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Writer's pictureTony Sleva, President

Climate Change and Security Risks Necessitate Updates to Power System Models

Updated: Sep 14, 2023

Last week, I shared my experience at the FERC and NERC joint technical conference on power system physical security. Because I was unable to share my feedback on improving grid security with officials at the conference, I will be sharing it through this new series.


Current models of the electric power grid are insufficient for a modern grid that relies heavily on renewable energy sources amidst a changing climate. The models that electric utilities and regional transmission organizations (RTOs) utilize to evaluate the robustness of the electric energy grid need to be updated to include next generation variables, such as increased air conditioning usage, expanded distributed renewable energy sources, anticipated electric vehicle charging stations, and more.


Though not traditionally considered a physical security risk, climate change is a risk to the resilience of the power grid. By updating models to include next generation variables, electric utilities and RTOs will be better prepared to face new climate change-related challenges and threats to physical security, which could occur simultaneously.


Let’s take a closer look.


Today’s Models Lack Key Data


Electric utilities and RTOs have developed very good computer-based models of transmission lines, substations, and components inside substations. They have decent models of distribution lines, resistive loads, and fan and pump motors. They have mediocre models of distributed energy sources and customer loads that have been introduced in the last 50 years.


Traditional transmission system models are used to estimate energy transfer from large, remote generating stations to neighborhood substations. Loads at neighborhood substations are represented as constant resistance or constant power. Other traditional power system models have been developed for individual distribution lines and for single neighborhood substations. Traditional models are fairly accurate during steady state conditions.


However, these models do not account for air conditioning usage, which is already increasing due to widespread heat waves. They do not consider distributed renewable energy sources, which are expanding each year, or anticipated electric vehicle charging stations, which will need to be as common as gas stations within the next decade or so.


Climate Change Increases Air Conditioning Usage


Climate change is increasing the frequency of heat waves across the globe, including the soaring temperatures in the northern hemisphere during June and July of 2023. When temperatures reach 90°F and higher, approximately 50% of connected load in the United States is due to air conditioning usage. This value is determined by comparing April load with August load, considering that the primary change in electricity usage during August is air conditioners. In some areas, as much as 70% of connected load is due to increased air conditioning usage during peak summer load conditions.


Most air conditioners operate continuously when temperatures exceed 90°F, especially when consumers expect their homes to be in a comfortable range of 70°-76°F. In this regard, air conditioning usage includes both traditional air conditioners and heat pumps.


It is known that a fault on the line during a period of increased air conditioning usage can lead to Fault Induced Delayed Voltage Recovery (FIDVR) conditions, or the cascaded stalling of induction motors, which can result in a statewide blackout. Though rare, the impacts of a statewide blackout could be devasting.


By modeling increased air conditioning usage, electric utilities and RTOs could simulate FIDVR conditions to preemptively determine solutions that would prevent a wide area blackout. Unfortunately, in an industry operating with innovation assassins, models typically exclude FIDVR analysis, and it remains an unresolved concern.


Winter Load and Electric Vehicle Charging


Winter energy consumption is also impacted by climate change, as winter storms are increasing in frequency and severity. As more homes convert to all-electric heating, about 50% of winter load will be space heating, heat pumps, and supplemental resistive heaters when temperatures are very low. These predictions need to be included in power system models.


In addition, electric vehicle charging will occur during winter peak load periods. A large amount of electric vehicle battery chargers will operate overnight, when solar panels are not producing; this adds demand to the grid when renewable energy supply is limited.


Update System Models to Include Distributed Renewables


As distributed renewable energy sources expand and replace some large generating stations, traditional system models will need to be updated. Modeling rooftop solar panels, large solar arrays on parking structures and community buildings, offshore wind farms, etc., adds a challenging but necessary layer to traditional models. Incorporating distribution system loads and distributed energy sources into regional models is even more of a challenge.


Regional models must also include environmental conditions that may impact renewable energy production, such as wildfire smoke that may limit the production capacity of solar panels.


Include Next Generation Variables in Updated Models


Electric utilities and RTOs would be wise to update all their models: distribution system models, transmission system models, and regional models. Each level of system will be impacted by the next generation variables of increased air conditioning usage, expanded renewable energy sources, and increased electric vehicle charging, especially during times of decreased renewable energy production. Therefore, each system model must be updated to reflect the impacts of these next generation variables.


I’ll continue to share my thoughts on updates to power system models in the coming weeks. Want to learn more about the next generation electric energy grid? Check out Prescient's blog and contact us with questions.

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