risk.

2017

Mean shift densification of scarce data sets in short-term electric power load forecasting for special days

Authors
Rego, L; Sumaili, J; Miranda, V; Frances, C; Silva, M; Santana, A;

Publication
ELECTRICAL ENGINEERING

Abstract
Short-term load forecasting plays an important role to the operation of electric systems, as a key parameter for planning maintenances and to support the decision making process on the purchase and sale of electric power. A particular case in this respect is the consumption forecasting on special days, which can be a complex task as it presents unusual load behavior, when compared to regular working days. Moreover, its reduced number of samples makes it hard to properly train and validate more complex and nonlinear prediction algorithms. This paper tackles this problem by proposing a new approach to improve the accuracy of the predictions amidst existing special days, employing an Information Theoretic Learning Mean Shift algorithm for pattern discovery, classifying and densifying the available scarce consumption data. The paper describes how this methodology was applied to an electrical load forecasting problem in the northern region of Brazil, improving the previously obtained accuracy held by the power company.

2016

Enhancing Stochastic Unit Commitment to Include Nodal Wind Power Uncertainty

Authors
Pinto, R; Carvalho, L; Sumaili, J; Miranda, V;

Publication
2016 13TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET (EEM)

Abstract
The Unit Commitment (UC) problem consists on the day-ahead scheduling of thermal generation units. The scheduling process is based on a forecast for the demand, which adds uncertainty to the decision of starting or shutting down units. With the increasing penetration of renewable energy sources, namely wind power, the level of uncertainty is such that deterministic UC approaches that rely uniquely on point forecasts are no longer appropriate. The UC approach reported in this paper considers a stochastic formulation and includes constraints for the technical limits of thermal generation units, like ramp-rates and minimum and maximum power output, and also for the power flow equations by integrating the DC model in the optimization process. The objective is to assess the ability of the stochastic UC approach to decrease the expected value of load shedding and wind power loss when compared to the deterministic UC approach. A case study based on IEEE-RTS 79 system, which has 24 buses and 32 thermal generation units, for two different penetrations of wind power and a 24-hour horizon is carried out. The computational performance of the methodology proposed is also discussed to show that considerable performance gains without compromising the robustness of the stochastic UC approach can be achieved.

2014

A linearized approach to the Symmetric Fuzzy Power Flow for the application to real systems

Authors
Heleno, M; Sumaili, J; Meirinhos, J; da Rosa, MA;

Publication
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Abstract
Many applications of Fuzzy Power Flow have been proposed not only for operational purposes considering uncertainties, but also for planning exercises with high level of intermittent sources, interconnection presence and, more recently, electric vehicles load. However, their use in real systems is not usual, mainly where the uncertainty level can be significant. This is due to the low accuracy of the results related to the classical methods, and the computational burden needed to achieve a high level of accuracy in the symmetric approaches. This paper aims to present a linearization of the Symmetric Fuzzy Power Flow in order to reduce the computational effort and make it possible for it to achieve high levels of accuracy when applied to real systems. With the purposes of demonstrating the applicability of the proposed approach, several IEEE test systems and a planning configuration of the Portuguese Transmission System will be studied.

2013

PV Module Parameter Characterization From the Transient Charge of an External Capacitor

Authors
Spertino, F; Sumaili, J; Andrei, H; Chicco, G;

Publication
IEEE JOURNAL OF PHOTOVOLTAICS

Abstract
In the classical model of the photovoltaic (PV) cell/module, based on the single-exponential or double-exponential representation of PV cell/module behavior, parasitic parameters are ignored. Their presence, however, has multiple effects, such as the maximum power point tracking on the current-voltage curve, the switching ON/OFF of the inverters for grid connection, and the electrical safety of persons against indirect contact due to ground leakage currents and lightning phenomena. The effects of parasitic parameters can be visualized in the experimental results gathered through the transient charge of an external capacitor connected to the PV generator terminals. The impact of the parasitic components is different when considering a single PV module or a PV array composed of several PV modules. At the module scale, an oscillation occurs in the initial part of the current waveform, which indicates the presence of some inductive components. At the array scale, the inductive phenomena are overdamped, and parasitic capacitive effects become predominant. This paper shows how to determine the parameters of an extended model of PV modules embedding the parasitic parameter effects. It starts from the experimental results obtained from the fast-sampled voltage and current waveforms during the transient charge of an external capacitor. Numerical examples taken from real cases with different PV technologies are provided.

2011

Wind Power Forecasting, Unit Commitment, and Electricity Market Operations

Authors
Audun Botterud; Jianhui Wang; Ricardo Jorge Bessa; Hrvoje Keko; Jean Sumaili; Vladimiro Miranda

Publication
IEEEGM2011 - IEEE Power & Energy Society General Meeting, Detroit, USA

Abstract
In this paper we discuss the use of wind power forecasting in electricity market operations. In particular, we demonstrate how probabilistic forecasts can contribute to address the uncertainty and variability in wind power. We focus on efficient use of forecasts in the unit commitment problem and discuss potential implications for electricity market operations.

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