A new methodology to estimate future water‐energy nexus based on artificial neural networks

Abstract

Summary We propose a new methodology to evaluate future electricity generation scenarios aiming to explore implications of different sets of power plants on the water‐energy nexus (W‐EN). We use two artificial neural networks: cascade forward back propagation and Kohonen neural networks (KNN). Initially, the future electricity production of the area under investigation is determined. Sequentially, water consumption is calculated for different combinations of plants. The scenarios with the lowest annual water consumption values are based only on wind and photovoltaic (PV) plants. Despite using only renewable energy, the inclusion of concentrating solar power in a future scenario brings a significant increase in water consumption, challenging the sustainability of this matrix. A conservative scenario (50% of electricity production by thermal power plants and 50% by renewable energy) shows the highest annual water consumption, also a barrier to sustainability.

Assessment of Climate Change Impacts and Water Restrictions on Solar Tower Plants

“…This could lead to water consumption constraints that force to reduce the water use in power plants. Carvalho and Carneiro [14] evaluated future electricity generation scenarios to study the effects of different sets of power plants on the water-energy nexus, and they concluded that CSP plants with wet or hybrid cooling systems would represent 92% of the water consumption by 2050 for the scenario where the 100% of the electricity is produced by renewable energies (combining solar and wind plants). Therefore, dry cooling should be considered as an alternative to wet cooling for CSP plants to reduce the water consumption.…”