Artículos (Ingeniería Eléctrica)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11352

Examinar

Mostrando 1 - 20 de 231

An evolutionary computational approach for the identification of distribution networks models
(Elsevier, 2024-11) Rodríguez del Nozal, Álvaro; Carmona Pardo, Rubén; Mauricio Ferramola, Juan Manuel; Romero Ramos, Esther; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
In this paper, we present a novel methodology for generating low-voltage distribution network models. The methodology is based on leveraging the existing knowledge of the network topology and a comprehensive catalog of the conductors that are installed in each segment of the grid. By using genetic algorithms and data obtained from the smart-meters in the network, the proposed method can produce highly accurate network models. The effectiveness of this methodology has been confirmed by extensive simulation studies achieving errors of less than 0.4 V in the estimation of nodal voltages in scenarios without measurements noise and on the order of the standard deviation of the error considered in the measurements when disturbances are added to the problem.
A sustainable electricity market design: Application to the Iberian market
(2024-11) Dorado Galatoire, Erick Andrés; Núñez Hernández, Fernando; Arcos Vargas, Ángel; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Universidad de Sevilla. Departamento de Organización Industrial y Gestión de Empresas I; Ministerio de Ciencia, Innovación y Universidades (MICIU). España; Agencia Estatal de Investigación. España; European Commission (EC). Plan de Recuperación, Transformación y Resiliencia de la UE (Next Generation EU/PRTR); European Commission (EC). Fondo Social Europeo Plus (ESF+); Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
Current electricity markets are not moving fast enough towards decarbonization, nor are they ensuring the economic sustainability of the different supply technologies in the short-term –cannibalization and depredation problems–. To solve these problems, this study presents an innovative market design to achieve a sustainable electricity system based on cleaner production. Based on the assumption that the energy supplied by manageable and non-manageable generators can be considered as two different goods, we propose a two-market system within the day-ahead market where non-manageable generators operate in the first market through long-term contracts and manageable generators operate in the (marginalist) second market. Under this system, the regulator appropriates an economic surplus that is given by the difference –produced in the first market– between what is received from the buyers in this market (second market's equilibrium price) and what is paid to each non-manageable generator (levelized cost of energy). This public surplus will be used to cover part of the regulated costs of the electricity system, lowering the final price of electricity. To simulate empirically our two-market design, we use hourly microdata from the supply and demand curves of the Iberian day-ahead market. The results of this case study are promising, showing a decrease in the electricity prices and CO2 emissions, an increase in the amount of energy exchanged and the obtainment of a surplus for the regulator of 5,753 M€ in 2021 and 9,944 M€ in 2022. The proposed design ensures the economic sustainability of intermittent renewables as well as provides signals for long-term investment in the deployment of flexible carbon-free resources.
Additional revenues estimation in a market-based redispatch: An opportunity for flexibility
(2024-10) Dorado Galatoire, Erick Andrés; Arcos Vargas, Ángel; Martínez Ramos, José Luis; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Universidad de Sevilla. Departamento de Organización Industrial y Gestión de Empresas I; Ministerio de Ciencia, Innovación y Universidades (MICIU). España; Agencia Estatal de Investigación. España; European Commission (EC). Plan de Recuperación, Transformación y Resiliencia de la UE (Next Generation EU/PRTR); European Commission (EC). Fondo Social Europeo Plus (ESF+); Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
The technical constraints in the transmission networks are exerting significant strain on the functioning of electricity markets as the share of variable renewable energy sources is increasing. To manage this issue, the transition to a nodal pricing market has been proposed in the literature. Given that the current structure of the European Union electricity market corresponds to a zonal pricing, the transition to nodal pricing would imply fundamental changes in its market structure. In order to avoid the latter, this study develops a method to identify locational price signals in a decentralized market with zonal pricing and subsequent market-based redispatch. To this end, first, nodes with structural technical constraints are identified –using energy programmes–. Then, the additional revenues of physical units located at these nodes are estimated –using electricity prices–. Finally, this strategic information will guide the development of flexibility solutions –manageable generation capacity and demand response– in these geographic locations, mimicking the main advantage of nodal pricing. Our methodology has been empirically tested on the Spanish power system, using hourly data from the System Operator and Market Operator for four full years, from 2019 to 2022. The results show a higher and constant economic revenue in certain nodes of this system –upward redispatch price is 74.90% higher than day-ahead market price–. Thus, this method can be used by market participants to evaluate publicly available data from a decentralized market with zonal pricing and subsequent market-based redispatch, and obtain essential information to make the best investment decisions.
