Differential Evolution with Stochastic Selection for Uncertain Environments: A Smart Grid Application

Vikas Palakonda; Noor H. Awad; Rammohan Mallipeddi; Mostafa Z. Ali; K. C. Veluvolu; P. N. Suganthan

doi:10.1109/CEC.2018.8477809

Differential Evolution with Stochastic Selection for Uncertain Environments: A Smart Grid Application

Vikas Palakonda
, Noor H. Awad
, Rammohan Mallipeddi
, Mostafa Z. Ali
, K. C. Veluvolu
, P. N. Suganthan

School of Electronics Engineering

Kyungpook National University
Nanyang Technological University
Jordan University of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

14 Scopus citations

Abstract

In smart grid, energy resource management is highly complex large-scale optimization problem where the aim is to maximize the incomes while minimizing operational costs. Due to presence of mixed-integer variables and non-linear constraints, recently the use of evolutionary algorithms as a tool to find optimal and near-optimal solutions is becoming popular. The energy resource management problem further gets complicated if the uncertainty associated with the renewable generation, load forecast errors, electric vehicles scheduling and market prices are considered. Therefore, in a real-world scenario, it is essential to address the issues brought by the variability of demand, renewable energy, electric vehicles, and market price variations while maximizing the incomes and minimizing the total operation costs. In this paper, we analyze the performance of Differential Evolution with a stochastic selection on a large-scale energy resource management problem with uncertainty designed for competition at CEC 2018. The system comprises of a 25-bus microgrid representing a residential area with high penetration of Distributed Energy Resources (DER), Electric Vehicles (EVs), Demand Response (DR) programs etc.

Original language	English
Title of host publication	2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509060177
DOIs	https://doi.org/10.1109/CEC.2018.8477809
State	Published - 28 Sep 2018
Event	2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Rio de Janeiro, Brazil Duration: 8 Jul 2018 → 13 Jul 2018

Publication series

Name	2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings

Conference

Conference	2018 IEEE Congress on Evolutionary Computation, CEC 2018
Country/Territory	Brazil
City	Rio de Janeiro
Period	8/07/18 → 13/07/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Differential Evolution
Energy Resource Management
Smart Grid
Stochastic Selection

Access to Document

10.1109/CEC.2018.8477809

Cite this

Palakonda, V., Awad, N. H., Mallipeddi, R., Ali, M. Z., Veluvolu, K. C., & Suganthan, P. N. (2018). Differential Evolution with Stochastic Selection for Uncertain Environments: A Smart Grid Application. In 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings Article 8477809 (2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2018.8477809

Palakonda, Vikas ; Awad, Noor H. ; Mallipeddi, Rammohan et al. / Differential Evolution with Stochastic Selection for Uncertain Environments : A Smart Grid Application. 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. (2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings).

@inproceedings{1c5502f8a1384123a61f27be9eefb38b,

title = "Differential Evolution with Stochastic Selection for Uncertain Environments: A Smart Grid Application",

abstract = "In smart grid, energy resource management is highly complex large-scale optimization problem where the aim is to maximize the incomes while minimizing operational costs. Due to presence of mixed-integer variables and non-linear constraints, recently the use of evolutionary algorithms as a tool to find optimal and near-optimal solutions is becoming popular. The energy resource management problem further gets complicated if the uncertainty associated with the renewable generation, load forecast errors, electric vehicles scheduling and market prices are considered. Therefore, in a real-world scenario, it is essential to address the issues brought by the variability of demand, renewable energy, electric vehicles, and market price variations while maximizing the incomes and minimizing the total operation costs. In this paper, we analyze the performance of Differential Evolution with a stochastic selection on a large-scale energy resource management problem with uncertainty designed for competition at CEC 2018. The system comprises of a 25-bus microgrid representing a residential area with high penetration of Distributed Energy Resources (DER), Electric Vehicles (EVs), Demand Response (DR) programs etc.",

