Article
Thermodynamics
Javier Valdes, Yunesky Masip Macia, Wolfgang Dorner, Luis Ramirez Camargo
Summary: Demand side management is a promising alternative for power systems with high shares of variable renewable energy sources. This study proposes a methodology to anonymize hourly electricity consumption profiles for industries and calculate their flexibility potential, finding significant flexibility potential in three case studies in Chile. The resulting demand profiles share the same statistical characteristics as the measured profiles but can be used in modeling exercises without confidentiality issues.
Article
Energy & Fuels
Mayank Jain, Mukta Jain, Tarek AlSkaif, Soumyabrata Dev
Summary: This paper discusses the application of clustering algorithms on electricity load demand profile datasets and the selection and applicability of cluster validation indices.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Review
Thermodynamics
Elisa Guelpa, Vittorio Verda
Summary: This paper is the first survey on the use of demand side application in district heating networks, clarifying the terminology and implementation stages. Demand side management is considered as a great technique for district heating management, achieving benefits such as peak shaving, doubled load factor, and reduction of primary energy needs.
Article
Construction & Building Technology
Mathieu Bourdeau, Philippe Basset, Solene Beauchene, David Da Silva, Thierry Guiot, David Werner, Elyes Nefzaoui
Summary: The study investigates clustering techniques on time series of daily electric load profiles in fourteen higher education buildings on the same campus, comparing different methods and analyzing the impact of data characteristics. Results indicate that using Euclidian distance under specific timeframes and time-steps provides the most consistent clustering results, revealing distinct patterns in electric load profiles of different building types.
ENERGY AND BUILDINGS
(2021)
Article
Thermodynamics
Hanguan Wen, Xiufeng Liu, Ming Yang, Bo Lei, Xu Cheng, Zhe Chen
Summary: Demand-side management is crucial to smart energy systems. This paper proposes a data-driven approach to understand the relationship between energy consumption patterns and household characteristics for better DSM services. The proposed method uses a clustering algorithm to generate optimal customer groups for DSM and a deep learning model for training. The model can predict the possibility of DSM membership for a given household. The results demonstrate the usefulness of weekly energy consumption data and household socio-demographic information for distinguishing consumer groups and the potential for targeted DSM strategies.
Article
Energy & Fuels
Jiaqi Ruan, Guolong Liu, Jing Qiu, Gaoqi Liang, Junhua Zhao, Binghao He, Fushuan Wen
Summary: This paper proposes a time-varying algorithm for estimating the price elasticity of demand (PED) in the smart energy system. It also introduces a demand-side smart dynamic pricing mechanism to encourage user participation in demand response programs. Experimental results demonstrate the feasibility of the proposed mechanism in reducing peak-to-average ratio (PAR) without exposure to price risk.
Article
Thermodynamics
Geremi Gilson Dranka, Paula Ferreira, A. Ismael F. Vaz
Summary: The study highlights the high potential of Demand-Response (DR) in power systems planning, which helps delay future investment in power capacity and reduce CO2 emissions. However, the limited potential of DR to integrate additional renewable plants and uncertainties related to future weather conditions need to be emphasized.
Article
Energy & Fuels
Rajesh K. Ahir, Basab Chakraborty
Summary: This paper presents a novel analysis framework to examine residential electricity consumption and understand consumption behavior through clustering analysis of energy usage patterns. The study emphasizes the importance of examining consumption habits and provides insights for better planning of future electricity needs for power utilities.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Engineering, Electrical & Electronic
Xiaohui Zhang, Ziyue Han, Junxin Cai, Jing Wu, Zhaoshuo Jin, Qiuxia Yang
Summary: This paper proposes a load management framework based on distributed clustering and introduces a heterogeneous load cluster response strategy, improving the efficiency and accuracy of load aggregation scheduling.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Aziah Khamis, M. H. Aiman, W. M. Faizal, C. Y. Khor
Summary: This study evaluates the impacts of integrating EV chargers into distribution networks and proposes a charging strategy. The proposed strategy manages the power in the distribution network during EV charger connection, reducing the impact of EV charging. Experimental results show that the proposed charging strategy can reduce peak active power losses by 2.2% to 3.2%.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Mathematics
Alessandro Niccolai, Gaia Gianna Taje, Davide Mosca, Fabrizio Trombello, Emanuele Ogliari
Summary: In the context of high dependency on fossil fuels, the efforts towards a more sustainable world are having significant economic and political impacts. This paper introduces a specific procedure for demand-side management in an industrial scenario, using evolutionary algorithms and considering different cost factors.
