Systematic Categorization of Optimization Strategies for Virtual Power Plants

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

2 Scopus Citations
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Author(s)

  • Amit Kumer Podder
  • Sayemul Islam
  • Aneesh A. Chand
  • Pulivarthi Nageswara Rao
  • Kushal A. Prasad
  • T. Logeswaran
  • Kabir A. Mamun

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number6251
Journal / PublicationEnergies
Volume13
Issue number23
Online published27 Nov 2020
Publication statusPublished - Dec 2020

Link(s)

Abstract

Due to the rapid growth in power consumption of domestic and industrial appliances, distributed energy generation units face difficulties in supplying power efficiently. The integration of distributed energy resources (DERs) and energy storage systems (ESSs) provides a solution to these problems using appropriate management schemes to achieve optimal operation. Furthermore, to lessen the uncertainties of distributed energy management systems, a decentralized energy management system named virtual power plant (VPP) plays a significant role. This paper presents a comprehensive review of 65 existing different VPP optimization models, techniques, and algorithms based on their system configuration, parameters, and control schemes. Moreover, the paper categorizes the discussed optimization techniques into seven different types, namely conventional technique, offering model, intelligent technique, price-based unit commitment (PBUC) model, optimal bidding, stochastic technique, and linear programming, to underline the commercial and technical efficacy of VPP at day-ahead scheduling at the electricity market. The uncertainties of market prices, load demand, and power distribution in the VPP system are mentioned and analyzed to maximize the system profits with minimum cost. The outcome of the systematic categorization is believed to be a base for future endeavors in the field of VPP development. 

Research Area(s)

  • virtual power plants, digital electricity, optimization strategies, distributed energy resources, renewable energy resources, energy management, energy scheduling, distributed generation, real-time energy markets, electricity market, demand response, optimization in virtual power plants, price-based unit commitment model, intelligent technique in power management, day-ahead scheduling

Citation Format(s)

Systematic Categorization of Optimization Strategies for Virtual Power Plants. / Podder, Amit Kumer; Islam, Sayemul; Kumar, Nallapaneni Manoj; Chand, Aneesh A.; Rao, Pulivarthi Nageswara; Prasad, Kushal A.; Logeswaran, T.; Mamun, Kabir A.

In: Energies, Vol. 13, No. 23, 6251, 12.2020.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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