SiteWatch provides valuable tools for managing demand in a monitored facility. In addition to identifying demand periods and quantifying major contributors - i.e. panels and machines with the highest energy-use during on-peak and off-peak periods - our platform offers intuitive graphical tools such as Heat Maps to show when peak demand occurs, the magnitude of the peaks, and the equipment contributing to them.

Did you know that most companies are billed twice for their peak demand (aka ‘Capacity’ charges), once by their local utility which re-sets them each month and again by their 3rd party energy supplier based on annual re-setting. Peak Demand charges are billed in $/kW. How do capacity charges affect your bill?

  • First by the local Utility company, billed as $/kW for maintaining sufficient capacity in their system to deliver the energy you require reliably.
  • Second by your 3rd party energy-supplier, billed for energy consumption in $/kWh. Anything you can do to spread your load over a longer period and lower the peaks will reduce your power bill significantly.

Anything you can do to reduce your peaks can save you substantially on your two power bills.

Heat maps are used to visually represent energy use for a site, production line, usage group, or individual machines, on an hour-by-hour basis, shown for a month at a time. The horizontal time scale represents 24 hours, with each row representing a single day. The color scale shown on the right of the graphic ranges from white (no usage) to red (highest usage across the month shown).

For the cement-manufacturing facility shown in this example, the site actively works to avoid usage during peak demand periods (12 PM to 6 PM on weekdays), by moving most production to hours outside that period. The site uses heat maps and scheduled alerts to control these peak demand costs.

SiteWatch actively reviews sites when requested to find out which machines are contributing to peak periods and to what extent. This type of active management is only possible with comprehensive machine monitoring and data-analysis.