Leveraging Simulation & Modeling for Resilient DER Integration

As distributed energy resource (DER) adoption has increased, the proliferation of valuable but disconnected efforts to improve situational awareness has produced a fragmented landscape of tools, models, repositories, and data sets across the public and private sectors. Existing efforts have been too narrowly focused: i.e. only considering power flow, simulating a few points, or monitoring some sensor points. Without a well-integrated approach, grid instability can increase.

In a recent fireside chat at the 2020 virtual North American Smart Energy Week, I sat down with Dr. Robert Broadwater, Chief Technology Officer at Electrical Distribution Design (EDD) Inc to explore how utilities can leverage their expertise in modeling and simulation to accurately predict abnormalities on the grid in high penetration of distributed energy resource (DER) environments.

“Our best approach to managing complexity is modeling”
Combining modeling and simulation with real-time operating data is the basis of a U.S. Department of Energy Solar Energy and Technologies Office project that aims to more effectively flag abnormalities than using pure operational data alone. The three-year project is led by EDD, and also includes utility PEPCO Holdings, and technology/research providers Clean Power Research, Florida State University, SEPA, University of Delaware, Dominion Voltage Inc, and KITU Systems.

The project is focused on a model-based operational analysis & control framework/architecture. By developing a common model that integrates simulation with operational data, the utility can better detect security threats, as well as provide enhanced grid situational awareness and visibility.

Specifically, this project works with a unique type of model for real-time operations, referred to as an integrated system model (ISM). In comparison with traditional modeling solutions, such as transmission or separate distribution models, an ISM is unique in its broad applicability. ISMs can model imbalances in the transmission system and help utility operators balance power fluxuations via controls in smart wires. An ISM contains elements from transmission to distribution down to each customer’s meter in one model. Consequently, ISMs can grow very large and can be technically challenging. For example, Pepco’s ISM has approximately six million nodes. However, modern grid technology and innovative modeling techniques have brought this powerful capability to reality.

Importance of balance
Imagine balancing on a playground seesaw. If someone gets off on one side, the other person topples to the ground. The same concept applies to the grid. If the system isn’t balanced, then generators can trip off line, and the system can collapse leaving customers without power.

Balancing has historically occurred at the transmission level, however growing PV and other DERs at the distribution level can lead to up-wire and up-channel impacts. Put another way, DERs are beginning to exacerbate the correlation and impact between transmission and distribution events.

So how do utilities coordinate this balance? The solution according to Dr. Broadwater, “leverage a model that includes all the details.” This includes transmission system imbalance, every PV system generation, time varying loads, etc. Through an analysis approach, the utility can better account for this complexity.

Obviously this level of modeling requires a lot of effort, so Dr. Broadwater also emphasized the importance of reusing the model across all functions, thereby enabling the functions to work together as a team to solve bigger problems. EDD designed their ISM to integrate with up to 10 existing applications, such as power flow, volt analysis, reliability analysis, load forecasting, etc.

Grid network topology
In an ISM, the model itself manages the topology. It offers the topology to the applications and then all of the applications share the same model. Furthermore, all of the applications share the same measurements and the measurements get attached to the model. As a result, the topology is “constant time.” This means that as the model size grows, if a switch operation occurs or a line fails, it doesn’t take any more time to manage the system.

As Dr. Broadwater explained, this breakthrough is achieved by avoiding matrices. Traditionally, the bigger the model, the slower the software runs. Instead of the power flow algorithm building matrices to solve the problem, EDD uses a graph trace analysis to dynamically implement Kirchhoff Voltage Law and Kirchhoff Current Laws as traces are performed throughout the system.

Dr. Broadwater also detailed their work to integrate with other existing systems in the utility. For example, they interface with AMS, SCADA, 24-hour generation forecasts for every PV in system, and 30-minute PV variability forecasts to control PV inverters.

The net result: utilities can effectively and efficiently run very large models integrated with their existing systems.

Detecting threats through simulation
It’s no surprise that when a system has a lot of connected points, extra emphasis must be placed on mitigating risk from external threat factors. As part of this three year project, EDD is developing a threat simulator in partnership with the University of Delaware and Florida State University. An industry first-of-its-kind, the simulator can intercept measurements going from the emulator to the control or operating systems, and delay/block/change those measurements. It can also intercept control signals.

As part of the training, the team has developed an Abnormality Detector Module, which operates faster than real-time, and uses statistics on expected system behavior. The detector constantly compares load data with SCADA data, and when big differences are detected, the system questions what’s going on. The threat simulator tests the robustness of the abnormality detection algorithms, and injects different threats to make sure they’re detected.

According to Dr. Broadwater, real-time ISM simulation should be the first line of defense in detecting cybersecurity breaches. This model and threat simulator, working in conjunction with operational data, will help better detect and address abnormalities before a situation gets out of control at the feeder level. These investments are key, especially given the proliferation of DERs and smart inverters on the system, to ensure visibility and reliability at the utility.

Looking forward
A successful transition to a carbon-free energy future will require targeted grid investments, new innovative approaches to system management, and partnerships to bring forward the best ideas and tools. This project offers a great example of collaboration between the entire energy ecosystem ecosystem; solution providers, utilities, government, academia and industry organizations.