Jairo Quiros-Tortos

Dynamic IEEE Test Systems for Transient Analysis

Transient stability analysis is performed to assess the power systems condition after a severe contingency and is carried out using simulations. To adequately assess the systems transient stability, the correct dynamic models for the machines (i.e., generators, condensers, and motors) along with their dynamic parameters must be defined. The IEEE test systems contain the data required for steady-state studies. However, neither the dynamic model of the machines nor their specific parameters have been established for transient studies. As a result, there is a demand for test bed systems suitable for transient analysis. This paper defines dynamic machine models along with their parameters for each IEEE test bed system, thus producing full dynamic models for all test systems. It is important to mention that the parameters of the proposed dynamic models are based on typical data. The test systems are subjected to large disturbances, and a case study for each test system, which examines the frequency, angle, and voltage stability, is presented. Furthermore, the proposed dynamic IEEE test systems, implemented in PowerWorld, are available online.

Control of EV Charging Points for Thermal and Voltage Management of LV Networks

High penetrations of domestic electric vehicles (EVs) in U.K. low voltage (LV) networks may result in significant technical problems. This paper proposes an implementable, centralized control algorithm, currently being trialed in 9 U.K. residential LV networks, that uses limited information to manage EV charging points to mitigate these technical problems. Two real U.K. LV networks are used to quantify the potential impacts of different EV penetration levels and to demonstrate the effectiveness of the control algorithm (using different control cycles) for simultaneous thermal and voltage management. Monte Carlo simulations (adopting 1-min resolution data) are undertaken to cater for domestic and EV demand uncertainties. Results for these LV networks show that problems may occur for EV penetrations higher than 20%. More importantly, they highlight that even for a 100% penetration and control cycles of up to 10 min, the control algorithm successfully mitigates problems on the examined LV networks. Crucially, to determine effects on the comfort of EV users, a metric is introduced and discussed. The results of different control settings are presented to analyze potential adaptations of the control strategy. Finally, a comparison with an optimization framework highlights that the proposed algorithm is as effective while using limited information.

Benchmarking and Validation of Cascading Failure Analysis Tools

Cascading failure in electric power systems is a complicated problem for which a variety of models, software tools, and analytical tools have been proposed but are difficult to verify. Benchmarking and validation are necessary to understand how closely a particular modeling method corresponds to reality, what engineering conclusions may be drawn from a particular tool, and what improvements need to be made to the tool in order to reach valid conclusions. The community needs to develop the test cases tailored to cascading that are central to practical benchmarking and validation. In this paper, the IEEE PES working group on cascading failure reviews and synthesizes how benchmarking and validation can be done for cascading failure analysis, summarizes and reviews the cascading test cases that are available to the international community, and makes recommendations for improving the state of the art.

A statistical analysis of EV charging behavior in the UK

To truly quantify the impact of electric vehicles (EVs) on the electricity network and their potential interactions in the context of Smart Grids, it is crucial to understand their charging behavior. However, as EVs are yet to be widely adopted, these data are scarce. This work presents results of a thorough statistical analysis of the charging behavior of 221 real residential EV users (Nissan LEAF, i.e., 24kWh, 3.6 kW) spread across the UK and monitored over one year (68,000+ samples). Probability distribution functions (PDFs) of different charging features (e.g., start charging time) are produced for both weekdays and week-ends. Crucially, these unique PDFs can be used to create stochastic, realistic and detailed EV profiles to carry out impact and/or Smart Grid-related studies. Finally, the effects of the EV demand on future UK distribution networks are discussed.

A graph theory based new approach for power system restoration

This paper presents a novel graph theory based approach for restoring large scale power systems affected by complete blackouts. The proposed graph theory based method assesses the power system in blackout and represents the required information in a graph. The graph is initially used to determine the sectionalizing strategy. To do so, an un-normalized spectral clustering algorithm is implemented. The method then applies parallel power system restoration, restoring the created islands in parallel. Thus, the restoration process is speeded up. An algorithm for computing the k-shortest simple paths from the blackstart unit in each island to the non-blackstart units and loads in the same island is then carried out. By implementing the proposed method, cranking power can be rapidly sent to non-blackstart units and loads can be picked up quickly. The new graph theory based method is tested on the New England 39-bus test system. Simulation results are used to demonstrate the effectiveness of the proposed method on restoring systems affected by complete blackouts.

