Model dimming profiles, occupancy patterns, and sensor boosts with confidence today quickly. Export results to share budgets, carbon goals, and payback estimates with teams.
The calculator converts dimming levels into power multipliers and estimates annual energy from operating hours.
Sample scenario for a medium corridor with sensor dimming.
| Parameter | Example | Unit |
|---|---|---|
| Number of streetlights | 250 | |
| Lamp wattage (nominal) | 90 | W |
| Driver/gear efficiency | 92 | % |
| Operating hours per night | 11 | h/night |
| Baseline dimming | 10 | % dim |
| Occupied dimming | 20 | % dim |
| Unoccupied dimming | 70 | % dim |
| Occupancy fraction | 0.35 | fraction |
| Motion events per night | 25 | events |
| Minutes per event | 1.5 | min |
| Electricity rate | 0.18 | per kWh |
| Emissions factor | 0.55 | kg CO₂/kWh |
Adaptive streetlighting is a practical energy strategy for municipalities, industrial parks, and large developments where nighttime activity varies by hour and by location. Traditional schedules keep every fixture near full output for the entire operating window, which can overshoot real lighting needs during low‑traffic periods. Adaptive control blends planned dimming with sensor‑driven boosting so illumination increases only when pedestrians, vehicles, or higher‑risk situations are detected.
This calculator estimates annual consumption by converting dimming levels into power multipliers and applying them to hours in three operating bands: occupied operation, unoccupied operation, and boost windows triggered by sensors. It also adjusts nominal lamp power for driver or gear efficiency to approximate the input power recorded at the meter. After annual kWh are calculated, the tool converts performance into cost and emissions outcomes using your electricity rate and emissions factor. If your utility applies demand charges, enter a demand rate and coincident factor to estimate peak‑related savings. Add any maintenance savings to see a more complete annual benefit.
For accurate planning, use inputs from asset inventories, control dashboards, maintenance logs, and short pilot studies. Start with the number of fixtures, nominal wattage, average hours per night, and operating days per year. Then set a baseline dimming level that represents your current schedule. For the adaptive case, enter separate dimming levels for occupied and unoccupied periods and the fraction of the night that is typically occupied. Finally, describe sensor activity using average motion events per night and minutes per event, and choose a boost dimming level.per night, minutes per event, and the boost dimming level. Choose realistic event counts, or use logged controller data when available.
Example scenario: 250 fixtures rated at 90 W with 92% driver efficiency operate 11 hours per night for 365 days. A baseline level of 10% dim is compared to adaptive settings of 20% dim during occupied periods and 70% dim when unoccupied. If occupancy averages 0.35 of the night and motion creates 25 boosts of 1.5 minutes each at 0% dim, the model typically shows reduced annual kWh and meaningful savings at a rate of 0.18 per kWh, with proportional emissions reductions using a 0.55 kg CO₂/kWh factor.
For project delivery, pair modeled savings with lighting design checks, roadway classifications, and stakeholder expectations. Energy modeling should never replace photometric compliance, but it helps select control policies, set commissioning targets, and communicate payback. After deployment, capture real occupancy and boost statistics, update seasonal assumptions, and re‑run the model to keep savings verifiable over time.
It is the percent reduction from full output. A 20% dim level means the fixture runs at about 80% of input power, before efficiency adjustments.
Use traffic counts, CCTV analytics, or controller logs to estimate the share of the night with regular activity. Start conservative, then refine after a pilot.
Enter an average events-per-night value that represents the controlled group behavior. If groups differ, run the calculator multiple times and sum the results.
No. It estimates energy and cost impacts. Confirm illumination, uniformity, and glare requirements with a lighting design and applicable roadway standards.
Run separate scenarios for summer and winter using different hours per night and occupancy assumptions. Compare results and compute a weighted annual average.
Use your utility’s published grid factor or a national/regional inventory value. If you track renewable procurement, adjust the factor to match your reporting method.
Yes. Use the “total annual savings” result and divide your retrofit or controls upgrade cost by that amount to get a simple payback estimate.
Smarter streetlights cut costs, improve safety, and reduce emissions.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.