Key Energy Analysis Techniques
Load Profile Analysis
Load profiles show how consumption varies throughout the day and across seasons. Typical commercial buildings show peaks during business hours, with lower baseloads overnight. Industrial facilities may run 24/7 with relatively flat profiles. Understanding your load shape reveals optimization opportunities specific to your operation.
Peak Demand Management
For customers on demand-based rates, monthly peak demand (typically the highest 15-minute average) can represent 30-70% of total electricity costs. Peak demand analysis identifies when peaks occur, which equipment drives them, and strategies to reduce them through load shedding, thermal storage, or operational changes.
Energy Regression Modeling
Regression analysis quantifies relationships between energy consumption and driving factors like temperature, production volume, or occupancy. These models enable accurate forecasting, normalization of consumption for fair comparisons, and measurement of energy savings independent of changing conditions.
Baseline Establishment
A baseline represents typical consumption under standard conditions before efficiency improvements. Properly established baselines are essential for measuring project savings, verifying performance in energy savings contracts, and tracking progress toward efficiency targets.
Time-of-Use Optimization
When electricity prices vary by time of day (time-of-use rates), shifting consumption from expensive peak periods to cheaper off-peak times generates savings. Analysis identifies which loads are flexible, quantifies potential savings, and optimizes scheduling.
Renewable Energy Correlation
Overlaying solar generation curves or wind production patterns with consumption profiles reveals self-consumption potential. This analysis determines optimal system sizing, identifies when grid import/export occurs, and calculates true economic value of distributed generation.
Proven Energy Optimization Strategies
Load Shifting and Scheduling
Move flexible loads—ice-making, water heating, battery charging, non-time-critical manufacturing—to off-peak periods when electricity is cheaper and demand charges aren't triggered. Even modest load shifting (10-15% of total consumption) can generate significant savings on demand-based rates.
Eliminate Baseload Waste
Consumption during unoccupied periods (nights, weekends) represents pure waste for many facilities. Pattern analysis identifies excessive baseload, points to specific equipment running unnecessarily, and quantifies savings from better controls or scheduling.
Optimize HVAC Operations
HVAC typically represents 30-50% of commercial building energy use. Pattern analysis reveals opportunities for setback schedules, optimal start/stop times, economizer use, and temperature adjustments that maintain comfort while reducing consumption.
Implement Demand Response
Utilities and grid operators pay customers to reduce consumption during peak events. Pattern analysis identifies which loads can be curtailed with minimal operational impact, estimates incentive earnings, and helps develop automated response strategies.
Right-Size Equipment
Oversized equipment runs inefficiently at partial load. Pattern analysis reveals whether equipment capacity matches actual load requirements, enabling right-sizing decisions during replacements or identifying candidates for variable speed drives.
Strategic Energy Storage
Battery storage can shift consumption from expensive peak periods to cheap off-peak times, provide backup power, and maximize self-consumption of solar energy. Pattern analysis determines optimal storage capacity and charging/discharging strategies for maximum economic benefit.
