An increasingly complex set of rules governs utility electric grids, and the financial consequences of failing to comply are rising. Utilities also face a business imperative to maximize grid reliability and operate cost-effectively.
Increasingly, utilities are finding the sweet spot to manage those priorities through better data — and better tools to manage the data.
Network model management (NMM) is a system of creating centralized master network models for transmission and distribution electrical grids. Through better data fidelity and more accurate models, an NMM system can improve:
- Regulatory compliance
- Protective relay settings and coordination between assets
- Grid planning
- Grid operations
However, without advanced grid modeling solutions such as NMM, utilities face the opposite problems. Fines due to failing to comply with grid regulations. Less efficient and effective planning and operations, which drive up costs. Avoidable grid events that negatively impact reliability and resilience, potentially drawing the ire of customers and regulators.
Complying with the complex web of grid regulations
Transmission grids are regulated by the Federal Energy Regulatory Commission (FERC) and must meet standards set by the North American Electric Reliability Corporation (NERC), making compliance a critical priority for utilities. Grid management models impact reliability and fall under NERC and FERC rules. A slew of new rules has made it more necessary than ever for tools like NMM, which enable the data fidelity required for compliance.
Key rules and network model-related requirements
- FERC Order No. 2003 includes provisions for the management of network models to ensure reliable interconnection of new generation facilities.
- FERC Order No. 2222 requires managing network models to integrate DERs effectively.
- FERC Order No. 845 requires more transparent and timely updates to network models.
- FERC Order No. 2023 amplifies the need for managing grid models by requiring improvements in the interconnection process for large and small generators.
- FERC Orders No. 1000 and 1920 require utilities to use accurate and up-to-date network models for regional transmission planning and cost allocation studies.
- NERC MOD-032-1 requires the collection and sharing of data necessary to develop planning models for reliable operation and planning of the bulk electric system.
- NERC MOD-033-1 ensures models used in reliability assessments are validated and accurate, requiring periodic reviews and updates.
These rules create more pressure for utilities to develop and maintain more accurate grid models that can reproduce results or track changes seamlessly. Yet, the current reality for utilities not using NMM is that when FERC or NERC asks for a change in planning or assumptions months or years after the utility submits a filing, they cannot reproduce the modeled results with the requested changes. It’s inefficient and costly, at best, and at worst, can result in compliance failures.
Compliance failures have real financial consequences. In 2018, Duke Energy was fined $10 million for failing to maintain accurate network models, which produced incorrect load forecasts and contributed to a major blackout. In 2019, Entergy was fined $2.5 million for violations related to inaccurate network models that contributed to a significant reliability event. In 2020, PG&E faced fines and intense scrutiny when inaccurate models were found to have contributed to widespread power outages during wildfire prevention efforts.
Changing grid rules can only be managed with higher-fidelity grid models shared across each utility’s application environments. NMM provides this form of modeling using a centralized system, enabling more powerful analytics and more accurate scenario planning. NMM becomes the one true source of accurate data from which utility teams can use individualized tools to comply with regulations and standards.
Centrally managed data means better planning and efficiency
Ensuring accurate data behind network models, tracking changes and recreating model results are essential to run high-quality scenario planning for peak load conditions, DER integration, grid reliability, and more.
On the transmission side, most utilities have an accurate transmission electrical network model. However, it’s a different story when it comes to meaning the model, which negatively impacts planning and efficiency. Different utility groups have different needs for the transmission network model, resulting in different versions built on similar data but diverge as teams optimize what they’re being used for.
When a state public utility commission asks a utility to update a filing that required the input of multiple utility teams — as is often the case with rate filings or integrated resource plan filings — it is difficult for the utility even to know which model they used if they aren’t managing their data with a centralized NMM solution. Inadequate version control means they can’t reproduce the results, and it then becomes costly and time-consuming to make the requested changes.
On the distribution grid side, accurate network electrical models are rare. Yet utilities increasingly need data fidelity to conduct more extensive studies for such purposes as understanding how more DERs will impact the distribution grid and associated impacts to the transmission system and generation needs.
If different utility groups from the protections team to the asset management team to the distribution operation center are all using different versions of a bad electrical model, the utility can face more questions than it has answers. These questions include things as simple as not knowing where solar systems, EVs and battery systems are located on the grid.
Utilities need a way to aggregate their data to build a quality distribution electrical network model, and NMM is an essential tool for this. Once a solid distribution electrical network model is in place, utilities can do more technical evaluations, plan further to the grid’s edge and run the grid closer to the edge.
Looking at the bigger picture, accurate and up-to-date network models help utilities synchronize transmission models with relevant ISOs and do real integrated transmission and distribution planning.
The power of integration
Regulatory compliance, grid reliability, and efficient and cost-effective operations are core motivators for every electric utility. Their success or failure often boils down to the quality of the tools they use to achieve them.
In today’s data-driven business environment, data fidelity and integration are foundational. NMM solutions are an integral piece of the applications puzzle to help utilities:
- Improve the accuracy and speed of data exchange, integrating data from utilities’ GIS, SCADA and AMI systems
- Provide model validation and quality control
- Deliver advanced analytics for efforts such as load balancing or asset optimization
- Ensure modeling tools used by different teams stay in sync with centralized data and a master network model
From those improved capabilities come improved grid and operations planning, reduced manual efforts and errors, improved coordination across departments, real-time system operation support, cost savings and future-proofed systems. Perhaps most importantly, NMM systems help utilities comply with increasingly complex grid rules, thereby avoiding costly fines and reputational damage with regulators and customers.
With its Gridscale X Network Model Manager solution, Siemens partners with utilities to break down the old boundaries of grid planning, development and operation. Learn more about Gridscale X.
Energy Changemakers Content Services prepared this article in partnership with Siemens, an Energy Changemakers member. It is the second article in a two-part series.
- See the first article: Is Siloed Electric Grid Model Management Hurting Your Utility’s Bottom Line?
- Watch the video: What is Utility Network Model Management?
