Nothing is static when it comes to electricity – unpredictable events can occur at any moment. Electrical installations are dynamic systems, with constantly varying behavior and quality of electricity. What’s more, electrical installations are gradually becoming increasingly complex, as electrical loads grow more powerful and sophisticated. This introduces endless different interactions between components. Through simulations, we can evaluate how systems will perform under a variety of different conditions, optimize Power Quality (PQ), predict potential issues, and optimize design and operation without (costly or impractical) physical testing.
Two main reasons for carrying out simulations
- An electrical installation which has not actually been built yet needs to be compliant to regulations, or you want to ensure issues such as unexpected PQ incidents will not occur.
- An electrical installation has already been modelled and physically exists. Based on simulation, optimizations, expansions, different load arrangements, safety enhancements and more can be identified and executed.
First, we record and analyze PQ parameters and phenomena in great detail. Simulating different scenarios based on this input and carefully constructed and verified models can reveal potential failures, allowing problems to be preemptively addressed before they manifest themselves. That avoids costly repairs or downtime. All the mentioned parameters can be extracted from the voltage and current waveform. If we run a ten-minute simulation and input all the current waveforms, for example, we can understand how current behavior will impact the voltage waveform (variations) and define a Flicker value. That allows us to design a solution capable of counteracting the disturbances in the current, thus improving flicker.
Benefits of simulation
Simulations are essential to installation reliability and optimization. They allow you to really understand your installation and ensure future additions or specific network conditions will not cause a blackout, for example. Accurately emulating the way in which a system behaves under different load conditions, for example, helps us understand how elements interact in a range of conditions. Based on the outcome, the design of systems and protection measures can be improved. Furthermore, carrying out simulations before modifications or extensions makes it possible to assess exactly how planned changes will affect overall systems. It becomes possible to explore multiple configuration and design options quickly, enhancing efficiency. Simulations also help ensure that electrical installations meet regulatory standards for power quality – non-compliance can lead to penalties or expensive retrofits.
Challenges related to simulation
Electrical systems can be highly complex. Simulating interactions between different loads, equipment, and external factors can be time-consuming, and requires sophisticated, expensive software and expertise. The accuracy with which components and systems are modelled is key. If models are oversimplified or don’t account for relevant real-world variables, results will not accurately reflect and predict system behavior. The quality of simulations also depends on detailed input data from relevant sources. Gathering this can be challenging, especially for installations which are older, poorly documented, and include erroneous connections or feature custom equipment.
Accurately modeling and verifying the dynamics of a system requires precise data to ensure the simulations reflect real-world behavior. Each component must perform as expected, and interpreting the results requires confirming that they make electrical sense. Additionally, the control models for specific components, such as the response time of a battery, must be accurate to achieve reliable simulation outcomes.
Gathering the correct data is a key challenge. You might look up information on a transformer’s nameplate and test report, but some parameters can only be obtained through a Factory Acceptance Test conducted by the manufacturer before purchase. These details are often difficult, if not impossible, to acquire at a later date. However, this information is essential for certain simulations. Traditionally, it was not common to request all the necessary details before buying a component. However, many large companies now recognize the importance of this practice and ensure they obtain all relevant data before making a purchase.
The role of CWR
Continuous Waveform Recording (CWR) captures high-resolution, real-time data on the electrical behavior of a system. As the name implies, data capture is ongoing – not periodic or triggered by events exceeding preset thresholds. Traditional approaches to simulation do not require Continuous Waveform Recording. However, more specialized equipment enables the recording of electrical data at high sampling rates, opening a new horizon for more complex and accurate simulation types.
Data captured with CWR is highly valuable for creating and validating simulation models. Accurate waveform recordings make it possible to compare simulated results with real-world performance, ensuring models reflect the actual conditions of the electrical installation. Using these models, corrective actions to mitigate PQ issues can be determined, such as adjustments in power factor correction equipment or filter installation. Simulations based on CWR data support predictive maintenance by identifying patterns in electrical behavior that indicate potential equipment failures or PQ degradation. When such disturbances or failures occur, CWR provides detailed data on the precise moment and nature of the event, making recreation and exploration of the underlying causes possible. Incorporating real-time CWR makes it possible to update models dynamically and reflect constant change in loads, power generation, and system configurations.
This is vital for systems In which conditions evolve quickly, such as renewable energy installations or highly variable industrial loads. System performance can be optimized by testing different configurations, load management strategies, or equipment upgrades to enhance power quality and efficiency. Over time, CWR provides a historical record of PQ and electrical performance. Such long-term data is valuable for simulations that need to account for trends, such as equipment aging, seasonal load variations, or gradual PQ degradation caused by increased harmonic content or load growth. Long-term waveform data enables simulations to predict future performance and plan upgrades or retrofits accordingly.
CWR offers significant benefits for enhancing simulations, but there are also several challenges. For one thing, CWR generates truly enormous amounts of data. Managing, storing, and analyzing this effectively is a challenge, especially in large-scale installations. Data needs to be carefully interpreted, and possible filtered or condensed, before it can be useful in simulations. Identifying the most critical parameters and extracting actionable insights from waveform recordings requires expertise in PQ analysis as well as simulation modeling. It’s also vital that CWR data integrates smoothly with simulation software, and that results reflect real-world dynamics as precisely as possible.
In short…
Simulations are essential for ensuring optimal PQ in electrical installations, which is crucial for reliable and efficient operation. They help predict system behavior, prevent disturbances, improve energy efficiency, and ensure regulatory compliance. However, challenges related to model accuracy, complexity, and data analysis need to be carefully overcome to make simulations effective. If these are dealt with appropriately, simulations provide substantial benefits, from reducing risks and costs to improving system performance and reliability.
Continuous Waveform Recording plays an essential role in enhancing the accuracy, reliability, and effectiveness of simulations, modeling, and analysis in important ways. By providing ongoing, real-time, high-resolution data electrical parameters, CWR enables more precise modeling and validation, thus helping identify and troubleshoot PQ issues, while supporting predictive maintenance and dynamic adjustments.