Industrialisation has changed the world in many ways for good and the evolution has been very interesting. The story began with coal-fired steam-based prime movers to artificial intelligence (AI)- and machine learning (ML)-assisted equipment today, and it is evolving at an exponential pace. The evolution from 1.0 to 2.0 took a century, 2.0 to 3.0 three quarters of a century, 3.0 to 4.0 less than half a century and now 4.0 to 5.0 (already talks are on) may happen in a decade or two. Automation has played a key role in this evolution, and it has evolved too from manual to pneumatic to electronic.
The opportunity
Automation and digitalisation are two sides of the same coin, complementing each other to achieve an objective. One of the biggest opportunities and challenges for India in the next decade would be the integration of renewable energy into the grid in a sustainable manner. The scale of new renewable energy generation assets likely to be built by India is humongous and the planned timelines make it even more challenging. It is mandatory to automate each component of the ecosystem for a successful integration. All the components of the ecosystem should have the ability to interact and respond to each other to maintain the quality and integrity of the grid.
The integration of renewable energy is creating new challenges in the system, which can only and only be resolved with the help of electronic automation. This electronic automation ecosystem would comprise smart instruments, smart controllers, edge computing devices, central computing devices (can be cloud-based), and an ecosystem of interacting collaborating systems.
The fundamental aspect of automation is that we cannot control what we cannot measure. Electronic automation has played a key role in enhancing the pace of industrial evolution, including that of power generation. However, in the pursuit of lower tariffs, automation has suffered a lot. Measuring instruments, controllers and SCADA are restricted to minimalistic designs. However, AI/ML utilities will need more information from the assets to provide actual benefits. At present, wind turbines are partially digital (analog: temp switch, electromechanical relays, etc.) and based on recent trends, they are expected to go completely digital (digital: temperature transmitters, numerical relays) in the newer versions. Solar inverters and battery storage systems are much smarter in comparison to wind turbines. However, the balance of plant in all asset classes is analog at the moment. I see it going digital in the future with the use of numerical relays, etc.
Enabling collaboration by design
The need for collaboration between renewable energy generation assets and other parts of the ecosystem will drive upgrades/retrofits in the existing assets. Some of these aspects are well known but were not considered in the minimalistic design for commercial reasons (in the quest for lower costs). As an engineer what brings fulfilment to me is a timely intervention, as the most depressive act is to rectify a breakdown. Broadly, I foresee the following changes in the near future:
Wind assets
- Upgrades of the existing instruments with higher accuracy alternatives and introduction of new measurements (such as vibration measurement for condition monitoring) to support predictive maintenance
- Transition from 10-minute average data to real-time and time-stamped high resolution data storage
- Exchange of site data with cloud-based AI/ML platforms
- Inclusion of balance of plant in SCADA (maybe an independent software-as-a-service)
- Inclusion of wind masts in SCADA and shift to real-time measurement from 10-minute average
- Scheduling of maintenance with the help of medium-term weather forecasts
- Digital twins to become a norm
Solar assets:
- Measurement of production on each module/string
- More irradiation and module temperature measurement
- Soiling measurement equipment-assisted optimised cleaning
- Inclusion of balance of plant in SCADA (may be an independent software-as-a-service)
- Inclusion of weather monitoring station in SCADA and shift to real-time measurement from the 10-minute average.
The size of renewable assets is growing to more than 250 MW. Thus, controllers have to be capable of collaborating with advanced SCADA systems. This infrastructure on site is an enabler to support predictive maintenance and examine asset under-performance using AI/ML-based tools. Such tools can become more effective for the industry with more data points.
The key shift required in the industry behaviour to “enable collaboration by design” is in the mindset, from lower initial investments (capex) to lifetime costing for the ecosystem. The industry is focused on the race towards the bottom (lowest tariffs), predominantly on Excel models. However, for the asset life of 25 years, sustainability will be better assured through the lifetime ecosystem costing approach. The industry will rapidly change over the next 10 years with electronic automation at an exponential pace, and this will force the existing assets to augment for collaboration, a set of costs that were not budgeted in the Excel models.
Cultural shift in O&M
With more instruments and better control systems monitoring equipment health, we would be able to visualise the interventions required. It does look simpler for solar operations and maintenance (O&M), but wind energy O&M, especially high plant load factor (PLF) sites with more than 35 per cent PLF, will undergo a significant transformation. Automation and digitalisation will transform O&M behaviour. The main things that stand to improve are:
- Reduction in response times due to advance planning of resources including manpower, material and maintenance tools
- Information and assessment-based intervention using condition monitoring feedback-based intervention
- Augmentations that need fewer interventions like ultrasonic wind vanes that are more reliable and require no maintenance
- Asset management tools with appropriate lifetime history management of equipment
- Improved mean time to repair
- New set of skills to be learnt for the team.
Automation and digitalisation will become key differentiators in the near future. They have the potential to provide more assistance to O&M teams and enable timely interventions. The teams will be able to interact with the equipment they maintain and keep them fighting fit all the time.
The automation and digitalisation of assets will bring more satisfaction to us as engineers and I am looking forward to the future with renewed curiosity, vigour and enthusiasm.
Notes:
Industry 1.0 started in the 18th century with steam-powered machines (coal-fired steam production). These developments were predominantly in the textile and transportation segments.
Industry 2.0 started in the 19th century with predominant developments in electrical energy, petroleum refining and internal combustion engines.
Industry 3.0 started in the 20th century with electronics at its heart, including the early computer era. This was an era when industrialisation rapidly covered the globe and laid the foundation for climate change.
Industry 4.0 started in the 21st century with advancements in electronics and computational power. The primary objective is to make each industrial component smart and harness its capabilities using high-end computing. This industrialisation process is the key to enable timely actions by the autonomous exchange of information between relevant devices and computing platforms.
