13 results on '"Castillo-Guerra, Eduardo"'
Search Results
2. Q-RPL: Q-Learning-Based Routing Protocol for Advanced Metering Infrastructure in Smart Grids.
- Author
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Duenas Santos, Carlos Lester, Mezher, Ahmad Mohamad, Astudillo León, Juan Pablo, Cardenas Barrera, Julian, Castillo Guerra, Eduardo, and Meng, Julian
- Subjects
REINFORCEMENT learning ,COMPUTER network protocols ,END-to-end delay ,MACHINE learning ,NETWORK performance - Abstract
Efficient and reliable data routing is critical in Advanced Metering Infrastructure (AMI) within Smart Grids, dictating the overall network performance and resilience. This paper introduces Q-RPL, a novel Q-learning-based Routing Protocol designed to enhance routing decisions in AMI deployments based on wireless mesh technologies. Q-RPL leverages the principles of Reinforcement Learning (RL) to dynamically select optimal next-hop forwarding candidates, adapting to changing network conditions. The protocol operates on top of the standard IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL), integrating it with intelligent decision-making capabilities. Through extensive simulations carried out in real map scenarios, Q-RPL demonstrates a significant improvement in key performance metrics such as packet delivery ratio, end-to-end delay, and compliant factor compared to the standard RPL implementation and other benchmark algorithms found in the literature. The adaptability and robustness of Q-RPL mark a significant advancement in the evolution of routing protocols for Smart Grid AMI, promising enhanced efficiency and reliability for future intelligent energy systems. The findings of this study also underscore the potential of Reinforcement Learning to improve networking protocols. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
3. Optimized routers positions for large-scale RF mesh networks based on clustering algorithms
- Author
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Mohamad Mezher, Ahmad, Cárdenas-Barrera, Julián, Rajendran, Nisha, Meng, Julian, and Castillo Guerra, Eduardo
- Published
- 2019
- Full Text
- View/download PDF
4. Automatic modeling of acoustic perception of breathiness in pathological voices
- Author
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Castillo-Guerra, Eduardo and Ruiz, Adel
- Subjects
Biosensors -- Acoustic properties ,Speech -- Health aspects ,Speech -- Measurement ,Bioacoustics -- Health aspects ,Pathology -- Research ,Respiratory organs -- Sounds ,Respiratory organs -- Health aspects ,Biological sciences ,Business ,Computers ,Health care industry - Abstract
This paper revisits the modeling of acoustic perceptions of breathy voice (BV) quality for automatic assessment of perturbations in pathologic speech. Several acoustic measures related with the signal periodicity, harmonic components, and aspiration noise are studied to predict breathiness judgments performed on sustained vowel phonations. A novel comprehensive automatic measure is proposed that provides the highest correlation index (88.5%) with breathiness judgment performed by trained specialists on simulated and recorded utterances. The new measure reveals the most relevant aspects of BV quality and provides a vehicle to obtain reliable objectives judgments of such speech perturbation. Index Terms--Acoustic analysis of speech, acoustic measures, biomedical acoustics, breathy voice (BV) quality.
- Published
- 2009
5. Employing Battery Storage Systems to Improve Power System Survivability.
- Author
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Chowdhury, Muhammad R. A., Saleh, Saleh A., Betancourt, Osleni Antonio, Cardenas-Barrera, Julian Luciano, and Castillo-Guerra, Eduardo
- Subjects
BATTERY storage plants ,SOLAR energy ,MICROGRIDS ,RELIABILITY in engineering ,SYSTEM dynamics ,DISTRIBUTED power generation - Abstract
This article presents the employment of battery storage systems (BSSs) to improve power system survivability. This application of BSSs is based on setting BSS charging/discharging as responses to integrating distributed generation units and/or adjusting load demands (load-side activities). The improvement of power system survivability is quantified by the survivability index $\Gamma$ , which can exceed its boundary values due to load-side activities. The improvement of power system survivability is achieved by maintaining $\Gamma$ within its boundary values post a load-side activity. The proposed approach to improve power system survivability is implemented and tested for the Barbados power system. Tests are conducted for integrating solar power generation units, and implementing demand response. Test results show that accurate BSS charging/discharging can maintain the index $\Gamma$ within its boundary values post-load-side activities. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
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6. A New Approach for Estimating Frequency Variations Due to Smart Grid Functions.
