With the growing role of wind energy in our power systems, the challenge of maintaining grid stability becomes increasingly critical. The key to this challenge is advanced and accurate modeling. Models are essential for ensuring the reliability and efficiency of our electric grid as we shift toward more renewable energy sources.
Evolution of Wind Energy and Modeling Demands
Thomas Grau
As wind energy becomes a more significant part of our energy landscape, the need for advanced modeling technologies grows. Utilities around the world now require more detailed and precise models, particularly for wind power plants. This is in response to the complex dynamics resulting from the integration of high percentages of renewable energy. Some traditional phasor-domain transient models (also known as root mean square (RMS) models), recognized for their computational efficiency, often struggle to accurately simulate the dynamic behavior of wind power plants in various grid conditions due to the previously established power system simplifications of the commercial tool solvers in the frequency domain. These models tend to omit some necessary details from control designs, leading to potential inaccuracies in scenarios like connection with a weak grid.
Advanced Modeling for Grid Interconnection Studies
As we envisage a power system with high penetration of inverter-based generation sources, the accuracy of models for grid interconnection studies becomes critical. It’s essential to understand not just the model’s capabilities but also its limitations, especially in the context of diverse operational scenarios that a dynamic grid presents. The reliability of these models in predicting grid behavior under various stress conditions is key to ensuring a stable energy supply.
Challenges in Utilizing Standard Library Models
Miguel A. Cova Acosta
The varying technology designs of wind turbines from different original equipment manufacturers (OEMs) and the tightened performance requirements by utilities worldwide make it challenging to use generic models such as standard library models (SLMs) for grid code compliance and system impact studies. This situation is further complicated by the fact that updates to these models depend solely on the simulation tool developer, often lagging behind the OEMs’ development of the latest control features. The gap in model performance between generic models and real product capabilities needs careful consideration, especially when it comes to specific control functionalities and varied test scenarios. Standard library models can be considered in research and education, as they provide a uniform reference point for academic studies and learning. They help introduce the fundamental concepts of wind turbine behavior and grid interaction, though they are not comprehensive in their depiction. However, standard library models are often misused in simulations of wind turbine generators and power plant controllers, and frequently fall short in simulating specific operational scenarios.
Addressing Standard Library Models Challenges
A critical limitation of standard library models is their high propensity to produce false positives when validated under very specific conditions. These models, once proven accurate in a narrow set of scenarios, can misleadingly appear reliable for many other situations. This discrepancy raises concerns about the reliability of standard library models in varied operational conditions and underscores the need for broader validation processes. Figure 1 illustrates the difference in model performance between specific validation scenarios and a range of operational conditions, highlighting the deviations and potential risks of relying solely on standard library models.
Figure 1: Comparison of tuned SLM and the site-parameterized UDM performance for MOD-026
Importance of Precise Modeling
Accurate electromagnetic transient (EMT) modeling based on user-defined models is crucial for integrating wind power plants into the grid. This accuracy comes thorough validation processes, including hardware in the loop (HiL) tests and field measurements, which are essential to ensure that the models accurately reflect the actual performance of wind plants under specific grid scenarios. However, it’s important to understand that simply using EMT models doesn’t automatically guarantee their accuracy or reliability. Effective EMT models require detailed source code integration to accurately reflect the products they simulate, incorporating specific control functionalities. For example, when managing multiple fault ride-through (FRT) events, a wind turbine’s EMT model must realistically represent thermal stress responses to prevent converter overheating. However, not every EMT model includes such refined thermal dynamics, highlighting the need for comprehensive and refined modeling to truly emulate real-world conditions. Precise, accurate, and reliable modeling in the context of wind energy is necessary for grid code compliance and power system stability.
Offshore Modeling Risk
It is also critical to accurately model offshore wind plants. Failure to adopt accurate models for offshore interconnections in the Northeast U.S. poses substantial risks. Outdated equipment models may lead to inaccurate grid planning, compromising reliability and stability. Inaccurate technical understanding leading to challenges in integrating large amounts of renewable energy are potential consequences. Non-compliance with evolving regulations and limited flexibility hinder grid resilience, resulting in increased risks to grid reliability and stability. Embracing updated equipment and allowing for technology advancement is essential to optimize offshore interconnections, ensuring a resilient and efficient power system in the dynamic Northeast U.S. offshore energy landscape. As OEMs, we need to provide help to the system operators so they can adapt and dramatically change the current approaches toward queue positions and support evolution in the industry.
Role of Collaboration and Industry Standards
In the renewable energy sector, collaboration between OEMs, utilities, and regulatory bodies is essential. The adoption of FERC (Federal Energy Regulatory Commission) Order 2023 and/or IEEE Standard 2800 demonstrates the industry’s commitment to enhancing grid reliability. Collaboration is crucial not only in setting these standards but also in validating and adapting them to real-world scenarios. A unified approach in modeling and validation is vital for accurately predicting and managing grid behavior with an increased mix of renewable energy.
As we move toward a future more reliant on wind energy, the effectiveness of our modeling practices will be key in ensuring a stable and reliable energy grid. Advanced modeling techniques, supported through validation and collaboration across the industry, are crucial in this transition. Through these efforts, we can secure a stable, efficient, and sustainable energy future, fully harnessing renewable resources.
Moving Forward
In conclusion, it is crucial to support the North American Electric Reliability Corporation (NERC), system operators, and utilities in adopting user-defined models, such as those mandated by FERC Order 2023, and to back the efforts of the IEEE Standard 2800.2 working groups, while ensuring their usability and maintenance. As the industry rapidly evolves, the need for accurate, tailored models for each wind power plant becomes paramount, steering us away from a reliance on standard library models. Opting for standard library models not only introduces a layer of complexity regarding intellectual property, but also poses significant risks to grid reliability in both current and future applications, which we may not be able to avoid in long-range planning studies where the equipment supplier is not known. Moreover, future standard library models will likely face limitations due to intellectual property constraints and the transition to new technologies. The successful implementation of IEEE standards depends on our commitment to precise user-defined models, emphasizing a proactive and usable approach to creating a resilient and progressive energy landscape. This approach is essential to ensure ongoing reliability.
Thomas Grau & Miguel A. Cova Acosta
Vestas
This is an important and timely discussion. I believe that, should OEMs decide to provide some details of their controllers even a positive sequence RMS modeling is sufficient to reproduce most of characteristics of the controllers and models. For example, if droop is a nonlinear function, then, it is a simple task to implement it in the SLM. There are two main topics here that needs attention. These are:
1. Phase domain instantaneous modeling vs positive sequence RMS modeling. Of course, one should appreciate the differences in these two methods regardless of IBR modeling
2. The SLM vs. OEM user-defined model which cannot be easily understood by general public due to trade secrecies and IP
The authors are commended for their valuable article.