Stand-alone hybrid power plant based on SiC solar PV and wind inverters with smart spinning reserve management

Martín-Arroyo, S. (Universidad de Zaragoza) ; Cebollero, J.A. (Universidad de Zaragoza) ; García-Gracia, M. (Universidad de Zaragoza) ; Llamazares, Á. (Universidad de Zaragoza)

Resumen: Stand-alone hybrid power plants based on renewable energy sources are becoming a more and more interesting alternative. However, their management is a complex task because there are many variables, requirements and restrictions as well as a wide variety of possible scenarios. Though a proper sizing of the power plant is necessary to obtain a competitive cost of the energy, smart management is key to guarantee the power supply at a minimum cost. In this work, a novel hybrid power plant control strategy is designed, implemented and simulated under a wide variety of scenarios. Thereby, the proposed control algorithm aims to achieve maximum integration of renewable energy, reducing the usage of non-renewable generators as much as possible and guaranteeing the stability of the microgrid. Different scenarios and case studies have been analyzed by dynamic simulation to verify the proper operation of the power plant controller. The main novelties of this work are: (i) the stand-alone hybrid power plant management regarding a battery energy storage system as a part of the spinning reserve, (ii) the characterization of the largest loads as non-priority loads, (iii) the minimization of the needed spinning reserve and fuel consumption from diesel generators.

Idioma: Inglés

DOI: 10.3390/electronics10070796

Año: 2021

Publicado en: Electronics 10, 7 (2021), 796 [27 pp]
ISSN: 2079-9292

Factor impacto JCR: 2.69 (2021)

Categ. JCR: COMPUTER SCIENCE, INFORMATION SYSTEMS rank: 100 / 164 = 0.61 (2021) - Q3 - T2
Categ. JCR: PHYSICS, APPLIED rank: 82 / 161 = 0.509 (2021) - Q3 - T2
Categ. JCR: ENGINEERING, ELECTRICAL & ELECTRONIC rank: 139 / 277 = 0.502 (2021) - Q3 - T2

Factor impacto CITESCORE: 3.7 - Computer Science (Q2) - Engineering (Q2)

Factor impacto SCIMAGO: 0.59 - Computer Networks and Communications (Q2) - Signal Processing (Q2) - Hardware and Architecture (Q2) - Control and Systems Engineering (Q2)

Financiación: info:eu-repo/grantAgreement/EC/H2020/783158/EU/first and euRopEAn siC eigTh Inches pilOt liNe/REACTION

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Ingeniería Eléctrica (Dpto. Ingeniería Eléctrica)