Optimal Planning of a Standalone Microgrid by Constrained Multi-objective Population Extremal Optimization

Zhen QIN; Guo-Qiang  ZENG; Kang-Di  LU; Rong WANG; Jun-Yi WU

doi:10.1007/978-981-96-1864-4_28

Optimal Planning of a Standalone Microgrid by Constrained Multi-objective Population Extremal Optimization

Zhen QIN
, Guo-Qiang ZENG
, Kang-Di LU
, Rong WANG
, Jun-Yi WU

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

Abstract

A standalone microgrid plays an important role in supplying power to residential and remote areas by integrating different types of distributed generation. One of the key open issues in both academic and engineering fields is how to provide an optimal planning strategy for distributed generations and storage systems in a standalone microgrid, considering multi-objective performance indices such as reliability and cost. In this paper, a novel constrained multi-objective population extremal optimization (CMOPEO) is proposed for standalone microgrid optimal planning. The fundamental concept of the suggested approach is to frame the problem as a standard constrained multi-objective problem, where power loss probability, fuel emission, and power cost of the system are considered as the objectives, and the maximum amount of extra power and the availability of renewable resources are the constraints. The superiority of the CMOPEO algorithm is demonstrated through simulation results on a standalone microgrid case over multi-objective particle swarm optimization.

Original language	English
Title of host publication	The Proceedings of 2024 International Conference of Electrical, Electronic and Networked Energy Systems
Editors	Aimin SHA, Zhigang LIU, Xiaojun WANG, Qian XIAO, Yiming ZANG, Longfei TANG
Publisher	Springer Singapore
Pages	266-273
Number of pages	8
ISBN (Electronic)	9789819618644
ISBN (Print)	9789819618637
DOIs	https://doi.org/10.1007/978-981-96-1864-4_28
Publication status	Published - 2025
Externally published	Yes
Event	2024 International Conference of Electrical, Electronic and Networked Energy Systems, EENES 2024 - Duration: 18 Oct 2024 → 20 Oct 2024

Publication series

Name	Lecture Notes in Electrical Engineering
Publisher	Springer
Volume	1331
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	2024 International Conference of Electrical, Electronic and Networked Energy Systems, EENES 2024
Period	18/10/24 → 20/10/24

Bibliographical note

Publisher Copyright:
© Beijing Paike Culture Commu. Co., Ltd. 2025.

Funding

The work was supported by the National Natural Science Foundation of China (No. 61972288).

Keywords

extremal optimization
microgrid
multi-objective evolutionary algorithms
optimal planning

Access to Document

10.1007/978-981-96-1864-4_28

Cite this

QIN, Z., ZENG, G.-Q., LU, K.-D., WANG, R., & WU, J.-Y. (2025). Optimal Planning of a Standalone Microgrid by Constrained Multi-objective Population Extremal Optimization. In A. SHA, Z. LIU, X. WANG, Q. XIAO, Y. ZANG, & L. TANG (Eds.), The Proceedings of 2024 International Conference of Electrical, Electronic and Networked Energy Systems (pp. 266-273). (Lecture Notes in Electrical Engineering; Vol. 1331). Springer Singapore. https://doi.org/10.1007/978-981-96-1864-4_28

QIN, Zhen ; ZENG, Guo-Qiang ; LU, Kang-Di et al. / Optimal Planning of a Standalone Microgrid by Constrained Multi-objective Population Extremal Optimization. The Proceedings of 2024 International Conference of Electrical, Electronic and Networked Energy Systems. editor / Aimin SHA ; Zhigang LIU ; Xiaojun WANG ; Qian XIAO ; Yiming ZANG ; Longfei TANG. Springer Singapore, 2025. pp. 266-273 (Lecture Notes in Electrical Engineering).

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abstract = "A standalone microgrid plays an important role in supplying power to residential and remote areas by integrating different types of distributed generation. One of the key open issues in both academic and engineering fields is how to provide an optimal planning strategy for distributed generations and storage systems in a standalone microgrid, considering multi-objective performance indices such as reliability and cost. In this paper, a novel constrained multi-objective population extremal optimization (CMOPEO) is proposed for standalone microgrid optimal planning. The fundamental concept of the suggested approach is to frame the problem as a standard constrained multi-objective problem, where power loss probability, fuel emission, and power cost of the system are considered as the objectives, and the maximum amount of extra power and the availability of renewable resources are the constraints. The superiority of the CMOPEO algorithm is demonstrated through simulation results on a standalone microgrid case over multi-objective particle swarm optimization.",

keywords = "extremal optimization, microgrid, multi-objective evolutionary algorithms, optimal planning",

