<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></abstract>

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.

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

Environmental and Climate Technologies

This work is licensed under the Creative Commons Attribution 4.0 International License.

The present study sought to address the scheduling of the grid-connected hybrid energy resources under uncertainty of renewable sources, and load in the...

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

Data publikacji: 15 paź 2020

Zakres stron: 580 - 603

DOI: https://doi.org/10.2478/rtuect-2020-0036

Słowa kluczowe
Day ahead real time pricing (RTP), demand response programs (DRP), Power management algorithm, two decision-making layers

© 2020 Abozar Hashemi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Data publikacji: 15 paź 2020

Zakres stron: 580 - 603

DOI: https://doi.org/10.2478/rtuect-2020-0036

Słowa kluczoweDay ahead real time pricing (RTP), demand response programs (DRP), Power management algorithm, two decision-making layers

© 2020 Abozar Hashemi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Day ahead real time pricing (RTP), demand response programs (DRP), Power management algorithm, two decision-making layers