New strategies for the massive introduction of electric vehicles in the operation and planning of Smart Power Systems

En el contexto actual, donde el calentamiento climático es cada vez más importante, existe la necesidad de limitar el consumo de combustibles fósiles. De esta manera, el transporte es uno de los sectores en los que más se están generando cambios en cuanto a la sostenibilidad. El vehículo eléctrico aparece como una solución para este cambio paulatino ya que no contamina localmente y su balance energético es muy eficiente. Así, se han propuesto diferentes programas para el crecimiento del vehículo eléctrico en el parque automotor. Sin embargo, el cambio de vehículos de gasolina por vehículos eléctricos genera desafíos en varios aspectos, como el impacto que ocasiona en la red eléctrica una implantación masiva: caídas de tensión, pérdidas de potencia, problemas con la calidad de la electricidad, inversiones importantes, etc. Se han planteado algunas soluciones en la parte operativa, pero muchas de ellas no han tomado en cuenta la flexibilidad de los usuarios, lo cual es muy importante para la adopción de vehículos eléctricos. De igual manera, en muchas ocasiones, en la literatura se asumen valores para ciertas variables (estado de carga, recorrido, tipo de batería, etc) que pueden cambiar según el comportamiento de cada usuario, lo que modificaría las previsiones realizadas. Finalmente, pocos trabajos han estudiado el impacto de lo vehículos eléctricos en redes eléctricas cuya gestión energética es más complicada debido a su aislamiento de una macrored y con alta penetración de energías renovables, como lo son las microredes. En este marco, esta tesis propone un enfoque novedoso en cuanto a la participación de los usuarios de vehículos eléctricos en la operación y planificación de diferentes sistemas eléctricos de potencia. Esta trata de algunos aspectos principales: disminución de costos de carga, participación en servicios de regulación, aprovechamiento de energía renovable, así como la planificación de generación de una microred incorporando vehículos eléctricos. En una primera parte, se presenta un análisis del vehículo eléctrico y su interacción en sistemas de potencia. De igual manera, se presentan los trabajos de investigación relacionados sobre la temática. En base al análisis de dichos trabajos, esta tesis propone una nueva metodología para optimizar la carga de los vehículos eléctricos. Se propone la participación de un nuevo agente del mercado eléctrico, el Agregador de vehículos eléctricos. Tendrá que gestionar la carga de dichos vehículos en una importante zona, coordinar con el operador de la red para evitar fallos y minimizar los costos de carga. De igual manera, se considera la diferente flexibilidad de los usuarios ya qu podrán escoger una tarifa que se adapte a su disponibilidad en espera y pagar el precio por aquello. La metodología ha sido aplicada a un caso de estudio a la red de Quito, Ecuador. Se propone también la participación en servicios de regulación, necesitando esta vez de usuarios que sean más flexibles al dejar su vehículo conectado a la red. Se considera las tarifas de la parte anterior para realizar dicho estudio. De igual manera, se aplicó al caso de estudio de la red de Quito, Ecuador. Con el crecimiento de las energías renovables, como solar y eólica, la gestión de la electricidad se vuelve más compleja. Con vistas a utilizar el exceso de energía renovable, se propone una tarifa de electricidad que permita al agregador de cargar los diferentes vehículos, tomando en cuenta precios bajos en periodos en donde la energía renovable esté en exceso. Finalmente, se plantea a planificación de generación de una microred que incluya la introducción masiva de vehículos eléctricos. Se aplicó al caso de las islas de Santa Cruz y Baltra, Galápagos, Ecuador, estudiando el impacto en los costos y en el medio ambiente de nueva generación y considerando la variación del precio del diésel debido a su incertidumbre.In the current context, where global warming is growing progressively, it is fundamental to limit fossil fuels consumption. Hence, transportation is one of the sectors in which several changes are occurring considering the sustainability. The Electric Vehicle appears as a new solution for this gradual change; it does not pollute locally and its energy's balance is very efficient. So, different programs have been proposed for the growth of electric vehicles in the automotive market. Nevertheless, the change from internal combustion vehicles to electric vehicles generates challenges in several aspects, such as the impact in the electric grid of a massive introduction of electric vehicles: voltage drops, power losses, quality of electricity issues, important investments, among others. Several solutions in operation have been formulated, but most of them do not consider the flexibility of users, which is a significant criterion for the electric vehicle acquisition. Moreover, in several works of the literature, many variables are assumed (stateof- charge, routes, type of battery, etc), which can vary significantly depending on the user, so also the results. Finally, few works have studied the impact of electric vehicles in very complex power systems, as the ones that are isolated from a macrogrid and because of significant penetration of renewable energy sources, such as microgrids. In this context, this thesis proposes a novel approach to the participation of the electric vehicle users in operation and planning of different electric power systems. This thesis is intended to cover various topics: charging costs decrease, regulation services participation, use of an excess of renewable energy, and the power generation planning of a microgrid considering the introduction of electric vehicles. In a first part, an