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Prof. Dr. Antonio Gabaldon
Department of Electrical Engineering, Universidad Politecnica de Cartagena, Cartagena, Spain

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Research Keywords & Expertise

0 Demand Response
0 Electricity Markets
0 Energy Efficiency
0 Analysis of electrical distribution systems
0 Electric haulage in railways and non-invasive monitoring techniques

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Demand Response
Electricity Markets
Energy Efficiency

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Journal article
Published: 28 April 2021 in Utilities Policy
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Demand Response (DR) is an opportunity and a concern for markets as well as power system flexibility. The deployment of DR depends on both knowledge on its performance and how to measure it effectively to provide adequate economic feedback. DR verification requires a baseline reference. This paper introduces a new baseline that provides an evaluation of response based on simple adjustment factors through physically-based models, tools which are also used in DR. The approach includes the detection of licit and gaming responses before and after DR. Results show that errors decrease by 10–15% with respect to conventional approaches.

ACS Style

A. Gabaldón; A. García-Garre; M.C. Ruiz-Abellón; A. Guillamón; C. Álvarez-Bel; L.A. Fernandez-Jimenez. Improvement of customer baselines for the evaluation of demand response through the use of physically-based load models. Utilities Policy 2021, 70, 101213 .

AMA Style

A. Gabaldón, A. García-Garre, M.C. Ruiz-Abellón, A. Guillamón, C. Álvarez-Bel, L.A. Fernandez-Jimenez. Improvement of customer baselines for the evaluation of demand response through the use of physically-based load models. Utilities Policy. 2021; 70 ():101213.

Chicago/Turabian Style

A. Gabaldón; A. García-Garre; M.C. Ruiz-Abellón; A. Guillamón; C. Álvarez-Bel; L.A. Fernandez-Jimenez. 2021. "Improvement of customer baselines for the evaluation of demand response through the use of physically-based load models." Utilities Policy 70, no. : 101213.

Journal article
Published: 18 December 2019 in Energies
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The development of Short-Term Forecasting Techniques has a great importance for power system scheduling and managing. Therefore, many recent research papers have dealt with the proposal of new forecasting models searching for higher efficiency and accuracy. Several kinds of artificial intelligence (AI) techniques have provided good performance at predicting and their efficiency mainly depends on the characteristics of the time series data under study. Load forecasting has been widely studied in recent decades and models providing mean absolute percentage errors (MAPEs) below 5% have been proposed. On the other hand, short-term generation forecasting models for photovoltaic plants have been more recently developed and the MAPEs are in general still far from those achieved from load forecasting models. The aim of this paper is to propose a methodology that could help power systems or aggregators to make up for the lack of accuracy of the current forecasting methods when predicting renewable energy generation. The proposed methodology is carried out in three consecutive steps: (1) short-term forecasting of energy consumption and renewable generation; (2) classification of daily pattern for the renewable generation data using Dynamic Time Warping; (3) application of Demand Response strategies using Physically Based Load Models. Real data from a small town in Spain were used to illustrate the performance and efficiency of the proposed procedure.

ACS Style

María Carmen Ruiz-Abellón; Luis Alfredo Fernández-Jiménez; Antonio Guillamón; Alberto Falces; Ana García-Garre; Antonio Gabaldón. Integration of Demand Response and Short-Term Forecasting for the Management of Prosumers’ Demand and Generation. Energies 2019, 13, 11 .

AMA Style

María Carmen Ruiz-Abellón, Luis Alfredo Fernández-Jiménez, Antonio Guillamón, Alberto Falces, Ana García-Garre, Antonio Gabaldón. Integration of Demand Response and Short-Term Forecasting for the Management of Prosumers’ Demand and Generation. Energies. 2019; 13 (1):11.

Chicago/Turabian Style

María Carmen Ruiz-Abellón; Luis Alfredo Fernández-Jiménez; Antonio Guillamón; Alberto Falces; Ana García-Garre; Antonio Gabaldón. 2019. "Integration of Demand Response and Short-Term Forecasting for the Management of Prosumers’ Demand and Generation." Energies 13, no. 1: 11.

