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In the last decade, the main attacks against smart grids have occurred in communication networks (ITs) causing the disconnection of physical equipment from power networks (OTs) and leading to electricity supply interruptions. To deal with the deficiencies presented in past studies, this paper addresses smart grids vulnerability assessment considering the smart grid as a cyber-physical heterogeneous interconnected system. The model of the cyber-physical system is composed of a physical power network model and the information and communication technology network model (ICT) both are interconnected and are interrelated by means of the communication and control equipment installed in the smart grid. This model highlights the hidden interdependencies between power and ICT networks and contains the interaction between both systems. To mimic the real nature of smart grids, the interconnected heterogeneous model is based on multilayer complex network theory and scale-free graph, where there is a one-to-many relationship between cyber and physical assets. Multilayer complex network theory centrality indexes are used to determine the interconnected heterogeneous system set of nodes criticality. The proposed methodology, which includes measurement, communication, and control equipment, has been tested on a standardized power network that is interconnected to the ICT network. Results demonstrate the model’s effectiveness in detecting vulnerabilities in the interdependent cyber-physical system compared to traditional vulnerability assessments applied to power networks (OT).
Monica Alonso; Jaime Turanzas; Hortensia Amaris; Angel T. Ledo. Cyber-Physical Vulnerability Assessment in Smart Grids Based on Multilayer Complex Networks. Sensors 2021, 21, 5826 .
AMA StyleMonica Alonso, Jaime Turanzas, Hortensia Amaris, Angel T. Ledo. Cyber-Physical Vulnerability Assessment in Smart Grids Based on Multilayer Complex Networks. Sensors. 2021; 21 (17):5826.
Chicago/Turabian StyleMonica Alonso; Jaime Turanzas; Hortensia Amaris; Angel T. Ledo. 2021. "Cyber-Physical Vulnerability Assessment in Smart Grids Based on Multilayer Complex Networks." Sensors 21, no. 17: 5826.
Sensors for monitoring electrical parameters over an entire electricity network infrastructure play a fundamental role in protecting smart grids and improving the network’s energy efficiency. When a short circuit takes place in a smart grid it has to be sensed as soon as possible to reduce its fault duration along the network and to reduce damage to the electricity infrastructure as well as personal injuries. Existing protection devices, which are used to sense the fault, range from classic analog electro-mechanics relays to modern intelligent electronic devices (IEDs). However, both types of devices have fixed adjustment settings (offline stage) and do not provide any coordination among them under real-time operation. In this paper, a new smart sensor is developed that offers the capability to update its adjustment settings during real-time operation, in coordination with the rest of the smart sensors spread over the network. The proposed sensor and the coordinated protection scheme were tested in a standard smart grid (IEEE 34-bus test system) under different short circuit scenarios and renewable energy penetration. Results suggest that the short-circuit fault sensed by the smart sensor is improved up to 80% and up to 64% compared with analog electromechanics relays and IEDs, respectively.
Monica Alonso; Hortensia Amaris; Daniel Alcala; Diana M. Florez R.. Smart Sensors for Smart Grid Reliability. Sensors 2020, 20, 2187 .
AMA StyleMonica Alonso, Hortensia Amaris, Daniel Alcala, Diana M. Florez R.. Smart Sensors for Smart Grid Reliability. Sensors. 2020; 20 (8):2187.
Chicago/Turabian StyleMonica Alonso; Hortensia Amaris; Daniel Alcala; Diana M. Florez R.. 2020. "Smart Sensors for Smart Grid Reliability." Sensors 20, no. 8: 2187.
In this paper, a new control strategy for power output smoothing in a hybrid wave energy installation coupled to a flywheel energy storage system (FESS) is proposed. The control scheme is composed by three stages: a wave generator clustering process at the farm connection point; a power filtering process; and the control of the flywheel energy storage in order to improve the power output of the hybrid wave farm. The proposed control is validated at the existing Lysekil Wave Energy Site located in Sweden, by using real generator measurements. Results show that the application of the flywheel energy storage system reduces the maximum peak power output from the wave energy installation by 85% and the peak/average power ratio by 76%. It is shown that the proposed system can reduce grid losses by 51%, consequently improving the energy efficiency of the power network. The application of the proposed control strategy allows the hybrid wave power plant to follow a power reference signal that is imposed by the grid operator. In addition, the study demonstrates that the application of the proposed control allows the hybrid wave power plant to follow a power reference signal that is imposed by the grid operator. In addition, the study demonstrates that the application of the proposed control enables a wave farm with flywheel energy storage to be a controllable, flexible resource in order to fulfill future grid code requirements for marine energy installations.
