Weathering the Drought: Simulation-Driven Resilience for CEE’s Energy Sector

River levels on the Danube, Tisza, and their tributaries are dropping, reservoirs are shrinking, and utilities across Hungary, Romania, Bulgaria, Serbia, and neighboring markets are being forced to rethink assumptions that held for decades.

For the energy sector specifically, the effects are already visible:

• Reduced inflow to hydropower reservoirs, cutting generation capacity exactly when flexible power is needed most
• Cooling water shortages at thermal and nuclear plants, sometimes forcing derating or temporary shutdowns
• Greater reliance on solar and wind to cover the gap, increasing pressure on grid stability and control
• Disrupted supply chains for biomass and agriculture-based fuel feedstocks

The question is no longer simply, “How do we respond to this drought?” It is increasingly, “How do we design and operate systems that stay resilient the next time this happens, and the time after that?”

This is exactly where simulation, modeling, and real-time testing can create value. Below are concrete ways MATLAB/Simulink, COMSOL Multiphysics, and Speedgoat can support energy companies in the region, together with customer examples that demonstrate similar approaches in practice.

Hydropower: forecasting and optimizing under uncertainty

When inflow is scarce, every cubic meter matters. Utilities need to extract more predictive accuracy and operational intelligence from their existing assets instead of relying only on historical rules of thumb.

How can MATLAB and Simulink support hydropower operators?

• Develop data-driven and physics-based streamflow forecasting models that combine hydrological data with machine learning to anticipate low-flow periods further in advance
• Build reservoir and cascade optimization models that balance power generation, irrigation, and ecological flow requirements under tightening water budgets
• Create digital twins of turbine and generator systems with Simscape to identify where efficiency can be recovered as head and flow rates move outside normal operating ranges

How can Speedgoat support control validation?

Speedgoat enables real-time hardware-in-the-loop testing of turbine governor and excitation control upgrades before those changes are introduced on a live unit. This is particularly valuable when plants are already operating under stressed or non-standard conditions.

Proven in the field — Naturgy Energy Group

Naturgy uses MATLAB to predict energy supply and demand. The same forecasting discipline can be applied when reservoir inflow, rather than demand, becomes the constraining variable.

Proven in the field — EDP Renewables North America

EDP Renewables built automated MATLAB systems for price forecasting and revenue-at-risk analysis, combining production estimates with market price forecasts to guide short- and long-term generation decisions. The same approach can support hydro operators managing output under variable water availability.

Proven in the field — Idaho National Laboratory / Idaho Falls Power

Researchers built Simulink and RSCAD models of a real run-of-river Kaplan turbine and its hydrogovernor. The models accurately matched plant response to changes in electrical load and water conditions and enabled hardware-in-the-loop testing of governor upgrades that had not previously been possible for this turbine class.

Thermal and nuclear generation: solving the cooling water problem

Reduced river flow and higher water temperatures directly threaten once-through and closed-loop cooling systems. Under these conditions, plants may need to evaluate alternative cooling strategies before a crisis forces a decision.

How can COMSOL Multiphysics support cooling-system decisions?

• Model cooling towers and heat exchangers using CFD and conjugate heat transfer under reduced water availability and elevated intake temperatures
• Compare dry cooling, hybrid wet/dry cooling, and air-cooled condenser retrofits before committing capital
• Evaluate thermal stress and other multiphysics effects to understand how alternative cooling strategies influence equipment life and performance envelopes

This kind of modeling can turn “we may eventually need to change cooling technology” into a data-backed investment case months or years before operating conditions force the issue.

Proven in the field — thermofin GmbH

thermofin GmbH uses COMSOL simulation to solve real airflow and heat-distribution problems before manufacturing. In one case, simulation revealed that a planned five-unit arrangement would allow backflow to bypass into the ceiling, allowing the design to be corrected before installation. The same simulation approach can be applied when reevaluating cooling towers and heat-exchanger layouts for water-constrained operation.

Grid stability: absorbing more renewables without losing control

As hydro output becomes less reliable, solar and wind may be asked to fill more of the gap. That shift introduces its own technical challenges, including lower system inertia, voltage regulation issues, and more complex dispatch decisions.

How can MATLAB and Simulink support grid-stability studies?

• Model power systems and microgrids as the generation mix shifts toward variable renewables
• Design and tune grid-forming inverter control strategies that help compensate for reduced hydro-based inertia
• Develop load-forecasting and demand-response models to reduce peak strain during periods of constrained generation

How can Speedgoat support real-time testing?

Speedgoat supports real-time simulation and hardware-in-the-loop testing of protection relays, inverter controllers, and grid-forming algorithms under realistic fault and stability scenarios. This allows engineering teams to prove new control strategies before they are deployed on live infrastructure.

Proven in the field — Sandia National Laboratories / Maui Electric

For a 1.2 MW solar farm on Lanai, Hawaii, Sandia engineers used Simulink and Simscape Electrical to model the supervisory control systems, PV arrays, inverters, batteries, and diesel generators that made up the island microgrid before the solar farm was brought online. This is closely related to the blended-generation modeling challenge CEE utilities face as hydro output becomes less predictable.

Proven in the field — WithBEER

WithBEER uses a digital twin built with Simulink and Speedgoat real-time test systems to safely validate high-voltage electrical systems. The same hardware-in-the-loop approach can support microgrid energy-management and grid-stability control strategies before they reach live infrastructure.

Why this matters now, not just after the next drought

The utilities and industrial energy producers that come through dry periods best will not simply be those with access to more water. They will be the organizations that use today’s stress conditions to build better models of their systems and make faster, better-informed engineering decisions when conditions tighten again.

That is the role these tools are built for: not predicting the weather, but helping ensure that whatever the weather does, systems, controls, and investment decisions are ready for it.

Learn more

• Naturgy / Gas Natural Fenosa — Load Forecasting with MATLAB
  Explore how MATLAB is used for energy supply and demand forecasting.
  Read more
• EDP Renewables North America — Renewable Energy Forecasting and Risk Analysis
  See how MATLAB supports production forecasting, market-price forecasting, and revenue-at-risk analysis.
  Read more
• Idaho National Laboratory / Idaho Falls Power — Hydropower Unit Models
  Explore open hydropower turbine and governor models used for simulation and hardware-in-the-loop validation.
  Read more
• thermofin GmbH — Heat Exchanger Simulation with COMSOL
  Learn how simulation is used to optimize airflow, heat distribution, and cooling-system design before manufacturing.
  Read more
• Sandia National Laboratories / Maui Electric — Microgrid Modeling
  Explore simulation-driven development of blended renewable generation and microgrid controls.
  Read more
• WithBEER — Hardware-in-the-Loop Validation with Speedgoat
  Learn how digital twins and real-time testing can be used to validate high-voltage electrical systems before deployment.
  Read more