- Author
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Saleh, Saleh A., Wo, Jeffery, St-Onge, Xavier F., and Castillo-Guerra, Eduardo
- Subjects
LOAD forecasting (Electric power systems) ,REACTIVE power ,NONLINEAR equations ,BUS transportation ,NEWTON-Raphson method ,FREQUENCY stability - Abstract
This article presents a new approach for estimating the frequency variations ($Df$) due to applying smart grid functions on a load bus. The proposed approach is based on constructing a ZIP model for the power demands at a load bus that is controlled by smart grid functions.The constructed ZIP model provides a relationship between the active and reactive power demands and the frequency at any load bus. This relationship can be formulated as a set of nonlinear equations, which can be numerically solved for $Df$. The load-model approach is implemented for performance evaluation using load buses in the IEEE 30-bus power system under different loading levels. Performance results show that the proposed approach has a simple implementation, and can provide an accurate estimation of frequency variations due to slow and small changes load power demands. Furthermore, performance results reveal the insensitivity of the load-model approach to load power demands and/or seasonal changes in load power demands. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
7. Developing and Testing a Unit-Commitment-Based Controller of Bus-Split Aggregated Residential Electric Water Heaters.
- Author
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Saleh, Saleh A., Ozkop, Emre, Castillo-Guerra, Eduardo, and Pijnenburg, Petrus C.
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WATER heaters ,ELECTRIC controllers ,SUMMER ,COST functions ,WATER demand management ,ENERGY consumption - Abstract
This article develops and tests a controller for residential electric water heaters (EWHs). The developed controller is operated to maximize the energy stored in EWHs during off-peak-demand times, in order to reduce their power demands during peak-demand times. Desired control actions aim to adjust the minimum temperature settings of EWHs using the unit commitment (UC). In order to eliminate the need for a direct measurement of EWH power demands, the bus-split (BS) aggregation method is employed. The BS method is employed due to its ability to extract the power demands of an EWH from household power meter readings. The UC is formulated using the energy stored in a EWH as a cost function, which is to be maximized during the off-peak-demand time. The solution of the UC problem is obtained using the Lagrange relaxation method that can offer fast convergence and reduced computations. The BS-UC controller is implemented for performance testing using power meter readings that are collected from 150 residential households during the fall, winter, spring, and summer seasons. Test results demonstrate the ability of the BS-UC controller to provide accurate and effective control of EWHs, which are complimented by a minor sensitivity to the number controlled EWHs, hot water consumption, and seasonal variations in residential load power demands. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
8. Bottom-Up Load Forecasting With Markov-Based Error Reduction Method for Aggregated Domestic Electric Water Heaters.
- Author
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Gong, Xun, Cardenas-Barrera, Julian L., Castillo-Guerra, Eduardo, Cao, Bo, Saleh, Saleh A., and Chang, Liuchen
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DEMAND forecasting ,LOAD forecasting (Electric power systems) ,PARTICLE swarm optimization ,ELECTRIC power consumption ,PROCESS optimization ,ENERGY storage - Abstract
Domestic electric water heaters (DEWHs) can provide operational flexibility for load control due to their energy storage capacity. Load forecasting for aggregated DEWHs is important for providing information of baseline load and controlling electricity demand profile without negative impact to the normal end use. Advanced metering infrastructures nowadays provide more possibilities to further enhance forecasting with bottom-up method. This article proposes a bottom-up forecasting with Markov-based error reduction method to predict power consumption of aggregated DEWHs for multiple forecast horizons. DEWHs are randomly divided into small aggregations, whose power consumption is forecasted by independent forecast engines. In this paper, the engines are K-means and wavelet decomposition-based neural networks. After summing all forecasting of small aggregations up, a new Markov-based error reduction method is proposed to extract features in residuals and mitigate forecasting error accumulation introduced by the summation, providing opportunities to further improve forecasting accuracy for the total DEWH load. Differing from traditional Markov-based error reduction, two new compensation parameters (compensation coefficient, and compensation threshold) are proposed. They are determined by using particle swarm optimization algorithm. Experiments on real and simulated DEWH loads verified the effectiveness of the proposed forecasting method. The proposed method improved the forecast accuracy over selected benchmark algorithms by about 20% to 80%, according to four performance metrics: mean absolute error, mean absolute percentage error, root-mean-square error, normalized form RMSE. The aggregation effects on performance were also analyzed in theory and tested with simulated DEWHs, providing a good indication of the forecast dependence on the aggregation size. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
9. Comparing the Performance of Protection Coordination and Digital Modular Protection for Grid-Connected Battery Storage Systems.
- Author
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Saleh, Saleh A., Richard, Christian, St. Onge, Xavier Francis, Meng, Julian, and Castillo-Guerra, Eduardo
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ENERGY storage ,BATTERY storage plants ,ELECTRIC power distribution grids ,ELECTRIC faults ,CONVERTERS (Electronics) - Abstract
This paper compares the performances of protection coordination [time setting and zone selection interlocking (ZSI)] and digital modular protection, when deployed for grid-connected battery storage systems (BSSs). The comparison between these protection management methods is made in terms of their structures, functionalities, and response capabilities. These criteria are selected to demonstrate possible impacts of the system configuration and mode of operating a grid-connected BSS on protection responses. The performance comparison among the time-setting coordination, the ZSI coordination, and the digital modular protection is conducted for different grid-connected BSSs, when operated for various fault and non-fault conditions. Performance results show that the protection coordination can offer a simple structure that is set to achieve specific response (TRIP and RESTRAIN). In addition, performance results show that the digital modular protection can offer diverse responses (TRIP, RESTRAIN, and ACTIVATE), which mandate for a digital implementation. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
