This innovative tool allows you to optimize the operational costs while achieving the target goals in terms of water quality and hydraulic parameters. It can help you identify the treatment criteria that are required to achieve target water quality goals operational parameters to achieve water quality and hydraulic goals and reduce operating costs by providing accurate decision support tools.
The user-friendly software interface puts commonly used features right at your fingertips. The software is designed to allow streamlined navigation, better workflow and timesaving shortcuts. You can even customize individual user views by dragging and dropping the features you use the most. Managing all your information is simpler and more straightforward than ever before. Provides easily configurable setups to allow autoruns and decision support with minimum user intervention.
Integration with SAMSWater Compliance Management
Our SAMSWater Compliance Management tool with integration to multiple types of data sources. This allows you to identify and import data such as water quality historical information, and integrate with predictive water models to forecast future compliance status based on a selected operational strategy.
Energy Rates and Energy Usage
SAMSWater accurately calculates energy costs using sophisticated rate structure information to accurately predict energy costs and impact of a selected operational energy consumption strategy. The systems operations optimization algorithm allows the introduction of complex energy rate structures and target criteria in combination with hydraulic parameters, compliance parameters, water quality target goals and energy use. This decision support tool will help identify optimum pump usage, optimum pump station usage and optimum time-of-day operations.
Demand Forecast Tools
SAMSWater has built-in demand forecasting tools that can use several pre-loaded as well as custom calculations defined by the user. Demand forecasting can be used for automatic global adjustments or auto population of demand allocations directly from billing data for model updates.
You can run the model with continuous snapshots to identify the correlation of the model setup and management with field conditions. Any deviations will be automatically identified and reported for troubleshooting. This helps develop and maintain a continuously well-calibrated model that is always readily available.