Journal article
Published: 02 September 2019 in Applied Sciences
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The objective of this paper involves the analysis, identification and evaluation of different possibilities offered by technology for the improvement and the management of the use of energy and hybridization in railways: On board generation, demand response and energy storage, both in traction and auxiliary loads, considering the aggregation of resources and its stochastic nature. The paper takes into account the importance of efficient use of energy in railways, both currently (trains in service, prototypes) and in the future, considering the trends driven by energy policy scenarios (2030–2050) that will affect service and operation of units during their lifetime. A new activity has been considered that will be relevant in the future in the framework of a new electricity supply paradigm: Smart-Grids. According to this paradigm, the interaction of the Electric Power System and the Railway Supply System (somehow embedded in the Power System) will bring new opportunities for the collaboration of these two systems to perform, in a wise economic fashion, a better and more reliable operation of the complete energy system. The paper is focused on a mixed profile with low-medium traffic (passenger and freight): The first part of the route is electrified (3 kV DC catenary) whereas the second part is not electrified. Results justify that complex policies and objectives bring an opportunity to make cost-effective the hybridization of railway units, especially in low/medium traffic lines, which improves their social and economic sustainability.

ACS Style

Ana García-Garre; Antonio Gabaldón. Analysis, Evaluation and Simulation of Railway Diesel-Electric and Hybrid Units as Distributed Energy Resources. Applied Sciences 2019, 9, 3605 .

AMA Style

Ana García-Garre, Antonio Gabaldón. Analysis, Evaluation and Simulation of Railway Diesel-Electric and Hybrid Units as Distributed Energy Resources. Applied Sciences. 2019; 9 (17):3605.

Chicago/Turabian Style

Ana García-Garre; Antonio Gabaldón. 2019. "Analysis, Evaluation and Simulation of Railway Diesel-Electric and Hybrid Units as Distributed Energy Resources." Applied Sciences 9, no. 17: 3605.

Conference paper
Published: 01 September 2018 in 2018 International Conference on Smart Energy Systems and Technologies (SEST)
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The development of Demand Response in residential segments is basic to develop a practical flexibility of demand, because these segments account for up to 40% of the overall demand. Energy Efficiency is another concern for these segments, but unfortunately present scenarios lack a practical coordination between Efficiency and Demand Response. This paper deals with an important problem in residential Demand Response: the determination of the flexibility and response on the demand-side, in this case through loads which can have a high potential for Demand Response and also a considerable interest for energy savings: Heat Pump Water Heaters. A residential load has been fully monitored (temperature, consumption, water flow) in the laboratory to obtain a Physically-Based Model which allows the evaluation of Demand Response options. Moreover, the model helps the aggregator obtain how the flexibility of demand (power, energy, energy payback or rebound effects) can be modified or limited, and how to deal with these characteristics and limitations to engage customers in Electricity Markets.

ACS Style

Antonio Gabaldon; Sergio Valero-Verdu; Ana Garcia-Garre; Carolina Senabre; Carlos Alvarez-Bel; Miguel Lopez; Elisa Penalvo; Eugenio P. Sanchez. A Physically-Based Model of Heat Pump Water Heaters for Demand Respose Policies: Evaluation and Testing. 2018 International Conference on Smart Energy Systems and Technologies (SEST) 2018, 1 -6.

AMA Style

Antonio Gabaldon, Sergio Valero-Verdu, Ana Garcia-Garre, Carolina Senabre, Carlos Alvarez-Bel, Miguel Lopez, Elisa Penalvo, Eugenio P. Sanchez. A Physically-Based Model of Heat Pump Water Heaters for Demand Respose Policies: Evaluation and Testing. 2018 International Conference on Smart Energy Systems and Technologies (SEST). 2018; ():1-6.

Chicago/Turabian Style

Antonio Gabaldon; Sergio Valero-Verdu; Ana Garcia-Garre; Carolina Senabre; Carlos Alvarez-Bel; Miguel Lopez; Elisa Penalvo; Eugenio P. Sanchez. 2018. "A Physically-Based Model of Heat Pump Water Heaters for Demand Respose Policies: Evaluation and Testing." 2018 International Conference on Smart Energy Systems and Technologies (SEST) , no. : 1-6.

