4.7 Article

Finding the most suitable existing irrigation dams for small hydropower development in Turkey: A GIS-Fuzzy logic tool

Journal

RENEWABLE ENERGY
Volume 172, Issue -, Pages 633-650

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2021.03.049

Keywords

Irrigation dams; Small hydropower; GIS; Fuzzy multi-criteria decision making; Turkey

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This paper uses GIS-fuzzy logic technology to evaluate and rank existing irrigation dams, select the most suitable dam for small hydropower development, and demonstrate feasibility through evaluation of Turkish dams. Additionally, the use of medium-head hydro turbines and optimized grid connection routes are proposed to minimize land expropriation.
This paper enables a screening of existing irrigation dams in order to assess and rank potential sites for small hydropower development by using a Geographic Information System (GIS)-fuzzy logic multi criteria scoring technique. The following criteria are evaluated: dam characteristics (reservoir normal level, reservoir capacity, dam purpose, dam ageing), and grid connection spatial characteristics. The proposed method estimates the suitability degree of each criterion separately and then aggregates them into a Site Suitability Index (SSI). Existing irrigation dams in Turkey are assessed in order to be utilized for hydropower development. The overall score of each candidate site is obtained and, their performance is compared for different strategies. One of the most suitable dams, Karadere, was chosen as a case study. By using the daily continuous monitored data, we showed that flow and head is highly variable during the irrigation season. Accordingly, we evaluated an innovative compact medium-head hydro turbine that can capture those fluctuations with its operational flexibility and minimal civil works. Moreover, an optimal path methodology was applied to find the best grid connection route from the dam to its nearest substation considering the site land use characteristics in order to minimize land expropriation. (c) 2021 Elsevier Ltd. All rights reserved.

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