Energy Management using IoT and Cloud Solutions – Are we solving kitchen issues now?

The Precinct

With the advent of Industry 4.0, disruption in the manufacturing & production industries is peaking. But, even the best of them can’t stay at the top due to unceasing innovation. Integration of new technologies such as cloud computing, IoT (Internet of Things), AI, and machine learning has led to organizations optimizing their distribution, manufacturing, and supply chain, leading to creations such as smart factories. These factories contain advanced robotics and sensors that collect and analyze data, which help in better decision-making for everyone in the organization, from site technicians to stakeholders. These innovations are no more just revolutionizing the workflow of the big sharks and industries but also transforming the daily operations of SMEs.

Facets of Industry 4.0–IoT and cloud computing are redefining the energy sector by providing complete transparency and access to energy data for residential, commercial, and industrial sectors. Both on-site and remote personnel can get information and control of assets such as electrical panels and production machinery. It helps organizations perform better by increasing reliability, reducing costs and downtime, and pre-planning maintenance and related operations. 

The Problem

DEWA- Dubai Electricity and Water authority apply slab tariffs and fuel surcharge on the monthly electricity & water consumption by residential, commercial, and industrial entities. Buildings that need a total connected load of 400kW or less do not need a substation in most cases, but they are permitted a maximum demand (kW) at the MDB connected to DEWA’s supply feeder/transformer by DEWA (after a thorough inspection).

It’s considered unsafe for the electrical network if the demand load crosses this maximum demand permitted by DEWA. It can cause instability in the transformer/feeder due to voltage drops and can also cause harm to the other loads connected in the MDB network or within the building.

A cloud kitchen business in UAE, Dubai, was facing a unique challenge. The business has 18 studio kitchens within their facility, allocating about 22.2kW of load to each kitchen, rented to individuals or companies for the preparation of delivery-only meals. Cloud Kitchens or ghost kitchens are commercially licensed food production facilities with delivery-only food brands renting space and operating within them. These kitchens provide the digital and automation infrastructure for virtual kitchens.

Apart from lighting and ventilation, these kitchens have electric loads such as:

• Freezers and Fridges
• Hot storage
• Glass and Dishwasher
• Ovens and Fryers
• Microwave ovens, coffee machines, and sundry sockets

Loads such as ovens and freezers, draw a high continuous current or have a high switch-on surge current.

The load patterns/schedule for such loads cannot be predicted accurately. Precisely in this case, since food and beverage orders vary daily, each kitchen serves a different cuisine with different recipes, leading to intermittent use of equipment round the clock.

The business was facing one major issue: They were crossing the 400 kW allocated load a few instances during the day, which led to DEWA imposing fines on them due to the situation of risk and safety on the stability of the power system.

To solve this problem, they needed to understand the load patterns and schedules of each kitchen.

The Solution

The company needed a solution that lets them measure and monitor the instantaneous power consumed by each kitchen space or restaurant. With the help of IoT and cloud-based solution, a monitoring system that helps the technicians, facility managers, and the stakeholders monitor the data and make the required decisions to amend the maximum load required for each restaurant.

Such a solution for energy management and monitoring was proposed and implemented for the cloud kitchen business by Royal Rubber Electric LLC (RRE). RRE took two approaches to this project and let the cloud kitchen company select the solution it preferred and found convenient.

Solution A

The engineering team installed energy meters with an in-built gateway and clamp-on micro-CTs with a programmable CT ratio. It enabled the implementation of the solution without disturbing the existing energy measurement as the existing equipment was not turned off. The meter is connected to the Wi-Fi using an app ( which can be installed on both Android and iPhone devices). The data is measured per second and sent to the cloud servers. This data can be accessed by web link to the cloud platform, parameters like:

• Current (both line and phase)
• Voltage (both line and phase)
• Active Power
• Reactive Power
• Energy
• Instantaneous Power factor

As you can see in Figure 1 below, the per-second data allows the restaurant to monitor the power consumption accurately and notice any surges or peak demand scenarios.

Solution B

The second solution implemented is developed by Nippen Instruments from India. The solution is very similar to the first one, but the IoT device/Gateway is an add-on device that can be connected to existing meters using RS485 ports in the meter, and data is transferred using the MODBUS protocol.

Figure 1 explains the solution implementation. This leads to reduced costs as meters with inbuilt gateways are expensive, and fewer man-hours are required since the number of devices installed is lesser. The measured data can be accessed through Nippen’s cloud-based application known as EASSY (Energy Automation with Smart Sense System).

In both cases, this type of energy and power consumption analysis solved the problem and gave the company the flexibility to share data unanimously across all levels of the organization. The information helped them get better insight into each kitchen’s energy consumption, and load patterns individually.

Deductions

From the stakeholders and ownership aspect, the data helps them comprehend the issue macroscopically and build a solid financial model for the present business since they can avoid unexpected costs (such as DEWA fines) and monitor the energy consumption and cost on a live dashboard from anywhere in the world with an internet connection.  

On a microscopic level, the technical team of the restaurant can improve the efficiency of the power system by working on a well-organized load schedule for each kitchen and work on the efficiency of the internal electric network by analyzing parameters like instantaneous reactive power and power factor.

The lion’s share is yet to come;

The stakeholders can use this data in scaling and replicating the business model. They could utilize the corrected load patterns and consumption data to solve these issues in the kitchen spaces that they build in the future.

These IoT-based solutions can be useful for different use-cases across the facility management industry and manufacturing plants, optimizing operation and increasing efficiency.

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