In 2026, the global energy market will reach a critical inflection point: renewables will become the largest source of electricity.
This milestone represents both a massive win for the industry and a powerful opportunity for renewable operators. But capitalizing on it will require a new level of operational discipline to overcome the growing complexity, increasing stakeholder demands, and compressed margins affecting the industry.
As we covered in our previous post, performance and maintenance optimization will be essential for capturing incremental, hidden value in existing assets. But the biggest potential lies in going one step further, beyond single-asset or site-level thinking.
In 2026, the leaders will be those who can optimize at the portfolio level.
For most of the last decade, site-level optimization was sufficient. Feed-in tariffs, fixed pricing, and generous incentives provided insulation against volatility.
But today, those cushions are disappearing, and renewable assets are now fully exposed to dynamic power markets. Revenue depends not just on how much power is delivered, but also on when and where it’s delivered. Operators must navigate real-time market competition, PPA obligations, congestion, curtailment, and ancillary service requirements that complicate decision-making.
At the same time, portfolios themselves are changing. Hybrid configurations that combine solar, wind, and storage across multiple regions are becoming the norm. Price volatility, weather conditions, transmission congestion, and operational decisions affect entire fleets, not just individual sites. In this environment, site-level optimization is a liability.
As the industry matures, single-asset thinking is becoming obsolete. According to McKinsey & Company, energy players must now "evaluate their entire portfolio to understand trade-offs across a collection of assets rather than focus on individual holdings." Operators that continue to manage in isolation risk underutilization, lost revenue, and missed market opportunities.
A Virtual Power Plant (VPP) demonstrates this portfolio-level optimization in action. By definition, VPPs are groups of diverse, distributed energy resources (DERS) aggregated to behave as a unified market-facing power source. VPP output is dispatched, optimized, and monetized as a single operational unit.
The VPP model only works because data is standardized, centralized, and analyzed holistically, and this shared intelligence enables coordinated decision-making. For example, a battery in one location can offset solar volatility in another. Robust wind production can cover for underperformance elsewhere. Risk is spread across the portfolio, and “the whole” captures more value than individual assets could on their own.
Portfolio-level thinking fundamentally changes how performance and maintenance decisions are made. Instead of treating every site equally, operators can focus attention where it can have the greatest financial impact—whether that’s preventing big-ticket failures before they happen or addressing smaller issues that quietly erode revenue over time.
Operators with unified intelligence can prioritize investments, mitigate risks, and improve performance across the entire portfolio.
With this holistic view, operators can make smarter, faster decisions that capitalize on dynamic market conditions. What does that look like in practice?
Consider two hybrid sites combining battery energy storage systems (BESS), solar, and wind. Together, the mix provides near round-the-clock availability.
If site-level analytics flag underperformance in several solar strings, the typical response would be immediate maintenance that takes the strings completely offline, further reducing output.
But with portfolio-wide optimization, the system can tap operators can’t achieve it with their current systems.
That insight changes the decision. Performing immediate PV maintenance would lower output at the worst possible time. Instead, the algorithm recommends delaying PV maintenance until a forecasted window of strong wind can compensate for taking the strings offline. Then, PV maintenance can proceed without compromising total energy delivery or grid commitments.
The result is less disruption, more predictable performance, more efficient use of resources, and the ability to make decisions based on measurable financial performance.
Maintenance is no longer a cost center, it’s a strategic lever.
Despite the clear advantages of portfolio-wide optimization, most operators can’t achieve it with their current systems.
While many report having some unified analytics, they admit they’re still using separate dashboards and tools. Asset data lives in siloed systems and proprietary or incompatible formats. That means it can’t integrate across sites or systems to function cohesively. Even when data is aggregated, operators can’t fully trust it due to potential data inconsistencies and gaps.
They’re running a portfolio “in name only” that can’t operate or respond to markets as a unified system.
Portfolio-wide optimization requires a system-wide viewpoint that includes:
Standardized, integrated data across all assets.
Centralized control for coordinated dispatch and maintenance planning.
A cloud-based platform capable of real-time, scalable analytics.
This is where scale becomes an asset instead of an obstacle: the larger and more diverse your portfolio, the more valuable unified analytics becomes. Operators can balance wind against solar, coordinate maintenance windows, and optimize dispatch across sites.
But you need the data infrastructure to unlock that advantage.
The Unity Renewable Energy Suite provides the portfolio-wide visibility, analysis, and control operators need to fine-tune operations at a granular level. The payoff is measurable: incremental performance improvements that translate into millions of dollars in additional value while positioning operators to manage volatility, allocate resources, and scale their portfolios with confidence.
Stay tuned for future installments in the “Navigating Renewables in 2026” series, where we dive into how data quality becomes a competitive advantage in the age of AI.
To explore these trends in more depth, access our on-demand webinar below.