Techno-economic analysis of autonomous PV-wind hybrid energy systems using different sizing methods


Celik A. N.

Energy Conversion and Management, vol.44, no.12, pp.1951-1968, 2003 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 44 Issue: 12
  • Publication Date: 2003
  • Doi Number: 10.1016/s0196-8904(02)00223-6
  • Journal Name: Energy Conversion and Management
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1951-1968
  • Keywords: Autonomous PV-wind energy system, Hybrid energy system, Optimisation, Sizing methodology
  • Hatay Mustafa Kemal University Affiliated: Yes

Abstract

The sizing and techno-economic optimisation of an autonomous PV-wind hybrid energy system with battery storage is addressed in this article. A novel sizing method is introduced. It is a developed version of similar earlier sizing methods, taking into account a further design parameter. The techno-economic optimisation of autonomous energy systems should include the following design parameters at the same time: the level of autonomy, i.e. the fraction of time for which the specified load can be met, and the cost of the system. Without one of these, the techno-economic optimisation would be incomplete. New concepts, which combine the system autonomy and cost, are also introduced to be used in the techno-economic optimisation process. The sizing of a PV-wind hybrid system on a yearly basis requires a detailed analysis of the solar radiation and wind speed on a monthly basis. It is common to size such renewable systems for the worst month. It is, however, shown that the worst month scenarios lead to too costly and, therefore, non-optimal a system in terms of techno-economics. It is, therefore, suggested that alternative solutions be sought, rather than using the worst month scenario. An alternative method is applied in the present article. It suggests a third energy source (auxiliary source) be incorporated into the system instead of increasing the hardware sizes excessively for the worst month. It is shown that this leads to techno-economically more optimum systems. © 2002 Elsevier Science Ltd. All rights reserved.