Evaluation of Direct Energy Savings and Demand Response Potential from PCM for Cold Storage Cooling Applications

This project will help determine the effectiveness of Phase Change Materials (PCMs) in cold storage applications at Low Temperature -10 - 0 F (-23 - 18 C). Controls will also be implemented into the study to determine how compatible it is with PCMs. A total of 4 tests will be done on warehouses to see if PCMs have an impact on energy savings, demand response and keeping the temperature at appropriate levels. The main research objective is to evaluate the effectiveness of PCM separately from the controls. We want to determine if it was either PCM or Viking cold’s controller that played a bigger role in energy savings. The purpose of this project is to explore the demand response potential from phase change materials for cold storage applications to SCE: 1. Critical peak load reduction – Can PCM be used to reduce electric loads in cold storage applications during critical peak load conditions? 2. Required notification times – Can cold storage loads with PCM reduce critical peak loads with day-of notification or do they require day-ahead notification? 3. Consistency of critical peak load reduction – Can cold storage loads with PCM respond to event notifications over successive days (3 or more days in a row)?

The purpose of this study is to evaluate the energy savings and Demand Response (DR) potential of passive Phase Change Materials (PCMs) and supplemental controls in cold storage freezer applications. PCM technology is designed to provide a freezer with a thermal battery effect that allows the space to better participate in DR and bring everyday electric energy and demand cost savings to utility customers. By increasing the freezer’s thermal capacity, this battery allows the mechanical cooling equipment to be curtailed during onpeak and critical-peak time periods, providing grid relief when it is needed the most. Load-shed DR enables load reductions in response to event notifications or signals, which are relayed through various means – some more automated than others. When customers respond to event signals and reduce load only on event days, it is called “event-driven loadshed DR.” Load-shape DR repeats load reductions each summer weekday, and shapes the facility’s load profile to avoid high summer on-peak demand charges. By reducing load repeatedly and consistently during all summer weekdays, customers can significantly reduce their on-peak energy use and associated energy and demand charges. Several types of PCM have been developed, notably from eutectic salts, paraffin wax, and bio-based organic materials. PCMs are proprietary formulas designed and produced so the PCM changes phase (leveraging the material’s latent heat value) at a eutectic point matched to the operating temperature in the specific refrigerated space. The PCM absorbs heat as it transitions from a solid to a liquid-like gel state. Various forms of encapsulation and rack mounting are available for installation. The field evaluation involved assessing the energy savings and DR potential impact on a 4,800 square foot frozen food distribution freezer in SCE territory. The technical approach accounted for variations in ambient conditions throughout the test period. PCM performance was measured by isolating the freezer’s system-level energy use. Each time one of these refrigeration systems cycles off, there are losses associated with the refrigerant being trapped in the lines as system pressures equalize. Also, these systems require a startup runtime while they ramp up to operating capacity. During these ramp times, the equipment efficiency is poor, due to high energy input and low cooling output. Longer compressor runtimes, coupled with fewer operation cycles, lead to higher operational efficiency by limiting the losses associated with these negative efficiency impacts. The freezer’s energy use data, along with key system-level operating parameters (temperatures, cycle timing, etc.), were monitored on a continuous basis throughout the project (please refer to Appendix A for a complete list of points and sensors used in this study). This continuous monitoring provided the greatest accuracy for the targeted performance calculations. In addition, five research questions were established and addressed as part of this study.