Beyond DERMS: Platform Development, Flexibility, Prediction, and Value Measurements
Open accessAbstract
This report describes the results from the “Beyond DERMS” project that aims to build, deploy, and demonstrate - at megawatt scale with thousands of devices - a holistic platform that supports the integrated operation and planning of future power distribution networks with bi-directional power flows, many diverse distributed energy resources (DERs), and inverter-based resources. The results demonstrate how emerging ‘internet of energy’ technologies can be leveraged to simultaneously solve the grid problems of today and prepare for the challenges of tomorrow in a way that goes beyond the capabilities of existing distributed energy resource management systems (DERMS).
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Most mentioned studies share a limitation of primarily utilizing a simple three-tier structure of EV, EVA, and DNO, which may lack scalability for integrating and operating large-scale EVs because the absence of an intermediate management layer such as an operational level increases the computational burden on the DNO.
“First, they primarily utilize a simple three-tier structure of EV, EVA, and DNO, which may lack scalability for integrating and operating large-scale EVs, as the absence of an intermediate manage ment layer, such as an operational level, increases the computational burden on the DNO [5].”
From Improving distribution system flexibility using electric vehicles under the distributed energy resource management system framework (2026) · cites this paper as [5]
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredDERMS has emerged as a software solution for managing the growing diversity and complexity of distributed energy resources in modern power distribution systems.
“In this context, the distributed energy resource management system (DERMS) has emerged as a new software solution for managing the growing diversity and complexity of distributed energy resources (DERs) in modern power distribution systems [2 -5].”
From Improving distribution system flexibility using electric vehicles under the distributed energy resource management system framework (2026) · cites this paper as [5]
DERMS integrates diverse stakeholders through a hierarchical framework and supports core capabilities such as translation, aggregation, simplification, and optimization, enabling effective management of large-scale DERs.
“DERMS integrates diverse stakeholders through a hierarchical framework and supports core capabilities such as translation, aggregation, simplification, and optimization, enabling the effective management of large-scale DERs.”
From Improving distribution system flexibility using electric vehicles under the distributed energy resource management system framework (2026) · cites this paper as [5]
Studies [5,12] lack an incentive mechanism.
“and [5,12] lack an incentive mechanism.”
From Improving distribution system flexibility using electric vehicles under the distributed energy resource management system framework (2026) · cites this paper as [5]
Section 8 (pp. 70–72) describes economic analysis tools and customer outreach, while Section 4 (p. 40) places wholesale-market bidding algorithms in future work. Neither passage establishes that this study lacks an incentive mechanism. Searches for incentives, participant rewards, and an incentive mechanism found no decisive passage. (LLM, conf=0.72)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cited by
Sorted by citations
Lee, S., & Jung, J. (2026) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2025.116292 · Cited by 13 · see citing works
- Authors
- Argonne National Laboratory (ANL), A., Singh, R., USDOE Office of Electricity (OE), Reilly Associates, P., Packetized Energy, B., Hines, P., Howerter, S., & Reilly, J.
- Affiliations
- Argonne National Laboratory (US)
- Packetized Energy, Burlington, VT (United States)
- Reilly Associates, Pittston, PA (United States)
- Published
- 2021-10-01
- OpenAlex
- W3205447099
- Cited by
- 3
- References
- 0
- Citations by year
- 2025: 2 · 2023: 1
- Type
- report
- Language
- en
- Open access
- green
- www.osti.gov
- Locations
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- USDOE Office of Electricity (OE)
- DOE (AC02-06CH11357)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid and Power Systems
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Keywords
- distributed energy resource management systems, distributed energy resources, power distribution networks, bidirectional power flow, inverter-based resources, energy internet, grid flexibility, value measurement
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
