Operating and maintenance cost in seawater reverse osmosis desalination plants. Artificial neural network based model

被引：10

作者：

Ruiz-Garcia, A. ^{[1
]}

Feo-Garcia, J. ^{[2
]}

机构：

[1] Univ Las Palmas Gran Canaria, Dept Mech Engn, Edificio Ingn,Campus Univ Tafira, Las Palmas Gran Canaria 35017, Spain

[2] Univ Las Palmas Gran Canaria, Dept Elect & Automat Engn, Edificio Ingn,Campus Univ Tafira, Las Palmas Gran Canaria 35017, Spain

来源：

DESALINATION AND WATER TREATMENT | 2017年 / 73卷

关键词：

Seawater; Reverse osmosis; Operating and maintenance; Costs; WATER-TREATMENT; CANARY-ISLANDS; OPTIMIZATION; SUSTAINABILITY; PREDICTION; ELEMENTS; SYSTEM;

D O I：

10.5004/dwt.2017.20807

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

The implementation of seawater reverse osmosis (SWRO) desalination plants was key to ensure the fresh water supply in arid and coastal regions. The high operating and maintenance (O&M) cost in these plants are an impediment. In this paper, the O&M cost of twelve SWRO desalination plants located in Fuerteventura (Canary Islands) were analyzed. A mathematical model was elaborated to estimate the O&M cost. The inputs were the production capacity of the line, recovery, energy consumption and the price per kWh. The specific cost related to the energy consumption is complex to be evaluated because of its dependence on other factors such as energy recovery system, chemical cleaning frequency and electrical energy tariffs. It was observed that the specific cost of the chemicals, cartridge filters, membrane replacement, staff and maintenance decreased with the production and recovery increase in the studied ranges. The model was verified with the data proving to be a good estimator.

引用

页码：73 / 79

页数：7

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