Digital transformation has evolved the city gas distribution (CGD) sector in the past few years. Digitalisation trends include technologies to act on predictions, predict optimisation, act on exception, identify exception at an early stage, management by exception and manual exception. There is an advanced energy management system to reduce site energy use, improve energy intensity and reduce emissions. Some of the recent advancements are the advanced analytics platform for process unit optimisation and asset performance, library of root cause failure analysis templates, big data (data lake) integration technology and services, pervasive sensors for reliability, digital twin, robotic process automation, machine learning (ML) systems, among others.
Emerson has been a leader in technology and holds about 20,000 or more active patents. Additionally, the business is constantly on the lookout for unique ideas and introducing fresh technology. Founded in 1890, the company has a long history in automation and controls. The standard technologies that the gas sector has already embraced for plant control, pipeline control, compressed natural gas (CNG) station controls, CGD controls, etc. are known as mainstream adoption. Emerson then began managing factories using fully automated methods. It began early exception identification as a result of technological advancements, going beyond simply setting an alarm threshold and acting accordingly to adopting more proactive and preemptive measures that allow for an early warning of potential asset failure as well as for immediate corrective action.
Along with robotics, ML, and artificial intelligence (AI), there is an intriguing technical development that is now under research. In order for a factory to operate smoothly and safely, automation has evolved with the use of sensors and user interface coverage. More sensors will be deployed in the coming years. With this, the visibility of the process would not just be the minimum visibility that one needs for the gas plant or the pipeline; rather, it will be a step further and provide insights about the health of assets, so that one can be more proactive and prevent failure. Thus, addition of more sensors and instruments will imply availability of more control points. Besides, gas operators are not only restricted to the control room, but they have wireless infrastructure which is built across the pipeline so that when the operators are going for field rounds or visits, they are actually looking at the assets. Thus, with integration of artificial intelligence and ML, one can actually have all the parameters of that particular asset visible to the operator on the front on a simple tap so that futuristics scenario can be predicted or analysed. Besides, operators should be able to not just get manual data, but they should be able to co-relate with what has been recorded in the system so that they can clearly identify what are the problems and the location of deviations, so that control actions for improvement can be taken on time.
Key challenges faced
There are some challenges faced with evolving CGD space. With expansion of assets, data is being collected from multiple sources. Sometimes, data lies in various silos and many a time it becomes a cumbersome task to consolidate it. But, now with technologies and the advent of data lake and other solutions, data can be integrated into a consolidated centralised supervisory control and data acquisition (SCADA) system. On top of SCADA, there can be advanced solutions which can easily run and look at efficiency. So, it’s not only about operating the unit but also about operating the stations more efficiently having high availability for units and getting maximum out of it.
When it comes to energy management, gas operators should look at the consumption pattern of energy, and then prepare a dashboard for consumption patterns. This will help in improving energy efficiency of overall operations. If there are multiple compressors, it might be the case that one of them is using more energy and another is using less energy. So, the differential should be made visible to the operators, so that the highest efficiency compressors can be to be put to use.
There are further challenges with respect to training and skill development. There should be a way so that one can insert some function and start training operator on virtual model of the asset. If the asset actually goes into failure, then everyone will be more prepared as they have already seen that sort of scenario and assimilation or an operator trainer. Earlier, operator trainer training solution were available but with evolving technology now the solution can be hosted on cloud, so they can be not just be limited to use on operation efficiency improvement but also can be used for demonstration to various customers or it can also be used for various other replications because cloud access enables to use it practically from anywhere.
Lastly, root cause analysis happens to be one of the biggest operational challenges of today. If there is a failure, then one has to return back to the experts. But, now with development, the system has become smart enough to keep a recording various failure one of the possible causes of those failures and what are the remedial actions taken so these can be registered by the system itself. Whenever there is a repetition of a failure the data is populated automatically and operators are able to see and analyse what can be the possible cause of the failure. With the technology and advancements, elimination has become a lot easier. Thus, technology can support the shift from a conventional plan to a smart plan for a smart pipeline as well as smart CNG facility.
In sum
Investing in digital technologies means additional capex when one is building a gas plant but then the recovery based
on the rate of investment is very fast. Thus, when it comes to digital transmission, there will be lot of advantages from improving reliability and availability of ones plans and assets to increase in revenue and profitability. This will all be done by eliminating all the leakages and lower efficiencies from the system. One can really be operating with the maximum possible efficiency or can have a golden benchmark set and against the benchmark which was initially being looked at for assets performance. Operators will be able to differentiate which assets are performing well and probably those that need improvement or replacement. Additionally, operations and maintenance expenses can also be reduced with operator training. Similarly, a lot of features and functions of operations can be built into and seen on a sample basis and one does not have to actually face the situation in the field. Digital twin provides a solution where one can create a replica of compressor stations, pumping stations, etc. There is a need to create a digital twin that improves insight and enables people to communicate better, learn faster and make more efficient decisions.
Further, there are solutions to reduce energy and emissions, and various other advance pipeline-related applications and, CNG-related applications which can help in the implementation of a more sustainable environment for all.
Based on inputs by Arvind Singla, Associate Director Sales, Emerson Electric Co, at a recent India Infrastructure conference