Conference paper
Published: 01 September 2018 in 2018 International Conference on Smart Energy Systems and Technologies (SEST)
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Buildings are an important segment from the point of view of the overall consumption and the flexibility or change in their demand through Demand Response, Energy Efficiency and Renewable Sources. The integration of renewables represents an opportunity for buildings because main end-uses (for example heat, cool, and ventilation) follow, at some extend, the potential of solar resource. The problem is that renewable resources are evaluated through simulators from average conditions (irradiation, external temperature) but in practice, and in the short term, the generation resource exhibits an important volatility and, in some cases, the integration of renewables can produce not only benefits but risks for the customer from an economic aspect. The aim of this paper is the evaluation of these risks, and to state how Demand Response policies and, of course, Renewable Energy Sources (RES) models, can help to reduce or mitigate these risks and volatility. A real university building is presented to exemplify the methodology.

ACS Style

Ana Garcia-Garre; Antonio Gabaldon; Luis A. Fernandez-Jimenez; Carlos Alvarez-Bel; Ignacio J. Ramirez-Rosado; Sergio Valero-Verdu; Carolina Senabre. Evaluation and Integration of Demand Response and Photovoltaic Generation in Institutional Buildings. 2018 International Conference on Smart Energy Systems and Technologies (SEST) 2018, 1 -6.

AMA Style

Ana Garcia-Garre, Antonio Gabaldon, Luis A. Fernandez-Jimenez, Carlos Alvarez-Bel, Ignacio J. Ramirez-Rosado, Sergio Valero-Verdu, Carolina Senabre. Evaluation and Integration of Demand Response and Photovoltaic Generation in Institutional Buildings. 2018 International Conference on Smart Energy Systems and Technologies (SEST). 2018; ():1-6.

Chicago/Turabian Style

Ana Garcia-Garre; Antonio Gabaldon; Luis A. Fernandez-Jimenez; Carlos Alvarez-Bel; Ignacio J. Ramirez-Rosado; Sergio Valero-Verdu; Carolina Senabre. 2018. "Evaluation and Integration of Demand Response and Photovoltaic Generation in Institutional Buildings." 2018 International Conference on Smart Energy Systems and Technologies (SEST) , no. : 1-6.

Journal article
Published: 26 August 2018 in Sustainability
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The development of renewable sources in residential segments is basic to achieve a sustainable energy scenario in the horizon 2030–2050 because these segments explain around 25% of the final energy consumption. Demand Response and its effective coordination with renewable are additional concerns for residential segments. This paper deals with two problems: the demonstration of cost-effectiveness of renewables in three different scenarios, and the application of the flexibility of demand, performing as energy storage systems, to efficiently manage the generation of renewable sources while improving benefits and avoiding penalties for the customer. A residential customer in Spain has been used as example. The work combines the use of a commercial simulator to obtain photovoltaic generation, the monitoring of customer to obtain demand patterns, and the development of a Physically-Based Model to evaluate the capability of demand to follow self-generation. As a main result, the integration of models (load/generation), neglected in practice in other approaches in the literature, allows customers to improve revenue up to 20% and reach a basic but important knowledge on how they can modify the demand, development of new skills and, in this way, learn how to deal with the characteristics and limitations of both Demand and Generation when a customer becomes a prosumer. This synergy amongst demand and generation physically-based models boosts the possibilities of customers in electricity markets.

ACS Style

Ana García-Garre; Antonio Gabaldón; Carlos Álvarez-Bel; María Del Carmen Ruiz-Abellón; Antonio Guillamón. Integration of Demand Response and Photovoltaic Resources in Residential Segments. Sustainability 2018, 10, 3030 .

AMA Style

Ana García-Garre, Antonio Gabaldón, Carlos Álvarez-Bel, María Del Carmen Ruiz-Abellón, Antonio Guillamón. Integration of Demand Response and Photovoltaic Resources in Residential Segments. Sustainability. 2018; 10 (9):3030.

Chicago/Turabian Style

Ana García-Garre; Antonio Gabaldón; Carlos Álvarez-Bel; María Del Carmen Ruiz-Abellón; Antonio Guillamón. 2018. "Integration of Demand Response and Photovoltaic Resources in Residential Segments." Sustainability 10, no. 9: 3030.

