DIE - REDES - Artículos en revistas internacionales / Articles in international journals

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Influence of Load Modeling on the Cost of Ensuring Stability Using TSCOPF
(IEEE, 2023-11-30) Arredondo Rodríguez, Francisco; Rachmanidis, Michail; Ledesma Larrea, Pablo; Castronuovo, Edgardo Daniel; Aghahassani, Mohammad Amin; Ministerio de Economía y Competitividad (España)
Load modeling significantly impacts the time-domain response of power systems in transient stability studies but this effect is often underestimated in Transient Stability Constrained Optimal Power flow (TSCOPF) studies. The object of this study is twofold: 1) it proposes a robust formulation based on a relevant node representation approach that allows the use of any type of load model in TSCOPF algorithms, while maintaining the accuracy and reducing the size of a full representation approach; and 2) it conducts a comparative analysis of how load modeling influences the cost of ensuring stability and provides a summary of several recommendations for load modeling in these algorithms. The results show that the usual approach in TSCOPF studies, which involves impedance-based load modeling, leads to a significant false stabilization effect in the rotor angle trajectories. On the other hand, the use of the constant power model yields conservative results at a significant computational cost. This paper advocates for the adoption of the relevant node TSCOPF approach proposed in this work, retaining detailed exponential or polynomial load models for their flexibility and accuracy, while incurring only a slight increase in the computational effort.
A 'Binocular' method for detecting faults in electrical distribution networks with distributed generation
(Kaunas University of Technology, 2016) Alcala, Daniel; Gonzalez Juarez, Lorena Guadalupe; Valino, Vanesa; Garcia, Jose Luis
The increase in the number of renewable energy generating facilities has transformed the electricity distribution network into a Distributed Generation (DG) system. This has given rise to a new monitoring scenario for protective devices already installed across radial distribution networks, which may execute unexpected and inappropriate protective actions that cause loss of supply to consumers. These devices are affected by the new condition of the electricity distribution network, as network currents vary. A common practice is to use electrical impedance-based fault localizers. This work describes a novel method for fault detection in radial networks with DG, which does not require knowing the electrical impedances of the lines that compose the network. The method only requires input data regarding the short circuit currents provided by the main feeder and the DG units in the area in which a fault has occurred. This information is sufficient to allow the area where the fault lies to be identified. The underlying idea is that the measurement of the current at two points provides a binocular view of the fault, thus allowing its location to be pinpointed. The method was tested using the IEEE 13-node test feeder system, locating different types of faults in different areas of a simulated radial network.
Detection of partial discharge sources using UHF sensors and blind signal separation
(MDPI, 2017-11-15) Boya Lara, Carlos Alan; Robles Muñoz, Guillermo; Parrado Hernández, Emilio; Ruiz Llata, Marta; Ministerio de Economía y Competitividad (España)
The measurement of the emitted electromagnetic energy in the UHF region of the spectrum allows the detection of partial discharges and, thus, the on-line monitoring of the condition of the insulation of electrical equipment. Unfortunately, determining the affected asset is difficult when there are several simultaneous insulation defects. This paper proposes the use of an independent component analysis (ICA) algorithm to separate the signals coming from different partial discharge (PD) sources. The performance of the algorithm has been tested using UHF signals generated by test objects. The results are validated by two automatic classification techniques: support vector machines and similarity with class mean. Both methods corroborate the suitability of the algorithm to separate the signals emitted by each PD source even when they are generated by the same type of insulation defect.
