Next Article in Journal
Rapid Estimation Method for State of Charge of Lithium-Ion Battery Based on Fractional Continual Variable Order Model
Previous Article in Journal
A Novel Nonlinear Combined Forecasting System for Short-Term Load Forecasting
Previous Article in Special Issue
Aggregation Potentials for Buildings—Business Models of Demand Response and Virtual Power Plants
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle
Energies 2018, 11(4), 713;

Reschedule of Distributed Energy Resources by an Aggregator for Market Participation

Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD), Polytechnic Institute of Porto (IPP), Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal
Author to whom correspondence should be addressed.
Received: 18 January 2018 / Revised: 6 March 2018 / Accepted: 20 March 2018 / Published: 22 March 2018
(This article belongs to the Special Issue Distributed Energy Resources Management)
Full-Text   |   PDF [2469 KB, uploaded 3 May 2018]   |  


Demand response aggregators have been developed and implemented all through the world with more seen in Europe and the United States. The participation of aggregators in energy markets improves the access of small-size resources to these, which enables successful business cases for demand-side flexibility. The present paper proposes aggregator’s assessment of the integration of distributed energy resources in energy markets, which provides an optimized reschedule. An aggregation and remuneration model is proposed by using the k-means and group tariff, respectively. The main objective is to identify the available options for the aggregator to define tariff groups for the implementation of demand response. After the first schedule, the distributed energy resources are aggregated into a given number of groups. For each of the new groups, a new tariff is computed and the resources are again scheduled according to the new group tariff. In this way, the impact of implementing the new tariffs is analyzed in order to support a more sustained decision to be taken by the aggregator. A 180-bus network in the case study accommodates 90 consumers, 116 distributed generators, and one supplier. View Full-Text
Keywords: aggregator; clustering; demand response; distributed generation aggregator; clustering; demand response; distributed generation

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Faria, P.; Spínola, J.; Vale, Z. Reschedule of Distributed Energy Resources by an Aggregator for Market Participation. Energies 2018, 11, 713.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top