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Spatial microgrid planning with renewable energy and electric vehicles


Microgrids include distributed energy resources (DER), such as distributed generation (DG), energy storage (ES), and onsite loads. This kind of grid can operate in either grid-connected or island autonomous mode. Among the benefits of implementing microgrids, the improvement of generation efficiency in a sustainable power distribution system have attracted the attention of several research groups to the optimal topology design of microgrids. Several loop-based microgrid topology methodologies have been presented in the specialized literature, because this topology can guarantee network reliability, satisfying a desired level of generation efficiency. In general, these methodologies consider two stages: graph partitioning for microgrid topology planning and loop-based structure design. For the first stage, the necessary clusters of microgrid nodes based on available DERs should be identified. The optimal electrical loop-based path is found in the second stage. In most power distribution networks, renewable energy (RE) equipment and electric vehicles (EVs) are distributed in a dispersed manner. This dispersed distribution allows the use of geographic information systems (GIS) in order to visualize socioeconomic characteristics, spatial distribution of energy resources, weather impacts on power distribution networks, and the geographical location of load centers within the studied zone, thus providing useful spatial information for loop-based microgrid topology studies. GIS provides tools to perform spatial clustering considering several characteristics of the study area. In addition, the definition of the connection point of the microgrid with the power distribution network can be defined using GIS. Therefore, this research project proposes the development of GIS methodologies to assist with the spatial planning of loop-based microgrid topologies through spatial partitioning and optimal electrical planning algorithms. These methodologies should allow to efficiently use distribution grids to supply the high demand required by EV recharging stations over a planning horizon, considering DERs in distribution feeders in the context of microgrids. (AU)

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Scientific publications (12)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
PALATE, BYRON O.; GUEDES, TATIANA P.; GRILO-PAVANI, AHDA; PADILHA-FELTRIN, ANTONIO; MELO, JOEL D.. Aggregator units allocation in low voltage distribution networks with penetration of photovoltaic systems. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, v. 130, p. 14-pg., . (15/21972-6, 19/00466-6)
RODRIGUES, JOAO L.; BOLOGNESI, HUGO M.; MELO, JOEL D.; HEYMANN, FABIAN; SOARES, F. J.. Spatiotemporal model for estimating electric vehicles adopters. ENERGY, v. 183, p. 788-802, . (19/00466-6, 17/22577-9)
VENTURA, LUCAS DE OLIVEIRA; MELO, JOEL D.; PADILHA-FELTRIN, ANTONIO; FERNANDEZ-GUTIERREZ, JUAN PABLO; SANCHEZ ZULETA, CARMEN C.; PIEDRAHITA ESCOBAR, CARLOS CESAR. A new way for comparing solutions to non-technical electricity losses in South America. UTILITIES POLICY, v. 67, . (17/22577-9, 15/21972-6, 19/00466-6)
GASTELU, JOEL VILLAVICENCIO; LEITE, JONATAS BOAS; MELO TRUJILLO, JOEL DAVID; IEEE. Stochastic Analysis of Hosting Capacity in Low-Voltage Networks with PV-plus-Storage Systems. 2020 IEEE PES TRANSMISSION & DISTRIBUTION CONFERENCE AND EXHIBITION - LATIN AMERICA (T&D LA), v. N/A, p. 6-pg., . (15/21972-6, 19/00466-6, 19/07436-5)
MORRO-MELLO, IGOOR; PADILHA-FELTRIN, ANTONIO; MELO, JOEL D.; CALVINO, AIDA. Fast charging stations placement methodology for electric taxis in urban zones. ENERGY, v. 188, . (19/00466-6, 15/21972-6, 17/01909-3, 17/22577-9)
MEJIA, MARIO A.; MELO, JOEL D.; ZAMBRANO-ASANZA, SERGIO; PADILHA-FELTRIN, ANTONIO. Spatial-temporal growth model to estimate the adoption of new end-use electric technologies encouraged by energy-efficiency programs. ENERGY, v. 191, . (19/00466-6, 17/22577-9, 15/21972-6)
LAYLAKAR, MARJHORRE; MAJOR, LUCAS V. L.; BELATI, EDMARCIO A.; FALCAO, DJALMA M.; HEYMANN, FABIAN; MELO, JOEL D.. Spatial-economic framework to estimate small biomass plant remuneration in reactive power markets. SUSTAINABLE ENERGY GRIDS & NETWORKS, v. 28, . (21/08832-1, 19/00466-6)
DE MELO, DIEGO MARCOCHI; GASTELU, JOEL VILLAVICENCIO; ASANO, PATRICIA T. L.; MELO, JOEL D.. Spatiotemporal estimation of photovoltaic system adopters using fuzzy logic. RENEWABLE ENERGY, v. 181, p. 1188-1196, . (15/21972-6, 19/00466-6)
MORRO-MELLO, IGOOR; PADILHA-FELTIRN, ANTONIO; MELO, JOEL D.; HEYMANN, FABIAN. Spatial connection cost minimization of EV fast charging stations in electric distribution networks using local search and graph theory. ENERGY, v. 235, . (15/21972-6, 17/22577-9, 17/01909-3, 19/00466-6)
HEYMANN, FABIAN; SILVA, JOAO; VILACA, PHILIPE; SOARES, FILIPE JOEL; DUENAS, PABLO; MELO, JOEL; MIRANDA, VLADIMIRO; IEEE. Vertical Load Uncertainty at the T/D Boundary under different spatial DER allocation techniques. 2019 2ND INTERNATIONAL CONFERENCE ON SMART ENERGY SYSTEMS AND TECHNOLOGIES (SEST 2019), v. N/A, p. 6-pg., . (19/00466-6, 17/22577-9)
VERA, ENRIQUE GABRIEL; CANIZARES, CLAUDIO A.; PIRNIA, MEHRDAD; GUEDES, TATIANA PONTUAL; TRUJILLO, JOEL DAVID MELO. Two-Stage Stochastic Optimization Model for Multi-Microgrid Planning. IEEE TRANSACTIONS ON SMART GRID, v. 14, n. 3, p. 13-pg., . (19/00466-6, 21/08832-1)
MELLO, IGOOR MORRO; FAUSTINO, FAUSTA J.; MELO, JOEL D.; FELTRIN, ANTONIO PADILHA; IEEE. Greenhouse Gas Reduction Through the Introduction of Electric Vehicles in Urban Zones. 2020 IEEE PES TRANSMISSION & DISTRIBUTION CONFERENCE AND EXHIBITION - LATIN AMERICA (T&D LA), v. N/A, p. 6-pg., . (15/21972-6, 19/00466-6, 17/22577-9)

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