author = "Zhen QIN and Guo-Qiang ZENG and Kang-Di LU and Rong WANG and Jun-Yi WU",

note = "Publisher Copyright: {\textcopyright} Beijing Paike Culture Commu. Co., Ltd. 2025.; 2024 International Conference of Electrical, Electronic and Networked Energy Systems, EENES 2024 ; Conference date: 18-10-2024 Through 20-10-2024",

year = "2025",

doi = "10.1007/978-981-96-1864-4\_28",

language = "English",

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QIN, Z, ZENG, G-Q, LU, K-D, WANG, R & WU, J-Y 2025, Optimal Planning of a Standalone Microgrid by Constrained Multi-objective Population Extremal Optimization. in A SHA, Z LIU, X WANG, Q XIAO, Y ZANG & L TANG (eds), The Proceedings of 2024 International Conference of Electrical, Electronic and Networked Energy Systems. Lecture Notes in Electrical Engineering, vol. 1331, Springer Singapore, pp. 266-273, 2024 International Conference of Electrical, Electronic and Networked Energy Systems, EENES 2024, 18/10/24. https://doi.org/10.1007/978-981-96-1864-4_28

Optimal Planning of a Standalone Microgrid by Constrained Multi-objective Population Extremal Optimization. / QIN, Zhen; ZENG, Guo-Qiang ; LU, Kang-Di et al.
The Proceedings of 2024 International Conference of Electrical, Electronic and Networked Energy Systems. ed. / Aimin SHA; Zhigang LIU; Xiaojun WANG; Qian XIAO; Yiming ZANG; Longfei TANG. Springer Singapore, 2025. p. 266-273 (Lecture Notes in Electrical Engineering; Vol. 1331).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

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T1 - Optimal Planning of a Standalone Microgrid by Constrained Multi-objective Population Extremal Optimization

AU - QIN, Zhen

AU - ZENG, Guo-Qiang

AU - LU, Kang-Di

AU - WANG, Rong

AU - WU, Jun-Yi

N1 - Publisher Copyright: © Beijing Paike Culture Commu. Co., Ltd. 2025.

PY - 2025

Y1 - 2025

N2 - A standalone microgrid plays an important role in supplying power to residential and remote areas by integrating different types of distributed generation. One of the key open issues in both academic and engineering fields is how to provide an optimal planning strategy for distributed generations and storage systems in a standalone microgrid, considering multi-objective performance indices such as reliability and cost. In this paper, a novel constrained multi-objective population extremal optimization (CMOPEO) is proposed for standalone microgrid optimal planning. The fundamental concept of the suggested approach is to frame the problem as a standard constrained multi-objective problem, where power loss probability, fuel emission, and power cost of the system are considered as the objectives, and the maximum amount of extra power and the availability of renewable resources are the constraints. The superiority of the CMOPEO algorithm is demonstrated through simulation results on a standalone microgrid case over multi-objective particle swarm optimization.

AB - A standalone microgrid plays an important role in supplying power to residential and remote areas by integrating different types of distributed generation. One of the key open issues in both academic and engineering fields is how to provide an optimal planning strategy for distributed generations and storage systems in a standalone microgrid, considering multi-objective performance indices such as reliability and cost. In this paper, a novel constrained multi-objective population extremal optimization (CMOPEO) is proposed for standalone microgrid optimal planning. The fundamental concept of the suggested approach is to frame the problem as a standard constrained multi-objective problem, where power loss probability, fuel emission, and power cost of the system are considered as the objectives, and the maximum amount of extra power and the availability of renewable resources are the constraints. The superiority of the CMOPEO algorithm is demonstrated through simulation results on a standalone microgrid case over multi-objective particle swarm optimization.

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A2 - XIAO, Qian

A2 - ZANG, Yiming

A2 - TANG, Longfei

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Y2 - 18 October 2024 through 20 October 2024

ER -

QIN Z, ZENG GQ, LU KD, WANG R, WU JY. Optimal Planning of a Standalone Microgrid by Constrained Multi-objective Population Extremal Optimization. In SHA A, LIU Z, WANG X, XIAO Q, ZANG Y, TANG L, editors, The Proceedings of 2024 International Conference of Electrical, Electronic and Networked Energy Systems. Springer Singapore. 2025. p. 266-273. (Lecture Notes in Electrical Engineering). Epub 2025 Feb 25. doi: 10.1007/978-981-96-1864-4_28

Optimal Planning of a Standalone Microgrid by Constrained Multi-objective Population Extremal Optimization

Abstract

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Keywords

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