Energy Storage
The use of battery storage is usually designed around one of two strategies; demand shaving, or solar PV over-production. Demand shaving is a strategy which uses the selective discharge of stored battery energy to reduce or ‘shave’ the peak demand of utility power. Cutting down the maximum demand or peak during the billing month lowers the demand charge portion of the utility bill. Storing energy for PV overproduction functions as a way to capitalize on the energy produced by a solar PV system in excess of what is being used by a facility. The stored energy can then be used when facility demand exceeds PV production rather than credited by the utility at a low rate or not at all.
Currently the majority of battery storage systems installed at commercial facilities in Indiana are designed with the intention of reducing the monthly peak demands. Sophisticated battery controllers monitor energy demands and model expected demand requirements. These systems use complex predictive analytics to optimize the amount of energy discharged, and consequently demand reduction, within the limit of the battery capacity. Many systems are capable of “learning” expected facility demand profiles so they discharge at the right time and cut down the worst peaks, ignoring lesser peaks and consequently conserving battery energy for only those times where the highest electrical demand is predicted to occur.
The use of battery storage is usually designed around one of two strategies; demand shaving, or solar PV over-production. Demand shaving is a strategy which uses the selective discharge of stored battery energy to reduce or ‘shave’ the peak demand of utility power. Cutting down the maximum demand or peak during the billing month lowers the demand charge portion of the utility bill. Storing energy for PV overproduction functions as a way to capitalize on the energy produced by a solar PV system in excess of what is being used by a facility. The stored energy can then be used when facility demand exceeds PV production rather than credited by the utility at a low rate or not at all.
Currently the majority of battery storage systems installed at commercial facilities in Indiana are designed with the intention of reducing the monthly peak demands. Sophisticated battery controllers monitor energy demands and model expected demand requirements. These systems use complex predictive analytics to optimize the amount of energy discharged, and consequently demand reduction, within the limit of the battery capacity. Many systems are capable of “learning” expected facility demand profiles so they discharge at the right time and cut down the worst peaks, ignoring lesser peaks and consequently conserving battery energy for only those times where the highest electrical demand is predicted to occur.
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Emergent Solar Energy is Indiana's Leader in Commercial Solar Solutions
Commercial | Municipal | Agricultural
Commercial | Municipal | Agricultural
