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Reducing Energy Costs through Industrial IoT-based Smart Energy Management Solutions

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By R. Venkateswaran

 In most manufacturing companies, energy costs can be as high as 40-50% of the operational costs. While these numbers are industry specific, any focus on reducing the energy consumption has the dual benefit of significant cost-savings, while simultaneously making a positive impact to the environment.

Unfortunately, our experience has been that most Indian manufacturing industries today have very little insight into their energy consumption. Usually, the energy monitoring happens on a monthly frequency – based on the consolidated monthly utility bill generated by the utility company. This consolidated bill provides no details about the energy consumption pattern across the various business units and manufacturing lines and hence does not translate into actions towards energy savings.

The manufacturing industries are further challenged by the introduction of dynamic tariffs based on time of day (tariffs published for 15-minute time intervals) or based on demand. Without real-time visibility into energy consumption, these industries are unable to get any significant insights that can translate to appropriate decisions towards leveraging the dynamic tariffs for reducing the overall energy costs.

Addressing the Challenges

Many of the challenges can be addressed by real-time monitoring of energy consumption across different processes within the manufacturing units. This requires smart energy meters to be installed across pre-identified critical sections of the manufacturing processes. Smart meters continuously display energy parameters such as current, voltage (multiple phases), number of units (KWH) and power factor. Some manufacturing companies have installed such smart meters, however, they still follow the pencil-and-paper method of periodically collecting the readings from these meters. The data collected this way are likely to be error-prone and any data analysis from erroneous data is of little help in data-driven decision process.

A data-logger connected to the smart meters can be used to eliminate the pencil-and-paper process of data collection. The logger collects the data from the smart meters in real-time and pushes this data to an IoT platform – deployed either in the Cloud or on premise. This ensures that the data is directly collected from the data origination point and hence its veracity is assured. For some of our customers, the real-time energy monitoring itself has led to cost savings of 3-5% with very little additional efforts. It has also helped them reduce considerable manual efforts during energy audits.

The next part of the challenge is addressed by an IoT platform with powerful analytics and machine learning capability. This platform continuously processes the data from the energy meters in real-time and generates actionable insights towards energy optimization, as detailed in the use cases.

Potential Areas for Energy Optimization

A significant reduction in energy consumption and overall improvement in operational efficiencies of a manufacturing company can be accomplished through the identification of one or more areas listed below.

1)      Energy Productivity – a higher level Key Performance Indicator (KPI) that tracks energy cost per unit of production. Oftentimes, the factory machines continue to run idle, especially during lunch/tea breaks or shift changeover. Over time, this consumed energy is a wasted cost and should be curtailed. Without real-time tracking of both energy consumption and produced output, such wastages are hard to detect. Manufacturing companies using our energy management solution have been able to demonstrate a consistent lowering of Energy Productivity on a month-on-month basis.

2)      Power Factor Monitoring and boosting – Manufacturing companies are expected to maintain a steady power factor of 0.95 and above or face stiff penalties imposed by the utility companies. Maintaining high power factor also helps in reducing carbon emissions, heat reduction and voltage drops. Real-time monitoring, combined with timely alerts and notifications for drop in power factor, leads to timely analysis of the reactive loads in the system. This ensures power factor compliance and mitigates the risks of high penalties.

3)      Energy spikes monitoring and management – Immediately after shift changeover or product turn-over, multiple machines are switched on simultaneously, leading to sudden spike in energy consumption. Such spikes can reduce the overall life of the equipment. Monitoring and analysis of such spikes can help manage them effectively through appropriate sequence of switching of machines, thereby, increasing their longevity.

4)      Process re-adjustments – With meaningful insights from the power consumption patterns, manufacturing processes can be re-adjusted so that processing consuming more power can be scheduled during non-peak / low-peak hours when the power tariffs are lower. This can result in substantial cost optimizations.

5)      Support for Energy Audits – Manufacturing companies are audited periodically to ensure proper benchmarks are set for “per-unit product costs”. With accurate measurement of energy parameters in real-time and the trends derived from this single source of truth, the process of energy audits becomes stream-lined and less onerous.

6)      Dynamic selection of Utility provider – Many states in India have authorized private utility providers to provide utility services – competing with the local state electricity department. This is a welcome arrangement wherein competition ensures that customers get the best services at affordable price points. Real-time power management mapped to the appropriate dynamic tariff ensures that the manufacturing company can choose the right utility provider dynamically – even potentially switching between them throughout the day.

Based on my experience with our energy management solutions, I recommend a phased approach for solution roll-out. The initial phases of roll-out address the energy monitoring use cases that have an immediate demonstrable cost savings in the range of 7-10%, with an RoI period between 8-12 months. The benefits of such solutions in the long term can be continuously sustained in subsequent rollout phases, when these solutions identify energy optimization opportunities based on historical energy data that contribute directly to the manufacturing operations through process improvement and regulatory compliance decisions.

The author is Senior Vice President, IoT Solutions at Persistent Systems

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