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POWER
Utilities
Improving analytics to increase efficiency Advances in big data technologies and services can help reduce electricity consumption
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he world we live in has become increasingly digital and connected, and we now have the ability to collect data from many new sources. Sophisticated sensor technology has given rise to the Internet of Things (IoT) and machine-to-machine (M2M) communication, embedding intelligence, integrating more data sources than ever and providing the potential for informed decisionmaking based on comprehensive insight. However, as a greater proportion of our world is driven by electricity, and populations continue to increase, we are seeing a year-onyear 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. The structure of control 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
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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. Mentoring and managing 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
African Review of Business and Technology - April 2016
Syed Mansoor Ahmad, vice president and global business head, EcoEnergy, Wipro Ltd
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. 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. leveraging big data. ■ Syed Mansoor Ahmad, vice president and global business head, EcoEnergy, Wipro Ltd www.africanreview.com