Digitalisation Strategies

Advanced BTG solutions to improve operational and cost efficiencies of TPPs

Digitalisation holds big promise for the power industry. The digitalisation of boiler, turbine and generation (BTG) operations can help reduce emissions, enhance plant efficiency, optimise operations and maintenance (O&M) costs, enhance reliability and maintain plant performance under flexible operations. Constant monitoring of boiler temperature and pressure with digital tools can help manage emissions and improve efficiency. Digitalisation also aids enterprise management through real-time network monitoring and reporting. With customised dashboards, business intelligence tools, digital work processes and blockchain-enabled transactions, gencos can move towards analytics and data-driven decision-making. Apart from this, developers are actively deploying advanced digitalisation solutions such as digital twins and industrial internet of things (IIoT) and have plans to adopt new technologies such as artificial intelligence (AI) and machine learning (ML) in the near future.

Use cases of BTG digitalisation 

One of the key applications of BTG digitalisation is maintaining reliable and efficient operations of a thermal power plant (TPP). This is particularly gaining significance owing to the growing share of renewable energy in the power generation mix, which requires flexible operations of conventional power generation assets. However, the flexible operation of plants deteriorates their operational performance, lowering the plant load factor, and increasing the heat rate and auxiliary consumption. Digital solutions provide an enhanced view of a plant’s health and operators can get a clear sense of asset flexibility. Digital solutions help in maintaining plant performance under flexible operations. Further, digital applications are being used to achieve the maximum steam temperature in the boiler without violating material limits. Temperature optimisers are robust and easy to parameterise and are equipped with adaptive state space controllers. They can be used during start-up/ shutdown and over the entire load range and can also work as a solution to control the reheat steam temperature. Digital solutions can be effectively used for a more accurate evaluation of the operational history (EOH) and implementation of state-of-the-art EOH solutions. EOH solutions are applicable when part load leads to steam temperature changes, especially reheat temperature. These solutions can provide better outage planning as well as enhanced operational flexibility.

Another popular area for the deployment of digitalisation solutions is monitoring and controlling power plant emissions. With the tightening of emission norms and an increasing focus on environment-friendly power generation, the deployment of digital solutions for emission control is fast gaining traction. A digital plant can help monitor power plant emissions in real time. This helps in saving reagent costs, while keeping a check on the pollution level. Besides, constant monitoring of the temperature and pressure of coal with digital tools can help manage emissions and improve efficiency.

Additionally, digital solutions in power plants are used for detection and plugging boiler leakages. These can be detected by comparing the expected and measured values recorded in the system, through the use of sensors. Further, digital solutions can record the heat rate based on the actual performance of steam turbines and report deviations, if any. Apart from this, soot blowing optimisation is another important application of digital solutions in power plants. Through this, the cleanliness factor of heating surfaces can be monitored. It is observed that many times cleanliness does not change uniformly over time, indicating that the deposition of soot is not always uniform.

Digital twin

The digital twin creates a digital model for feedback of the plant’s characteristics and helps power plants leverage big data for driving efficiency. The digital twin can be made available in different configurations, covering the complete power plant including boiler, turbine, generator and balance of plant system. The overall objective is to build a model of power plant behaviour. There are two digital models for this – thermodynamic model and ML model. TDM is based on thermodynamic equations with data input. It is a traditional approach based on the conservation of mass and energy. MLM is based on training data, that is, input plus measured output. It is equipped to automatically detect the most relevant input data, based on actual operations data, and remove systemic errors.

Flexible operations and O&M

Digital solutions help monitor and enhance the flexibility of the BTG equipment of a power plant. Common software systems for automatic mill operation (mill scheduler), main steam temperature control, reheat steam temperature control, automated start of fans and pumps, integrated start-up automation, flame detection system, flue gas temperature control and the online coal flow measurement system can be deployed by TPPs. Digital tools such as merit order, oil planning and coal mill window can help improve the operational performance across key O&M processes. Management dashboards increase transparency and drive O&M excellence. Various dashboards give a unified view of the financial and operational parameters at various levels, thereby improving data tracking and transparency. Some other digital solutions for flexible power plant operations are process automation/boiler auto-tune; combustion stability advanced monitoring systems; and online predictive tools for predicting failures.

Reliability-centred maintenance

Reliability-centred maintenance (RCM) employs preventive maintenance, predictive maintenance, real-time monitoring, reactive maintenance and proactive maintenance techniques in an integrated manner to increase the probability of the functioning of a machine or equipment in a required way that enables to increase equipment availability and reduce maintenance and resource costs. RCM focuses on reliability instead of availability. It follows a proactive approach to prevent failures, as compared to a reactive approach. It is analytics-driven optimised maintenance with higher availability and life cycle cost optimisation. RCM uses data for analytics and predictions (run-repair-replace) and uses real-time data and analytics to identify interventions for reliability improvement. RCM undertakes proactive health monitoring through equipment-wise health indices based on real-time measurement data from operator rounds. It raises automatic notifications to the engineer when the health index crosses thresholds. The analysis and reporting segment of RCM evaluates the effectiveness of the ongoing strategy and can tell the possibility of an equipment failure in advance. It provides information with the help of key performance indicator dashboards. RCM’s optimisation strategy undertakes a cost-benefit analysis of maintenance activities based on the actual notification history, and frequency optimisation and life cycle costing based on multiple factors including failure costs, action item costs and equipment reliability.

Conclusion

To conclude, in view of the ageing power plant fleet and the growing share of renewable energy in the grid, undertaking digitalisation of TPPs can help in maintaining the operational efficiency of plants and ensure cost-effective power generation.

That said, with increasing digitalisation, data security becomes a key aspect. Cybersecurity is a cause for concern for power plant managers exploring digital deployments. Gencos, therefore, need to ensure that their risk management and response practices are aligned to a digitally controlled environment. Besides, adequate workforce training and change management are essential for the smooth adoption of digital solutions.

Priyanka Kwatra

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