analysis of the electric vehicle and its interaction with power systems is presented. Additionally, the principal works on the topic are summarized. Based on the analysis of these works, this thesis proposes a new methodology for optimizing the charge of electric vehicles. The participation of a new agent of the electricity market, the electric vehicle aggregator, is proposed. It has the ability to manage the charge of the electric vehicles in a zone with significant size, to coordinate with the grid operator in order to avoid troubles and to minimize charging costs. Furthermore, the different flexibility of electric vehicle users is considered because they will choose an EV customer choice product (CCP) that is adapted to their waiting needs and to the cost they can pay. The methodology has been applied to a case study in the grid of Quito, Ecuador. The participation in regulation services has been also considered to discuss this participation in Ancillary services. The CCPs from the part before are considered for performing such study but assuming more involvement from the electric vehicle users. The case study of Quito, Ecuador, was also studied. With the growth of renewable energies, such as solar and wind, the electricity management becomes more complicated. In order to use the excess of renewable energy, an EV charging mechanism for the aggregator is proposed, based on low prices when the renewable energy is in excess. Finally, a power generation planning for a microgrid is proposed, considering the massive introduction of electric vehicles. The case of the Santa Cruz and Baltra islands, Galapagos, Ecuador are studied to determine its costs and environmental impacts, based on diesel costs sensitivity studies to account for its uncertainty.En el context actual, on l'escalfament climàtic és cada vegada més important, hi ha la necessitat de limitar el consum de combustibles fòssils. El transport és un dels sectors en els quals més s'estan generant canvis pel que fa a la sostenibilitat. El vehicle elèctric apareix com una solució per a aquest canvi gradual ja que no contamina localment i el seu balanç energètic és molt eficient. Així, s'han proposat diferents programes per al creixement del vehicle elèctric al parc automotor. No obstant això, el canvi de vehicles de gasolina per vehicles elèctrics generen desafiaments en diversos aspectes, com son l'impacte que ocasiona a la xarxa elèctrica una implantació massiva: caigudes de tensió, pèrdues de potència, problemes amb la qualitat de l'electricitat, inversions importants, disminució de la vida útil dels transformadors, etc. S'han plantejat algunes solucions a la part operativa, però moltes d'elles no han tingut en compte la flexibilitat dels usuaris, la qual cosa és molt important per a l'adopció de vehicles elèctrics. De la mateixa manera, en moltes ocasions, en la literatura s'assumeixen valors per certes variables (estat de càrrega, recorregut, tipus de bateria, etc.) que poden canviar segons el comportament de cada usuari, el que modificaria les previsions realitzades. Finalment indicar que pocs treballs han estudiat l'impacte del que vehicles elèctrics en xarxes elèctriques on la gestió energètica és més complicada a causa del seu aïllament d'una macroxarxa i amb alta penetració d'energies renovables, com ho són les microxarxes. En aquest marc, aquesta tesi proposa un enfocament nou pel que fa a la participació dels usuaris de vehicles elèctrics en l'operació i planificació de diferents sistemes elèctrics de potència. Aquesta tracta alguns aspectes principals: disminució de costos de càrrega, participació en serveis de regulació, aprofitament d'energia renovable, així com la planificació de generació d'una microxarxa incorporant vehicles elèctrics. En una primera part, es presenta una anàlisi del vehicle elèctric i la seva interacció en sistemes de potència. De la mateixa manera, es presenten els treballs de recerca relacionats sobre la temàtica. En base a l'anàlisi d'aquests treballs, aquesta tesi proposa una nova metodologia per optimitzar la càrrega dels vehicles elèctrics. Es proposa la participació d'un nou agent del mercat elèctric, el Agregador de vehicles elèctrics. Haurà de gestionar la càrrega d'aquests vehicles en una important zona, coordinar amb l'operador de la xarxa per evitar fallades i minimitzar els costos de càrrega. De la mateixa manera es considera la diferent flexibilitat dels usuaris ja que podran escollir una tarifa que s'adapti a la seva disponibilitat en espera i pagar el preu per allò. La metodologia ha estat aplicat a un cas d'estudi a la xarxa de Quito, Equador. Es proposa també la participació en serveis de regulació, necessitant aquest cop d'usuaris que siguin més flexibles en deixar el seu vehicle connectat a la xarxa. Es consideren les tarifes de la part anterior per a realitzar dit estudi. De la mateixa manera, es va aplicar al cas d'estudi de la xarxa de Quito, Equador. Amb el creixement de les energies renovables, com solar i eòlica, la gestió de l'electricitat es torna més complexa. Amb vista a utilitzar l'excés d'energia renovable, es proposa un tarifa d'electricitat que permeti a l'agregador de carregar els diferents vehicles, especialment en períodes on l'energia renovable estigui en excés. Finalment, es planteja la planificació de generació d'una microxarxa que inclogui la introducció massiva de vehicles elèctrics. En concret, es va aplicar al cas de la illes de Santa Cruz i Baltra, Galápagos, Equador, estudiant l'impacte de la nova generació en els costos i en el medi ambient i considerant la variació del preu del dièsel, causa de la seva incertesa.Clairand Gómez, JM. (2018). New strategies for the massive introduction of electric vehicles in the operation and planning of Smart Power Systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/110971TESI