Reliability assessment of distribution networks with optimal coordination of distributed generation, energy storage and demand management
(MDPI, 2019-08-02) Escalera, Alberto; Castronuovo, Edgardo Daniel; Prodanović, Milan; Roldán-Pérez, Javier
Modern power distribution networks assume the connection of Distributed Generators (DGs) and energy storage systems as well as the application of advanced demand management techniques. After a network fault these technologies and techniques can contribute individually to the supply restoration of the interrupted areas and help improve the network reliability. However, the optimal coordination of control actions between these resources will lead to their most efficient use, maximizing the network reliability improvement. Until now, the effect of such networks with optimal coordination has not been considered in reliability studies. In this paper, DGs, energy storage and demand management techniques are jointly modelled and evaluated for reliability assessment. A novel methodology is proposed for the calculation of the reliability indices. It evaluates the optimal coordination of energy storage and demand management in order to reduce the energy-not-supplied during outages. The formulation proposed for the calculation of the reliability indices (including the modelling of optimal coordination) is described in detail. The methodology is applied to two distribution systems combining DGs, energy storage and demand management. Results demonstrate the capability of the proposed method to assess the reliability of such type of networks and emphasise the impact of the optimal coordination on reliability.
Midiendo la pobreza energética. Una revisión de indicadores
(Universidad del Bío-Bío, 2020-06) Castaño de la Rosa, Raúl; Solís-Guzmán, Jaime; Marrero-Meléndez, Madelyn
Identificar aquellos hogares en una situación de vulnerabilidad a la pobreza energética es el primer paso para abordar una problemática social a nivel mundial asociada a la falta de servicios energéticos mínimos, conocido por los términos anglosajones-Fuel Poverty y Energy Poverty, FP y EP, respectivamente. El concepto FP, definido en el Reino Unido como "la incapacidad para obtener un adecuado confort térmico debido a la ineficiencia de la vivienda", mientras que el concepto EP refleja la imposibilidad de tener acceso a un servicio energético mínimo en países en desarrollo. La falta de un consenso a la hora de definir una ruta clara ha originado que algunos países no la reconozcan como un problema social. La investigación se basa en la revisión de ambos conceptos, a través del análisis conceptual de los términos FP y EP, revisión de indicadores utilizados, estudio de la capacidad de los indicadores para identificar y proponer soluciones a la problemática. Todo ello en relación a los objetivos incluidos: infraestructuras disponibles, eficiencia energética, pobreza social y económica, bienestar y salud social. El resultado es la revisión desde una perspectiva técnica en el sector residencial que ayude a desarrollar soluciones que cubran las carencias encontradas.
Small-signal stability analysis of the asymmetrical DC operation in HVDC networks
(Elsevier, 2023-01-15) Serrano Sillero, Jesús; Moreno López de Saá, María Ángeles; Agencia Estatal de Investigación (España)
The increase in High Voltage Direct Current (HVDC) projects favors their future interconnection to form regional networks, but this interconnection can be hindered by the lack of standardization in station's configuration and converter's differing grounding schemes. Whilst other studies have studied the effect of Direct Current (DC) asymmetrical operation, they are limited in their scope. This paper proposes a more realistic perspective, considering stations with different topologies, permanent DC asymmetries and the influence of the grounding systems. This more complex point of departure requires the re-examination of the modeling methods, from time-domain to frequency-domain. This paper proposes a small-signal stability model of the system, which is validated with the electromagnetic transient (EMT) dynamic simulations using PowerFactory. This model provides guidelines for designing the grounding impedance and allows the proper design of a specific controller to dampen the asymmetrical DC operation mode.
