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- W2912363362 abstract "Hybrid power system is seen as a viable alternative to the conventional systems. Estimating the potential of these hybrid power systems for a selected site is a major input required for making informed decisions. Often, estimation of the kWhr production is a very elaborate and tedious exercise due to lack of a reliable model for the same. This article proposed an Artificial Neural Network based model that can be used to easily estimate the total kWhr/year for a given combination of Solar PV, Wind generator and Battery. The variable load considered for the model is a desalination plant load. The data is modelled using Neural Network and validated. The proposed Neural Network model offers a reliable estimation on the total annual power generation for a given combination of Solar PV, Wind generator and battery capacity," @default.
- W2912363362 created "2019-02-21" @default.
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- W2912363362 date "2019-01-01" @default.
- W2912363362 modified "2023-09-26" @default.
- W2912363362 title "Modeling Renewables Based Hybrid Power System with Desalination Plant Load Using Neural Networks" @default.
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- W2912363362 doi "https://doi.org/10.1080/21563306.2019.12054396" @default.
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