Brenda Rojas-Delgado; Monica Alonso; Hortensia Amaris; Juan De Santiago. Wave Power Output Smoothing through the Use of a High-Speed Kinetic Buffer. Energies 2019, 12, 2196 .
AMA StyleBrenda Rojas-Delgado, Monica Alonso, Hortensia Amaris, Juan De Santiago. Wave Power Output Smoothing through the Use of a High-Speed Kinetic Buffer. Energies. 2019; 12 (11):2196.
Chicago/Turabian StyleBrenda Rojas-Delgado; Monica Alonso; Hortensia Amaris; Juan De Santiago. 2019. "Wave Power Output Smoothing through the Use of a High-Speed Kinetic Buffer." Energies 12, no. 11: 2196.
Technical losses of smart grids can be computed using the customer's smart meter measurements (active and reactive energy) and the energy measurement registered by the Low Voltage (LV) supervisor deployed at secondary substations. However, in some LV networks, some customers do not provide information regarding the energy consumed and produced in real time. This fact complicates the calculation of technical losses because this information is necessary for estimating the load demand for this subset of customers. In this paper, a stochastic approach is proposed for the estimation of technical losses in smart grids under uncertain load demands (e.g., non-telemetered customers and uncertain smart meters readings). Load demand estimation of non-metered customers was performed by means of a top-down approach. Intra-hour load demand profiles of customers were synthetically generated by applying a Markov process. The data and network used in this process corresponded to the roll-out deployed by the Spanish Research and Development (R&D) demonstration project OSIRIS.
J-A. Velasco; Hortensia Amaris; Monica Alonso; M. Miguelez. Stochastic Technical Losses Analysis of Smart Grids under Uncertain Demand. 2018 53rd International Universities Power Engineering Conference (UPEC) 2018, 1 -6.
AMA StyleJ-A. Velasco, Hortensia Amaris, Monica Alonso, M. Miguelez. Stochastic Technical Losses Analysis of Smart Grids under Uncertain Demand. 2018 53rd International Universities Power Engineering Conference (UPEC). 2018; ():1-6.
Chicago/Turabian StyleJ-A. Velasco; Hortensia Amaris; Monica Alonso; M. Miguelez. 2018. "Stochastic Technical Losses Analysis of Smart Grids under Uncertain Demand." 2018 53rd International Universities Power Engineering Conference (UPEC) , no. : 1-6.
This article outlines a procedure for loss allocation in both radial and meshed distribution networks with distributed generation that could be regulated in various ways. The method is analytically developed based on the theory of electrical circuits combined with game theory based on Aumann-Shapley, which guarantees both the electrical principles and the fair axioms of game theory. The proposed method obtains unitary participation coefficients for each network user based on the currents demanded/injected by each user and the network topology. The proposed allocation method based on Aumann-Shapley has been compared with other traditional allocation methods, is adaptable to distribution networks, and shows great potential and ease of implementation. Moreover, it can be applied to any kind of distribution network (radial or meshed) with distributed energy resources.
Hortensia Amaris; Yuri Perci Molina; Monica Alonso; Jaime E. Luyo. Loss Allocation in Distribution Networks Based on Aumann–Shapley. IEEE Transactions on Power Systems 2018, 33, 6655 -6666.
AMA StyleHortensia Amaris, Yuri Perci Molina, Monica Alonso, Jaime E. Luyo. Loss Allocation in Distribution Networks Based on Aumann–Shapley. IEEE Transactions on Power Systems. 2018; 33 (6):6655-6666.
Chicago/Turabian StyleHortensia Amaris; Yuri Perci Molina; Monica Alonso; Jaime E. Luyo. 2018. "Loss Allocation in Distribution Networks Based on Aumann–Shapley." IEEE Transactions on Power Systems 33, no. 6: 6655-6666.