Assessment of Technical and Economic Impacts of EV User Behavior on EV Aggregator Smart Charging

[EN] The increase in global electricity consumption has made energy efficiency a priority for governments. Consequently, there has been a focus on the efficient integration of a massive penetration of electric vehicles (EVs) into energy markets. This study presents an assessment of various strategies for EV aggregators. In this analysis, the smart charging methodology proposed in a previous study is considered. The smart charging technique employs charging power rate modulation and considers user preferences. To adopt several strategies, this study simulates the effect of these actions in a case study of a distribution system from the city of Quito, Ecuador. Different actions are simulated, and the EV aggregator costs and technical conditions are evaluated.All the authors wish to thank Manuel Alcázar Ortega and José Francisco Carbonell Carretero from Universitat Politècnica de València for their contributions to this paper. We also thank the Ministry of Electricity and Renewable Energy of Ecuador (MEER) and Empresa Eléctrica Quito (EEQ) for providing important information for this study.Clairand-Gómez, J.; Rodríguez-García, J.; Álvarez, C. (2020). Assessment of Technical and Economic Impacts of EV User Behavior on EV Aggregator Smart Charging. Journal of Modern Power Systems and Clean Energy (Online). 8(2):356-366. https://doi.org/10.35833/MPCE.2018.000840S3563668

