What is smart grid big data analytics?
Smart grid big data analytics is promising to shake up an industry not known for its technological innovations: Utilities. There is a growing overlap between utilities and data, with data sensors and other equipment being integrated into the provision of utility resources. Energy companies are using smart grid analytics to measure various variables, like the amount of energy distributed from smart network triggers. Smart data analytics is, therefore, going to have a huge impact on how we live (if it hasn’t already). Hence, in this blog, we are taking a look at smart grid big data analytics.
What is the smart grid?
Before explaining the benefits of smart grid analytics, it is necessary to explain what the smart grid is. It refers to the energy infrastructure of the future, fusing transmissions, transformers and substations that direct energy to households with modern technology like computers, automated technology along with other new equipment, which allows for digital communication or transmission of information, while also providing energy to households and organisations.
The ‘smart’ in smart grid refers to the additional infrastructure layer that allows for two-way communication between consumer devices and transmission lines. This two-way communication is possible thanks to the development of several innovations, like IoT and cloud computing.
The smart grid is a vital part of energy because it allows energy providers to draw full value from the smart grid. The smart grid refers to the new infrastructure where there is an emphasis on connected devices. It allows for a layer of communication between local actuators, central controllers and logistic units. This layer of communication is useful in many different areas because it allows for better response time during an emergency, more efficient use of resources and even improve the delivery of the network through automation. While the smart grid is all about keeping different devices like generators and consumer-end devices connected.
The smart grid is an exciting development because it represents a massive leap forward for the energy industry. It brings several benefits, like more efficient energy transmission, lower management costs, better security, operations costs and better integration of renewable energy. Naturally, the smart grid generates a lot of data, and smart grid analytics is needed to analyse the information produced. Otherwise, it would be impossible to extract any value from the data.
Are there any benefits of analytics?
Collect and analyse data to improve service quality
The smart grid produces large volumes of data, thanks to IoT devices like smart meters. IoT devices are placed in different areas of the smart grid, like the substations and consumer devices. These devices produce petabytes of data, and it’s impossible to make sense of the data without smart grid big data analytics. The analytics platforms can analyse data to generate invaluable findings that lead to several benefits, like cost reduction and operational efficiency. With smart grid analytics, energy companies can address issues, like finances and grid operations effectively and in a short time. This leads to several other improvements in grid optimisation and customer engagement.
It analyses unstructured data
A smart grid produces a lot of unstructured data and analysing this format of data can be very challenging. Moreover, in certain cases, unstructured data needs to be analysed in real-time. Unstructured data can be analysed by smart grid big data analytics. For example, SAS Asset Performance Analytics captures sensor and MDM data to improve performance, uptime and productivity.
Analytics comes in different formats
Smart grid big data analytics comes in different formats to suit the needs of the energy company. Utility firms can choose between point solutions and a software platform containing a suite of software solutions. Point solutions are effective because they target a specific problem. However, a single multisolution platform offers its fair share of benefits because it allows for greater flexibility and can be seen as a long-term investment.
Choose between on-premise and managed service
Furthermore, organisations can choose between an on-premise solution or a managed service. The on-premise solution provides the organisation with direct control over the analytics platform. However, it requires a significant investment to get the right talent and technology. Furthermore, building a team from the ground up takes a lot of time because a said team needs to get acclimatized to their work environment. Meanwhile, a managed service is much more affordable to set up because organisations do not have to deal with talent recruitment and capital expenditures. However, the tradeoff is that organisations do not have direct control over the platform. This level of flexibility between on-premise, managed and software as a service is one of the reasons why smart grid big data analytics is appealing to organisations.
Trends in the utility industry
Research indicates that the industry for smart grid big data analytics will grow to $4.8 billion by 2022 with a compound annual growth rate of 16%. Several trends in the utility industry are responsible for this growth.
Trust is growing for smart grid data analytics
The technology is relatively new, so most managers and executives are not as quick to embrace analytics. However, the growing popularity of IoT combined with the immense value to be gained in different areas, like customer management has made analytics an enticing proposition to many executives. However, it should be noted that in an industry as heavily regulated as utilities, change takes time to manifest.
Sensors are replacing MDM
While MDMs are still the norm and will continue to be so for quite some time. There is a growing trend where data sensors will overtake MDM as the device to measure utilities. Devices like cap banks, distributed PV solar panels, transformer sensors and voltage regulators represent the next wave of innovation in the utility industry.
Integrating data is a core function
Between the rise of unstructured data and the next wave of IoT devices, there is going to be a lot of data collected from different sources. To make sense of all the data collected, it needs to be integrated and represented in a format that generates useful insights. For these reasons, data integration is getting a lot of focus.
Collecting the right data in the right place
While smart grid big data analytics has the potential to transform the utility industry. It needs to be used properly to maximise its value. Not all data can be analysed in the same fashion. For example, some data should be assessed in the device itself, while other forms of data should be added to a data lake for analysis at a later time. To assess the right data at the right time, organisations need to look at analytics platforms that work at the right location. Hence, why smart grid analytics is vital, it can be divided into two categories: Back-office analytics and distributed analytics.
Backoffice analytics are perfect for certain functions, like overseeing grid connectivity, load forecasting and reliability reporting. For example, load forecasting collects data for analysis, so that utility companies know how much power is needed to meet short, medium and long-term demand. It reduces uncertainty, increases operational efficiency and provides better insight when making investment decisions. Meanwhile, distribution analytics can analyse data from meters, sensors and other devices. This type of analytics platform performs several real-time functions that include outage decision, voltage management and real-time load disaggregation. For example, real-time load disaggregation can identify how energy is used in distant loads and daily usage patterns. If utility organisations can learn about loads in real-time, they can devise measurements that improve energy management. It also identifies new ways to better serve customers.
When the right data is analysed in the right place, it brings several benefits to the organisation. Firstly, it allows for quick action. For real-time decision-making to be effective, granular, one-second data is needed to address the problem. This type of data can only be found on a local device due to lower latency and higher data volume. Having the right analytics platform analyse the data also ensures that useful information is generated at the right time and place. Secondly, organisations can be assured that they have the right data for the right purpose. For example, if there is a problem, having the right data allows organisations to determine if the problem is a device-based issue, a network-level issue or a system-wide issue. Furthermore, the right data analytics platform can make a huge difference, especially if real-time data is important for operations. Leveraging the right data in the right place leads to several improvements, like better customer engagement, smarter energy efficiency, superior asset management and stronger system integrity. It is also a better use of resources by the organisation.
The importance of smart grid data analytics
Smart grid analytics is going to have a huge impact on the future. With the energy infrastructure of the developed world moving towards a smart grid, there needs to be an analytics platform that can capture and analyse data from different endpoints. The right analytics platform allows utility companies to distribute resources more efficiently, cut costs and discover better ways to serve customers. Furthermore, the right data analytics platform allows them to make the most out of the data produced. Every analytics company is looking to provide some variant of smart grid big data analytics, including SAS because utility companies will be looking for any way to improve energy management.
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