10. Load Aggregation From Generation-Follows-Load to Load-Follows-Generation: Residential Loads.
- Author
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Saleh, S. A., Pijnenburg, Petrus, and Castillo-Guerra, Eduardo
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ELECTRICAL load ,ELECTRIC power distribution ,SMART power grids ,ENERGY consumption ,METHODOLOGY - Abstract
The growing interest in optimizing the generation, distribution, and delivery of electric power have motivated the implementation of several smart grid functions in many power systems around the globe. Among such functions are the peak-load management, demand response, direct load control, and integration of distributed power generation. Nowadays, smart grid functions are being implemented for industrial, residential, and/or commercial loads. One of the key requirements for implementing smart grid functions is the accurate and reliable load aggregation. The bottom-up, coordinated, and bus-split aggregation methods have been found applicable for different load types that are included in smart grid functions. This paper reviews the methods and approaches for performing the load aggregation, and provides a discussion for the critical role of load aggregation in power systems operating and smart grid functions. In addition, this paper discusses the applicability of the load aggregation methods in smart grid functions for residential loads. [ABSTRACT FROM PUBLISHER]
- Published
- 2017
- Full Text
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11. Extracting the Phase of Fault Currents: A New Approach for Identifying Arc Flash Faults.
- Author
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Saleh, S. A., Aljankawey, A. S., Errouissi, R., and Castillo-Guerra, Eduardo
- Subjects
FAULT currents ,FLASHOVER ,ELECTRIC fault location ,TEST validity ,FINITE impulse response filters - Abstract
This paper proposes a new approach for detecting and identifying arc flash faults in power systems. The proposed approach is structured to extract the phases of transient frequency components present in arc flash fault currents. The desired phases can be extracted by processing fault currents using a modulated filter bank that is composed of high-pass finite impulse response (FIR) filters. These filters are designed by using the Kaiser window method to achieve linear phase responses. Extracting the phases of transient frequency components, present in arc flash fault currents, can provide signature information for accurate and fast detection and distinguish of an arc flash fault. The proposed phase-based approach is implemented for off-line testing to evaluate its performance. Test cases of parallel and series arch flash faults are conducted for supplying linear, nonlinear, and dynamic loads. Simulation and off-line results demonstrate the validity, accuracy, speed, and reliability of the phase-based approach to detect and distinguish arc flash faults with minor sensitivities to the load type and arch flash type. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
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12. Adaptive Re-estimation of Speaker Verification Threshold.
- Author
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Castillo-Guerra, Eduardo, Cárdenas-Barreras, Julian L., and Diaz-Amador, Roberto
- Abstract
This paper describes an adaptive threshold estimation mechanism for speaker verification systems. The mechanism estimates speaker-dependent thresholds based on successful verifications considering the minimization of a relation-based cost function. Speaker authentication systems commonly use a threshold to decide whether a claimed identity matches a voice-print previously enrolled. Speaker independent threshold is a common option but it does not consider specific speaker characteristics that are relevant to achieve better system performance. Speaker dependent threshold on the contrary, uses speaker-specific data to estimate individual thresholds but the system performance can also suffer from suboptimal threshold conditioned by the limited number of true scores available in early deployment stages. The algorithm reported in this paper starts with the speaker dependent threshold and use an adaptive algorithm to perform online re-estimation of the initial threshold based on speaker-dependent data. The threshold is re-estimated in each successful authentication transaction according to a custom-made confidence score. The reported technique is more robust to impostor scores and score outliers than traditional speaker dependent threshold. The algorithm provides a performance enhancement of up to 36.2% when compared to traditional speaker independent or dependent thresholds. [ABSTRACT FROM AUTHOR]
- Published
- 2008
- Full Text
- View/download PDF
13. Automatic Assessment of Perturbations Produced by Audible Inspirations in Pathological Voices.
- Author
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Castillo-Guerra, Eduardo and Lee, Williams
- Abstract
Audible inspiration is a type of speech perturbation used in conjunction with other acoustic observations to assess different types of pathologic conditions of speech associated with neurological or vocal cord disorders. The perception of this voice perturbation is very subjective and difficult to appraise in a consistent form across multiple utterances, subjects and disorders. This work reports an algorithm to model the perception of audible inspirations. It automatically segments the inspirations in continuous speech based on time-frequency characteristics and estimates the magnitude of the perturbation through a linear combination of the number, duration and the intensity of the inspirations. The segmentation algorithm was evaluated with the Massachusetts Eye and Ear Infirmary Voice database and two other databases containing recording from motor speech disorders. Results: a new method to automatically segment inspiratory phonations was developed in addition to effective multi-variable models of the perception of inspirations. An average segmentation accuracy of 84.4% was achieved enabling accurate objective judgments of the perturbations associated with audible inspirations (80.9% correlation). [ABSTRACT FROM AUTHOR]
- Published
- 2008
- Full Text
- View/download PDF
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