Low-Cost, Low-Power Edge Computing System for Structural Health Monitoring in an IoT Framework
(Multidisciplinary Digital Publishing Institute (MDPI), 2024-08) Hidalgo Fort, Eduardo; Blanco-Carmona, Pedro; Muñoz Chavero, Fernando; Torralba Silgado, Antonio Jesús; Castro-Triguero, Rafael; Universidad de Sevilla. Departamento de Ingeniería Electrónica; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Universidad de Sevilla. TIC192: Ingeniería Eléctronica
A complete low-power, low-cost and wireless solution for bridge structural health monitoring is presented. This work includes monitoring nodes with modular hardware design and low power consumption based on a control and resource management board called CoreBoard, and a specific board for sensorization called SensorBoard is presented. The firmware is presented as a design of FreeRTOS parallelised tasks that carry out the management of the hardware resources and implement the Random Decrement Technique to minimize the amount of data to be transmitted over the NB-IoT network in a secure way. The presented solution is validated through the characterization of its energy consumption, which guarantees an autonomy higher than 10 years with a daily 8 min monitoring periodicity, and two deployments in a pilot laboratory structure and the Eduardo Torroja bridge in Posadas (Córdoba, Spain). The results are compared with two different calibrated commercial systems, obtaining an error lower than 1.72% in modal analysis frequencies. The architecture and the results obtained place the presented design as a new solution in the state of the art and, thanks to its autonomy, low cost and the graphical device management interface presented, allow its deployment and integration in the current IoT paradigm.
Implementation and validation of a dual P- and M- class compliant PMU prototype based on the delayed in-quadrature interpolated DFT
(Elsevier, 2024-11) García-Veloso, César; Paolone, Mario; Maza Ortega, José María; Karpilow, Alexandra; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Caixa Catalunya; Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
In this paper, the design and experimental validation of a prototype phasor measurement unit (PMU) that simultaneously meets the P and M class requirements of the IEC/IEEE Std 60255-118-1-2018 are presented. The device is based on a synchrophasor estimation (SE) algorithm, previously formulated by the authors, which exploits the generation and use of a delayed in-quadrature complex signal to mitigate the self-interference of the fundamental tone. The method is deployed to a NI CompactRIO-9039 platform, requiring a total use of 19.2% flip-flops, 50.6% LUTs, 77.9% DSPs and 13.7% BRAM for a single-channel configuration and operating under a 50-fps report rate, 50 kHz sampling rate, and three nominal cycle observation windows. A PMU calibrator is used to perform a comprehensive metrological analysis of the device and verify its compliance with the standard. The results show that the prototype meets the requirements of both P and M classes with a worst-case measurement reporting latency of 36.21 ms.
Impact of renewables on the Peruvian electricity system
(Elsevier, 2024-10-15) Fiestas-Chévez, Hugo; Roldán Fernández, Juan Manuel; Trigo García, Ángel Luis; Burgos Payán, Manuel; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Junta de Andalucía; Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
Peru is committed by international agreements such as the Paris Agreement and the UN 2030 Agenda for Sustainable Development to reduce its Green House Gas (GHG) emissions. Although Peru began promoting power plant projects based on renewable energies in 2008, the institutional impulse seems to have ceased today. Nonetheless, adopting renewable energy sources not only aids in fulfilling these commitments but also reduces electricity prices, fostering a more competitive economy. This study aims to provide a thorough analysis and evaluation of the impact that integrating Non-Conventional Renewable Energy Resources (NCRER) has on Peru's wholesale electricity market. Specifically, it focuses on the net total savings for the system, calculated as the difference between the reduction in energy costs traded and the cost of the renewable premium. To reach that goal a simplified yet analytical tool has been developed based on a multivariable regression of the real data of the market. The volume of natural gas not consumed and the volume of GHG emissions avoided will also be evaluated. The results show that based on the 2021 scenario, a NCRER share of 28.26% would lead to a net saving for the final users of 316.04 MUSD in the annual energy traded in the market. The reduction of conventional thermal generation prevents the annual burning of 2.04 normal km3 of natural gas and the emission of 4.99 million tons of CO2-eq. To the authors' knowledge, this is the first time that the impact of NCRER production in the Peruvian electricity system has been quantitatively evaluated.
