NewEnergyNews: TODAY’S STUDY: How To Deal With The Coming Time-Of-Use Rates

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    Monday, June 25, 2018

    TODAY’S STUDY: How To Deal With The Coming Time-Of-Use Rates

    Understanding Time-of-Use

    May 2018 (Artis Energy Intelligence)

    Introduction

    The energy industry adage emphasizing “the cheapest energy is the energy you don’t use in the first place,” may not be 100% accurate. This prevailing adage involves only looking at reducing kWh consumption via energy conservation measures. This approach, however, does not consider time-of-use. Using energy during periods of high grid demand can have significant cost implications for coincident users and for the entire system.

    Using our energy analytics software (EAS), RTIS®, on several client sites has clearly demonstrated that if facility managers, energy management vendors, legislators, and regulators all operate based on this conservation principle alone, the adverse consequences to facility energy usage, costs, and greenhouse gas emissions (GHGs) could be significant.

    Consider the following:

    • A few instances of peak demand can cause spikes that lead to significantly increased monthly costs, often including demand ratchets that result in increased costs for the entire year ahead. In many cases, even if a facility uses considerably more demand during just one billing interval when compared to all other times during the year, the facility will pay for the maximum demand sizing for that delivery “pipe” in their monthly demand charges all year long.

    • To ensure that enough power can be generated during peak demand periods, utilities need to build substations, transformers, and other infrastructure to meet peak demand, even if a large amount of peak demand occurs over a short duration in any given area. Eventually, all customers pay for this in the form of rate increases.

    • During periods of peak demand, additional and dirtier “load following” power plants are deployed, resulting in significantly higher GHG emissions and fine particulate matter emissions. The difference in GHG emissions between a peak day and non-peak day can be as high as 50%.

    • In some jurisdictions, distribution utilities can also charge a punitive “critical peak” demand charge for periods of peak societal demand, a pricing strategy to discourage use during peak periods.

    • Similarly, regarding kWh power supply costs, suppliers incorporate capacity charges into their cost of goods. This cost can constitute up to 20% of the kWh price and it is expected to rise as much as four-fold in some areas over the next few years.

    The Importance of Time-of-Use

    A common recommendation stemming from an energy audit is to use a building or energy management system (BMS or EMS) to cut back kWh usage during evenings, weekends, and other unoccupied periods to achieve energy-efficiency targets.

    Logically this makes sense, but in the absence of additional information a strategy like this can backfire. For example, on successive days of a heatwave, a building can retain too much heat from day to day, and if efficiency setbacks prevent the building from being cooled during the evening or weekend, HVAC systems will work much harder to maintain comfort, thereby using more energy and causing significantly more kW demand and related charges during more expensive, onpeak utility billing periods.

    Case in Point: High School Campus (HSC)

    The following chart was exported from our real-time energy analytics software platform, RTIS®. It contains an actual example of the staggering budget impact of “avoidable” peak demand costs that occurred at a high school with a fine-tuned EMS being managed under an energy savings performance contract.

    The X-axis of the load curve represents the extent of time a peak demand level was reached throughout the year; the Y-axis represents the actual kW demand level. For this high school, reducing an incremental peak of 295 kW by managing the peak usage that is occurring during just 1% of the year would reduce their annual energy costs by approximately 12%.

    Had the high school been cooled more aggressively during just a few unoccupied evenings and weekends during heat waves, significant kW demand would have been avoided. Moreover, evening/weekend kWh usage would have been during off-peak hours, when the kWh costs are much lower. The facility’s kWh power supply capacity cost of goods would have been much lower for the year as well

    Adding Intelligence to Understand Nuance

    Modern energy efficiency measures (EEMs) like HVAC and lighting controls can be harnessed to provide addressable end points to better manage demand, and reduce energy costs and GHG emissions. The key is deploying an intelligent EAS like RTIS® that can analyze real-time data from different sources to determine the optimal treatment of a given situation. Rather than simply curtailing loads during unoccupied periods, RTIS® takes into account weather conditions, facility usage, historical performance, and power grid demand, adding a new level of intelligence. Further, by integrating RTIS® with a BMS or EMS that can control individual EEMs, the system can autonomously capture previously invisible avoidable cost opportunities.

    With the advent of modern IoT and analytics technology, perhaps the energy industry adage should be changed to “the cheapest energy may be the energy you don’t use, depending upon the time.”

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