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Grid Enhancing Technologies

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Shailesh Jain's picture
Shailesh Jain 668
Lead Consultant / Operations Manager Pike Engineering

"Modern Power Systems And Big Data : Let the Grids Learn for Themselves"“I lead a new team focused on Emerging Technologies such as Battery Energy Storage, Distributed Energy Resources, System...

  • Member since 2018
  • 16 items added with 11,723 views
  • Feb 26, 2021
  • 996 views

Report by Brattle:

Link to report:  https://watt-transmission.org/wp-content/uploads/2021/02/Brattle__Unlock...

Goal: Analyze how much additional renewables can be added to the grid using Grid-Enhancing Technologies (GETs):

GETs enhance transmission operations and planning.

GETs complement building new transmission—they can bridge the timing gap until permanent expansion solutions can be put in place.

While there are various types of GETs, this study focuses on the combined impact of the following three technologies: –

*Advanced Power Flow Control: Injects voltage in series with a facility to increase or decrease effective reactance, thereby pushing power off overloaded facilities or pulling power on to under-utilized facilities.

*Dynamic Line Ratings (DLR): Adjusts thermal ratings based on actual weather conditions including, at a minimum, ambient temperature and wind, in conjunction with real-time monitoring of resulting line behavior. –

*Topology Optimization: Automatically finds reconfiguration to re-route flow around congested or overloaded facilities while meeting reliability criteria.

Goal: Analyze how much additional renewables can be added to the grid using Grid-Enhancing Technologies (GETs):  Use the Southwest Power Pool (SPP) grid (focused on Kansas and Oklahoma, looking at 2025) as an illustrative case study. – SPP Generation Interconnection Queue* (GI Queue) shows ~9 GW of renewable resources with an Interconnection Agreement (IA) executed in Kansas and Oklahoma. – SPP Integrated Transmission Planning (ITP) Reports** show high congestion.  Results metrics for the combined (not for individual) three GETs include: – Renewables added (capacity [GW] and energy [GWh]). – Economic benefits (production costs, investments, jobs, etc.) – Carbon emissions reduction

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Thank Shailesh for the Post!
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Matt Chester's picture
Matt Chester on Feb 26, 2021

Thanks for sharing, Shailesh-- was there any single big breakthrough takeaway from this report that you think is worth pocketing, a new idea or suggestion we haven't seen elsewhere yet? 

Shailesh Jain's picture
Shailesh Jain on Feb 26, 2021

Thanks y Matt,

I think the breakthrough take away is (Study Results - 1/5)

GETs enable more than twice the amount of additional new renewables to be integrated.

Roger Arnold's picture
Roger Arnold on Feb 27, 2021

I second Matt's thanks for the post, Shailesh. It's great to see a study that quantifies gains available from affordable, commonsense measures to enhance grid performance. I do have some technical comments, however.

I notice that the study doesn't address the intelligent use of battery storage as a GET. There are two dimensions for dealing with the problems of variability that wind and solar resources present: space and time. Transmission averages supply and load variations over space; storage averages them over time. Control for either can be optimized separately for cost-performance. The study you report here appears to have focused exclusively on the spatial aspects of transmission. Many studies of battery storage focus exclusively on the time aspects. But the global cost-performance optimum almost certainly is to be found in co-optimization of the two.

As a concrete example, congestion on a particular transmission link can be relieved by making use of the power flow control measures you mention to redirect flow around the congested link. But it can also be relieved by directing a portion of the power flow at the upstream end of the link into storage, and withdrawing power from storage at the downstream end. Optimal control would take account of the location and state of storage points on the grid, along with all the other information on current and projected supply and load.

It's a complex problem -- optimized use of real-world systems nearly always is. But that's what modern computers are good for.

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