a study on electrification of agricultural wells using fuzzy clustering algorithm and selection of optimal scenarios

Every year a large amount of subsidized diesel fuel is delivered to farmers for irrigation purposes. in addition to low efficiency and high maintenance costs, diesel pumps increase environmental pollution and produce greenhouse gases. for this reason, in recent decades, the replacement of diesel pumps with electric pumps has been a priority for governments in most developing countries. despite the many benefits of electrifying agricultural wells, providing the required demand for electric pumps has always been one of the main challenges facing grid operators. the development of renewable resources and distributed generation resources can be an effective strategy to provide economically justifiable solutions to supply the demand for agricultural wells and result in savings in fossil fuel consumption. policymakers must have a clear understanding of different approaches regarding the electrification of irrigation systems and conceivable scenarios. in this paper, economic studies based on the enactments of the plan to supply electricity to iran’s agricultural wells are presented on a pilot scale. in this paper, a clustering of agricultural wells based on the fuzzy clustering method is presented. the purpose of using the fuzzy clustering method is to present the best classification of wells in terms of dispersion rate and select the best demand-supply scenario (of the four proposed scenarios) based on the analysis of the economic indices. in the final section of the paper, the analysis of the results of the proposed method is discussed.