Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response

Distributed energy resources can improve the operation of power systems, improving economic and technical efficiency. Aggregation of small size resources, which exist in large number but with low individual capacity, is needed to make these resources’ use more efficient. In the present pap...

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Main Authors: Cátia Silva, Pedro Faria, Zita Vale
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/12/7/1248
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spelling doaj-1002b6b0c3f643ae8ed2c69770b5f99d2020-11-25T00:15:25ZengMDPI AGEnergies1996-10732019-04-01127124810.3390/en12071248en12071248Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand ResponseCátia Silva0Pedro Faria1Zita Vale2GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, IPP-Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, PortugalGECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, IPP-Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, PortugalGECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, IPP-Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, PortugalDistributed energy resources can improve the operation of power systems, improving economic and technical efficiency. Aggregation of small size resources, which exist in large number but with low individual capacity, is needed to make these resources’ use more efficient. In the present paper, a methodology for distributed resources management by an aggregator is proposed, which includes the resources scheduling, aggregation and remuneration. The aggregation, made using a k-means algorithm, is applied to different approaches concerning the definition of tariffs for the period of a week. Different consumer types are remunerated according to time-of-use tariffs existing in Portugal. Resources aggregation and remuneration profiles are obtained for over 20.000 consumers and 500 distributed generation units. The main goal of this paper is to understand how the aggregation phase, or the way that is performed, influences the final remuneration of the resources associated with Virtual Power Player (VPP). In order to fulfill the proposed objective, the authors carried out studies for different time frames (week days, week-end, whole week) and also analyzed the effect of the formation of the remuneration tariff by considering a mix of fixed and indexed tariff. The optimum number of clusters is calculated in order to determine the best number of DR programs to be implemented by the VPP.https://www.mdpi.com/1996-1073/12/7/1248clusteringdemand responsedistributed generationsmart grids
collection DOAJ
language English
format Article
sources DOAJ
author Cátia Silva
Pedro Faria
Zita Vale
spellingShingle Cátia Silva
Pedro Faria
Zita Vale
Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response
Energies
clustering
demand response
distributed generation
smart grids
author_facet Cátia Silva
Pedro Faria
Zita Vale
author_sort Cátia Silva
title Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response
title_short Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response
title_full Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response
title_fullStr Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response
title_full_unstemmed Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response
title_sort multi-period observation clustering for tariff definition in a weekly basis remuneration of demand response
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2019-04-01
description Distributed energy resources can improve the operation of power systems, improving economic and technical efficiency. Aggregation of small size resources, which exist in large number but with low individual capacity, is needed to make these resources’ use more efficient. In the present paper, a methodology for distributed resources management by an aggregator is proposed, which includes the resources scheduling, aggregation and remuneration. The aggregation, made using a k-means algorithm, is applied to different approaches concerning the definition of tariffs for the period of a week. Different consumer types are remunerated according to time-of-use tariffs existing in Portugal. Resources aggregation and remuneration profiles are obtained for over 20.000 consumers and 500 distributed generation units. The main goal of this paper is to understand how the aggregation phase, or the way that is performed, influences the final remuneration of the resources associated with Virtual Power Player (VPP). In order to fulfill the proposed objective, the authors carried out studies for different time frames (week days, week-end, whole week) and also analyzed the effect of the formation of the remuneration tariff by considering a mix of fixed and indexed tariff. The optimum number of clusters is calculated in order to determine the best number of DR programs to be implemented by the VPP.
topic clustering
demand response
distributed generation
smart grids
url https://www.mdpi.com/1996-1073/12/7/1248
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