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When Data meets Algorithm: Cornerstones for a DERMS system

Stephen Callahan's picture
EVP GridBright

Stephen J. Callahan is Executive Vice President for Grid Modernization and Chief Marketing Officer at GridBright, Inc (https://gridbright.com/). Over his 35 plus year career in industry...

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The Data

It is hard to read an article these days that does not 1) highlight, 2) underline, 3) put into bold, and then 4) italicize that well-curated data is needed to develop the systems required to integrate into the grid the coming title wave of grid connect devices. This is the mission of the non-profit BetterGrids.org’s open Repository.

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The GRID DATA Repository is a free electronic library of publicly available grid models established by the US Department of Energy (DOE) Advanced Research Project Agency-Energy (ARPA-E).  It allows anyone to find public grid models, publish their innovations, and collaborate with researchers worldwide to support grid optimization and modernization. 

The Repository pulls together grid models and related test data from across the utility industry to improve community access. It provides an open public forum for collecting and sharing data from new grid research, including all the grid models created under the ARPA-E GRID DATA program. This program generates non-confidential and realistic test data for new distribution and transmission algorithms and grid models. The Repository created as part of the ARPA-E GRID DATA program is available for the public to submit new grid models or search for a growing volume of grid models provided by other model contributors. The latest extensions allow researchers to share their open-source software for grid analytics, along with test datasets.  The BetterGrids Foundation, a nonprofit organization, supports the Repository in a self-funding and self-governing manner through volunteers. Contributors from more than 45 countries currently use the Repository.  Visit www.bettergrids.org/ for more information or to access the Repository. 

The Algorithm(s)

To create the future grid, data is necessary, but without an algorithm(s), insufficient.  Addressing the gap, the BetterGrids repository is now supporting the collection and sharing of grid algorithms.  The inaugural set is the outcome of the ENERGISE project at UC Riverside to integrate a DER Management System.[1]

Four specific algorithms were created and are now available in the BetterGrids repository.

  1. Phase Identification (PI) Algorithm - The primary value that PI provides to the utility is the opportunity to “audit” the distribution network by comparing the outputs of the PI algorithm to the manual records kept by the system operators. Once the utility has an accurate picture of the phasing and associated loads per phase, the operator then has the knowledge needed to make decisions with the assurance that actions taken in the field will produce the intended results. A secondary benefit to the PI algorithm is that with accurate data in regards to phase identification is that the data set of correct phasing can then be fed into other algorithms such as the DSSE algorithm, which will then produce a reliable state estimation in conjunction with the outputs of the PI algorithm being fed into the distribution systems state estimation (DSSE) application.
  2. Resource Forecasting (RF) Algorithm - The RF algorithm helps the utility to have a more accurate ‘net load’ forecast at load transformers and the feeder.  Accordingly, the output of the RF algorithm can ultimately benefit other optimization algorithms that make use of day-ahead (or multiple hour-ahead) net load forecast. The output of the RF algorithm can potentially be used in other algorithms such as VWC.
  3. Distribution System State Estimation (DSSE) Algorithm - As the primary benefit, the output of the DSSE algorithm can be used by the utility customer to monitor whether and when the nodal voltage or line thermal constraints are violated. Accordingly, the overall operation status of the distribution network is monitored, indicating normal, emergency, and critical conditions.
  4. Voltage/Watt Control Optimization (VWC) Algorithm - The VWC algorithms in this ENERGISE project are intended for inverter-based DERs, such as PV units. They are a non-wire solution that can help defer the upgrade cost for utility equipment such as voltage regulators and tap-changing load transformers. If the inverter supports per-phase control, then the VWC algorithm can also help with phase balancing.

 

Data and Algorithms for DERMS

Distributed Energy Resource Management Systems (DERMS) is a relatively new breed of industry solutions.  As with any immature solutions market, the actual definition of “DERMS” is subject to evolving interpretation. Many entrants from many different directions try to claim the space and carve out a niche.

In research funded by CEATI in 2016, a “DER Operational Maturity Model” framework for integration of DER into distribution utilities, transmission utilities, and ISOs was created. This work concluded that the industry largely accepts the emerging role of DERMS as a distinct solution category to help operate Distributed Energy Resources (DERs) in concert with the functions in other grid management applications like Advanced Distribution Management Systems (ADMS) and Demand Response Management Systems (DRMS) to produce more efficient and reliable outcomes.  A DERMS is typically necessary before reaching Maturity Level 3 (the ‘Integrating’ phase) but can also be necessary earlier to fulfill Level 2 (the ‘Enabling’ phase). The driving factor is usually the pace (and type) of DER growth in the region coupled with the robustness of the utility’s existing network infrastructure to host higher DER penetration rates.  This results in different deployment timing and approach roadmaps taken by different utilities and the specific DERMS features necessary to support that approach.  Thus, we now see a wide degree of functionality variation among DERMS vendors to serve these divergent needs, even though they all consider themselves ‘DERMS.’

The above definition of DERMS is consistent with the solution developed as part of ENERGISE. In particular: the solution is distributed control system that monitors and controls DERs and the overall power distribution to improve power quality and enable increased capacity for additional DERs to be connected. The developed platform and the monitoring and control algorithms are an active network management approach that optimizes the feeder and the DERs connected to the feeder. This optimization is necessary for a utility to achieve level 4 of the DER Operational Matured Model.  

Market analysis has identified three predominant variations of DERMS solutions –

  1. Enterprise DRMS ‘Evolutions’ – Products that evolved out of ‘Demand Response Management Systems’ (DRMS) enterprise software to handle new DER asset types, capabilities, and grid services products. 
  2. Enterprise ADMS ‘Extensions’ – Products that extend ‘Advanced Distribution Management Systems’ (ADMS) enterprise software to handle modeling, forecasting, telemetry, and control of DER assets similarly to more traditional load or network resources. 
  3. Standalone DERMS Solutions – Mostly start-ups and innovative products that merge selected DRMS and ADMS functionality into a completely new hybrid solution focused specifically on DER operations.   

The ‘Enterprise’ class DERMS solution types are typically deployed within the Information Technology (IT) or Operations Technology (OT) environment of a utility central control room.  The ‘Standalone’ DERMS solutions may be deployed centrally or in a more distributed fashion closer to the grid edge, though many have multi-layered architectures with central, cloud-based, and grid-edge components.

Expanding the availability of critical grid algorithms for animating the grid of the future amplifies the value of the grid data models in the BetterGrids repository. It enables the creation of impactful systems to meet the goals of a clean and resilient grid.


[1] https://www.energy.gov/sites/prod/files/2019/08/f65/2.3.d.%20-%20SETO%20...

 

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