keywords = "Differential Evolution, Energy Resource Management, Smart Grid, Stochastic Selection",

author = "Vikas Palakonda and Awad, \{Noor H.\} and Rammohan Mallipeddi and Ali, \{Mostafa Z.\} and Veluvolu, \{K. C.\} and Suganthan, \{P. N.\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Congress on Evolutionary Computation, CEC 2018 ; Conference date: 08-07-2018 Through 13-07-2018",

year = "2018",

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day = "28",

doi = "10.1109/CEC.2018.8477809",

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Palakonda, V, Awad, NH, Mallipeddi, R, Ali, MZ, Veluvolu, KC & Suganthan, PN 2018, Differential Evolution with Stochastic Selection for Uncertain Environments: A Smart Grid Application. in 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings., 8477809, 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE Congress on Evolutionary Computation, CEC 2018, Rio de Janeiro, Brazil, 8/07/18. https://doi.org/10.1109/CEC.2018.8477809

Differential Evolution with Stochastic Selection for Uncertain Environments: A Smart Grid Application. / Palakonda, Vikas; Awad, Noor H.; Mallipeddi, Rammohan et al.
2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8477809 (2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Differential Evolution with Stochastic Selection for Uncertain Environments

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AU - Palakonda, Vikas

AU - Awad, Noor H.

AU - Mallipeddi, Rammohan

AU - Ali, Mostafa Z.

AU - Veluvolu, K. C.

AU - Suganthan, P. N.

PY - 2018/9/28

Y1 - 2018/9/28

N2 - In smart grid, energy resource management is highly complex large-scale optimization problem where the aim is to maximize the incomes while minimizing operational costs. Due to presence of mixed-integer variables and non-linear constraints, recently the use of evolutionary algorithms as a tool to find optimal and near-optimal solutions is becoming popular. The energy resource management problem further gets complicated if the uncertainty associated with the renewable generation, load forecast errors, electric vehicles scheduling and market prices are considered. Therefore, in a real-world scenario, it is essential to address the issues brought by the variability of demand, renewable energy, electric vehicles, and market price variations while maximizing the incomes and minimizing the total operation costs. In this paper, we analyze the performance of Differential Evolution with a stochastic selection on a large-scale energy resource management problem with uncertainty designed for competition at CEC 2018. The system comprises of a 25-bus microgrid representing a residential area with high penetration of Distributed Energy Resources (DER), Electric Vehicles (EVs), Demand Response (DR) programs etc.

AB - In smart grid, energy resource management is highly complex large-scale optimization problem where the aim is to maximize the incomes while minimizing operational costs. Due to presence of mixed-integer variables and non-linear constraints, recently the use of evolutionary algorithms as a tool to find optimal and near-optimal solutions is becoming popular. The energy resource management problem further gets complicated if the uncertainty associated with the renewable generation, load forecast errors, electric vehicles scheduling and market prices are considered. Therefore, in a real-world scenario, it is essential to address the issues brought by the variability of demand, renewable energy, electric vehicles, and market price variations while maximizing the incomes and minimizing the total operation costs. In this paper, we analyze the performance of Differential Evolution with a stochastic selection on a large-scale energy resource management problem with uncertainty designed for competition at CEC 2018. The system comprises of a 25-bus microgrid representing a residential area with high penetration of Distributed Energy Resources (DER), Electric Vehicles (EVs), Demand Response (DR) programs etc.

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Y2 - 8 July 2018 through 13 July 2018

ER -

Palakonda V, Awad NH, Mallipeddi R, Ali MZ, Veluvolu KC, Suganthan PN. Differential Evolution with Stochastic Selection for Uncertain Environments: A Smart Grid Application. In 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. 8477809. (2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings). doi: 10.1109/CEC.2018.8477809

Differential Evolution with Stochastic Selection for Uncertain Environments: A Smart Grid Application

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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