There is one line on every high-tension electricity bill in Maharashtra that businesses often treat as fixed: the demand charge. Unlike energy charges, it is based on the highest capacity drawn during the billing period. This cost is becoming increasingly important.
Under MERC’s tariff framework for the fifth control period, HT demand charges for industrial and commercial consumers rise from ₹600 per kVA per month in FY 2025–26 to ₹750 by FY 2029–30, a 25% increase. Over the same period, the HT-I industry energy charge falls from around ₹8.68 to ₹7.45 per kVAh. The shift makes managing peak capacity increasingly valuable.
What Businesses Are Actually Paying For
Demand charges reflect the network capacity a distribution company must maintain to serve a consumer’s maximum draw, even if that peak occurs for only a short period.
For many industrial facilities, maximum demand is not created by normal operations but by coinciding loads—a compressor starting while a furnace ramps up and a chiller is operating at full capacity. Such events may occur only a few times a year, but they can determine the billed demand.
This is where demand management can deliver significant savings without requiring businesses to reduce production.
A battery energy storage system (BESS) configured for peak shaving continuously monitors demand against a defined ceiling. As demand approaches that threshold, the battery discharges to supply the difference, preventing the meter from recording the excess. It can then recharge during the rebated 09:00–17:00 window.
BESS offers three advantages. First, its response is effectively instantaneous, unlike a generator that may not start quickly enough to prevent a demand excursion. Second, peak shaving is primarily a power application, meaning relatively modest energy capacity can address short peaks. Third, the same battery can generate additional value through tariff arbitrage, diesel displacement and power-factor support.
Consider a facility with 2,000 kVA contracted demand, where recorded maximum demand is around 1,800 kVA, with short excursions above a 1,500 kVA baseline.
A 500 kW/2-hour battery could help maintain demand around 1,500 kVA. At ₹600 per kVA per month, reducing billed demand by 300 kVA saves ₹1.8 lakh per month or ₹21.6 lakh annually. At ₹750 per kVA, the annual saving rises to approximately ₹27 lakh.
The battery can also be cycled between the daytime and evening tariff windows across roughly 300 operating days, while supporting short outages and reducing diesel generator usage, typically costing ₹18–30 per kWh. Combining multiple value streams is what can make the investment more attractive.
Right-Size Contracted Demand First
Before installing storage, businesses should review contracted demand against actual consumption over the previous 24 months. Many facilities continue paying fixed charges on capacity they no longer require.
Reducing contracted demand can cost little, but exceeding the revised limit may attract penalties. A battery can make a lower contracted demand safer by maintaining the site below its ceiling.
The sequence therefore matters: right-size the contract first, then use BESS to defend the new limit.
Maharashtra bills HT consumers on kVAh rather than kWh, making apparent power relevant to the bill. A facility operating at a power factor of 0.92 effectively pays for around 8% more apparent power than useful real power.
Storage inverters can provide reactive power support and help maintain power factor closer to unity, creating an additional, if relatively modest, saving.
Let Data Drive the System Size
Peak shaving works best where demand is peaky, with short and identifiable excursions. It is less attractive where loads are flat or peaks persist for several hours.
The key metric is load factor, calculated as average demand divided by maximum demand. A low load factor indicates greater peak-shaving potential, while a high load factor may point towards energy arbitrage and longer-duration storage.
Ultimately, 15-minute interval demand data covering a full year is more valuable than a generic vendor proposal. It reveals the frequency and duration of peaks and the BESS capacity required.
Finally, the Energy Management System must anticipate peaks, maintain sufficient state of charge and respond reliably. A system that misses even one critical peak can fail to deliver the expected monthly demand-charge savings, because billing is determined by the highest recorded demand during the period.