Las interconexiones eléctricas como habilitadoras de la transición energética
(Ministerio de Industria, Energía y Turismo, 2024) Almagro Yravedra, Fernando; Marano-Marcolini, Alejandro; Martínez Ramos, José Luis; Universidad de Sevilla. Departamento de Ingeniería Energética; Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
En este artículo se pone de relieve la importancia de las interconexiones eléctricas en tres aspectos: la seguridad del suministro, el coste de la energía eléctrica, y la capacidad de integrar generación renovable. Para cada uno se presentan ejemplos en el ámbito del sistema eléctrico europeo, repasando eventos en los que la seguridad, el coste o la penetración renovable supusieron retos para la operación segura del sistema. Finalmente, se describe la situación de las interconexiones del sistema español, destacando los beneficios que aportan en la red actual y las oportunidades que ofrecerían las interconexiones previstas para los próximos años.
Estimation of Equivalent Model of Photovoltaic Array Using Unscented Kalman Filters
(State Grid Electric Power Research Institute (SGEPRI), 2024-05) González Cagigal, Miguel Ángel; Rosendo Macías, José Antonio; Gómez Expósito, Antonio; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
This paper proposes the use of the unscented Kalman filter to estimate the equivalent model of a photovoltaic (PV) array, using external measurements of current and voltage at the inverter level. The estimated model is of interest to predict the power output of PV plants, in both planning and operation scenarios, and thus improves the efficient operation of power systems with high penetration of renewable energy. The proposed technique has been assessed in several simulated scenarios under different operating conditions. The results show that accurate estimates are provided for the model parameters, even in the presence of measurement noise and abrupt variations under the external conditions.
A neural network-based classifier for identifying and locating neutral wire breaks in low voltage distribution networks
(Elsevier, 2024-09) Carmona Pardo, Rubén; Rodríguez del Nozal, Álvaro; Romero Ramos, Esther; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
The breakage of the neutral conductor in low voltage distribution networks is a major concern for distribution companies. This breakage causes significant voltage deviations that can damage the connected equipment as well as jeopardizing people. The detection and localization of the breakage is a major challenge as it does not always manifest in the same way. This work presents a methodology based on artificial intelligence for the detection and localization of neutral conductor breaks in distribution networks. Two neural networks are trained in attempt to solve each of the challenges. For this purpose, measurements commonly taken by smartmeters such as power and nodal voltages are used. The methodology is evaluated in simulation exhibiting a good performance.
Model-Based Control for Power Converters With Variable Sampling Time: A Case Example Using Five-Phase Induction Motor Drives
(Institute of Electrical and Electronics Engineers Inc. (IEEE), 2019-08) Arahal, Manuel R.; Martín Torres, Cristina; Barrero, Federico; González Prieto, Ignacio; Durán, Mario J.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Ministerio de Economía y Competitividad (MINECO). España; Universidad de Sevilla; Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica; Universidad de Sevilla. TIC201: ACE-TI
Discrete-time control of power converters without modulation blocks have been considered in recent times in modern high-performance electromechanical drives, particularly with the appearance of model predictive control in its finite set version. The shortcomings produced by the fixed discretization of time used in this kind of control systems has been analyzed, and several methods have been put forward to deal with them. Most of the alternatives increase the complexity of the controller introducing different analytical modulation methods. However, a variable sampling time can be a simpler and more natural solution, at the expense of using a less-known paradigm for implementation. This paper introduces a new control approach based on a model of the system as in predictive controllers but using variable sampling time. It can be applied to modern power converters and drives, including conventional three-phase or advanced multiphase ones. Experimental results are provided to test the ability of the controller using a five-phase induction motor drive as a case example.