This paper presents the implementation of an adaptive load forecasting methodology in two different power networks from a smart grid demonstration project deployed in the region of Madrid, Spain. The paper contains an exhaustive comparative study of different short-term load forecast methodologies, addressing the methods and variables that are more relevant to be applied for the smart grid deployment. The evaluation followed in this paper suggests that the performance of the different methods depends on the conditions of the site in which the smart grid is implemented. It is shown that some non-linear methods, such as support vector machine with a radial basis function kernel and extremely randomized forest offer good performance using only 24 lagged load hourly values, which could be useful when the amount of data available is limited due to communication problems in the smart grid monitoring system. However, it has to be highlighted that, in general, the behavior of different short-term load forecast methodologies is not stable when they are applied to different power networks and that when there is a considerable variability throughout the whole testing period, some methods offer good performance in some situations, but they fail in others. In this paper, an adaptive load forecasting methodology is proposed to address this issue improving the forecasting performance through iterative optimization: in each specific situation, the best short-term load forecast methodology is chosen, resulting in minimum prediction errors.
Ricardo Vazquez; Hortensia Amaris; Monica Alonso; Gregorio Lopez; Jose Ignacio Moreno; Daniel Olmeda; Javier Coca; Jose Ignacio Moreno. Assessment of an Adaptive Load Forecasting Methodology in a Smart Grid Demonstration Project. Energies 2017, 10, 190 .
AMA StyleRicardo Vazquez, Hortensia Amaris, Monica Alonso, Gregorio Lopez, Jose Ignacio Moreno, Daniel Olmeda, Javier Coca, Jose Ignacio Moreno. Assessment of an Adaptive Load Forecasting Methodology in a Smart Grid Demonstration Project. Energies. 2017; 10 (2):190.
Chicago/Turabian StyleRicardo Vazquez; Hortensia Amaris; Monica Alonso; Gregorio Lopez; Jose Ignacio Moreno; Daniel Olmeda; Javier Coca; Jose Ignacio Moreno. 2017. "Assessment of an Adaptive Load Forecasting Methodology in a Smart Grid Demonstration Project." Energies 10, no. 2: 190.
Congestion management is one of the core enablers of smart distribution systems where distributed energy resources are utilised in network control to enable cost-effective network interconnection of distributed generation (DG) and better utilisation of network assets. The primary aim of congestion management is to prevent voltage violations and network overloading. Congestion management algorithms can also be used to optimise the network state. This study proposes a hierarchical and distributed congestion management concept for future distribution networks having large-scale DG and other controllable resources in MV and LV networks. The control concept aims at operating the network at minimum costs while retaining an acceptable network state. The hierarchy consists of three levels: primary controllers operate based on local measurements, secondary control optimises the set points of the primary controllers in real-time and tertiary control utilises load and production forecasts as its inputs and realises network reconfiguration algorithm and connection to the market. Primary controllers are located at the connection point of the controllable resource, secondary controllers at primary and secondary substations and tertiary control at the control centre. Hence, the control is spatially distributed and operates in different time frames.
Anna Kulmala; Monica Alonso; Sami Repo; Hortensia Amaris; Angeles Moreno; Jasmin Mehmedalic; Zaid Al‐Jassim. Hierarchical and distributed control concept for distribution network congestion management. IET Generation, Transmission & Distribution 2017, 11, 665 -675.
AMA StyleAnna Kulmala, Monica Alonso, Sami Repo, Hortensia Amaris, Angeles Moreno, Jasmin Mehmedalic, Zaid Al‐Jassim. Hierarchical and distributed control concept for distribution network congestion management. IET Generation, Transmission & Distribution. 2017; 11 (3):665-675.
Chicago/Turabian StyleAnna Kulmala; Monica Alonso; Sami Repo; Hortensia Amaris; Angeles Moreno; Jasmin Mehmedalic; Zaid Al‐Jassim. 2017. "Hierarchical and distributed control concept for distribution network congestion management." IET Generation, Transmission & Distribution 11, no. 3: 665-675.
R. Vazquez; M.A. Muñoz; Monica Alonso; Hortensia Amaris; C. Alvarez. Background harmonic distortion measurement at power networks with wind farms. Renewable Energy and Power Quality Journal 2016, 873 -878.
AMA StyleR. Vazquez, M.A. Muñoz, Monica Alonso, Hortensia Amaris, C. Alvarez. Background harmonic distortion measurement at power networks with wind farms. Renewable Energy and Power Quality Journal. 2016; ():873-878.
Chicago/Turabian StyleR. Vazquez; M.A. Muñoz; Monica Alonso; Hortensia Amaris; C. Alvarez. 2016. "Background harmonic distortion measurement at power networks with wind farms." Renewable Energy and Power Quality Journal , no. : 873-878.
