Urban photovoltaic potential estimation based on architectural conditions, production-demand matching, storage and the incorporation of new eco-efficient loads

Sergio Zambrano-Asanza, Esteban F. Zalamea-León, Edgar A. Barragán-Escandón, Alejandro Parra-González

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

The photovoltaic solar potential in an urban sector and the effects produced by the electricity input into a low-voltage grid are determined, the analysis is performed for one year. First, the generation profiles are estimated, assuming the incorporation limits of typical silica panels and using photovoltaic (PV) tiles on roofs as an architectural alternative. Then, the consumer class demand is estimated. Production-demand matching is performed at the load point level to avoid impacts on the grid. A scenario incorporating a new load, induction heating cookers (IHCs) for all residential users, is posed, the use of which coincides with high-radiation hours. Finally, electrical storage is assumed to maximise the PV supply. A 16% coverage with silica PV panels, or 33% with PV tiles, would supply 46% or 39% of the consumption, respectively. With massive incorporation of IHCs and storage, the supply is increased to 73% and 59% of the consumption with silica panels and PV tiles, respectively. An annual consumption reduction of 16 Tn of liquefied petroleum gas is attained in the cases studied. Additionally, it is necessary to redirect the current subsidies for hydro dams and the overall energy sector towards promoting distributed microgeneration.

Original languageEnglish
Pages (from-to)224-238
Number of pages15
JournalRenewable Energy
Volume142
DOIs
StatePublished - 1 Nov 2019

Bibliographical note

Publisher Copyright:
© 2019 Elsevier Ltd

Keywords

  • Demand side management
  • Photovoltaics
  • Solar energy
  • Spatial distribution
  • Urban energy system

Fingerprint

Dive into the research topics of 'Urban photovoltaic potential estimation based on architectural conditions, production-demand matching, storage and the incorporation of new eco-efficient loads'. Together they form a unique fingerprint.

Cite this