Article
Engineering, Electrical & Electronic
Christian Hecht, David Sprake, Yuriy Vagapov, Alecksey Anuchin
Summary: This paper provides a high-accuracy assessment of domestic demand-side management approach in the context of distributed renewable energy sources, showing an increase of 3% in self-consumption ratio in the microgrid under DSM. The study highlights the potential benefits of implementing DSM under the impact of RES for efficiency assessment of various load shifting methods.
ELECTRICAL ENGINEERING
(2021)
Review
Energy & Fuels
Eity Sarker, Pobitra Halder, Mehdi Seyedmahmoudian, Elmira Jamei, Ben Horan, Saad Mekhilef, Alex Stojcevski
Summary: The integration of demand side management with smart grid can promote residents' transition into smart homes and sustainable cities by reducing carbon emissions. Previous literature has shown that DSM practice can effectively reduce energy costs and carbon emissions, but challenges in SG implementation include security, privacy, tariff regulation, energy transmission, distribution, and effective energy resource utilization. Various international organizations have taken measures to ensure the security and privacy of DSM in SG, and hybrid algorithms have shown better performance in optimizing DSM problems compared to single algorithms. Overall, the paper highlights research gaps and future directions in this field.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Wagner J. F. Silva, Pedro J. C. Souza, Renata M. C. R. Souza, Francisco Jose A. Cysneiros
Summary: This paper introduces a dynamical clustering algorithm for symbolic polygonal data and applies it to build scientific journals profiles. The study reveals that one of the main variables describing journals is the number of difficult words in the abstract.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Energy & Fuels
Henrique S. Eichkoff, Daniel P. Bernardon, Julio A. Bitencourt, Vinicius J. Garcia, Daiana W. Silva, Lucas M. Chiara, Sebastian A. Butto, Solange M. K. Barbosa, Alejandre C. A. Pose
Summary: This study introduces a demand-side management methodology to address the problem of excessive loading on power grids due to irrigation activities in rural areas of southern Brazil. By adjusting the load of irrigation customers, the study proposes a load shifting strategy to reduce demand during peak periods and shift it to lower load periods. The results show that this model can reduce maximum demand and daily load variations, ensuring the continuity of electric power supply and benefiting both customers and power utilities.
Article
Computer Science, Information Systems
Eslam Montaser, Jose-Luis Diez, Paolo Rossetti, Mudassir Rashid, Ali Cinar, Jorge Bondia
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2020)
Article
Automation & Control Systems
Ricardo Sanz, Pedro Garcia, Jose-Luis Diez, Jorge Bondia
Summary: This brief focuses on closed-loop control of postprandial glucose levels in patients with type 1 diabetes after unannounced meals, introducing a strategy utilizing a disturbance observer to estimate the effect of meals and a feedforward compensator for insulin pharmacokinetics. The proposed method successfully prevents hypoglycemia and maintains glucose levels within range, even in scenarios with high carbohydrate content and variability.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2021)
Review
Chemistry, Analytical
Elena Munoz Fabra, Jose-Luis Diez, Jorge Bondia, Alejandro Jose Laguna Sanz
Summary: CGM monitoring during exercise periods is less accurate and can impact CGM-based treatments for diabetes patients. Most papers did not provide accuracy metrics that differentiated between exercise and rest (non-exercise) periods, hindering comparative data analysis.
