Jacques Szczupak

Power quality event detection based on the divide and conquer principle and innovation concept

The aim of this paper is to introduce a novel real-time digital signal processing technique for power quality disturbance detection. The proposed technique is inspired on the Divide and Conquer Principle and on the Innovation Concept. Essentially, the Divide and Conquer Principle is applied in splitting the monitored disturbance event into stationary and nonstationary components, allowing localized individual signal analysis. Thereafter, the Innovation Concept is introduced for revealing new information not previously observed in the energy of the nonstationary signals and so detecting a new event. In addition, this paper demonstrates a straightforward and feasible way to evaluate the Total Harmonic Distortion (THD) or a distortion measure for voltage signals. Simulation results indicate that the proposed technique is able to accurately detect a variety of voltage disturbances.

Emerging signal processing techniques for power quality applications

1Department of Electrical Circuit, Federal University of Juiz de Fora, CEP 36036-330 Juiz de Fora, Brazil 2Department of Electrical Engineering, Pontifical Catholic University of Rio de Janeiro, CEP 22453-900 Rio de Janeiro, Brazil 3The Edward S. Rogers SR., Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada M5S 3G4 4Department of Signals and Systems, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden 5C. V. Raman, College of Engineering Bhubaneswar, Utkal University, Bhubaneswar 751024, Orissa, India 6Department of Electrical Engineering, University of Washington, Seattle, WA 98195-2500, USA

Load Modeling and Forecast based on a Hilbert Space Decomposition

Many energy markets have experienced extreme changes in load dynamics - due, for instance, to energy shortages or changes in market rules. Under these situations, new history may correspond to a mere few years, leaving insufficient amount of data to be explored by classic models, from statistical to neural networks. This paper addresses this problem - modeling under lack of data - and proposes a new method based on functional analysis, applied as a sequential iterative procedure. A real case- study enlightens the approach advantages.

A Novel Risk Management Model Based on the Real Options Concept

This paper proposes a novel solution to the risk management problem based on the real options concept. Global and scenario-dependent variables are mixed together and optimized in order to achieve global optimum according to companys needs and targets. A special constraint set - maximum admissible risk levels- ensures the risk management environment. The resulting model corresponds to a stochastic non-linear integer programming problem and is solved by a customized algorithm, designed for efficiency and reliability. Possible extensions (targeting special markets customization) are straightforward and may be easily taken into account.

Long term wind production modelling and forecast

This work introduces a comprehensive approach for the long term wind farm production analysis and forecast. Initially, a customized model overcomes the usually limited set of measurements by recreating a long, “virtual” history based on available climatological records. This local “virtual” history series is then analyzed and decomposed by associated “explaining” physical variables. These “explanations” are finally used to extend the resulting series, yielding a prediction (next twelve months) and a set of future scenario forecasts (at least 20 years ahead). A real case study with an application to the Northeastern Brazil is presented and discussed.

Overcoming renewable energy climatological risks: the hydroeolic pool

This paper analyzes the systems and markets risks associated to renewables climatological uncertainty. It will be shown that complementary eolic/hydrological dynamics allow the design of a customized regulatory framework based on a pool scheme. Each participant will “cede” resources surplus and receive “coverage” during severe shortages. The result is a strong risk mitigation, stabilizing investors results and consumers supply. The potentiality of the proposed approach is discussed through a case study with the Brazilian system and market.

Climatological Analysis: A Fast Non-linear Signal Filtering Approach

This paper proposes a new approach to detect, model and analyze climatological signals solely based on the largest eigenvalue of a signal derived matrix, used as a measure of innovation. The resulting process offers a substantial reduction in computational complexity with respect to presently applied methods. Furthermore, the approach yields much precise and detailed result. A case study illustrates the application of the proposed approach to the identification and analysis of a Nino event, tracing the interactions between different regions in the planet and pointing out perturbation paths otherwise unknown, allowing the prediction of the phenomena months before the climatological development.

Subband decomposition oriented multirate electrical power network digital simulation

A new approach to linear electric network simulation/analysis is introduced. The processing structure operates as a multirate digital filter, decomposing signals and network into frequency subbands, naturally leading to parallelism. Although general, the method is here applied to electric power networks as a generalization of the EMTP approach. As a result of the decomposition procedure, each subband integration time step is always maximized, reducing computational burden. The computational load is further reduced by on-line controlling subnetworks that could be momentarily disconnected with negligible loss of accuracy in the final result. This adaptive feature further improves the simulator efficiency, adjusting the network model complexity, according to the simulation requirements. Illustrative case is included.

A renewable generation portfolio: Maximizing delivery, minimizing risks

This paper presents a model for the optimal generation portfolio, specially designed to accommodate the characteristics of renewable generators and mitigate associated risks. The mathematical model is flexible enough to adjust to planners desired goals - from economy to sustainability - and provide regulatory solutions to induce such adjustments. A realistic case study with the Brazilian system illustrates the potentiality of the proposed approach and paves the way to an efficient and fair regulatory framework.

Power Network Port Measurements Synchronization

This work introduces a new procedure for software synchronization of electrical power signals collected over a large geographical area. The idea is to use not necessarily synchronized, but stable, local clocks, and synchronize the sparsely collected data windows by an offline procedure. An approach for the estimation of non monitored internal system buses serves as a basis for the synchronization process. The electrical power network description yields the desired phase corrections, compensating the loss of data window synchronism. Typical sub determined situations are avoided by a proposed alternative network monitoring scheme, illustrated by a case example. Simulation results emphasize the method robustness with respect to usual network parameters uncertainties.