A detailed view of the Adaptive-Comfort-Control-Implementation Script (ACCIS): The capabilities of the automation system for adaptive setpoint temperatures in building energy models
(Elsevier, 2023-06-01) Sánchez García, Daniel; Martínez Crespo, Jorge; Ruiz-Rivas Hernando, Ulpiano; Alonso, Carmen; European Commission
Recent research has looked into the potential for energy savings from adopting setpoint temperatures based on adaptive comfort. The recently suggested Adaptive-Comfort-Control-Implementation Script (ACCIS), a computational method that expands the use of air conditioning to adaptive comfort, can be used to accomplish this. The user's setup and an Input Data File (IDF) are used by ACCIS to convert PMV-based EnergyPlus models into adaptive setpoint models. The Adaptive Comfort Control Implemented Model ("accim") Python module has been used to nest ACCIS, which was originally an Energy Management System (EMS) script. This research focuses on the creation of ACCIS and offers a more in-depth understanding of how the computational method functions based on the connections between the objects that compose it. Since all weather file quantity constraints have been overcome and studies can now be generated based on millions of simulations, ACCIS opens up new opportunities for performing energy simulations on a worldwide scale rather than only on a national or continental level. This potential is increased considering that, until recently only international models ASHRAE Standard 55 and European standard EN16798-1 were considered in ACCIS, but now a recent update allows to select local comfort models developed for specific areas. As a result, this potential is firstly demonstrated by means of the study of the 3 arguments that have the most important impact on the setpoint temperatures: the thermal comfort model, the acceptability levels and the behaviour of setpoint temperatures when adaptive comfort models are not applicable; and secondly by means of an actual example of use of accim.
Towards a just energy transition, barriers and opportunities for positive energy district creation in Spain
(MDPI, 2021-08-02) Hearn, Adam X.; Castaño de la Rosa, Raúl; European Commission
To mitigate the effects of climate change, the European Commission created a Strategic Energy Technology Plan committing to forming 100 Positive Energy Districts (PEDs) by 2025. These are considered to potentially be major instruments for decarbonization in a just transition. This plan has led to some districts being defined as PEDs, although none have fully met the criteria to be a PED yet. Research shows that new forms of energy ownership and production, as could potentially be found in PEDs, could help reduce energy poverty, which affects a significant segment of the population, as households can reduce their energy expenditure as well as improve their energy behavior. This paper set out to shed light on the PED landscape, investigating the barriers and opportunities to PED creation in Spain and its potential to mitigate energy poverty. We conducted a literature review on community-owned energy in Spain, followed with expert interviews (energy researchers, stakeholders, and NGOs) who focus on sustainability issues in Spain. Results show a number of barriers (lack of knowledge and awareness, and lack of trust from consumers) and opportunities connected with the creation of PEDs. In conclusion, policymaker engagement and support play a key role in successfully implementing PEDs.
Evaluation of numerical methods for TSCOPF in a large interconnected system
(IEEE, 2022-06-30) Aghahassani, Mohammadamin; Castronuovo, Edgardo Daniel; Ledesma Larrea, Pablo; Arredondo Rodríguez, Francisco; Ministerio de Ciencia e Innovación (España)
Transient stability-constrained optimal power flow (TSCOPF) models comprehensively analyze the security and economic operation of power systems. However, they require a high computational effort and can suffer from convergence problems when applied to large systems. This study analyzes the performance of eleven numerical integration algorithms applied to ordinary differential equations that represent power system dynamics in a TSCOPF model. The analyzed algorithms cover a range of explicit and implicit methods, including the recently published semi-explicit and semi-implicit Adams-Bashforth-Moulton formulas, together with several initialization techniques. The integration methods are applied to a model of the Iberian Peninsula power system, and their performance is discussed in terms of convergence, accuracy, and computational effort. The results show that most implicit methods converge to the solution, even for large time steps. In particular, the Adams-Moulton method of order two and Simpson's rule, both initialized with RK4, outperform the trapezoidal rule, which is the default method in TSCOPF models.
A nested decision tree for event detection in smart grids
(European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ), 2022-09) Turanzas, J.; Alonso Martínez, Mónica; Amarís Duarte, Hortensia Elena; Gutierrez, J.; Pastrana Portillo, Sergio
Digitalization process experienced by traditional power networks towards smart grids extend the challenges faced by power grid operators to the field of cybersecurity. False data injection attacks, one of the most common cyberattacks in smart grids, could lead the power grid to sabotage itself. In this paper, an event detection algorithm for cyberattack in smart grids is developed based on a decision tree. In order to find the most accurate algorithm, two different decision trees with two different goals have been trained: one classifies the status of the network, corresponding to an event, and the other will classify the location where the event is detected. To train the decision trees, a dataset made by co-simulating a power network and a communication network has been used. The decision trees are going to be compared in different settings by changing the division criteria, the dataset used to train them and the misclassification cost. After looking at their performance independently, the best way to combine them into a single algorithm is presented.