Smart Charging for Electric Vehicle Aggregators considering Users Preferences

(c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works[EN] Most of the road transportation currently depends on fossil fuels, which result in significant environmental and health issues. This is being addressed with the deployment of electric vehicles. However, a massive penetration will lead to new technical and economic challenges for power systems. This paper proposes a novel way to account for the effect of this new load and to minimize the negative impacts by providing new tools for the agent responsible of managing the EV charge in some area (EV aggregator). The proposed method allows EV charging at the lowest cost while complying with technical constraints required by Distribution System Operator (DSO) and Transmission System Operator (TSO). Moreover, EV users are able to choose among different customer choice products (CCPs) that meets their needs in terms of charging time. A case study in the city of Quito (Ecuador) is analyzed in the paper where the advantages of the proposed coordinated charging method are quantified. The model presents cost benefits compared to uncoordinated charging while complying with technical constraints. Additionally, the savings using the presented model are at least 5% higher than uncoordinated charging, and can reach more than 50% at best.Clairand-Gómez, J.; Rodríguez-García, J.; Álvarez, C. (2018). Smart Charging for Electric Vehicle Aggregators considering Users Preferences. IEEE Access. 6:1-12. https://doi.org/10.1109/ACCESS.2018.2872725S112

Non-Linear Control of a DC Microgrid for Electric Vehicle Charging Stations

Environmental concerns push governments to invest in renewable energy (RE). They are natural sources with a low carbon footprint and do not pollute locally. However, it is technically difficult to deploy high penetration of RE into the utility grid, due to the generation uncertainties and high installation costs, which are some of the most critical issues in RES use in this area. To address this issue, DC microgrids arise as a solution to integrate local distributed generation (DG) and storage, and to mitigate the issues related to AC/DC and DC/AC converters. Thanks to their main advantages for the power grid and energy consumers, microgrids have gained significant interest in recent years.  By another side, the electric vehicles (EVs) market is expected to grow in the coming years, which represent a new load that must be properly managed to avoid grid issues. Thus, this paper discusses the operation of DC microgrid considering the introduction of EVs. A nonlinear control is presented, including the modeling of charging of EVs. The simulated DC microgrid includes solar PV, a battery, and a supercapacitor. Significant variations from PV generation were included to highlight the performance of the methodology. The results show that the voltage fluctuations are small, which provides the DC microgrid with the required voltage stability. Moreover, it has been demonstrated that DC microgrids can be integrated in isolated locations that are not connected to the main grid in view of the RESs and EVs

Impact of Electric Vehicle Charging Strategy on the Long-Term Planning of an Isolated Microgrid

[EN] Isolated microgrids, such as islands, rely on fossil fuels for electricity generation and include vehicle fleets, which poses significant environmental challenges. To address this, distributed energy resources based on renewable energy and electric vehicles (EVs) have been deployed in several places. However, they present operational and planning concerns. Hence, the aim of this paper is to propose a two-level microgrid problem. The first problem considers an EV charging strategy that minimizes charging costs and maximizes the renewable energy use. The second level evaluates the impact of this charging strategy on the power generation planning of Santa Cruz Island, Galapagos, Ecuador. This planning model is simulated in HOMER Energy. The results demonstrate the economic and environmental benefits of investing in additional photovoltaic (PV) generation and in the EV charging strategy. 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Non-Linear Control of a DC Microgrid for Electric Vehicle Charging Stations

[EN] Environmental concerns push governments to invest in renewable energy (RE). They are natural sources with a low carbon footprint and do not pollute locally. However, it is technically difficult to deploy high penetration of RE into the utility grid, due to the generation uncertainties and high installation costs, which are some of the most critical issues in RES use in this area. To address this issue, DC microgrids arise as a solution to integrate local distributed generation (DG) and storage, and to mitigate the issues related to AC/DC and DC/AC converters. Thanks to their main advantages for the power grid and energy consumers, microgrids have gained significant interest in recent years. By another side, the electric vehicles (EVs) market is expected to grow in the coming years, which represent a new load that must be properly managed to avoid grid issues. Thus, this paper discusses the operation of DC microgrid considering the introduction of EVs. A nonlinear control is presented, including the modeling of charging of EVs. The simulated DC microgrid includes solar PV, a battery, and a supercapacitor. Significant variations from PV generation were included to highlight the performance of the methodology. The results show that the voltage fluctuations are small, which provides the DC microgrid with the required voltage stability. Moreover, it has been demonstrated that DC microgrids can be integrated in isolated locations that are not connected to the main grid in view of the RESs and EVs.This work belongs to the project SIS.JCG.19.03 from Universidad de las Américas - EcuadorBenamar, A.; Travaillé, P.; Clairand Gómez, J.; Escrivá-Escrivá, G. (2020). Non-Linear Control of a DC Microgrid for Electric Vehicle Charging Stations. International Journal on Advanced Science, Engineering and Information Technology. 10(2):593-598. https://doi.org/10.18517/ijaseit.10.2.10815S59359810