OpenDSS-based distribution network analyzer in open source GIS environment

The adoption of low carbon technologies (e.g., phoxadtovoltaic systems) is expected to increase in the near future given their contribution to reduce greenhouse gas emissions. However, high penetrations of these new technologies are likely to result in technical problems on the distribution networks. To truly understand these impacts, nonetheless, utilities need to have detailed models of their networks and advanced simulation tools, so studies can then be performed. This paper presents an OpenDSS-based distribution network analyzer in an open source GIS environment that enables engineers to easily carry out complex network analyzes ranging from snapshot to harmonic power flows. Critical to facilitate its use, the simulation tool needs limited input information to undertake these detailed studies. Illustrations on a real distribution network with more than 10,000 customers demonstrate the efficiency of the analyzer to perform studies, display and store the corresponding results.

Controlling electric vehicle charging points for congestion management of UK LV networks

High penetration of Electric Vehicles (EVs) in residential UK Low Voltage (LV) networks may result in significant asset congestion (transformers and cables), particularly during peak hours. Therefore, this work proposes an implementable, centralized control algorithm that manages EV charging points to mitigate congestion in LV networks. To assess the need of control actions to avoid congestion issues, this work initially quantifies the potential impacts of different EV penetration levels on a real UK LV network. To demonstrate the effectiveness of the proposed control algorithm, analyses for uncontrolled and controlled charging of EVs are carried out. Monte Carlo simulations (considering 1-min resolution data) are undertaken to cater for domestic and EV load profile uncertainties. Results for this particular LV network indicate that asset congestion might occur for EV penetration levels larger than 40%. More importantly, the results show the effectiveness of the proposed centralized control algorithm in avoiding the congestion effects on the LV network, even for a 100% penetration of EVs.

Geo-Information Is Power: Using Geographical Information Systems to Assess Rooftop Photovoltaics in Costa Rica

Economies of scale, incentives, and technological advances have made photovoltaic (PV) systems more affordable and common in developed nations. In Latin America, however, cost and regulation are still barriers for their widespread adoption, particularly by residential and commercial customers. In Costa Rica, there has only recently been interest in rooftop PV systems thanks to a major pilot project carried out from 2010 to 2015 by the Costa Rican Institute of Electricity (Instituto Costarricense de Electricidad, ICE), the administrator of the generation, the transmission system operator, and one of the eight distribution network operators (DNOs) who also supply electricity. The hundreds of installations involved in this project created the momentum needed by the local emerging PV industry to push for changes in the regulatory framework and demonstrate the economic benefits, given the relatively high electricity prices. Although this project represented only a modest PV penetration, ICE recognized that the ability of distribution circuits to host rooftop PV systems should be adequately assessed. This prompted the Ministry of Energy and Environment to create a new and important requirement for Costa Rican DNO s: the generation-hosting capacity of distribution circuits should be quantified considering a comprehensive set of studies, with most of them requiring detailed network models.

Distribution network model builder for OpenDSS in open source GIS software

This paper presents a tool to automatically generate distribution network models for the power engineering software OpenDSS. The tool was developed in a free and open source Geographical Information System (GIS) software that allows a direct translation of GIS to OpenDSS files. The paper shows the potential of the developed piece of software and how it can help power engineers to carry out detailed studies of medium and low voltage networks. It also explains data requirements in the GIS database and all the steps followed to create the OpenDSS files. In order to demonstrate the capabilities of the model builder, the paper presents the translation of a real distribution circuit GIS model to OpenDSS.

On implementing a spectral clustering controlled islanding algorithm in real power systems

Wide area blackouts can be caused by unexpected fault scenarios, in particular protection maloperation, or simultaneous low probability events, which as such might lead to e.g., un-damped electromechanical oscillations. A Spectral Clustering Controlled Islanding (SCCI) method to find a suitable islanding solution for preventing such events was previously proposed and tested using different IEEE test networks. The sole constraint applied to this solution was related to generator coherency. The method demonstrated promising results when it was implemented on these IEEE test networks. The SCCI method was later tested using a simplified Cypriot Network and the Polish Network. The results achieved when implementing the SCCI method on actual power systems highlight practical issues that were not previously considered and require to be addressed when using it. Therefore, this paper presents a robust SCCI method. An outlier problem which affects the quality of clustering and a problem with the computational efficiency of the algorithm (when dealing with systems larger than 500 nodes) are presented and analyzed in this paper. To improve the clustering quality, a more robust clustering algorithm, k-medoids, is used to cluster all nodes in the solution subspace and to find the islanding solution.