A fast data-driven topology identification method for dynamic state estimation applications
(Elsevier, 2023-05) Gotti, Davide; Ledesma Larrea, Pablo; Amarís Duarte, Hortensia Elena; Agencia Estatal de Investigación (España)
This paper proposes a fast topology identification method to avoid estimation errors caused by network topology changes. The algorithm applies a deep neural network to determine the switching state of the branches that are relevant for the execution of a dynamic state estimator. The proposed technique only requires data from the phasor measurement units (PMUs) that are used by the dynamic state estimator. The proposed methodology is demonstrated working in conjunction with a frequency divider-based synchronous machine rotor speed estimator. A centralized and a decentralized approach are proposed using a modified version of the New England test system and the Institute of Electrical and Electronics Engineers (IEEE) 118-bus test system, respectively. The numerical results in both test systems show that the method demonstrate the reliability and the low computational burden of the proposed algorithm. The method achieves a satisfactory speed, the decentralized approach simplifies the training process and the algorithm proves to be robust in the face of wrong input data.
Exploring backup requirements to complement wind, solar and hydro generation in a highly renewable Spanish power system
(Elsevier BV., 2021-11-02) Tapetado Moraleda, Pablo; Victoria, M.; Greiner, M.; Usaola García, Julio
A weather-driven model is used to investigate the requirements for the backup generation (annual energy, power capacity and flexibility) in a power system with different penetrations of wind, solar photovoltaics, and hydroelectricity. The impact of interannual variability is assessed by using 26 years of weather data. The flexibility needed for the backup generation is found to be higher as the solar penetration increases since ramps caused by sunrises and sunsets are more significant than those caused by hour-to-hour wind fluctuations. The model is applied to the Spanish power system and two dispatch strategies for reservoir hydro and pumped hydro storage are evaluated. The currently installed gas power capacity is found to be sufficient to secure hourly demand for high renewable penetration.
Multi-contingency TSCOPF based on full-system simulation
(Wiley Open Access, 2017-01-05) Ledesma Larrea, Pablo; Calle, Ignacio Antonio; Castronuovo, Edgardo Daniel; Arredondo Rodríguez, Francisco; Ministerio de Ciencia y Tecnología (España)
Transient stability constrained optimal power flow (TSCOPF) is a non-linear optimisation problem used to perform economic dispatches while ensuring TS. This study proposes a multi-contingency TSCOPF model that retains the dynamics of all generators and includes a transient synchronous generator fourth-order dq-axis model. A program is developed that automatically reads the system data from standard files, builds the multiple-contingency TSCOPF model on a high-level modelling system and solves it using a non-heuristic interior point algorithm. This approach facilitates the application of the model to a variety of systems and scenarios. A TSC based on the speed deviation instead of the rotor angle is proposed. Results obtained on several standard systems are shown. The proposed method is applied to the northwest Spanish transmission system to obtain an optimised dispatch that ensures TS after any of a number of faults, and to assess the economic impact of fault-clearing times at different substations.
Optimization of the operation of a flywheel to support stability and reduce generation costs using a Multi-Contingency TSCOPF with nonlinear loads
(Elsevier, 2019-01-01) Arredondo Rodríguez, Francisco; Ledesma Larrea, Pablo; Castronuovo, Edgardo Daniel
Multi-Contingency Transient Stability Constrained Optimal Power Flow (MC-TSCOPF) models optimize the economic dispatch of power systems while ensuring their stability after a series of reference incidents. This paper proposes a MC-TSCOPF model that represents the power balance at each node of the system and at each sample time. The proposed model includes non-linear loads, synchronous generators, a windfarm, and a Flywheel Energy Storage system (FESS). The model is written on GAMS and solved using a standard Interior Point algorithm. This study focuses on the Fuerteventura-Lanzarote insular grid in Spain, where stability problems and load shedding cause high additional costs due to the low inertia of the system. A FESS has been recently installed in the system to improve its stability, taking advantage of its high-power capacity and rapid response. The proposed TSCOPF model has been applied to optimize the operation of the FESS to support stability in the event of a contingency. The results of the study show that 1) a proper model of non-linear loads is essential in TSCOPF studies; 2) the proposed MC-TSCOPF provides a tool for minimizing the generation costs while ensuring transient and frequency stability; and 3) it is possible to further reduce the generation costs by using the proposed model to calculate an optimal dynamic response of the FESS.