Power Generation Planning of Galapagos Microgrid Considering Electric Vehicles and Induction Stoves

[EN] Islands located far away from the mainland and remote communities depend on isolated microgrids based on diesel fuel, which results in significant environmental and cost issues. This is currently being addressed by integrating renewable energy sources (RESs). Thus, this paper discusses the generation planning problem in diesel-based island microgrids with RES, considering the electrification of transportation and cooking to reduce their environmental impact, and applied to the communities of Santa Cruz and Baltra in the Galapagos Islands in Ecuador. A baseline model is developed in HOMER for the existing system with diesel generation and RES, while the demand of electric vehicles and induction stoves is calculated from vehicle driving data and cooking habits in the islands, respectively. The integration of these new loads into the island microgrid is studied to determine its costs and environmental impacts, based on diesel cost sensitivity studies to account for its uncertainty. The results demonstrate the economic and environmental benefits of investing in RES for Galapagos' microgrid, to electrify the local transportation and cooking system.J.-M. Clairand would like to thank Universidad de las Americas for funding his visit to the University of Waterloo. The authors would like to thank W. Mendieta, F. Calero, and E. Vera from the University of Waterloo for their valuable comments and helpful suggestions.Clairand-Gómez, J.; Arriaga, M.; Cañizares, CA.; Álvarez, C. (2019). Power Generation Planning of Galapagos Microgrid Considering Electric Vehicles and Induction Stoves. IEEE Transactions on Sustainable Energy. 10(4):1916-1926. https://doi.org/10.1109/TSTE.2018.2876059S1916192610

Review on Multi-Objective Control Strategies for Distributed Generation on Inverter-Based Microgrids

[EN] Microgrids have emerged as a solution to address new challenges in power systems with the integration of distributed energy resources (DER). Inverter-based microgrids (IBMG) need to implement proper control systems to avoid stability and reliability issues. Thus, several researchers have introduced multi-objective control strategies for distributed generation on IBMG. This paper presents a review of the different approaches that have been proposed by several authors of multi-objective control. This work describes the main features of the inverter as a key component of microgrids. Details related to accomplishing efficient generation from a control systems' view have been observed. This study addresses the potential of multi-objective control to overcome conflicting objectives with balanced results. Finally, this paper shows future trends in control objectives and discussion of the different multi-objective approaches.Gonzales-Zurita, Ó.; Clairand, J.; Peñalvo-López, E.; Escrivá-Escrivá, G. (2020). Review on Multi-Objective Control Strategies for Distributed Generation on Inverter-Based Microgrids. Energies. 13(13):1-29. https://doi.org/10.3390/en13133483S1291313Ross, M., Abbey, C., Bouffard, F., & Joos, G. (2015). Multiobjective Optimization Dispatch for Microgrids With a High Penetration of Renewable Generation. IEEE Transactions on Sustainable Energy, 6(4), 1306-1314. doi:10.1109/tste.2015.2428676Murty, V. V. S. N., & Kumar, A. (2020). Multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems. Protection and Control of Modern Power Systems, 5(1). doi:10.1186/s41601-019-0147-zKatircioğlu, S., Abasiz, T., Sezer, S., & Katırcıoglu, S. (2019). 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International Journal of Electrical Power & Energy Systems, 98, 531-542. doi:10.1016/j.ijepes.2017.12.023Khayat, Y., Naderi, M., Shafiee, Q., Batmani, Y., Fathi, M., Guerrero, J. M., & Bevrani, H. (2019). Decentralized Optimal Frequency Control in Autonomous Microgrids. IEEE Transactions on Power Systems, 34(3), 2345-2353. doi:10.1109/tpwrs.2018.2889671Arcos-Aviles, D., Pascual, J., Marroyo, L., Sanchis, P., & Guinjoan, F. (2018). Fuzzy Logic-Based Energy Management System Design for Residential Grid-Connected Microgrids. IEEE Transactions on Smart Grid, 9(2), 530-543. doi:10.1109/tsg.2016.2555245Alyazidi, N. M., Mahmoud, M. S., & Abouheaf, M. I. (2018). Adaptive critics based cooperative control scheme for islanded Microgrids. Neurocomputing, 272, 532-541. doi:10.1016/j.neucom.2017.07.027Buduma, P., & Panda, G. (2018). Robust nested loop control scheme for LCL‐filtered inverter‐based DG unit in grid‐connected and islanded modes. IET Renewable Power Generation, 12(11), 1269-1285. doi:10.1049/iet-rpg.2017.0803Batiyah, S., Sharma, R., Abdelwahed, S., & Zohrabi, N. (2020). An MPC-based power management of standalone DC microgrid with energy storage. International Journal of Electrical Power & Energy Systems, 120, 105949. doi:10.1016/j.ijepes.2020.105949Baghaee, H. R., Mirsalim, M., Gharehpetan, G. B., & Talebi, H. A. (2018). Nonlinear Load Sharing and Voltage Compensation of Microgrids Based on Harmonic Power-Flow Calculations Using Radial Basis Function Neural Networks. IEEE Systems Journal, 12(3), 2749-2759. doi:10.1109/jsyst.2016.2645165Benhalima, S., Miloud, R., & Chandra, A. (2018). Real-Time Implementation of Robust Control Strategies Based on Sliding Mode Control for Standalone Microgrids Supplying Non-Linear Loads. 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A Time-Series Treatment Method to Obtain Electrical Consumption Patterns for Anomalies Detection Improvement in Electrical Consumption Profiles