Influence of Covariance-Based ALS Methods in the Performance of Predictive Controllers With Rotor Current Estimation
(Institute of Electrical and Electronics Engineers Inc. (IEEE), 2017-04) Rodas, Jorge; Martín Torres, Cristina; Arahal, Manuel R.; Barrero, Federico; Gregor, Raúl; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Ministerio de Ciencia e Innovación (MICIN). España; Universidad de Sevilla; Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
The use of online rotor current estimators with predictive current controllers has been very recently stated in five-phase induction motor drives, where the closed-loop performance of the system is improved by using suboptimal estimators based on Kalman filters. In this paper, the interest of using optimization methods in the definition of the Kalman filter, like the covariance technique, is analyzed. Obtained system performances using optimal and suboptimal rotor current estimators are experimentally compared.
Five-Phase Induction Motor Rotor Current Observer for Finite Control Set Model Predictive Control of Stator Current
(Institute of Electrical and Electronics Engineers Inc. (IEEE), 2016-07) Martín Torres, Cristina; Arahal, Manuel R.; Barrero, Federico; Durán, Mario J.; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
Model predictive control (MPC) has recently been applied to induction motor (IM) drives in a configuration known as finite control set MPC (FCS-MPC). Its implementation must solve the problem of estimating rotor quantities, a task that is usually done using a simple backtracking procedure. On the other hand, observers have been used with field-oriented control (FOC), sensorless drives, and for fault detection but they have not been used yet for finite control set predictive current control of drives. This paper shows the benefits of incorporating a rotor current observer in a finite control set model predictive controller for the stator current of a five-phase drive. The observer design methodology employed in this work uses pole placement based on Butterworth filter design. The new estimation scheme is compared with the standard one in which nonmeasurable state components and other variables are lumped into one term that is updated. The differences between both approaches are experimentally analyzed and verified.
Multiphase rotor current observers for current predictive control: A five-phase case study
(Elsevier, 2016-04) Martín Torres, Cristina; Arahal, Manuel R.; Barrero, Federico; Durán, Mario J.; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Junta de Andalucía; Ministerio de Economía y Competitividad (MINECO). España; Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
The use of multiphase drives has gained importance in recent times due to some advantages that they provide over conventional three-phase ones. High performance stator current control can be achieved by means of direct command of voltage source inverter. In this context finite-state model predictive control is a very flexible strategy that has been recently proposed and analyzed. Nevertheless, its implementation must solve the problem of estimating rotor quantities, being the conventional solution a simple backtracking procedure. In this respect, observers appear as an attractive alternative. However, while they have been used with FOC, sensorless drives and for fault detection, they have not been used yet for predictive control of drives as a way to provide rotor values estimates. In this paper the authors propose to incorporate a full-order rotor current observer in a finite-state model predictive controller of a five-phase induction machine. Pole placement design based on Butterworth filters is used. The new estimation scheme and the standard procedure are compared. By means of experimental tests, the differences between both approaches and the benefits of including a rotor observer are illustrated and verified.
Open-Switch Fault Detection in Five-Phase Induction Motor Drives Using Model Predictive Control
(Institute of Electrical and Electronics Engineers (IEEE), 2018-04) González Prieto, Ignacio; Duran, Mario J.; Ríos García, Natalia; Barrero, Federico; Martín Torres, Cristina; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Ministerio de Ciencia e Innovación (MICIN). España; Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
Achieving a self-reconfigurable fault-tolerant control in multiphase machines requires a fast fault detection and localization. Most fault detection techniques inherit the three-phase approach by defining fault indices in a per-phase basis. A recent approach suggests an alternative fault detection mechanism based on vector space decomposition (VSD) variables, but the study is limited to open-phase faults (OPFs) for a six-phase drive that is regulated under field-oriented control. It is known, however, that 1) the open-switch faults (OSFs) in the converter are more likely than the OPF in the machine and 2) the drive performance in the event of an open-circuit fault is more critical when model predictive control (MPC) is used. This work extends the study of the VSD fault detection method to multiphase machines with different number of phases (five), control strategy (MPC), and type of faults (OPF and OSF). Although experimental results show that MPC misbehaves after the fault occurrence, the fast detection provided by the VSD approach allows a satisfactory transition to postfault mode of operation.