Capacity credits of wind and solar generation: The Spanish case
(Elsevier, 2019-12-01) Tapetado Moraleda, Pablo; Usaola García, Julio; Universidad Carlos III de Madrid
This paper analyses the capacity credits (CCs) of renewable photovoltaic (PV), concentrated solar power (CSP) and wind technologies in the Spanish power system. This system has steadily increased the share of renewables, reaching a penetration level of over 30%. The predictions made by ENTSO-e suggest that this level will increase to 50% by 2030. Therefore, different scenarios are studied in this paper to investigate the evolution of renewable integration and assess the corresponding contributions to reliability. The assessment is performed using a sequential Monte Carlo (SMC) method considering the seasonality of renewable generation and the uncertainties related to renewable sources, failure issues and the maintenance of thermal-based units. The baseline for SMC is provided by historical annual time series of irradiance and wind power data from the Spanish system. In the solar case, these time series are transformed into power time series with models of CSP and PV generation. The former includes different thermal storage strategies. For wind generation, a moving block bootstrap (MBB) technique is used to generate new wind power time series. The CC is assessed based on the equivalent firm capacity (EFC) using standard reliability metrics, namely, the loss of load expectation (LOLE). The results highlight the low contribution of renewables to power system adequacy when the Spanish power system has a high share of renewable generation. In addition, the results are compared with those of similar studies.
An optimal day-ahead load scheduling approach based on the flexibility of aggregate demands
(Elsevier, 2017-07-15) Ayón Flores, Xiaolin Ivonne; Gruber, J.K.; Hayes, B.P.; Usaola García, Julio; Prodanović, Milan; Ministerio de Economía y Competitividad (España)
The increasing trends of energy demand and renewable integration call for new and advanced approaches to energy management and energy balancing in power networks. Utilities and network system operators require more assistance and flexibility shown from consumers in order to manage their power plants and network resources. Demand response techniques allow customers to participate and contribute to the system balancing and improve power quality. Traditionally, only energy-intensive industrial users and large customers actively participated in demand response programs by intentionally modifying their consumption patterns. In contrast, small consumers were not considered in these programs due to their low individual impact on power networks, grid infrastructure and energy balancing. This paper studies the flexibility of aggregated demands of buildings with different characteristics such as shopping malls, offices, hotels and dwellings. By using the aggregated demand profile and the market price predictions, an aggregator participates directly in the day-ahead market to determine the load scheduling that maximizes its economic benefits. The optimization problem takes into account constraints on the demand imposed by the individual customers related to the building occupant comfort. A case study representing a small geographic area was used to assess the performance of the proposed method. The obtained results emphasize the potential of demand aggregation of different customers in order to increase flexibility and, consequently, aggregator profits in the day-ahead market.