Monica Alonso; Hortensia Amaris; B. Rojas; Davide Della Giustina; A. Dedè; Zaid Al-Jassim. Optimal network reconfiguration for congestion management optimization in active distribution networks. Renewable Energy and Power Quality Journal 2016, 879 -884.
AMA StyleMonica Alonso, Hortensia Amaris, B. Rojas, Davide Della Giustina, A. Dedè, Zaid Al-Jassim. Optimal network reconfiguration for congestion management optimization in active distribution networks. Renewable Energy and Power Quality Journal. 2016; ():879-884.
Chicago/Turabian StyleMonica Alonso; Hortensia Amaris; B. Rojas; Davide Della Giustina; A. Dedè; Zaid Al-Jassim. 2016. "Optimal network reconfiguration for congestion management optimization in active distribution networks." Renewable Energy and Power Quality Journal , no. : 879-884.
Transportation electrification has become an important issue in recent decades and the large scale deployment of electric vehicles (EVs) has yet to be achieved. The smart coordination of EV demand addresses an improvement in the flexibility of power systems and reduces the costs of power system investment. The uncertainty in EV drivers’ behaviour is one of the main problems to solve to obtain an optimal integration of EVs into power systems. In this paper, an optimisation algorithm to coordinate the charging of EVs has been developed and implemented using a Genetic Algorithm (GA), where thermal line limits, the load on transformers, voltage limits and parking availability patterns are taken into account to establish an optimal load pattern for EV charging-based reliability. This methodology has been applied to an existing residential low-voltage system. The results indicate that a smart charging schedule for EVs leads to a flattening of the load profile, peak load shaving and the prevention of the aging of power system elements.
Monica Alonso; Hortensia Amaris; Jean Gardy Germain; Juan Manuel Galan. Optimal Charging Scheduling of Electric Vehicles in Smart Grids by Heuristic Algorithms. Energies 2014, 7, 2449 -2475.
AMA StyleMonica Alonso, Hortensia Amaris, Jean Gardy Germain, Juan Manuel Galan. Optimal Charging Scheduling of Electric Vehicles in Smart Grids by Heuristic Algorithms. Energies. 2014; 7 (4):2449-2475.
Chicago/Turabian StyleMonica Alonso; Hortensia Amaris; Jean Gardy Germain; Juan Manuel Galan. 2014. "Optimal Charging Scheduling of Electric Vehicles in Smart Grids by Heuristic Algorithms." Energies 7, no. 4: 2449-2475.
Today, Photovoltaic (PV) inverters are working with very small values of reactive power. Then, the Power Factor (PF) is very close to the unit. So, the PV installations only inject active power into the grid. This paper aims to investigate the limits of reactive power capacity in PV generators. In this way, PV generators could be used as a controlled reactive power sources. In this paper, an introduction to the voltage control in photovoltaic generators is described and implemented in Simulink/Matlab and PSS/E.
R. Albarracin; Monica Alonso. Photovoltaic reactive power limits. 2013 12th International Conference on Environment and Electrical Engineering 2013, 13 -18.
AMA StyleR. Albarracin, Monica Alonso. Photovoltaic reactive power limits. 2013 12th International Conference on Environment and Electrical Engineering. 2013; ():13-18.
Chicago/Turabian StyleR. Albarracin; Monica Alonso. 2013. "Photovoltaic reactive power limits." 2013 12th International Conference on Environment and Electrical Engineering , no. : 13-18.
Nowadays wind turbines are generally required to offer ancillary services similar to those provided by conventional generators. One of the most important services wind turbines must offer is to stay connected to the grid in fault situations delivering the reactive current specified in the recent grid codes. In this article, FACTS solutions for fixed speed wind farms such as DVR are presented as well as classic control and crowbar solutions for variable speed wind turbines. Real results are also presented.
Hortensia Amaris; Lorena Gonzalez; Monica Alonso; Carlos Alvarez Ortega. LVRT capability of wind farms. 2013 12th International Conference on Environment and Electrical Engineering 2013, 352 -357.
AMA StyleHortensia Amaris, Lorena Gonzalez, Monica Alonso, Carlos Alvarez Ortega. LVRT capability of wind farms. 2013 12th International Conference on Environment and Electrical Engineering. 2013; ():352-357.
Chicago/Turabian StyleHortensia Amaris; Lorena Gonzalez; Monica Alonso; Carlos Alvarez Ortega. 2013. "LVRT capability of wind farms." 2013 12th International Conference on Environment and Electrical Engineering , no. : 352-357.