Article
Cardiac & Cardiovascular Systems
Raul Moreno, Jose-Luis Diez, Jose-Antonio Diarte, Pablo Salinas, Jose Maria de la Torre Hernandez, Juan F. Andres-Cordon, Ramiro Trillo, Juan Alonso Briales, Ignacio Amat-Santos, Rafael Romaguera, Jose-Francisco Diaz, Beatriz Vaquerizo, Soledad Ojeda, Ignacio Cruz-Gonzalez, Daniel Morena-Salas, Armando Perez de Prado, Fernando Sarnago, Pilar Portero, Alejandro Gutierrez-Barrios, Fernando Alfonso, Eduard Bosch, Eduardo Pinar, Jose-Ramon Ruiz-Arroyo, Valeriano Ruiz-Quevedo, Jesus Jimenez-Mazuecos, Fernando Lozano, Jose-Ramon Rumoroso, Enrique Novo, Francisco J. Irazusta, Bruno Garcia Del Blanco, Jose Moreu, Sara M. Ballesteros-Pradas, Araceli Frutos, Manuel Villa, Eduardo Alegria-Barrero, Rosa Lazaro, Emilio Paredes
Summary: During the COVID-19 pandemic, elective invasive cardiac procedures (ICP) have been frequently cancelled or postponed, leading to higher mortality and cardiovascular mortality in patients with diabetes. It is important to prioritize clinical management for diabetic patients in whom ICP procedures are cancelled or postponed.
CARDIOVASCULAR DIABETOLOGY
(2021)
Article
Chemistry, Analytical
Eslam Montaser, Jose-Luis Diez, Jorge Bondia
Summary: Accurate glucose prediction is crucial for improving type 1 diabetes treatment, but faces challenges due to patient variability. Clustering and local modeling techniques, combined with seasonal stochastic models, have shown promise in achieving accurate long-term glucose predictions.
Article
Computer Science, Interdisciplinary Applications
S. Faccioli, I. Sala-Mira, J. L. Diez, A. Facchinetti, G. Sparacino, S. Del Favero, J. Bondia
Summary: Hybrid automated insulin delivery systems rely on carbohydrate counting for postprandial control in type 1 diabetes, which can be burdensome and prone to errors. This study proposes an automated meal detection algorithm and evaluates its performance on real-life data. The results show a high recall and precision for the algorithm, but there are still false positives and false negatives, which are associated with low-risk situations.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2022)
Article
Energy & Fuels
Ignacio Benitez, Jose-Luis Diez
Summary: This article reviews and studies the application of dynamic clustering techniques for analyzing time patterns of energy consumption. The performance comparison of different algorithms helps experts evaluate and predict energy consumption scenarios.
Article
Education & Educational Research
Jose-Luis Diez, Amparo Ramos, Carlos Candela
Summary: Gender stereotypes still influence students' career choices, particularly in the under-representation of women in the fields of science, technology, engineering, and mathematics. Boys have more stereotypes than girls, and this difference is especially prevalent among students who intend to study engineering. These gender stereotypes have increased over the past 10 years.
INTERNATIONAL JOURNAL OF TECHNOLOGY AND DESIGN EDUCATION
(2023)
Article
Computer Science, Interdisciplinary Applications
Ivan Sala-Mira, Pedro Garcia, Jose-Luis Diez, Jorge Bondia
Summary: The study extends a hybrid artificial pancreas system with an add-on module that relieves patients from the need to announce meals and exercise. The add-on module utilizes an internal-model controller to generate a virtual control action for compensation, resulting in improved blood glucose control performance.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2022)
Article
Biochemistry & Molecular Biology
Jose-Luis Diez, Vicente Masip-Moret, Asuncion Santafe-Moros, Jose M. Gozalvez-Zafrilla
Summary: Peristaltic pumping combined with three artificial intelligence control strategies were used to regulate a microfiltration system under high fouling conditions. Different control approaches showed varying degrees of performance and dynamics, with artificial neural networks achieving specifications but demonstrating poor dynamics, expert control showing fast response but encountering problems in certain working areas, and local models requiring less data yet achieving high accuracy and robustness. The choice of control technique depends on available information and application dynamics requirements.