Journal article
Published: 06 August 2018 in Energies
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Load forecasting models are of great importance in Electricity Markets and a wide range of techniques have been developed according to the objective being pursued. The increase of smart meters in different sectors (residential, commercial, universities, etc.) allows accessing the electricity consumption nearly in real time and provides those customers with large datasets that contain valuable information. In this context, supervised machine learning methods play an essential role. The purpose of the present study is to evaluate the effectiveness of using ensemble methods based on regression trees in short-term load forecasting. To illustrate this task, four methods (bagging, random forest, conditional forest, and boosting) are applied to historical load data of a campus university in Cartagena (Spain). In addition to temperature, calendar variables as well as different types of special days are considered as predictors to improve the predictions. Finally, a real application to the Spanish Electricity Market is developed: 48-h-ahead predictions are used to evaluate the economical savings that the consumer (the campus university) can obtain through the participation as a direct market consumer instead of purchasing the electricity from a retailer.

ACS Style

María Del Carmen Ruiz-Abellón; Antonio Gabaldón; Antonio Guillamón. Load Forecasting for a Campus University Using Ensemble Methods Based on Regression Trees. Energies 2018, 11, 2038 .

AMA Style

María Del Carmen Ruiz-Abellón, Antonio Gabaldón, Antonio Guillamón. Load Forecasting for a Campus University Using Ensemble Methods Based on Regression Trees. Energies. 2018; 11 (8):2038.

Chicago/Turabian Style

María Del Carmen Ruiz-Abellón; Antonio Gabaldón; Antonio Guillamón. 2018. "Load Forecasting for a Campus University Using Ensemble Methods Based on Regression Trees." Energies 11, no. 8: 2038.

Journal article
Published: 11 February 2018 in Sustainability
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The objectives of improving the efficiency, and integration, of renewable sources by 2030–2050 are complex in practice and should be linked to an increase of demand-side flexibility. The main challenges to achieving this flexibility are the lack of incentives and an adequate framework. For instance, customers’ revenue is usually low, the volatility of prices is high and there is not any practical feedback to customers from smart meters. The possibility of increasing customer revenue could reduce the uncertainty with respect to economic concerns, improving investments in efficiency, enabling technology and thus, engaging more customers in these policies. This objective could be achieved by the participation of customers in several markets. Moreover, Demand Response and Energy Efficiency can share ICT technologies but this participation needs to perform an aggregation of demand. The idea of this paper is to present some methodologies for facilitating the definition and evaluation of energy versus cost curves; and subsequently to estimate potential revenues due to Demand Response. This can be accomplished by models that estimate: demand and energy aggregation; economic opportunities and benefits; impacts on customer convenience; customer feedback and price analysis. By doing so, we would have comprehensive information that can help customers and aggregators to define energy packages and their monetary value with the objective of fostering their market participation.

ACS Style

Antonio Gabaldón; Carlos Álvarez; María Del Carmen Ruiz-Abellón; Antonio Guillamón; Sergio Valero-Verdú; Roque Molina; Ana García-Garre. Integration of Methodologies for the Evaluation of Offer Curves in Energy and Capacity Markets through Energy Efficiency and Demand Response. Sustainability 2018, 10, 483 .

AMA Style

Antonio Gabaldón, Carlos Álvarez, María Del Carmen Ruiz-Abellón, Antonio Guillamón, Sergio Valero-Verdú, Roque Molina, Ana García-Garre. Integration of Methodologies for the Evaluation of Offer Curves in Energy and Capacity Markets through Energy Efficiency and Demand Response. Sustainability. 2018; 10 (2):483.

Chicago/Turabian Style

Antonio Gabaldón; Carlos Álvarez; María Del Carmen Ruiz-Abellón; Antonio Guillamón; Sergio Valero-Verdú; Roque Molina; Ana García-Garre. 2018. "Integration of Methodologies for the Evaluation of Offer Curves in Energy and Capacity Markets through Energy Efficiency and Demand Response." Sustainability 10, no. 2: 483.

Conference paper
Published: 01 October 2017 in CIRED - Open Access Proceedings Journal
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ACS Style

Carlos Álvarez; José I. Moreno; Gregorio López; Antonio Gabaldón; Maricarmen Ruiz; Javier Matanza; Antonio Guillamón; Sergio Valero-Verdú; Miguel López. Simplification and evaluation of demand response by the use of statistical aggregated models. CIRED - Open Access Proceedings Journal 2017, 2017, 2901 -2905.

