The Energy Transition Will Be Won or Lost on Grid

Grid inefficiency has evolved from a technical constraint into an economic one. When renewable energy cannot be moved and utilised effectively, congestion, curtailment, and rising costs undermine competitiveness and weaken confidence in the transition.

July 21, 2026. By News Bureau

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Remote Monitoring and Diagnostics Center

For years, energy transition has been measured by how quickly we can replace fossil fuels with renewable energy. Today, a more consequential question is emerging: can our grids keep pace with an increasingly electrified world? That concern is fast becoming the defining economic constraint on decarbonisation.

Electrification is accelerating across industries, while artificial intelligence (AI) and hyperscale data centres are driving unprecedented growth in power demand. Yet, grid congestion and curtailment continue to prevent clean energy from reaching where it is needed most.

This is the new reality of the energy transition: success will depend not only on how much clean power we generate, but on how effectively we can move, manage, and use it. Grid efficiency is emerging as the critical factor that will determine how affordable, resilient, and durable decarbonisation ultimately becomes.

This is Now a System Challenge

Electrification remains one of the clearest paths to decarbonisation, but it is increasingly constrained by grid infrastructure that was designed for a very different energy system. Built around predictable demand and one-way power flows, today's grids must now accommodate variable renewable generation, distributed energy resources, and rapidly growing sources of demand such as data centres and electric vehicle charging networks.

In markets such as India, initiatives like PM-KUSUM are transforming the grid from a one-way delivery network into a dynamic, two-way energy ecosystem. India's operational IT load capacity has risen from 1.2 GW in 2024 to approximately 1.3-1.53 GW in early 2026, supporting a market valued at USD 9-10 billion and infrastructure investments projected to reach USD 28.5 billion.

With supply expected to grow by 30 percent annually, capacity could reach 4-5 GW by 2030, while AI-driven demand may push it as high as 8-9.2 GW. This underscores a broader shift that is the success of the energy transition will depend less on how much clean energy we generate and more on how effectively grids can move, manage, and optimise it.

What a Greener Grid Now Demands

Grid inefficiency has evolved from a technical constraint into an economic one. When renewable energy cannot be moved and utilised effectively, congestion, curtailment, and rising costs undermine competitiveness and weaken confidence in the transition. The result is a decarbonisation pathway that becomes harder and more expensive to sustain.

A greener grid requires more than additional capacity as it needs the intelligence to integrate diverse renewable sources efficiently. Rather than relying solely on new infrastructure, operators must maximise existing networks through greater visibility across supply, demand, and asset performance.

We are already seeing what this looks like in practice. Tata Power, one of the country’s largest integrated power companies, implemented a centralised Remote Monitoring and Diagnostics Center (RMDC) to oversee its massive fleet of generation and transmission assets. By utilising an advanced industrial data infrastructure to aggregate real-time sensor data, Tata Power moved away from conservative, schedule-based maintenance toward a model of Predictive Analytics. This system continuously monitors the health of critical assets, identifying subtle changes in equipment behavior that human operators or static assumptions might miss. This means that the next gains in decarbonisation will come not just from building more infrastructure, but from extracting more value from the infrastructure already in place.

Moreover, the industry is also recognising that grid efficiency is an information challenge. This is driving investment in industrial intelligence platforms that can unify operational, engineering, and asset data within a single environment. By creating a common source of truth across complex energy ecosystems, these platforms enable operators to move beyond monitoring individual assets and instead optimise performance across the grid as a whole. As renewable energy penetration increases and power flows become more dynamic, this ability to contextualise data and support real-time decision-making is becoming a critical enabler of grid efficiency.

Why this Now Shapes the Energy Transition

Grid efficiency is no longer merely an operational concern; it is emerging as a critical economic constraint as electrification, AI, and renewable energy place unprecedented demands on power networks. In this environment, technologies such as AI deliver value only when powered by trusted, real-time data that enables better forecasting, grid balancing, reduced curtailment, and more effective integration of renewables.

The question now is no longer how much clean energy we can generate, but how effectively we can use it. And that will determine not just the pace of decarbonisation, but its staying power.

- Tarun Singh, VP Sales and India Market Leader, AVEVA