As the energy sector shifts and changes to focus on renewable technologies, the optimization of wind power becomes a key practical issue. Reactive Power Management of Power Networks with Wind Generation brings into focus the development and application of advanced optimization techniques to the study, characterization, and assessment of voltage stability in power systems. Recent advances on reactive power management are reviewed with particular emphasis on the analysis and control of wind energy conversion systems and FACTS devices. Following an introduction, distinct chapters cover the 5 key areas of FACTS devices, voltage stability, wind generators, reactive power optimization and management. These are supported with applications and example including real-life data from the Spanish Power system. Together with power system engineers, operators and planners will also benefit from this insightful resource. Reactive Power Management of Power Networks with Wind Generation provides a key reference to advanced undergraduate and graduate students in electrical and power engineering.
Hortensia Amaris; Monica Alonso; Carlos Alvarez Ortega. Reactive Power Management of Power Networks with Wind Generation. The Interrelationship Between Financial and Energy Markets 2013, 1 .
AMA StyleHortensia Amaris, Monica Alonso, Carlos Alvarez Ortega. Reactive Power Management of Power Networks with Wind Generation. The Interrelationship Between Financial and Energy Markets. 2013; ():1.
Chicago/Turabian StyleHortensia Amaris; Monica Alonso; Carlos Alvarez Ortega. 2013. "Reactive Power Management of Power Networks with Wind Generation." The Interrelationship Between Financial and Energy Markets , no. : 1.
This paper presents a methodology for optimal Var/Volt management of Distributed Generation (DG) and FACTS units in power networks. The methodology is based on Genetic Algorithm in order to achieve the desired system reliability requirements taking into account voltage stability limits. Results indicate that the proposed formulation could be used to determine the optimal points in which the incorporation of DG units and connection of FACTS devices would allow a voltage stability enhancement, minimizing, at the same time, real power losses and minimizing the investment cost of the FACTS devices.
Monica Alonso; Hortensia Amaris; Mircea Chindris. A multiobjective Var/Volt Management System in Smartgrids. Energy Procedia 2012, 14, 1490 -1495.
AMA StyleMonica Alonso, Hortensia Amaris, Mircea Chindris. A multiobjective Var/Volt Management System in Smartgrids. Energy Procedia. 2012; 14 ():1490-1495.
Chicago/Turabian StyleMonica Alonso; Hortensia Amaris; Mircea Chindris. 2012. "A multiobjective Var/Volt Management System in Smartgrids." Energy Procedia 14, no. : 1490-1495.
Monica Alonso; Hortensia Amaris; Carlos Alvarez-Ortega. Integration of renewable energy sources in smart grids by means of evolutionary optimization algorithms. Expert Systems with Applications 2012, 39, 5513 -5522.
AMA StyleMonica Alonso, Hortensia Amaris, Carlos Alvarez-Ortega. Integration of renewable energy sources in smart grids by means of evolutionary optimization algorithms. Expert Systems with Applications. 2012; 39 (5):5513-5522.
Chicago/Turabian StyleMonica Alonso; Hortensia Amaris; Carlos Alvarez-Ortega. 2012. "Integration of renewable energy sources in smart grids by means of evolutionary optimization algorithms." Expert Systems with Applications 39, no. 5: 5513-5522.
Monica Alonso; Hortensia Amaris; Carlos Alvarez-Ortega. A multiobjective approach for reactive power planning in networks with wind power generation. Renewable Energy 2012, 37, 180 -191.
AMA StyleMonica Alonso, Hortensia Amaris, Carlos Alvarez-Ortega. A multiobjective approach for reactive power planning in networks with wind power generation. Renewable Energy. 2012; 37 (1):180-191.
Chicago/Turabian StyleMonica Alonso; Hortensia Amaris; Carlos Alvarez-Ortega. 2012. "A multiobjective approach for reactive power planning in networks with wind power generation." Renewable Energy 37, no. 1: 180-191.
Reactive power management is a critical issue when dealing with the planning and operation of power networks with high wind energy penetration. This paper is intended to introduce a coordinated Reactive Power Planning strategy among Doubly-Fed Induction Generator (DFIG) variable speed wind turbines and Flexible AC Transmission Systems (FACTS) devices. According to this strategy, the reactive power capability from DFIG wind turbines is obtained and the limitations on deliverable power are deduced for each operation point. Furthermore, instead of using the reactive power limit as it is traditionally done, the reactive power injection from Static Var Compensator (SVC) is related to the existing physical limits of the control variables. The optimization strategy is based on genetic algorithms and includes directly in its formulation both the reactive power capability from wind turbines and the reactive power injection from SVC units. An existing 140-bus power system is used to validate the performance and effectiveness of the proposed method.