AMA Style

Carlos Álvarez, José I. Moreno, Gregorio López, Antonio Gabaldón, Maricarmen Ruiz, Javier Matanza, Antonio Guillamón, Sergio Valero-Verdú, Miguel López. Simplification and evaluation of demand response by the use of statistical aggregated models. CIRED - Open Access Proceedings Journal. 2017; 2017 (1):2901-2905.

Chicago/Turabian Style

Carlos Álvarez; José I. Moreno; Gregorio López; Antonio Gabaldón; Maricarmen Ruiz; Javier Matanza; Antonio Guillamón; Sergio Valero-Verdú; Miguel López. 2017. "Simplification and evaluation of demand response by the use of statistical aggregated models." CIRED - Open Access Proceedings Journal 2017, no. 1: 2901-2905.

Conference paper
Published: 01 October 2017 in CIRED - Open Access Proceedings Journal
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ACS Style

Carlos Álvarez; José I. Moreno; Gregorio López; Camilo Carrillo; Ignacio J. Ramírez; Javier Matanza; Sergio Valero-Verdu; Antonio Gabaldón; Maricarmen Ruiz. Methodologies and proposals to facilitate the integration of small and medium consumers in smart grids. CIRED - Open Access Proceedings Journal 2017, 2017, 1895 -1898.

AMA Style

Carlos Álvarez, José I. Moreno, Gregorio López, Camilo Carrillo, Ignacio J. Ramírez, Javier Matanza, Sergio Valero-Verdu, Antonio Gabaldón, Maricarmen Ruiz. Methodologies and proposals to facilitate the integration of small and medium consumers in smart grids. CIRED - Open Access Proceedings Journal. 2017; 2017 (1):1895-1898.

Chicago/Turabian Style

Carlos Álvarez; José I. Moreno; Gregorio López; Camilo Carrillo; Ignacio J. Ramírez; Javier Matanza; Sergio Valero-Verdu; Antonio Gabaldón; Maricarmen Ruiz. 2017. "Methodologies and proposals to facilitate the integration of small and medium consumers in smart grids." CIRED - Open Access Proceedings Journal 2017, no. 1: 1895-1898.

Special section on managing electricity demand
Published: 30 December 2016 in Journal of Modern Power Systems and Clean Energy
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Demand response is a basic tool used to develop modern power systems and electricity markets. Residential and commercial segments account for 40%–50% of the overall electricity demand. These segments need to overcome major obstacles before they can be included in a demand response portfolio. The objective of this paper is to tackle some of the technical barriers and explain how the potential of enabling technology (smart meters) can be harnessed, to evaluate the potential of customers for demand response (end-uses and their behaviors) and, moreover, to validate customers’ effective response to market prices or system events by means of non-intrusive methods. A tool based on the Hilbert transform is improved herein to identify and characterize the most suitable loads for the aforesaid purpose, whereby important characteristics such as cycling frequency, power level and pulse width are identified. The proposed methodology allows the filtering of aggregated load according to the amplitudes of elemental loads, independently of the frequency of their behaviors that could be altered by internal or external inputs such as weather or demand response. In this way, the assessment and verification of customer response can be improved by solving the problem of load aggregation with the help of integral transforms.

ACS Style

Antonio Gabaldón; Roque Molina; Alejandro Marín-Parra; Sergio Valero-Verdú; Carlos Álvarez-Bel. Residential end-uses disaggregation and demand response evaluation using integral transforms. Journal of Modern Power Systems and Clean Energy 2016, 5, 91 -104.

AMA Style

Antonio Gabaldón, Roque Molina, Alejandro Marín-Parra, Sergio Valero-Verdú, Carlos Álvarez-Bel. Residential end-uses disaggregation and demand response evaluation using integral transforms. Journal of Modern Power Systems and Clean Energy. 2016; 5 (1):91-104.

Chicago/Turabian Style

Antonio Gabaldón; Roque Molina; Alejandro Marín-Parra; Sergio Valero-Verdú; Carlos Álvarez-Bel. 2016. "Residential end-uses disaggregation and demand response evaluation using integral transforms." Journal of Modern Power Systems and Clean Energy 5, no. 1: 91-104.

