Predicting environmental risks : using water balances for sustainable power at Kusile power station (South Africa)

Abstract

Predictive water balances play a critical role in mitigating environmental risks in power generation by leveraging historical and real-time data for proactive resource management. At Kusile Power Station, these frameworks were used to identify a major environmental challenge and guide the development of an alternative wastewater management strategy. This study introduces a novel approach by integrating predictive modelling with a diffusion-based blending strategy, offering a cost-effective alternative to conventional chemical treatment methods. Instead of direct blending in pollution control dams, which was impractical due to high wastewater levels, a targeted blending strategy within the Flue Gas Desulphurisation (FGD) system was explored. A diffusion model confirmed that this approach could meet 53% of the FGD system’s water demand using wastewater, significantly reducing reliance on raw water. By incorporating these findings into the predictive water model, Kusile Power Station successfully optimized wastewater reuse, demonstrating the potential of data-driven strategies for sustainable industrial water management.