[EN] Electricity consumption patterns reveal energy demand behaviors and enable strategY implementation to increase efficiency using monitoring systems. However, incorrect patterns can be obtained when the time-series components of electricity demand are not considered. Hence, this research proposes a new method for handling time-series components that significantly improves the ability to obtain patterns and detect anomalies in electrical consumption profiles. Patterns are found using the proposed method and two widespread methods for handling the time-series components, in order to compare the results. Through this study, the conditions that electricity demand data must meet for making the time-series analysis useful are established. Finally, one year of real electricity consumption is analyzed for two different cases to evaluate the effect of time-series treatment in the detection of anomalies. The proposed method differentiates between periods of high or low energy demand, identifying contextual anomalies. The results indicate that it is possible to reduce time and effort involved in data analysis, and improve the reliability of monitoring systems, without adding complex procedures.Serrano-Guerrero, X.; Escrivá-Escrivá, G.; Luna-Romero, S.; Clairand, J. (2020). A Time-Series Treatment Method to Obtain Electrical Consumption Patterns for Anomalies Detection Improvement in Electrical Consumption Profiles. Energies. 13(5):1-23. https://doi.org/10.3390/en13051046S123135Hong, T., Yang, L., Hill, D., & Feng, W. (2014). Data and analytics to inform energy retrofit of high performance buildings. Applied Energy, 126, 90-106. doi:10.1016/j.apenergy.2014.03.052Ogunjuyigbe, A. S. O., Ayodele, T. R., & Akinola, O. A. (2017). User satisfaction-induced demand side load management in residential buildings with user budget constraint. Applied Energy, 187, 352-366. doi:10.1016/j.apenergy.2016.11.071Huang, Y., Sun, Y., & Yi, S. (2018). Static and Dynamic Networking of Smart Meters Based on the Characteristics of the Electricity Usage Information. Energies, 11(6), 1532. doi:10.3390/en11061532Lin, R., Ye, Z., & Zhao, Y. (2019). OPEC: Daily Load Data Analysis Based on Optimized Evolutionary Clustering. Energies, 12(14), 2668. doi:10.3390/en12142668Hunt, L. C., Judge, G., & Ninomiya, Y. (2003). Underlying trends and seasonality in UK energy demand: a sectoral analysis. Energy Economics, 25(1), 93-118. doi:10.1016/s0140-9883(02)00072-5Serrano-Guerrero, X., Escrivá-Escrivá, G., & Roldán-Blay, C. (2018). Statistical methodology to assess changes in the electrical consumption profile of buildings. Energy and Buildings, 164, 99-108. doi:10.1016/j.enbuild.2017.12.059Chandola, V., Banerjee, A., & Kumar, V. (2009). Anomaly detection. ACM Computing Surveys, 41(3), 1-58. doi:10.1145/1541880.1541882Escrivá-Escrivá, G., Álvarez-Bel, C., Roldán-Blay, C., & Alcázar-Ortega, M. (2011). New artificial neural network prediction method for electrical consumption forecasting based on building end-uses. Energy and Buildings, 43(11), 3112-3119. doi:10.1016/j.enbuild.2011.08.008Serrano-Guerrero, X., Prieto-Galarza, R., Huilcatanda, E., Cabrera-Zeas, J., & Escriva-Escriva, G. (2017). Election of variables and short-term forecasting of electricity demand based on backpropagation artificial neural networks. 2017 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC). doi:10.1109/ropec.2017.8261630Jain, R. K., Smith, K. M., Culligan, P. J., & Taylor, J. E. (2014). Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracy. 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Identifying spikes and seasonal components in electricity spot price data: A guide to robust modeling. Energy Economics, 38, 96-110. doi:10.1016/j.eneco.2013.03.013Angelos, E. W. S., Saavedra, O. R., Cortés, O. A. C., & de Souza, A. N. (2011). Detection and Identification of Abnormalities in Customer Consumptions in Power Distribution Systems. IEEE Transactions on Power Delivery, 26(4), 2436-2442. doi:10.1109/tpwrd.2011.2161621Milton, M.-A., Pedro, C.-O., Xavier, S.-G., & Guillermo, E.-E. (2018). Characterization and Classification of Daily Electricity Consumption Profiles: Shape Factors and k-Means Clustering Technique. E3S Web of Conferences, 64, 08004. doi:10.1051/e3sconf/20186408004Chicco, G. (2012). Overview and performance assessment of the clustering methods for electrical load pattern grouping. Energy, 42(1), 68-80. doi:10.1016/j.energy.2011.12.031Seem, J. E. (2005). Pattern recognition algorithm for determining days of the week with similar energy consumption profiles. 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Techno-Economic Assessment of Renewable Energy-based Microgrids in the Amazon Remote Communities in Ecuador

