Distributed Energy Resources Scheduling and Aggregation in the Context of Demand Response Programs
Open accessAbstract
Distributed energy resources can contribute to an improved operation of power systems, improving economic and technical efficiency. However, aggregation of resources is needed to make these resources profitable. The present paper proposes a methodology for distributed resources management by a Virtual Power Player (VPP), addressing the resources scheduling, aggregation and remuneration based on the aggregation made. The aggregation is made using K-means algorithm. The innovative aspect motivating the present paper relies on the remuneration definition considering multiple scenarios of operation, by performing a multi-observation clustering. Resources aggregation and remuneration profiles are obtained for 2592 operation scenarios, considering 548 distributed generators, 20,310 consumers, and 10 suppliers.
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Most aggregator studies focus on large-scale or regional grid services, with less attention paid to localized overloads at individual transformers.
“First, most aggregator studies focus on large-scale or regional grid services, with less attention paid to localized overloads at individual transformers [9][10][11].”
From A Multi-Agent, Laxity-Based Aggregation Strategy for Cost-Effective Electric Vehicle Charging and Local Transformer Overload Prevention (2025) · cites this paper as [10]
The Introduction (p. 2) describes aggregator management at the distribution-network level, and the Conclusions discuss a different gap in prior work: how resources are grouped and remunerated. Neither passage says that most aggregator studies focus on large-scale or regional services rather than individual-transformer overloads. Searches for transformer overload and local congestion found no passage addressing that comparison. (LLM, conf=0.76)
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References 28 · Cited by 27
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- CrossRef · DOI
- Authors
- Faria, P., Spínola, J., & Vale, Z.
- Affiliations
- Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento (PT)
- Universidade Técnica do Porto (PT)
- Corresponding author
- Faria, Pedro
- Venue
- Energies
- Publisher
- MDPI AG
- Published
- 2018-07-31
- Volume
- 11
- Issue
- 8
- Pages
- 1987
- ISSN
- 1996-1073 (ISSN-L)
- OpenAlex
- W2886892933
- Cited by
- 27
- References
- 28
- Citations by year
- 2025: 7 · 2024: 2 · 2023: 1 · 2022: 3 · 2021: 4 · 2020: 3 · 2019: 6 · 2018: 1
- FWCI
- 1.34
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Energies (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by-sa)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, cc-by-nc-nd)
- Funders
- Fundação para a Ciência e a Tecnologia (UID/EEA/00760/2013)
- European Regional Development Fund (SIMOCE)
- H2020 Marie Skłodowska-Curie Actions (DREAM-GO)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Integrated Energy Systems Optimization
- Keywords
- distributed energy resources, demand response, virtual power plants, resource aggregation, K-means clustering, resource scheduling, distributed generators, operation scenarios, power system operation
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