Journal article
Published: 11 October 2016 in Energies
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In this paper, we propose a novel approach for clustering time series, which combines three well-known aspects: a permutation-based coding of the time series, several distance measurements for discrete distributions and hierarchical clustering using different linkages. The proposed method classifies a set of time series into homogeneous groups, according to the degree of dependency among them. That is, time series with a high level of dependency will lie in the same cluster. Moreover, taking into account the nature of the codifying process, the method allows us to detect linear and nonlinear dependences. To illustrate the procedure, a set of fourteen electricity price series coming from different wholesale electricity markets worldwide was analyzed. We show that the classification results are consistent with the characteristics of the electricity markets in the study and with their degree of integration. Besides, we outline the necessity of removing the seasonal component of the price series before the analysis and the capability of the method to detect changes in the dependence level along time.

ACS Style

María Del Carmen Ruiz-Abellón; Antonio Gabaldón; Antonio Guillamón. Dependency-Aware Clustering of Time Series and Its Application on Energy Markets. Energies 2016, 9, 809 .

AMA Style

María Del Carmen Ruiz-Abellón, Antonio Gabaldón, Antonio Guillamón. Dependency-Aware Clustering of Time Series and Its Application on Energy Markets. Energies. 2016; 9 (10):809.

Chicago/Turabian Style

María Del Carmen Ruiz-Abellón; Antonio Gabaldón; Antonio Guillamón. 2016. "Dependency-Aware Clustering of Time Series and Its Application on Energy Markets." Energies 9, no. 10: 809.

Journal article
Published: 10 January 2014 in Energy Efficiency
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This paper is intended to explain how the possibilities of enabling technologies (advanced metering infrastructures) can be expanded on to evaluate end uses at the demand-side level. For example, these data allow validating the effective response to market prices (energy markets) or system events (demand response), and besides, the possibilities that energy efficiency offers (in capacity markets), mainly under the supervision of a load aggregator. Hilbert transform properties along with other mathematical tools are used to extract the characteristics of the more suitable uses for demand response policies from the aggregated load demand of the user. This is achieved without complex statistical analysis of the demand loads. The tool filters pulse waveforms (in this case, the components of daily demand) and provides the aggregator the main characteristics of load, both in normal state or under response to system events or market prices.

ACS Style

Antonio Gabaldón; Mario Ortiz-García; Roque Molina; Sergio Valero-Verdú. Disaggregation of the electric loads of small customers through the application of the Hilbert transform. Energy Efficiency 2014, 7, 711 -728.

AMA Style

Antonio Gabaldón, Mario Ortiz-García, Roque Molina, Sergio Valero-Verdú. Disaggregation of the electric loads of small customers through the application of the Hilbert transform. Energy Efficiency. 2014; 7 (4):711-728.

Chicago/Turabian Style

Antonio Gabaldón; Mario Ortiz-García; Roque Molina; Sergio Valero-Verdú. 2014. "Disaggregation of the electric loads of small customers through the application of the Hilbert transform." Energy Efficiency 7, no. 4: 711-728.

Journal article
Published: 01 January 2013 in International Journal of Power and Energy Systems
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ACS Style

Mario Ortiz; Sergio Valero; Antonio Gabaldón; Carlos Álvarez-Bel. CLASSIFICATION AND IDENTIFICATION OF POWER SYSTEM EVENTS USING HILBERT HUANG TRANSFORM. International Journal of Power and Energy Systems 2013, 33, 1 .

AMA Style

Mario Ortiz, Sergio Valero, Antonio Gabaldón, Carlos Álvarez-Bel. CLASSIFICATION AND IDENTIFICATION OF POWER SYSTEM EVENTS USING HILBERT HUANG TRANSFORM. International Journal of Power and Energy Systems. 2013; 33 (3):1.

Chicago/Turabian Style

Mario Ortiz; Sergio Valero; Antonio Gabaldón; Carlos Álvarez-Bel. 2013. "CLASSIFICATION AND IDENTIFICATION OF POWER SYSTEM EVENTS USING HILBERT HUANG TRANSFORM." International Journal of Power and Energy Systems 33, no. 3: 1.

