An alternative methodology to evaluate sites using climatology criteria for hosting wind, solar, and hybrid plants

ABSTRACT

Nowadays a suitable place selection for hosting alternative technologies in power plant installation has been a problem, such as wind and photovoltaic plants. Additionally, the hybrid plant inclusion from these two alternative energy sources is even more challenging for project planners who consider different criteria such as orographic, economic, geographic, and the most important climatological. This paper presents an alternative methodology to evaluate the available wind and solar energy resources in a site for determining if it is a candidate to host wind, solar, or hybrid power plants (wind and solar) with only climatological criteria using databases of automatic meteorological stations. To evaluate the available wind resource, the Weibull distribution was conducted according to on-site wind speed and the parameters are calculated using the modified maximum likelihood (MML) method. The available solar resource is analyzed in the peak hours of solar radiation at the site. The wind speed and peak solar time variables are addressed to a decision tree that determines if the site is suitable to host wind, solar, hybrid, or no power generation technologies according to the weather criteria. The methodology was performed in four sites with different weather according to Köppen–Geigen climate classification in Mexico and showed that two sites have potential to host hybrid plants with 80%; three sites with wind power plant at 100% and one site with solar power plant about 60% of power on-site resource available. Murcia, Spain, was considered to validate its application in any site, showing a similar performance, getting the potential to host wind, solar, and hybrid plants with 100%, 46%, and 70% of power on-site resources available, respectively. The results show that this methodology is the easiest and useful alternative to evaluate sites by using climatology criteria for hosting wind, solar, or hybrid power generation plants.

KEYWORDS:

• Renewable energy
• statistical analysis
• planning and scheduling
• climate change
• power generation systems

Nomenclature

$A$	=	Surface: $m^2$
AWS	=	Automatic weather station
$c$	=	Scale factor in $m/s$
$F_e$	=	Energy factor
$f\left(v\right)$	=	Probability of wind speed occurrence
$h$	=	Elevation of the site: m.a.s.l.
$k.s.$	=	Shape factor (fitting) of Weibull distribution
m.a.s.l.	=	Meters above sea level
MML	=	Modified maximum likelihood method
$N$	=	Data number
$P_e$	=	Site wind power: $W$
$R^2$	=	Determination coefficient
$Rad$	=	Solar radiation measured in the site: $W/m^2$
$SEP$	=	Solar energy production: $W/m^2$
SMN	=	Meteorological national service
$SPH$	=	Sun peak hours: $hours$
$T$	=	Air temperature: ${ }^{\circ }C$
UTM	=	Universal transverse mercator
$v$	=	Wind speed: $m/s$
$\bar{v}$	=	Average wind speed: $m/s$
$\rho$	=	Air density:$kg/m^2$

Acknowledgments

Special thanks to Consejo Nacional de Ciencia y Tecnología (CONACYT) for the financial support and the Project “Fortalecimiento de las capacidades e infraestructura de un laboratorio para la investigación científica y desarrollo tecnológico en el área del aprovechamiento de la energía térmica solar” (No. 249606) of Secretaría de Energía – Consejo Nacional de Ciencia y Tecnología.

Additional information

Notes on contributors

José Manuel Álvarez-Alvarado

José ManuelÁlvarez-Alvarado was born in Durango, Mexico in 1990.He received his B.S degree in mechatronic in Instituto Tecnológico de la Laguna in Coahuila, México and his M.S. degree in Automatic Control degree in the School of Engineering from the Universidad Autónoma de Querétaro, México in 2013 and 2017 respectively. He is currently a student of a Ph.D. program in the School of Engineering at the Universidad Autónoma de Querétaro, México. His research interests include renewable energy; prediction, energy sustainability, and control systems energy generation systems.

José Gabriel Ríos-Moreno

José Gabriel Ríos-Moreno received his B.S and M.S. degrees in Automatic Control, and his Ph.D. degree in the School of Engineering from the Universidad Autónoma de Querétaro, México in 2003, 2005 and 2008 respectively. He is currently Professor of the School of Engineering at the Universidad Autónoma de Querétaro, México. His research interests include signal processing; modeling; prediction, energy sustainability, and control systems for intelligent buildings. He is currently a member of the Sistema Nacional de Investigadores (SNI), CONACYT, México, and member of the Academic Group of Instrumentation and Control in the School of Engineering U.A.Q.

Eusebio Jr Ventura-Ramos

Eusebio Jr Ventura-Ramos received the degree of Agricultural Engineer Specialist in Soils from the Universidad Autónoma Chapingo, Mexico, the Master of Science degree in the area of Soil Physics at the Colegio de Posgraduados, Mexico, the degree of Doctor in the area of Water Erosion by Purdue University in West Lafayette, Indiana, USA, and a Postdoctoral in Water Erosion Mechanics at the Laboratorio Nacional de Investigación en Erosión de Suelos, Mexico, in 1988, 1992, 1998, and 1999. He has published some scientific papers in journals and has presented conferences about soil mechanics.

Guillermo Ronquillo-Lomeli

Guillermo Ronquillo-Lomeli received the Ph.D. in Science and Technology in Mechatronics awarded by the Inter-institutional Postgraduate in Science and Technology at CIDESI. Master of Science with an honorable mention in instrumentation and automatic control area at the Autonomous University of Querétaro. Electronics Engineer by the Technological Institute of Querétaro. He has a degree in Industrial Automation from for Engineering and Industrial Development Center. He has 23 years of experience in research and technological development in instrumentation, automatic control, and electronics area. He has collaborated in at least twelve technology transfer and applied research projects in electronic design, energy optimization processes, and testbeds for alternative energy systems subjects. He has two patents, five publications in indexed journals, two book chapters and participation in two international congresses. Currently, He is Principal Investigator in the management of conventional energies in the Energy Direction in the Engineering and Industrial Development Center and National researcher level 1 from 2017 to 2019.

Mario Trejo-Perea

Mario Trejo-Perea was born in Querétaro, Mexico, in 1968. He received the B.S. and M.S. degrees in automatic control and the Ph.D. degree from the Universidad Autónoma de Querétaro, Mexico, in 1994, 2005, and 2008, respectively. In 1994, he joined the School of Engineering, Universidad Autónoma de Querétaro, where he is currently a Researcher-Professor. He is also a member of the Sistema Nacional de Investigadores, Mexico. He has published some scientific papers in journals and has presented conferences on energy consumption prediction using neural networks’ models. His research interest includes the development of models’ prediction energy in intelligent buildings.