Optimization of Biogas Plant Operational Efficiencies Using Evolutionary Algorithms

Desmond Eseoghene Ighravwe; Daniel Mashao

doi:10.1109/REPE48501.2019.9025127

Optimization of Biogas Plant Operational Efficiencies Using Evolutionary Algorithms

Desmond Eseoghene Ighravwe
, Daniel Mashao

University of Johannesburg

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

2 Citations (Scopus)

Abstract

The growing needs for clean energy will continue to attract global attention, especially as it has been recognized as a means of managing solid wastes - especially from households and industrial sector. We now have different waste-to-energy technologies for small and medium-scale plants. But sparse information exists on how to optimize these plants operational efficiencies, especially boilers and reformers. Hence, this article considers the optimization of these efficiencies to optimal electricity generation. This objective is achieved using a nonlinear programming approach. The proposed model utility was tested using a case study of six locations in Southwest Nigeria. A comparison of Genetic algorithm (GA) and Differential Evolution (DE) algorithm are presented as solution methods for the model. In terms of the total electricity generated, there is no significant difference between these algorithms results. The total electricity generated is 10MW, while the average boilers and reformers efficiencies are 0.9 and 0.8, respectively. To be strategic with a waste-to-energy operation, this article recommends that optimal parametric settings for a plant's operational efficiencies should be combined with experts' opinions.

Original language	English
Title of host publication	2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	135-139
Number of pages	5
ISBN (Electronic)	9781728145624
DOIs	https://doi.org/10.1109/REPE48501.2019.9025127
Publication status	Published - Nov 2019
Externally published	Yes
Event	2nd IEEE International Conference on Renewable Energy and Power Engineering, REPE 2019 - Toronto, Canada Duration: 2 Nov 2019 → 4 Nov 2019

Publication series

Name	2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019

Conference

Conference	2nd IEEE International Conference on Renewable Energy and Power Engineering, REPE 2019
Country/Territory	Canada
City	Toronto
Period	2/11/19 → 4/11/19

UN SDGs

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

SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities
SDG 12 Responsible Consumption and Production

Keywords

evolutionary algorithm
food waste
hydrogen gas
optimization model

ASJC Scopus subject areas

Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering

Access to Document

10.1109/REPE48501.2019.9025127

Cite this

Ighravwe, D. E., & Mashao, D. (2019). Optimization of Biogas Plant Operational Efficiencies Using Evolutionary Algorithms. In 2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019 (pp. 135-139). Article 9025127 (2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/REPE48501.2019.9025127

Ighravwe, Desmond Eseoghene ; Mashao, Daniel. / Optimization of Biogas Plant Operational Efficiencies Using Evolutionary Algorithms. 2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 135-139 (2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019).

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title = "Optimization of Biogas Plant Operational Efficiencies Using Evolutionary Algorithms",

abstract = "The growing needs for clean energy will continue to attract global attention, especially as it has been recognized as a means of managing solid wastes - especially from households and industrial sector. We now have different waste-to-energy technologies for small and medium-scale plants. But sparse information exists on how to optimize these plants operational efficiencies, especially boilers and reformers. Hence, this article considers the optimization of these efficiencies to optimal electricity generation. This objective is achieved using a nonlinear programming approach. The proposed model utility was tested using a case study of six locations in Southwest Nigeria. A comparison of Genetic algorithm (GA) and Differential Evolution (DE) algorithm are presented as solution methods for the model. In terms of the total electricity generated, there is no significant difference between these algorithms results. The total electricity generated is 10MW, while the average boilers and reformers efficiencies are 0.9 and 0.8, respectively. To be strategic with a waste-to-energy operation, this article recommends that optimal parametric settings for a plant's operational efficiencies should be combined with experts' opinions.",

keywords = "evolutionary algorithm, food waste, hydrogen gas, optimization model",

author = "Ighravwe, \{Desmond Eseoghene\} and Daniel Mashao",

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year = "2019",

month = nov,

doi = "10.1109/REPE48501.2019.9025127",

language = "English",

series = "2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019",

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Ighravwe, DE & Mashao, D 2019, Optimization of Biogas Plant Operational Efficiencies Using Evolutionary Algorithms. in 2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019., 9025127, 2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019, Institute of Electrical and Electronics Engineers Inc., pp. 135-139, 2nd IEEE International Conference on Renewable Energy and Power Engineering, REPE 2019, Toronto, Canada, 2/11/19. https://doi.org/10.1109/REPE48501.2019.9025127

Optimization of Biogas Plant Operational Efficiencies Using Evolutionary Algorithms. / Ighravwe, Desmond Eseoghene; Mashao, Daniel.
2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 135-139 9025127 (2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019).

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

TY - GEN

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AU - Ighravwe, Desmond Eseoghene

AU - Mashao, Daniel

PY - 2019/11

Y1 - 2019/11

N2 - The growing needs for clean energy will continue to attract global attention, especially as it has been recognized as a means of managing solid wastes - especially from households and industrial sector. We now have different waste-to-energy technologies for small and medium-scale plants. But sparse information exists on how to optimize these plants operational efficiencies, especially boilers and reformers. Hence, this article considers the optimization of these efficiencies to optimal electricity generation. This objective is achieved using a nonlinear programming approach. The proposed model utility was tested using a case study of six locations in Southwest Nigeria. A comparison of Genetic algorithm (GA) and Differential Evolution (DE) algorithm are presented as solution methods for the model. In terms of the total electricity generated, there is no significant difference between these algorithms results. The total electricity generated is 10MW, while the average boilers and reformers efficiencies are 0.9 and 0.8, respectively. To be strategic with a waste-to-energy operation, this article recommends that optimal parametric settings for a plant's operational efficiencies should be combined with experts' opinions.

AB - The growing needs for clean energy will continue to attract global attention, especially as it has been recognized as a means of managing solid wastes - especially from households and industrial sector. We now have different waste-to-energy technologies for small and medium-scale plants. But sparse information exists on how to optimize these plants operational efficiencies, especially boilers and reformers. Hence, this article considers the optimization of these efficiencies to optimal electricity generation. This objective is achieved using a nonlinear programming approach. The proposed model utility was tested using a case study of six locations in Southwest Nigeria. A comparison of Genetic algorithm (GA) and Differential Evolution (DE) algorithm are presented as solution methods for the model. In terms of the total electricity generated, there is no significant difference between these algorithms results. The total electricity generated is 10MW, while the average boilers and reformers efficiencies are 0.9 and 0.8, respectively. To be strategic with a waste-to-energy operation, this article recommends that optimal parametric settings for a plant's operational efficiencies should be combined with experts' opinions.

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KW - hydrogen gas

KW - optimization model

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Y2 - 2 November 2019 through 4 November 2019

ER -

Ighravwe DE, Mashao D. Optimization of Biogas Plant Operational Efficiencies Using Evolutionary Algorithms. In 2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 135-139. 9025127. (2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019). doi: 10.1109/REPE48501.2019.9025127

Optimization of Biogas Plant Operational Efficiencies Using Evolutionary Algorithms

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this