Dynamic Equivalents for Large-Scale Power Systems Using PSS®E – A Systematic Approach

Introduction: Why Dynamic Equivalents Are Critical in Modern Power Grids

As today’s electrical grids grow more interconnected and complex, utilities face a key challenge: how to accurately simulate vast power systems without overwhelming computational resources. With regional grids linked for reliability and economic dispatch, full-model simulations become impractical.

Dynamic equivalents offer a solution: they allow system planners to simplify the model while retaining essential dynamic behavior. This reduces simulation time, eases control design and tuning, and protects confidential data — all without compromising on accuracy.

In this article, we outline a systematic, utility-tested approach for building dynamic equivalents using PSS®E (Power System Simulator for Engineers). This method, based on real-world practices from the Saudi Electricity Company (SEC) and presented in a CIGRE 2016 paper, is applicable to large-scale grids across North America and beyond.

What Are Dynamic Equivalents in Power Systems?

A dynamic equivalent is a reduced representation of a portion of the power system that has limited impact on a study area. Instead of modeling distant or low-impact sections in detail, engineers substitute them with a simplified equivalent that behaves dynamically similar under disturbances.



This approach is widely used in power system modeling, especially in scenarios involving dynamic security assessment, controller tuning, and real-time simulation.

Key benefits of using dynamic equivalents:

• Substantial reduction in simulation time and model complexity
• Easier controller design and parameter tuning
• Enhanced data privacy — sensitive utility network data remains secure
• Enables fast EMT simulation, real-time studies, and operator training

Challenges in Modeling Large Power Systems

Several key challenges drive the need for dynamic equivalencing:

• Computational limits make simulating thousands of buses and devices slow and inefficient.
• Geographic separation means some network areas have minimal influence on local events, yet still burden the model.
• Data security restricts access to detailed topology from utilities.
• Model maintenance becomes burdensome with frequent updates.
• Control complexity increases with high-order, detailed system dynamics.

To address these, engineers use dynamic equivalents as a focused and efficient way to simulate only the parts of the system that matter most.

Methods for Developing Dynamic Equivalents

Dynamic reduction techniques have evolved significantly over the years:

• Coherency-based methods group generators that respond similarly during disturbances.
• Modal analysis identifies critical oscillation modes and retains them in the model.
• Slow coherency emphasizes long-term behavior of generator groups.
• Time-domain aggregation preserves time-series behavior of key components.
• AI and ANN-based methods (neural networks) are emerging to automate and improve accuracy.

Today, hybrid approaches that combine traditional methods with AI offer the best potential for future-ready power system modeling.

A Proven Approach Using PSS®E

This approach follows a three-step process for creating effective dynamic equivalents within PSS/E:

Step 1: Net Small Generators with Loads

All generation sources below 380 kV are “netted” with their associated loads. This step removes unnecessary generator detail, streamlining the base model.

Step 2: Aggregate Coherent Generators

Using time-domain simulation in PSS®E, coherent generators — those with nearly identical dynamic responses — are identified and aggregated. This process ensures essential dynamics like inertia, exciter, governor, and PSS models are retained.

Step 3: Apply Static Network Reduction

With PSS®E’s built-in network equivalencing tools, engineers reduce the external network (typically below 230 kV). The external grid is replaced by an equivalent admittance matrix, connected to the internal system via equivalent branches and shunts.

Why This Method Stands Out | Key Advantages of This PSS/E-Based Method

• Python Automation: The entire workflow is scriptable in Python within PSS®E, reducing manual effort
• Accuracy: The reduced model closely matches the full system in both steady-state and dynamic simulations
• Efficiency: A real-world case saw model size reduced from 2,785 buses to just 127
• Practical Use Cases: Ideal for controller design, online dynamic assessment, and EMT modeling

Real-World Applications of Dynamic Equivalents

Dynamic equivalents are widely used in power system engineering and operations. Key applications include:

• Dynamic Security Assessment (DSA): Reduced models enable near real-time simulations to evaluate grid resilience during contingencies.
• Controller Design: Simplified systems allow more effective and stable controller tuning for governors, exciters, and power system stabilizers.
• EMT Simulations: Aggregated systems are faster and more stable when used in electromagnetic transient tools like PSCAD.
• Operator Training: Faster models help simulate disturbances and train control room personnel in real-time environments.
• Renewable Integration Studies: Ideal for analyzing behavior in grids with a high penetration of inverter-based resources (IBRs).

Conclusion

This systematic dynamic equivalencing method using PSS®E offers an effective, accurate, and scalable approach to simplifying large power system models. Whether you're conducting stability studies, designing control strategies, or preparing for EMT simulations, this approach saves time, preserves key dynamics, and meets industry standards.

At Keentel Engineering, we support utilities and developers across the U.S. with:

• Dynamic equivalents and model reduction
• Dynamic security assessment
• Renewable and inverter-based resource modeling (See Utility Scale Farms Engineering)
• Advanced control system tuning

Reach out today to explore how we can improve your system modeling workflow and simulation performance.

FAQ: Dynamic Equivalents in Power Systems

1. What is a dynamic equivalent?

A simplified model of part of a power system that preserves key dynamic behaviors while reducing model size.

2. Why are dynamic equivalents used?

To speed up simulations, simplify models, protect data, and enable advanced studies like dynamic security assessment.

3. What software is used for dynamic equivalents?

PSS/E is a widely used tool, often combined with Python or MATLAB for automation.

4. What is "coherency" in generator aggregation?

Generators that respond similarly to disturbances are grouped as coherent and aggregated.

5. How is accuracy validated?

By comparing steady-state voltages, angles, and power flows, as well as dynamic responses under faults.

6. Can this method be applied to renewable-rich grids?

Yes, but careful modeling of inverter-based resources (IBRs) and their controls is required.

7. Is ANN-based dynamic reduction mature?

Research is ongoing, but hybrid ANN + traditional methods show great promise.

8. Can reduced models be used for EMT studies?

Yes, if the aggregation retains sufficient dynamic detail.

9. How much size reduction can be achieved?

In the SEC example, a 2785-bus system was reduced to 127 buses — a massive simplification.

10. Does PSS/E require custom coding?

 The reduction can be automated via Python, but core functionality is available in PSS/E.

Ready to Simplify and Accelerate Your Power System Studies?

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