Model Predictive Control of Six-Phase Induction Motor Drives Using Virtual Voltage Vectors
(Institute of Electrical and Electronics Engineers (IEEE), 2018-06) González Prieto, Ignacio; Duran, Mario J.; Aciego, Juan José; Martín Torres, Cristina; Barrero, Federico; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
The most serious and recent competitor to the standard field oriented control for induction motors (IM) is the finite control set model predictive control (FCS-MPC). Nevertheless, the extension to multiphase drives faces the impossibility to simultaneously regulate the flux/torque and the secondary current components (typically termed $x-y$ in the literature). The application of a single switching state during the whole sampling period inevitably implies the appearance of $x-y$ voltage/currents that increase the system losses and deteriorate the power quality. These circulating currents become intolerably high as per the unit $x-y$ impedance and the switching frequency diminish. Aiming to overcome this limitation, this work suggests the integration of virtual voltage vectors (VVs) into the FCS-MPC structure. The VVs ensure null $x-y$ voltages on average during the sampling period and the MPC approach selects the most suitable VV to fulfill the flux/torque requirements. The experimental results for a six-phase case study compare the standard FCS-MPC with the suggested method, confirming that the VV-based MPC maintains the flux/torque regulation and successfully improves the power quality and efficiency.
Improving partial discharges location under dispersion and multi-path propagation
(Elsevier, 2021-05) Granado Romero, Joaquín; Torralba Silgado, Antonio Jesús; Álvarez Arroyo, Cesar; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. TIC192: Ingeniería Electrónica
Dispersion and multi-path propagation distort partial discharge (PD) pulses that travel along power cables. Two new techniques to improve the location accuracy using double-ended methods are proposed: the inclusion of a pre-filter (PF), that increases the signal to noise ratio by properly selecting the filter bandwidth and the center frequency, and an echo suppression (ES) technique, that reduces the peak value of the interfering echoes. Two location algorithms (based on cross-correlation and the energy criterion function) are combined with the proposed techniques and their performances against noise, dispersion, and multi-path propagation are evaluated. Simulation results show that the proposed PF technique improves the location accuracy, even for high dispersion conditions, where the location error can be reduced down to half a meter. In addition, the proposed ES technique reduces the number of false detections in those cases where the first PD echo is close to the original PD. Experimental results confirm the benefits of the proposed PF technique, showing that, even under adverse conditions, the location error can be smaller than 1m in a 300m long cable.
Quantification of household electricity consumption for supporting energy efficiency of urban metabolism: Material flow analysis
(Center of Biomass and Renewable Energy (CBIORE), 2024-09) Ali, S.S.S.; Kasavan, S.; Razman, M.R.; Zarco Periñán, Pedro Javier; Universidad de Sevilla. Departamento de Ingeniería Eléctrica
Despite growing public, academic, and government awareness of the energy consumption issue, there is still little research on the scales and patterns of Household Electricity Consumption (HEC), particularly in developing countries such as Malaysia. Therefore, the present study examines the status of HEC using electricity consumption breakdowns, key performance indicators (KPIs) for electricity consumption and Material Flow Analysis (MFA) by showing potential electricity savings, cost savings, and emission reductions using 5-star energy efficiency appliances. This study used a face-to-face survey of 400 participants in Seremban, the capital city of Negeri Sembilan. The study found that the majority of respondents (49%) consumed about 300-600 kWh/month of electricity with an estimated cost of MYR231.80 per month. Additionally, the study found that households in flats recorded lower average electricity consumption (460.16 kWh/unit) than bungalow households (885.92 kWh/unit) due to respondents’ socio-economic status, the physical size of the houses and the number of appliances owned. The study also revealed that the average energy consumption was higher for refrigerators (9.6 kWh/day) and air conditioners (4.5 kWh/day) due to the use of large amounts of energy to maintain a steady temperature. The material flow analysis shows that energy savings were approximately 22.53%, potential cost savings were MYR12,676.15 per month, and the potential reduction emissions were about 100,759.92 kgCO2e for one month with using EEA compared to non-EEA. The present study empirically discussed the significance of HEC quantification and the opportunity for energy efficiency is critical as a solution for sustainable urban metabolism in a developing country
Dynamic optimisation of unbalanced distribution network management by model predictive control with Markov reward processes
(Elsevier, 2024-01) Álvarez Arroyo, César; Vergine, Salvatore; D’Amico, Guglielmo; Escaño González, Juan Manuel; Alvarado-Barrios, Lázaro; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Universidad de Sevilla. TEP175: Ingeniería Eléctrica; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
In this work, a two-level control system is used to minimize the total active power losses of an active distribution system connected to the external grid and composed of a wind turbine, two photovoltaic power sources, and two batteries. At the first control level, a model-based predictive control (MPC) is run, using non-homogeneous Markov reward models for wind power prediction and homogeneous Markov reward models for photovoltaic power. At the second level, an algorithm is run for optimal management of voltage control assets, such as voltage regulating transformers, to minimize losses. Different scenarios have been considered, highlighting the advantages of using an MPC framework. This results in an optimization process that can be influenced by different time horizons depending on whether or not the MPC is applied. The predictions allow considering a long-horizon stepwise optimization process that leads to an increasing number of variables along with the decrease of total active power losses. When the MPC is not applied, a short-horizon analysis is performed with a decrease in both the number of variables and the quality of the results. Different cases are considered in which the nominal power of a photovoltaic unit and the battery capacity are modified.
