An optimization algorithm-based pinch analysis and GA for an off-grid batteryless photovoltaic-powered reverse osmosis desalination system

Highlights

Proposing freshwater pinch analysis (FWaPA) for retrofitting PVS-RO systems.

Definition of graphical and numerical tools of FWaPA.

Developing economical and mathematical models of PVS-RO system.

Proposing multi-objective optimization algorithm based FWaPA and GA.

Implementation of proposed FWaPA-GA for a case study.

Abstract

Freshwater pinch analysis (FWaPA) as an extended pinch analysis technique has been proposed for retrofitting the off-grid batteryless photovoltaic-powered reverse osmosis system (PVS-RO) with a water storage tank to minimize the required outsourced freshwater. The freshwater composite curve (FWaCC) as the graphical tool, and freshwater storage cascade table (FWaSCT) as the numerical tool of the FWaPA are introduced to determine the optimal delivered electricity to the RO system, water storage tank capacity, and wasted electricity in each time-interval with minimized outsourced freshwater. A multi-objective optimization algorithm by combining FWaPA numerical tool and genetic algorithm (FWaPA-GA) minimizes three objective functions including required outsourced freshwater during first operation year, outsourced freshwater during normal operation year, and total annual cost of the system to obtain the optimal number of PV panels, membranes, and capacity of water storage tank. The FWaPA-GA was implemented to find optimal design of an off-grid PVS-RO-WT system for a case study in Kish island, Iran. The results clearly represented that the FWaPA-GA can be used to grassroots design of the desalination systems with renewable energy sources, where the designed PVS-RO-WT system for the case study needs 178.5 m3 freshwater to provide 10 m3/d freshwater-on-demand with the total annual cost of 13,652 $/year.

Keywords

  • Photovoltaic-powered reverse osmosis;
  • Freshwater pinch analysis;
  • Multi-objective optimization;
  • Water storage tank;
  • Genetic algorithm

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