Big data analytics can reduce energy consumption

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However, as a greater proportion of our world is driven by electricity, and populations continue to increase, we are seeing a year-on-year increase in the demand for energy. In some countries, including South Africa, the result has been a gap between supply and demand. The only way to reduce demand and bridge this gap is to improve energy efficiency.

Harnessing the power of big data analytics, organisations can become empowered not only to reduce energy consumption, but to leverage wider supply-side optimisation, including demand management, energy procurement, and tariff-based savings. This not only helps to improve energy efficiency, it also reduces energy costs, and helps organisations to meet carbon emission reduction targets.

Managing consumption

Energy may be one of the largest operational expenses of many organisations, but it is also highly controllable. However, organisations without a structured means of managing energy consumption frequently end up compromising on operational policies. The impact of this is that it can negatively affect the organisation's sales and brand image. Compromising on policies results in lower productivity of staff, a decrease in the equipment performance and lifespan and a reduction in the quality of the goods sold.

Aside from the pressing need to optimise energy consumption in order to reduce electricity cost and demand, one of the biggest challenges organisations around the world currently face is to achieve sustainability targets, as well as profitability and customer acquisition targets. Often, enterprises are also tasked with achieving this in a massively distributed infrastructure environment, which may include large office buildings, warehouses, and even water treatment plants. Achieving energy efficiency in such scenarios is exceptionally challenging.

The IoT, M2M communication and the availability of big data and analytics can offer the solution. Organisations in possession of data around their infrastructure are able to generate greater awareness of their operations, and the analysis of this data can assist in delivering actionable insight for improvement and optimisation. Energy management, utilising interconnected infrastructure and big data analytics, is essential.

Improved performance

Energy management involves monitoring and managing all energy-consuming assets in a single location or across various locations, with a view to optimising consumption and improving performance and asset lifespan. Energy management ensures that assets are run as and when they are needed, reducing the running time of equipment, which results in reduced wear and tear, ultimately extending the lifespan of assets.

This is all achieved without compromising on service or product quality. In addition, by running assets at the optimum set points and as per the specifications given by the manufacturers, organisations can also optimise the performance of various assets. By managing and reducing energy costs, organisations can also free up budget for other areas that can add value to the business, including improving the customer experience, which in turn is key to driving increased sales.

Energy management requirements are often unique to a customer, market or environment, because of variables such as climate conditions, equipment that needs to be run and more. Energy management practices must, therefore, be tailored to each individual organisation. However, in order to achieve this, it is essential to have sufficient data available to aid in the decision-making process around how operations, services, locations and energy consumption can be optimised.

Limited availability

This frequently proves to be a further challenge, as the availability of data is limited in buildings utilising legacy building management systems. In addition, many organisations do not have data collection mechanisms in place, primarily because they do not have a clearly defined objective making this necessary. It is only now that organisations are realising the value of data when it comes to making decisions in all areas, including energy efficiency, which they have begun to work toward tracking data and deriving insight from it.

Not only will the availability and analysis of big data around energy usage assist organisations to optimise their consumption, it can also provide significant insight to utility providers themselves. Energy consumption data and the analysis of this data will help providers to plan better. In addition, utilities can use the data to drive programmes and incentives that encourage users to adopt more energy efficient devices, which in turn will reduce overall demand.

By reducing the overall demand, the utilities will be better able to provide adequate supply. This will help bridge the growing demand-supply gap. The effectiveness of this approach is well-proven - there are credible industry case studies in which our clients have saved up to 20% on energy costs and maintenance and operations expenses across the portfolio by leveraging big data.

Improving energy efficiency should be one of the highest priorities for all organisations. Sustainability is becoming increasingly important, and energy consumption is a significant contributor in this area. Every kilowatt hour (kWh) saved contributes positively to our environment - 1kWh saved is equivalent to removing 200 cars from the road or planting 20,000 tree saplings.

Economic impact

The economic impact is also important. Energy is one of the few controllable costs in many organisations, making up a large proportion of expenses. Just a 10% reduction in energy costs will significantly improve the bottom line over time.

In order to address this growing need and challenge, it is essential to leverage technologies and tools to optimise energy consumption, reduce energy cost and enable better usage of energy infrastructure, effectively improving the management of enterprise operations. In order to achieve this, it is essential to build efficient platforms and solutions that will provide available, reliable and consistent building performance data, with the goal in the long term of analysing customer operations and consumption patterns.

The ultimate aim is to achieve notable savings and results that can be replicated and accelerated over time to ensure sustainability. This will assist customers as well as utility providers to work together to address the growing supply and demand problem.