Research article
Published: 31 October 2012 in Electric Power Systems Research
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The use of neural networks in load forecasting has been a popular research topic over the last decade. However, the use of Kohonen's self-organizing maps (SOM) for this purpose remains yet mostly unexplored. This paper presents a forecasting model based on this particular type of neural network. The scope of this study is not only to prove that SOM neural networks can be effectively used in load forecasting but to provide a deep and thorough analysis of the prediction and a real-world application. The data used to assess the validity of the model corresponds to Spain energy consumption from 2001 to 2010. Also meteorological data from this period has been used. The analysis comprises the study of the significance of different meteorological variables, the relevance of these meteorological data when recent load values are used as input and the effect of using different patterns to select the days to train the map. In addition, the evaluation of the frequency components of the data has provided an explanation to why apparently similar data sets allow different forecasting performances of the model. In order to build an application to the Spanish electricity market, the model was adjusted to timely forecast a load profile for each session of the daily and intra-daily markets. These forecasts are intended as an input to a decision support system for any commercializing company bidding on the market.

ACS Style

Miguel Lopez; S. Valero; C. Senabre; J. Aparicio; Antonio Gabaldon. Application of SOM neural networks to short-term load forecasting: The Spanish electricity market case study. Electric Power Systems Research 2012, 91, 18 -27.

AMA Style

Miguel Lopez, S. Valero, C. Senabre, J. Aparicio, Antonio Gabaldon. Application of SOM neural networks to short-term load forecasting: The Spanish electricity market case study. Electric Power Systems Research. 2012; 91 ():18-27.

Chicago/Turabian Style

Miguel Lopez; S. Valero; C. Senabre; J. Aparicio; Antonio Gabaldon. 2012. "Application of SOM neural networks to short-term load forecasting: The Spanish electricity market case study." Electric Power Systems Research 91, no. : 18-27.

Conference paper
Published: 01 July 2012 in 2012 IEEE Power and Energy Society General Meeting
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This paper proposes the use of an indicator of the predictability of the load series along with an accuracy value such as Mean Average Percentage Error as standard measures of load forecasting performance. Over the last 10 years, there has been a significant increase in load forecasting models proposed in engineering journals. Most of these models provide a description of the inner design of the model, the results from applying this model to a specific data base and the conclusions drawn from this application. However, a single accuracy value may not be sufficient to describe the performance of the model when applied to other data bases. The aim of this paper is to provide researchers with a tool that is able to assess the predictability of a load series and, therefore, contextualize the forecasting accuracy reported. Thirteen different data bases were used to determine its validity.

ACS Style

Miguel López; Sergio Valero; Carolina Senabre; Antonio Gabaldón. Short-term load forecasting: Revising how good we actually are. 2012 IEEE Power and Energy Society General Meeting 2012, 1 -6.

AMA Style

Miguel López, Sergio Valero, Carolina Senabre, Antonio Gabaldón. Short-term load forecasting: Revising how good we actually are. 2012 IEEE Power and Energy Society General Meeting. 2012; ():1-6.

Chicago/Turabian Style

Miguel López; Sergio Valero; Carolina Senabre; Antonio Gabaldón. 2012. "Short-term load forecasting: Revising how good we actually are." 2012 IEEE Power and Energy Society General Meeting , no. : 1-6.

Conference paper
Published: 01 May 2012 in 2012 9th International Conference on the European Energy Market
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There has been a significant production of load forecasting models over the last 5 years. These models present a wide variety of techniques, most of them using novel artificial intelligence approaches. Load forecasting is a complex matter and it is the result of several processes that, depending on the database, may be of more or less importance. However, most models focus their attention only on one process like the “forecasting engine”, neglecting other processes like variable selection or pre-processing. This paper proposes a standard scheme for load forecasting models that includes all sub-processes within load forecasting. The analysis of load forecasting models through this scheme allows identifying the effect of each process on the overall performance of the model. Also, proposing load forecasting models following this scheme will enhance benchmarking possibilities and hybridization of models. Finally, this paper presents such analysis of an actual load forecasting model.

ACS Style

M. Lopez; S. Valero; C. Senabre; J. Aparicio; Antonio Gabaldon. Standardization of short-term load forecasting models. 2012 9th International Conference on the European Energy Market 2012, 1 -7.

AMA Style

M. Lopez, S. Valero, C. Senabre, J. Aparicio, Antonio Gabaldon. Standardization of short-term load forecasting models. 2012 9th International Conference on the European Energy Market. 2012; ():1-7.

