Optimal Scheduling of Residential Electricity Demand Based on the Power Management of Hybrid Energy Resources

The present study sought to address the scheduling of the grid-connected hybrid energy resources under uncertainty of renewable sources, and load in the residential sector. After introducing hybrid resources, scheduling model was implemented through a power management algorithm in an attempt to opti...

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Main Authors: Hashemi Abozar, Derakshan Ghasem, Alizadeh Pahlavani M. R., Abdi Babak
Format: Article
Language:English
Published: Sciendo 2020-01-01
Series:Environmental and Climate Technologies
Subjects:
Online Access:https://doi.org/10.2478/rtuect-2020-0036
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spelling doaj-8aa7b5e0cb64491aa608598aff4b645f2021-09-05T14:01:33ZengSciendoEnvironmental and Climate Technologies2255-88372020-01-0124158060310.2478/rtuect-2020-0036rtuect-2020-0036Optimal Scheduling of Residential Electricity Demand Based on the Power Management of Hybrid Energy ResourcesHashemi Abozar0Derakshan Ghasem1Alizadeh Pahlavani M. R.2Abdi Babak3Department of Electrical Engineering, Damavand Branch, Islamic Azad University, Damavand, IranDepartment of Electrical Engineering, Damavand Branch, Islamic Azad University, Damavand, IranDepartment of Electrical Engineering, Malek Ashtar University, Tehran, IranDepartment of Electrical Engineering, Damavand Branch, Islamic Azad University, Damavand, IranThe present study sought to address the scheduling of the grid-connected hybrid energy resources under uncertainty of renewable sources, and load in the residential sector. After introducing hybrid resources, scheduling model was implemented through a power management algorithm in an attempt to optimize resource cost, emissions, and energy not supplied (ENS). The stated problem consists of two decision-making layers with different weight coefficients based on the prioritization of each objective function. The proposed algorithm is selected for energy optimal management based on technical constraints of the dispatchable and non-dispatchable resources, uncertainty parameters and day ahead real time pricing (RTP). Furthermore, the impact of demand response programs (DRP) on the given algorithm was investigated using load shedding and load shifting techniques. Finally, the results obtained led to the optimization of the functions in all decision-making layers with different modes of operation.https://doi.org/10.2478/rtuect-2020-0036day ahead real time pricing (rtp)demand response programs (drp)power management algorithmtwo decision-making layers
collection DOAJ
language English
format Article
sources DOAJ
author Hashemi Abozar
Derakshan Ghasem
Alizadeh Pahlavani M. R.
Abdi Babak
spellingShingle Hashemi Abozar
Derakshan Ghasem
Alizadeh Pahlavani M. R.
Abdi Babak
Optimal Scheduling of Residential Electricity Demand Based on the Power Management of Hybrid Energy Resources
Environmental and Climate Technologies
day ahead real time pricing (rtp)
demand response programs (drp)
power management algorithm
two decision-making layers
author_facet Hashemi Abozar
Derakshan Ghasem
Alizadeh Pahlavani M. R.
Abdi Babak
author_sort Hashemi Abozar
title Optimal Scheduling of Residential Electricity Demand Based on the Power Management of Hybrid Energy Resources
title_short Optimal Scheduling of Residential Electricity Demand Based on the Power Management of Hybrid Energy Resources
title_full Optimal Scheduling of Residential Electricity Demand Based on the Power Management of Hybrid Energy Resources
title_fullStr Optimal Scheduling of Residential Electricity Demand Based on the Power Management of Hybrid Energy Resources
title_full_unstemmed Optimal Scheduling of Residential Electricity Demand Based on the Power Management of Hybrid Energy Resources
title_sort optimal scheduling of residential electricity demand based on the power management of hybrid energy resources
publisher Sciendo
series Environmental and Climate Technologies
issn 2255-8837
publishDate 2020-01-01
description The present study sought to address the scheduling of the grid-connected hybrid energy resources under uncertainty of renewable sources, and load in the residential sector. After introducing hybrid resources, scheduling model was implemented through a power management algorithm in an attempt to optimize resource cost, emissions, and energy not supplied (ENS). The stated problem consists of two decision-making layers with different weight coefficients based on the prioritization of each objective function. The proposed algorithm is selected for energy optimal management based on technical constraints of the dispatchable and non-dispatchable resources, uncertainty parameters and day ahead real time pricing (RTP). Furthermore, the impact of demand response programs (DRP) on the given algorithm was investigated using load shedding and load shifting techniques. Finally, the results obtained led to the optimization of the functions in all decision-making layers with different modes of operation.
topic day ahead real time pricing (rtp)
demand response programs (drp)
power management algorithm
two decision-making layers
url https://doi.org/10.2478/rtuect-2020-0036
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