Stability improvement of a transmission grid with high share of renewable energy using TSCOPF and inertia emulation
(IEEE, 2022-07) Arredondo Rodríguez, Francisco; Ledesma Larrea, Pablo; Castronuovo, Edgardo Daniel; Aghahassani, Mohammadamin; Ministerio de Ciencia e Innovación (España)
This paper proposes a Transient Stability Constrained Optimal Power Flow (TSCOPF) formulation that models non-synchronous renewable generation equipped with synthetic inertia. The proposed optimization problem calculates the optimal operating point of the system, accommodating high shares of non-synchronous renewable generation while ensuring transient stability in the event of critical incidents. Synthetic inertia controllers are used to improve the dynamic stability of the system in cases of very high share of renewable generation. The proposed tool is tested in the North-West Spanish system, a network with a high penetration of wind energy that causes a reduction in the total system inertia. The results of the study show that 1) synthetic inertia in renewable power plants can diminish electromechanical oscillations after a severe contingency, reducing the cost of ensuring transient stability; 2) using synthetic inertia the system becomes more stable when conventional generation is decommissioned following de-carbonization and renewable promotion policies; and 3) the proposed model can be used to calculate the parameters of the synthetic inertia control.
Renewables and Advanced Storage in Power Systems: The Iberian Case
(MDPI AG, 2022-04-01) Usaola García, Julio; Ministerio de Ciencia, Innovación y Universidades (España)
Storage has many benefits for power systems with a high share of renewable energy. It reduces renewable curtailment, can participate in ancillary services and contributes to system adequacy. However, its business model is far from clear since most of its revenues come from arbitrage in energy markets, and this is usually not enough to recover the investment. Advanced storage can facilitate the profitability of storage and ease the integration of renewables in power systems by reducing costs and allowing an enhanced performance. The profitability requirements of future advanced storage systems (batteries) are assessed in this paper by means of an optimization method and an uncertainty analysis for an optimal Iberian (Spain and Portugal) power system that meets the targets of their National Energy and Climate Plans. Results show that needed storage capacity is only a small part of the demanded energy, but technical advances are required for optimal performance. High prospective storage cost leads to a wind-dominated renewable mix, while low storage cost favours photovoltaics. Arbitrage with storage may cover its investment costs under carbon prices close to the actual Social Cost of Carbon.
Endogenous Approach of a Frequency-Constrained Unit Commitment in Islanded Microgrid Systems
(MDPI, 2021-10-02) Rebollal Jordán, David; Chinchilla Sánchez, Mónica; Santos Martín, David; Guerrero, Josep M.; Ministerio de Ciencia e Innovación (España)
Power reserves are usually scheduled in day-ahead unit commitment (UC) to minimize operating costs while maintaining system security. In applying basic UC (bUC) after a contingency, the system frequency may fall upon the activation of the load-shedding global control (under-frequency load-shedding or UFLS) limits. Small isolated microgrids are more sensitive to this issue due to their lack of inertia. Including dynamic considerations into the bUC problem can minimize UFLS activation and also avoid the need for the operator to later check the short-term feasibility of a bUC solution. These proposals are known as Frequency-Constrained UC (FCUC), although the implementation are very time-consuming. FCUC implementation will increase the system’s operational costs, which should be calculated to estimate remuneration to the safety service based on the additional reserve provision. The electrical system of Gran Canaria island has suffered several episodes of greater blackouts in recent years. Shortly, there will be 242 MW of wind generation installed (26% of the thermal power installed on Gran Canaria). The main objective of this work is to improve the island system reliability by means of an FCUC formulation applied by the system operator in practice, including renewable sources. The results show that the frequency values remained within the admissible boundaries, but the system’s operational costs increased by around 13%.
Co-simulation platform for interconnected power systems and communication networks based on PSS/E and OMNeT++
(Elsevier, 2022-07) Ledesma Larrea, Pablo; Gotti, Davide; Amarís Duarte, Hortensia Elena; Ministerio de Ciencia e Innovación (España)
This paper proposes a co-simulator that combines OMNeT++ for communication systems with PSS/E for the electrical transmission network. The cosimulator applies an event-driven synchronization method that minimizes errors due to delays in the synchronization between both simulators. The synchronization method pauses the simulation of the power system at each communication event, while a supervisory module in PSS/E returns control to the event simulator if any condition from a pre-specified set is met. The proposed co-simulator is demonstrated on a protection system based on peer-to-peer communication and used to evaluate the effect of communication latency times on an online state estimator.

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