Design of a Fuzzy Cognitive Maps variable-load energy management system for autonomous PV-reverse osmosis desalination systems: A simulation survey

Abstract

In the last decades, much effort has been made in order to couple desalination technologies with renewable energy systems consisting usually of photovoltaics, wind-turbines and batteries, in order, οn one hand to reduce cost, and, οn the other hand, to be able to power desalination units in regions where electricity availability is low. Normally, the reverse osmosis desalination units operate at nominal point of operation. However, it has been reported that operation of reverse osmosis desalination units at partial load presents lower specific energy consumption. In this paper a variable load Energy Management System (EMS) based on Fuzzy Cognitive Maps (FCM) is developed. In order to assess variable load operation two cases studies are investigated through simulation. For both cases studied, initially a PV-battery system is sized through optimization for a desalination unit operating only at full load. The difference between the two case studies is the capacity factor of the desalination unit considered; for the first case a capacity factor of the desalination unit of about 30% (which translates to about 7h daily operation at full load) is considered and for the second case study a capacity factor of about 70% (translating to about 17h of daily operation at full load). Then, the ON-OFF EMS is considered to be exchanged with the FCM variable load EMS that was developed and the yearly drinking water production is compared. The obtained results clearly show that, for an already installed PVROD system, an upgrade to a variable load operation scheme can present considerable increase in the drinking water production from the same system ranging from nearly 41% for the first case study to nearly 54% for the second.