H&M Stores

Challenge:

The H&M facility management team manages more than 52 stores across the country. They needed a unified energymanagement platform to provide insights across key energy parameters for their portfolio of stores. Control and monitoring of HVAC operations was a prime requirement along with lighting control. The 75F team piloted their solution capabilities at a H&M’s Bengaluru store. During the course of the pilot, 75F’s IoT-based BMS successfully delivered 23.9% overall energy savings for the HVAC system, resulting in the Client choosing to deploy 75F’s solutions across 10 stores in 8 cities.

Solution:

The H&M facility management team expected savings on HVAC and Lighting energy consumption, monitoring of Indoor Air Quality (IAQ), and automation coupled with remote manageability of its HVAC and Lighting Systems. The 75F Team implemented the necessary solutions across stores using the most appropriate configurations while allowing the H&M team to access customized dashboards to view data on emissions, energy consumption and energy spend.

Installation and Execution:

H&M stores were primarily divided into two configuration types with respect to their cooling systems. The first configuration type was a complete set up of AHUs and Chillers, whereas the second configuration type had a Variable Air Volume (VAV) system. The kolkata store comes under second category. Based on the number of Direct Expansion Cooling Units (Cassette Type/Ducted system) on any floor in any store, the 75F Team created clusters of 2-3 groups per floor. 75F HyperStats were installed to control DECU groups allowing for maintenance of temperature levels of any particular floor. This strategy allowed for a modular approach to switch on or off cooling units based on the difference in actual temperature levels versus the set point. 75F also provided a single Central Control Unit (CCU) for each floor to communicate with HyperStats, work as a master control, and serve as a cloud gateway. The installed HyperStats have 8 or more sensors on board to monitor parameters such as Temperature, CO2 levels, VOC, PM2.0, and Occupancy Levels which were used to monitor the indoor air quality. Also additional CCU was provided to capture energy meter data for energy consumption analysis.