Hortensia Amarís; Monica Alonso. Coordinated reactive power management in power networks with wind turbines and FACTS devices. Energy Conversion and Management 2011, 52, 2575 -2586.
AMA StyleHortensia Amarís, Monica Alonso. Coordinated reactive power management in power networks with wind turbines and FACTS devices. Energy Conversion and Management. 2011; 52 (7):2575-2586.
Chicago/Turabian StyleHortensia Amarís; Monica Alonso. 2011. "Coordinated reactive power management in power networks with wind turbines and FACTS devices." Energy Conversion and Management 52, no. 7: 2575-2586.
Monica Alonso; Hortensia Amaris; C. Álvarez; Ricardo Albarracin. Reactive power planning in distribution networks with distributed generation. 7th Mediterranean Conference and Exhibition on Power Generation, Transmission, Distribution and Energy Conversion (MedPower 2010) 2010, 1 .
AMA StyleMonica Alonso, Hortensia Amaris, C. Álvarez, Ricardo Albarracin. Reactive power planning in distribution networks with distributed generation. 7th Mediterranean Conference and Exhibition on Power Generation, Transmission, Distribution and Energy Conversion (MedPower 2010). 2010; ():1.
Chicago/Turabian StyleMonica Alonso; Hortensia Amaris; C. Álvarez; Ricardo Albarracin. 2010. "Reactive power planning in distribution networks with distributed generation." 7th Mediterranean Conference and Exhibition on Power Generation, Transmission, Distribution and Energy Conversion (MedPower 2010) , no. : 1.
This paper presents a methodology for optimal placement of DG units in power networks to guarantee the voltage profile, maximize loadability conditions in normal and in contingencies situations. The methodology aims in finding the configuration, among a set of system components, which meets the desired system reliability requirements taking into account stability limits. Results shown in the paper indicate that the proposed formulations can be used to determine which the best buses are where the addition of small distributed generator units can greatly enhance the voltage stability of the whole network and power transfer capability under contingencies.
Monica Alonso; Hortensia Amaris. Voltage stability in distribution networks with DG. 2009 IEEE Bucharest PowerTech 2009, 1 -6.
AMA StyleMonica Alonso, Hortensia Amaris. Voltage stability in distribution networks with DG. 2009 IEEE Bucharest PowerTech. 2009; ():1-6.
Chicago/Turabian StyleMonica Alonso; Hortensia Amaris. 2009. "Voltage stability in distribution networks with DG." 2009 IEEE Bucharest PowerTech , no. : 1-6.
Dynamic voltage restorers (DVR) have been successfully applied for voltage dip mitigation in the last years. Especially in systems with nonlinear loads and wind turbine generation DVR units support the power quality enhancement. The reliability and quality of DVR operation depends mostly on fast and accurate voltage dip detection. Detection methodologies must be able to detect a voltage dip as fast as possible and be immune to other types of perturbations. In this paper we address the problem of voltage dip estimation using carefully selected advanced signal processing methods such as Fourier based algorithm, Kalman filtering and wavelets. Additionally, the traditional and common technique of RMS value tracking has been mentioned. The algorithms have been tested under different conditions: voltage dip with phase jump, noise, frequency variations.
Hortensia Amaris; C. Alvarez; Monica Alonso; D. Florez; T. Lobos; P. Janik; J. Rezmer; Z. Waclawek. Computation of voltage sag initiation with Fourier based algorithm, Kalman filter and Wavelets. 2009 IEEE Bucharest PowerTech 2009, 1 -6.
AMA StyleHortensia Amaris, C. Alvarez, Monica Alonso, D. Florez, T. Lobos, P. Janik, J. Rezmer, Z. Waclawek. Computation of voltage sag initiation with Fourier based algorithm, Kalman filter and Wavelets. 2009 IEEE Bucharest PowerTech. 2009; ():1-6.
Chicago/Turabian StyleHortensia Amaris; C. Alvarez; Monica Alonso; D. Florez; T. Lobos; P. Janik; J. Rezmer; Z. Waclawek. 2009. "Computation of voltage sag initiation with Fourier based algorithm, Kalman filter and Wavelets." 2009 IEEE Bucharest PowerTech , no. : 1-6.