This is the peer reviewed version of the following article: Clairand, J., Serrano-Guerrero, X., González-Zumba, A. and Escrivá-Escrivá, G. (2022), Techno-Economic Assessment of Renewable Energy-based Microgrids in the Amazon Remote Communities in Ecuador. Energy Technol., 10: 2100746, which has been published in final form at https://doi.org/10.1002/ente.202100746. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.[EN] Several remote communities have limited electricity access and are mainly dependent on environmentally damaging fossil fuels. The installation of microgrid networks and green energy initiatives are currently addressing this issue. Thus, the techno-economic assessment of a microgrid that comprises photovoltaic arrays, a micro-hydro turbine, and diesel generation is proposed herein. Two scenarios are evaluated considering the inclusion or not of diesel generation. This model is performed in HOMER. The results demonstrate that the best option in economics is to invest in a PV/hydro/diesel microgrid, resulting in an net present cost of 2.33 M$, and a cost of energy of 0.194$ kWh(-1). Furthermore, to address diesel price uncertainties, a sensitivity analysis is carried out based on three different projected diesel prices.Clairand, J.; Serrano-Guerrero, X.; González-Zumba, A.; Escrivá-Escrivá, G. (2022). Techno-Economic Assessment of Renewable Energy-based Microgrids in the Amazon Remote Communities in Ecuador. Energy Technology. 10(2):1-13. https://doi.org/10.1002/ente.202100746S11310