The deployment of digital technologies for power plant operations and maintenance (O&M) can lead to significant savings due to enhanced asset life and reduced maintenance costs. These benefits coupled with improved capacity utilisation, reduced emissions and lower technical losses make a strong case for investment in digital technologies. The integration of cutting-edge technologies such as IoT, blockchain, cloud computing, machine learning (ML) and artificial intelligence (AI) in power plants and the grid will improve the operational efficiency of the plant and reduce maintenance costs as well as outages.
Broadly, the process of digitalisation be-gins with the introduction of real-time supervisory control and data acquisition systems by embedding IoT devices in the equipment. This is followed by asset performance management and finally the introduction of predictive systems to avoid outages.
Applications in power plant O&M
In a digital power plant, a large number of digital sensors are added to provide real-time information about the power plant operations. These sensors provide updates on combustion temperature, input flow of fuel, air and cooling water and output flows of electricity or emissions. A data analytics platform processes the data with its software tools and a third component utilises the insights derived from the data to make alterations to the operation of the utility with limited time lag.
Introducing digital data analytics and diagnostic solutions will help in improving combustion efficiency and plant performance by optimising the rankine cycle in the case of thermal power plants (TPPs) in order to augment output. Data analytics, ML and AI can also offer several benefits. The implementation of data analytics to track the operating parameters for reliable operation can help in the early detection of excursions or defects. Data analytics can assist in detecting energy loss online and taking corrective actions, thus improving the cyclic efficiency of plants. It can also help optimise the maintenance strategy by restricting unscheduled outages and eliminating unnecessary preventive maintenance. Equipment health monitoring can also be undertaken through real-time monitoring of critical parameters deviations and condition monitoring.
With the digitalisation of power plant O&M, utilities can undertake predictive and preventive maintenance to improve the asset life performance and enhance the operational efficiency of the plant. AI/ML tools integrated with remote monitoring systems enable real-time data streaming; help build predictive models utilising the available data; provide insights from the data; identify issues by tracking activity at all levels; and prioritise resolution urgently.
Moreover, predictive insights acquired through digital technologies such as AI/ML give information on future demand and supply schedules, as well as other design aspects. Gencos using these technologies will be able to improve plant performance by scheduling their downtime and outages at a time when the electricity tariff is low so as to minimise losses.
Digital twin is another technology for strengthening the real-time monitoring capacities with predictive capacity through simulation. It replicates the process of generation to model, simulate and estimate future performance while charting an optimal method to extend the life of the power plant. Furthermore, the technology helps the power plant to increase the efficiency such that the capacity utilisation of the plant is optimally high while ensuring that it does not result in downtime and maintenance issues in the medium to long term.
There is significant potential to improve generation, capacity utilisation, output efficiency, etc., by introducing reliability-centred maintenance (RCM), wherein a key performance indicator provides real-time data about the operational parameters. RCM employs preventive maintenance, predictive maintenance, real-time monitoring, reactive maintenance and proactive maintenance techniques in an integrated manner to improve the functioning of a machine or equipment. It increases equipment availability and reduces maintenance and resource costs.
RCM also includes proactive health monitoring through equipment-wise health indices based on real-time measurement data from operator rounds. It sends 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 for equipment family or failure mode, and predicts the time of the next failure (useful in planning and budgeting). It provides information with the help of KPI (key performance indicator) dashboards. The RCM optimisation strategy undertakes cost-benefit analysis of maintenance activities based on the actual notification history. It also covers frequency optimisation and life cycle costing based on multiple factors such as failure costs, action item costs and equipment reliability.
Tata Power, in collaboration with GE Power, is on track to implement RCM at all of its thermal assets from 2019 onwards. This, along with a proactive approach towards daily operations and maintenance, is expected to increase the reliability of all its equipment. Furthermore, it has helped Tata Power to reduce its O&M expenses, optimise availability, improve reliability, reduce risks, and reduce costs through intelligent asset strategies. It has also improved maintenance planning for its power plants. It has helped the genco avoid costly emergency repairs with the early recognition of problems, thereby turning unplanned downtime into planned downtime.
The way forward
With the transformation of the power sector and the emergence of decentralised power plants, it is important for utilities to incorporate digital technologies and embed them in their operational structure in order to improve their yield and reduce operational costs. In addition, the digital assets in power plants will play a key role in ramping up and down generation in view of the expansion of variable renewable energy assets in India.
Utilities should establish best-in-class O&M procedures to achieve business excellence and ensure long-term economic viability. To keep the cost of generation low, activity-based budgeting, cost-cutting measures, and optimal fuel mixing are required. Utilities should have a plant performance improvement suite and aim to reduce the start-up time to achieve operational excellence, and maximise the plant availability and load factor. Their focus should be on the adoption of new and innovative technologies, cost savings and work mechanisation. Capacity building and training using augmented reality along with hands-on maintenance work can allow TPPs to improve their O&M. Furthermore, best practices in O&M provide optimal solutions to overcome the difficulties in the power industry, help maintain plant safety and availability, and enhance asset flexibility, while keeping maintenance costs at a minimum. To increase the productivity of various units, a tailored strategy is required.
An effective digital monitoring and maintenance solution requires an ideal balance and blend of people, processes and digital tools. Hence, power plants have to focus on retraining their engineers, hiring process experts and software maintenance engineers. In addition, utilities need to adopt practices such as real-time anomaly detection; prioritise risk and devise measures to mitigate those risks; and formulate standard operating procedures for emergencies.