Chicago/Turabian Style

M. Lopez; S. Valero; C. Senabre; J. Aparicio; Antonio Gabaldon. 2012. "Standardization of short-term load forecasting models." 2012 9th International Conference on the European Energy Market , no. : 1-7.

Journal article
Published: 23 January 2012 in Entropy
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Several measures of volatility have been developed in order to quantify the degree of uncertainty of an energy price series, which include historical volatility and price velocities, among others. This paper suggests using the permutation entropy, topological entropy and the modified permutation entropy as alternatives to measure volatility in energy markets. Simulated data show that these measures are more appropriate to quantify the uncertainty associated to a time series than those based on the standard deviation or other measures of dispersion. Finally, the proposed method is applied to some typical electricity markets: Nord Pool, Ontario, Omel and four Australian markets.

ACS Style

Maria Del Carmen Ruiz; Antonio Guillamón; Antonio Gabaldón. A New Approach to Measure Volatility in Energy Markets. Entropy 2012, 14, 74 -91.

AMA Style

Maria Del Carmen Ruiz, Antonio Guillamón, Antonio Gabaldón. A New Approach to Measure Volatility in Energy Markets. Entropy. 2012; 14 (1):74-91.

Chicago/Turabian Style

Maria Del Carmen Ruiz; Antonio Guillamón; Antonio Gabaldón. 2012. "A New Approach to Measure Volatility in Energy Markets." Entropy 14, no. 1: 74-91.

Conference paper
Published: 01 May 2011 in 2011 8th International Conference on the European Energy Market (EEM)
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The study presented in this paper used Kohonen's Self-Organized Maps, which is one of the more uncommon techniques based on neural networks in load forecasting. The aim of this study is not only to show that this technique is capable of producing accurate short-term load forecasting results which should not be neglected, but also to provide a deep and thorough analysis of these results in order to extract solid conclusions about the inner design of the network, the selection of variables and also about the training periods. In addition, an application for the Spanish electricity market is developed.

ACS Style

M. Lopez; S. Valero; C. Senabre; J. Aparicio; Antonio Gabaldon. Development of a model for short-term load forecasting with neural networks and its application to the electrical Spanish market. 2011 8th International Conference on the European Energy Market (EEM) 2011, 321 -326.

AMA Style

M. Lopez, S. Valero, C. Senabre, J. Aparicio, Antonio Gabaldon. Development of a model for short-term load forecasting with neural networks and its application to the electrical Spanish market. 2011 8th International Conference on the European Energy Market (EEM). 2011; ():321-326.

Chicago/Turabian Style

M. Lopez; S. Valero; C. Senabre; J. Aparicio; Antonio Gabaldon. 2011. "Development of a model for short-term load forecasting with neural networks and its application to the electrical Spanish market." 2011 8th International Conference on the European Energy Market (EEM) , no. : 321-326.

Journal article
Published: 01 January 2010 in IET Generation, Transmission & Distribution
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The aim of this study is to propose a methodology in order to obtain a better support management decisions in terms of planning of bids and energy offers in real-time energy markets. Specifically, the authors use self-organising maps and statistical Ward's linkage to classify electricity market prices into different clusters (high homogeneity inside each cluster). In the second stage, the authors use non-parametric estimation to extract some price patterns in the above mentioned clusters. The knowledge contained within these patterns supplies customers with market-based information on which to focus its energy use decisions. The methodology proposed has been applied to New England (USA) market.

ACS Style

A. Gabaldón; A. Guillamón; M.C. Ruiz; S. Valero; C. Álvarez; M. Ortiz; C. Senabre. Development of a methodology for clustering electricity-price series to improve customer response initiatives. IET Generation, Transmission & Distribution 2010, 4, 706 -715.

AMA Style

A. Gabaldón, A. Guillamón, M.C. Ruiz, S. Valero, C. Álvarez, M. Ortiz, C. Senabre. Development of a methodology for clustering electricity-price series to improve customer response initiatives. IET Generation, Transmission & Distribution. 2010; 4 (6):706-715.

Chicago/Turabian Style

A. Gabaldón; A. Guillamón; M.C. Ruiz; S. Valero; C. Álvarez; M. Ortiz; C. Senabre. 2010. "Development of a methodology for clustering electricity-price series to improve customer response initiatives." IET Generation, Transmission & Distribution 4, no. 6: 706-715.