Article
Chemistry, Analytical
Francesco Prendin, Jose-Luis Diez, Simone Del Favero, Giovanni Sparacino, Andrea Facchinetti, Jorge Bondia
Summary: Accurate blood glucose forecasting is essential in diabetes management. This study introduces a methodology called C-SARIMA, which utilizes seasonal stochastic models to predict blood glucose levels in real-time. The results show that C-SARIMA performs well compared to other linear and nonlinear black-box methods.
Proceedings Paper
Automation & Control Systems
Clara Furio-Novejarque, Ricardo Sanz, Asbjorn Thode Reenberg, Tobias K. S. Ritschel, Ajenthen G. Ranjan, Kirsten Norgaard, Jose-Luis Diez, John Bagterp Jorgensen, Jorge Bondia
Summary: A novel insulin-glucagon-glucose model is proposed in this study, which describes the effect of glucagon on endogenous glucose production (EGP) through the dynamics of glucagon receptors. The model is validated and shown to explain some glucagon-related phenomena observed in clinical data. This physiology-focused model is important for the development of artificial pancreas algorithms.
Proceedings Paper
Engineering, Biomedical
Corinna Schroeder, Jose Luis Diez, Alejandro J. Laguna, Jorge Bondia, Cristina Tarin
2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
(2019)
Meeting Abstract
Endocrinology & Metabolism
J. L. Diez, E. Montaser, M. Rashid, A. Cinar, J. Bondia
DIABETES TECHNOLOGY & THERAPEUTICS
(2019)
Article
Engineering, Electrical & Electronic
Wandry R. Faria, Gregorio Munoz-Delgado, Javier Contreras, Benvindo R. Pereira Jr
Summary: This paper proposes a new bilevel mathematical model for competitive electricity markets, taking into account the participation of distribution systems operators. A new pricing method is introduced as an alternative to the inaccessible dual variables of the transmission system.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Chao Zhang, Liwei Zhang, Dong Wang, Kaiyuan Lu
Summary: The load disturbance rejection ability of electrical machine systems is crucial in many applications. Existing studies mainly focus on improving disturbance observers, but the speed response control during the transient also plays a significant role. This paper proposes a sliding mode disturbance observer-based load disturbance rejection control with an adaptive filter and a Smith predictor-based speed filter delay compensator to enhance the transient speed response.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Arif Hussain, Arif Mehdi, Chul-Hwan Kim
Summary: The proposed scheme in this research paper is a communication-less islanding detection system based on recurrent neural network (RNN) for hybrid distributed generator (DG) systems. The scheme demonstrates good performance in feature extraction, feature selection, and islanding detection, and it also performs effectively in noisy environments.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Zonghui Sun, Xizheng Guo, Shinan Wang, Xiaojie You
Summary: This paper presents a status pre-matching method (SPM) that eliminates the iterative calculations for resistance switch model, and simulates all operation modes of PECs through a more convenient approach. Furthermore, a FPGA implementation scheme is proposed to fully utilize the multiplier units of FPGA.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Rui Zhou, Shuheng Chen, Yang Han, Qunying Liu, Zhe Chen, Weihao Hu
Summary: In power system scheduling with variable renewable energy sources, considering both spatial and temporal correlations is a challenging task due to the complex intertwining of spatiotemporal characteristics and computational complexity caused by high dimensionality. This paper proposes a novel probabilistic spatiotemporal scenario generation (PSTSG) method that generates probabilistic scenarios accounting for spatial and temporal correlations simultaneously. The method incorporates Latin hypercube sampling, copula-importance sampling theory, and probability-based scenario reduction technique to efficiently capture the spatial and temporal correlation in the dynamic optimal power flow problem. Numerical simulations demonstrate the superiority of the proposed approach in terms of computational efficiency and accuracy compared to existing methods.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Juan Manuel Mauricio, J. Carlos Olives-Camps, Jose Maria Maza-Ortega, Antonio Gomez-Exposito
Summary: This paper proposes a simplified thermal model of VSC, which can produce accurate results at a low computational cost. The model consists of a simple first-order thermal dynamics system and two quadratic equations to model power losses. A methodology is also provided to derive the model parameters from manufacturer data.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Jae-Kyeong Kim, Kyeon Hur