Estimation of Energy Distribution Coefficients in Collective Self-Consumption Using Meta-Heuristic Optimization Techniques
(MDPI, 2024) Villalonga Palou, Joan Tomás; Serrano González, Javier; Riquelme Santos, Jesús Manuel; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Ministerio de Ciencia e Innovación (MICIN). España; Universidad de Sevilla. TEP-196: Sistemas de Energía Eléctrica
The expansion of collective self-consumption is set to be a fundamental pillar for the devel- opment of energy-positive communities. In Spain, the regulation establishes an allocation scheme of self-consumed and surplus energy among the participants, based on distribution coefficients. This implies that the members of the self-consumption community must decide (or otherwise are assigned by default, according to the criteria established in the regulation) the distribution coefficients assigned to each of the consumers for the allocation of the distribution of the energy generated by the self-consumption system, as well as for the allocation of the surpluses. In this paper, the behavior of several algorithms based on heuristic techniques will be analyzed, with the aim of achieving an adequate economic optimization focused on obtaining the distribution coefficients that maximize the net present value (NPV) of the collective installation (according to the annual savings from the imple- mentation of the self-consumption facility, compared to conventional consumption). The modeling of the problem is performed under fully realistic conditions, considering hourly consumption data, electricity prices for domestic consumers and irradiation and photovoltaic production. The results obtained show a clear improvement in the economic performance of the plant by optimizing the distribution coefficients, compared to the standard approach corresponding to the default coefficients established in the regulatory framework.
Reliability assessment of dynamic line rating methods based on conductor temperature estimation
(Elsevier, 2024-08) González Cagigal, Miguel Ángel; Rosendo Macías, José Antonio; Bachiller-Soler, Alfonso; Del-Pino-López, Juan Carlos; Universidad de Sevilla. Departamento de Ingeniería Eléctrica; Junta de Andalucía; Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica
Dynamic line rating techniques are increasingly prevalent in the computation of ampacity for overhead transmission lines. Some of these methods, commonly employed by system operators, rely on real-time measurements to calculate conductor temperature, either directly or indirectly. Despite their widespread usage, the susceptibility of these techniques to measurement errors has been largely disregarded in prior research. In this regard, this paper includes a groundbreaking reliability analysis addressing the impact of measurement errors on various dynamic line rating techniques in overhead lines, based on conductor temperature estimation. Two case studies are presented, incorporating typical errors from simulations. The first case study adopts a standard 24-hour profile for the variables involved in the conductor ampacity calculation. In the second study, Monte Carlo simulations are conducted, in which meteorological variables are randomly assigned with five load levels to evaluate the current’s influence on measurement noise sensitivity. The resulting ampacity errors across all methods considered are remarkably high, with mean values exceeding 150% in specific scenarios. This unequivocally demonstrates that the commonly accepted levels of measurement accuracy in these widely used rating techniques yield estimations falling far below acceptable reliability standards.

Examinar

Envíos recientes