Flexible operation of grid-connected microgrid using ES

This study presents a new solution to cope with the intermittent nature of renewable generations (RGs) and facilitate the integration of RGs in the smart active distribution network. Electric spring (ES) as one of the most influential solutions in demand-side management is proposed as a flexible res...

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Published inIET generation, transmission & distribution Vol. 14; no. 2; pp. 254 - 264
Main Authors Norouzi, Mohammadali, Aghaei, Jamshid, Pirouzi, Sasan, Niknam, Taher, Lehtonen, Matti
Format Journal Article
LanguageEnglish
Published The Institution of Engineering and Technology 31.01.2020
Subjects
33‐bus IEEE test system
demand‐side management
distributed power generation
distribution networks
electric spring
energy price
ES model
flexible operation
flexible resource
flexi‐renewable microgrid
forecasted load demand
general algebraic modelling system software
grid‐connected microgrid
influential solutions
intermittent nature
load flow
operating cost
optimisation
optimisation problem
renewable generations
Research Article
RGs constraints
RGs output
roulette wheel mechanism
scenario generation process
smart active distribution network
static model
stochastic problem
system flexibility
technical system limitations
static model
energy price
RGs output
distribution networks
smart active distribution network
distributed power generation
33-bus IEEE test system
optimisation problem
optimisation
grid-connected microgrid
ES model
electric spring
flexible operation
forecasted load demand
general algebraic modelling system software
technical system limitations
flexi-renewable microgrid
RGs constraints
system flexibility
renewable generations
flexible resource
scenario generation process
operating cost
influential solutions
stochastic problem
roulette wheel mechanism
load flow
demand-side management
intermittent nature
Online AccessGet full text
ISSN1751-8687
1751-8695
DOI10.1049/iet-gtd.2019.0483

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Abstract This study presents a new solution to cope with the intermittent nature of renewable generations (RGs) and facilitate the integration of RGs in the smart active distribution network. Electric spring (ES) as one of the most influential solutions in demand-side management is proposed as a flexible resource for flexible operation of grid-connected microgrid against other sources of uncertainty such as forecasted load demand and energy price as well as the RGs output. This innovative approach has been considered in the context of a stochastic problem by presenting the static model of ES for the first time. The modelling of uncertainties is done by the roulette wheel mechanism as a scenario generation process and backward method for reducing the number of scenarios. In the proposed optimisation problem, the objective function is minimising the operating cost and voltage deviation as well as maximising system flexibility, subject to the AC power flow, ES and RGs constraints and technical system limitations. Finally, the proposed solution is tested on 33-bus IEEE test system by the general algebraic modelling system software. The case studies demonstrate the efficiency of the proposed ES model in different simulation and experimental cases in providing flexi-renewable microgrid.
AbstractList This study presents a new solution to cope with the intermittent nature of renewable generations (RGs) and facilitate the integration of RGs in the smart active distribution network. Electric spring (ES) as one of the most influential solutions in demand‐side management is proposed as a flexible resource for flexible operation of grid‐connected microgrid against other sources of uncertainty such as forecasted load demand and energy price as well as the RGs output. This innovative approach has been considered in the context of a stochastic problem by presenting the static model of ES for the first time. The modelling of uncertainties is done by the roulette wheel mechanism as a scenario generation process and backward method for reducing the number of scenarios. In the proposed optimisation problem, the objective function is minimising the operating cost and voltage deviation as well as maximising system flexibility, subject to the AC power flow, ES and RGs constraints and technical system limitations. Finally, the proposed solution is tested on 33‐bus IEEE test system by the general algebraic modelling system software. The case studies demonstrate the efficiency of the proposed ES model in different simulation and experimental cases in providing flexi‐renewable microgrid.
Author Lehtonen, Matti
Niknam, Taher
Norouzi, Mohammadali
Aghaei, Jamshid
Pirouzi, Sasan
Author_xml – sequence: 1
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  surname: Norouzi
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  organization: 1Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran
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  givenname: Jamshid
  orcidid: 0000-0002-5254-9148
  surname: Aghaei
  fullname: Aghaei, Jamshid
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  organization: 1Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran
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  givenname: Sasan
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  surname: Niknam
  fullname: Niknam, Taher
  organization: 1Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran
– sequence: 5
  givenname: Matti
  surname: Lehtonen
  fullname: Lehtonen, Matti
  organization: 3Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland
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Issue 2
Keywords static model
energy price
RGs output
distribution networks
smart active distribution network
distributed power generation
33-bus IEEE test system
optimisation problem
optimisation
grid-connected microgrid
ES model
electric spring
flexible operation
forecasted load demand
general algebraic modelling system software
technical system limitations
flexi-renewable microgrid
RGs constraints
system flexibility
renewable generations
flexible resource
scenario generation process
operating cost
influential solutions
stochastic problem
roulette wheel mechanism
load flow
demand-side management
intermittent nature
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Snippet This study presents a new solution to cope with the intermittent nature of renewable generations (RGs) and facilitate the integration of RGs in the smart...
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StartPage 254
SubjectTerms 33‐bus IEEE test system
demand‐side management
distributed power generation
distribution networks
electric spring
energy price
ES model
flexible operation
flexible resource
flexi‐renewable microgrid
forecasted load demand
general algebraic modelling system software
grid‐connected microgrid
influential solutions
intermittent nature
load flow
operating cost
optimisation
optimisation problem
renewable generations
Research Article
RGs constraints
RGs output
roulette wheel mechanism
scenario generation process
smart active distribution network
static model
stochastic problem
system flexibility
technical system limitations
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Title Flexible operation of grid-connected microgrid using ES
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