A Software-Based Solution to Increase DER Hosting Capacity

Written by Heng Chen and Ryan Burg

In response to accelerating rates of DER adoption, electric utilities are demonstrating advanced technologies to maintain system reliability without overloading grid assets or exceeding voltage limits. To that end, Utilities can avail themselves of a wide range of approaches such as traditional system upgrades, grid hardening, energy storage, and analytical software solutions. While traditional investments are the tried-and-true option for system reliability and capacity, alternative approaches have the potential to support alternative use cases in new ways.

Software approaches to the management of distributed energy resources (DERs) are a potentially compelling option to support the integration of distributed renewables. ComEd, the distribution utility serving 4 million customers in northern Illinois, including the city of Chicago, has commissioned a demonstration project entitled “distributed energy resource management system” (DERMS) to manage output from newly installed renewable generators at a site in the Western region of ComEd’s territory. The first demonstration of this system went live in April of 2021.

The traditional solution to limited renewable hosting capacity could involve an upgrade of additional power lines and a new substation transformer. Deploying instead a DERMS solution, has the potential to reduce up-front costs, helping make additional renewable energy projects viable to support stakeholder goals of reducing carbon emissions from the energy sector.

An analytical software solution also seeks to demonstrate new capabilities like increasing reliability, operational efficiency, and system utilization while maintaining power quality within prescribed limits for distribution circuits. On the long-term innovation roadmap, DERMS may become a module in a future advanced distribution management system (ADMS) that can provide even higher levels of service, including improved reliability and resiliency.

In the area where this technology is being demonstrated, there is already significant adoption of large-scale wind generation and growing interest for the deployment of additional renewable generators. This DERMS implementation will monitor inputs such as substation transformer loading, DER output, and system conditions. A control algorithm relies on these inputs to determine when output needs to be managed before substation transformers can become overloaded during reverse power flow conditions.

The algorithm that uses priority-based optimal power flow to manage the output of the renewable DER. The methodology considers distribution asset capacity limits, DER generation limits, and power flow constraints to evaluate the objective function and minimize system loss. Though this methodology is computationally intensive, it also provides accurate results to reduce the need to manage production and therefore provide higher level of service.

After initially developing this methodology and algorithm, ComEd tested it in a near-real world environment at its Grid Integration and Technology Lab. Using Real-Time Digital Simulator (RTDS) capabilities and Control Hardware-in-the-loop (CHIL) testing, ComEd considered the efficacy of the technology in a wide range of conditions. Across over forty scenarios, including different network topologies, and varying solar, wind and load profiles, the CHIL testbed confirmed connectivity, communications, and DER management functionality to better understand and assess the accuracy and performance of the DERMS solution. The field demonstration that began in April 2021 is the next step in confirming the effectiveness, efficiency, and reliability of this solution.

The DER management strategy relies upon rolling average observations. Priority rules are implemented by assigning contribution factors and gains to each priority group. This process allows us to issue management setpoints; and when the rolling average falls below target, management constraints can begin to be released. In addition to the active management process, historical system data is used to support Measurement and Verification (M&V) efforts, to benchmark system performance, and to fine-tune system parameter configurations. M&V efforts are ongoing and ComEd expects to have some initial results from the demonstration project in 2022.

To maximize the efficiency of the data being collected for the DERMS, ComEd is deploying advanced sensors. The locations of these sensors are a key aspect of the effectiveness of their deployment. To determine the optimal location for distribution phasor measurement units (PMUs), ComEd developed and tested a methodology that considered different topological scenarios, as well as physical limitations of installations while maximizing the observability of the DERMS footprint. This capability will support the eventual deployment of real-time fast control of DERs which could increase the hosting capacity of the grid still further.

Demonstrating capabilities like these requires advanced communications infrastructure, reliable measurement equipment, responsive energy supply, and sufficient computational power to manage the optimization scheme used to determine grid needs. Analytical computing solutions like DERMS require not just sensors to collect the data, but the infrastructure to relay it back and analyze it in a timely fashion. If the demonstration of this system is successful, a wider deployment has the potential to increase DER hosting capacity and provide higher levels of resiliency and sustainability to the communities that rely upon it. Using advanced technology solutions to manage power output from DERs within the limits of grid equipment capacity presents important opportunities for facilitating higher DER integration into the existing grid and meeting stakeholder goals.

References

  1. Himanshu Jain, Gab-Su Seo, Eric Lockhart, Vahan Gevorgian, and Benjamin Kroposki, "Blackstart of Power Grids with Inverter-Based Resources", presented at the IEEE Power and Energy Society General Meeting, 2020.
  2. Benjamin Kroposki, Brian Johnson, Yingchen Zhang, Vahan Gevorgian, Paul Denholm, Bri-Mathias Hodge, Bryan Hannegan, "Achieving a 100% Renewable Grid", IEEE Power & Energy Magazine, March/April 2017.
  3. https://www.energy-storage.news/news/roundup-first-ever-blackstart-battery-li-ion-for-haiti-and-solarmax-goes-st
  4. https://www.energy-storage.news/news/california-batterys-black-start-capability-hailed-as-major-accomplishment-i
  5. "ScottishPower in 'pioneering world first' after wind farm black-out boost". www.scotsman.com. Reid, Scott, 3 November 2020.
  6. National Grid ESO, "Black Start from Non‐Traditional Generation Technologies: Technology Capability and Readiness for Distributed Restoration", June 2019.

 

This article edited by Geev Mokryani

For a downloadable copy of the May 2021 eNewsletter which includes this article, please visit the IEEE Smart Grid Resource Center.

Heng Chen
Heng (Kevin) Chen is the Manager, Grid Strategy & Analytics in Smart Grid and Emerging Technology Department at ComEd. He is the technical lead in several emerging technology projects such as DOE SHINES project, microgrid monitoring and control,  Distributed Energy Resource Management System (DERMS) pilot, Distribution Linear State Estimator, and data analytics & applications projects. Prior to ComEd, he led many projects including synchrophasor analytic platform development and deployment at multiple ISOs and utilities. He is a licensed Professional Engineer, and a senior member of IEEE.

Ryan Burg Headshot
Ryan Burg is a Principal Business Analyst on the smart grid programs team at Commonwealth Edison where he manages academic partnerships on air quality, quantum computing, and climate change resilience. Ryan also supports programs to anticipate the effects of beneficial electrification and EV adoption and to improve the performance of grid-edge technologies. He holds a Ph.D. from the Wharton School of Business and, prior to joining ComEd, taught sustainable management and ethics at Bucknell, HSE, Georgetown, and Wharton. His first book was published by Cambridge University Press in 2017.

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