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Techno-economic optimization of hybrid wind and marine current turbine connected to the grid: a case study in Ksar Sghir, Morocco

Published: 02 October 2019 Publication History

Abstract

In this paper, we present a techno-economic feasibility study of a hybrid power system connected to the grid. The hybrid system contains wind and marine current turbines, and it will provide green electric energy to a coastal village in the region of Ksar Sghir, northern Morocco. The total electric demand of the village is about 2.17 GWh per year. We used HOMER pro software to analyze and simulate different systems in order to determine the optimal solution. In this regard and in order to get reliable results that describe the local conditions, of the villages under study we conducted a consistent survey of several parameters such as: interest rate, project lifetime and different technical parameters of the energy converters and batteries as well the wind's and marine current's potentials and monthly and daily loads.

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cover image ACM Other conferences
SCA '19: Proceedings of the 4th International Conference on Smart City Applications
October 2019
788 pages
ISBN:9781450362894
DOI:10.1145/3368756
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 October 2019

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Author Tags

  1. HOMER
  2. economical simulation
  3. hybrid system cost of energy
  4. marine current
  5. wind

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Overall Acceptance Rate 183 of 487 submissions, 38%

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