Summary: This paper investigates the relationship between the accuracy of finite difference-based trajectory sensitivity (FDTS) analysis and the perturbation size in non-smooth systems. The study reveals that the approximation accuracy is significantly influenced by the perturbation size, and linear approximation is the most suitable method for practical applications.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yuan Si, Amjad Anvari-Moghaddam
Summary: This paper investigates the impact of geomagnetic disturbances on small signal stability in power systems and proposes the installation of blocking devices to mitigate the negative effects. Quantitative evaluation reveals that intense geomagnetic disturbances significantly increase the risk of small signal instability. Optimal placement of blocking devices based on sensitivity scenarios results in a significant reduction in the risk index compared to constant and varying induced geoelectric fields scenarios.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xuejian Zhang, Wenxin Kong, Nian Yu, Huang Chen, Tianyang Li, Enci Wang
Summary: The intensity estimation of geomagnetically induced currents (GICs) varies depending on the method used. The estimation using field magnetotelluric (MT) data provides the highest accuracy, followed by the estimation using 3D conductivity models and the estimation using a 1D conductivity model. The GICs in the North China 1000-kV power grid have reached a very high-risk level, with C3 and C4 having a significant impact on the geoelectric field and GICs.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yue Pan, Shunjiang Lin, Weikun Liang, Xiangyong Feng, Xuan Sheng, Mingbo Liu
Summary: This paper introduces the concept and model of offshore-onshore regional integrated energy system, and proposes a stochastic optimal dispatch model and an improved state-space approximate dynamic programming algorithm to solve the model. The case study demonstrates the effectiveness and high efficiency of the proposed method in improving economic and environmental benefits.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Mohammad Eydi, Reza Ghazi, Majid Oloomi Buygi
Summary: Proportional current sharing, voltage restoration, and SOCs balancing in DC microgrid control algorithms are the leading challenges. This paper proposes a novel communication-less control method using a capacitor and a DC/DC converter to stabilize the system and restore the DC bus voltage. The method includes injecting an AC signal into the DC bus, setting the current of energy storage units based on frequency and SOC, and incorporating droop control for system stability. Stability analysis and simulation results validate the effectiveness of the proposed method.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xiangjian Meng, Xinyu Shi, Weiqi Wang, Yumin Zhang, Feng Gao
Summary: With the increasing penetration of photovoltaic power generation, regional power forecasting becomes critical for stable and economical operation of power systems. This paper proposes a minute-level regional PV power forecasting scheme using selected reference PV plants. The challenges include the lack of complete historical power data and the heavy computation burden. The proposed method incorporates a novel reference PV plant selection method and a flexible approach to decrease the accumulated error of rolling forecasting.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Huabo Shi, Yuhong Wang, Xinwei Sun, Gang Chen, Lijie Ding, Pengyu Pan, Qi Zeng
Summary: This article investigates the dynamic stability characteristics of the full size converter variable speed pumped storage unit and proposes improvements for the control strategy. The research is important for ensuring the safe and efficient operation of the unit.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Firmansyah Nur Budiman, Makbul A. M. Ramli, Houssem R. E. H. Bouchekara, Ahmad H. Milyani
Summary: This paper proposes an optimal harmonic power flow framework for the daily scheduling of a grid-connected microgrid, which addresses power quality issues and ensures effective control through demand side management.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Cong Zeng, Ziyu Chen, Jizhong Zhu, Fellew Ieee
Summary: This paper introduces a distributed solution method for the multi-objective OPF problem, using a coevolutionary multi-objective evolutionary algorithm and the idea of decomposition. The problem is alleviated by decomposing decision variables and objective functions, and a new distributed fitness evaluation method is proposed. The experimental results demonstrate the effectiveness of the method and its excellence in large-scale systems.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
