The Optimal and Economic Planning of a Power System Based on the Microgrid Concept with a Modified Seagull Optimization Algorithm Integrating Renewable Resources

In the past, planning to develop an electricity generation capacity supply of consumable load, an acceptable level of reliability, and minimum cost has played significant roles. Due to technological development in energy and the support of energy policymakers to make the most of these clean and chea...

Full description

Bibliographic Details
Main Authors: Zhigao Wang, Zhi Geng, Xia Fang, Qianqian Tian, Xinsheng Lan, Jie Feng
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/12/9/4743
_version_ 1797505503462424576
author Zhigao Wang
Zhi Geng
Xia Fang
Qianqian Tian
Xinsheng Lan
Jie Feng
author_facet Zhigao Wang
Zhi Geng
Xia Fang
Qianqian Tian
Xinsheng Lan
Jie Feng
author_sort Zhigao Wang
collection DOAJ
description In the past, planning to develop an electricity generation capacity supply of consumable load, an acceptable level of reliability, and minimum cost has played significant roles. Due to technological development in energy and the support of energy policymakers to make the most of these clean and cheap resources, a significant amount of research has been conducted to make the most of such energy. Constraints such as low capacity, output power uncertainty, and sustainability problems have made using distributed energy sources costly and complex. Theoretically, capacity development planning in a power system is part of macro-energy planning. It is generally based on specific development policies in each country’s national interest. In addition to being economical, the purpose of this planning was to find the best capacity development plan commensurate with the amount of consumption so that the development plan does not go beyond the permissible limits of reliability, environmental issues, and other constraints. On the other hand, due to the considerable growth of divided production, especially energy sources, it is essential to use microgrids. Accordingly, in this research study, in the process of solving the problem of planning and providing load growth by the distributed generation units to maximize reliability and minimize investment costs, the creation of smaller networks was investigated. To optimize zoning, the weighted graph theory method, in which the weight of the edges is the apparent power passing through the lines, was adopted. In addition, reactive power reliability was included in the calculations to improve the economic aspects. Probabilistic modeling for the presence of renewable resources was employed to bring the model to reality. Since the above problem is very complex, a Seagull-based algorithm and chaos theory were utilized to solve this matter. Finally, the suggested method for the sample system is discussed in different scenarios, indicating an improvement in the system’s performance. According to the numerical results, the NSGA, SPEA, and MOPSO have mean values of 68.3%, 50.2%, and 48.3%, which are covered by the proposed optimization algorithm.
first_indexed 2024-03-10T04:19:31Z
format Article
id doaj.art-f9d3b8e3409d4741b2b4768887215ff4
institution Directory Open Access Journal
issn 2076-3417
language English
last_indexed 2024-03-10T04:19:31Z
publishDate 2022-05-01
publisher MDPI AG
record_format Article
series Applied Sciences
spelling doaj.art-f9d3b8e3409d4741b2b4768887215ff42023-11-23T07:53:19ZengMDPI AGApplied Sciences2076-34172022-05-01129474310.3390/app12094743The Optimal and Economic Planning of a Power System Based on the Microgrid Concept with a Modified Seagull Optimization Algorithm Integrating Renewable ResourcesZhigao Wang0Zhi Geng1Xia Fang2Qianqian Tian3Xinsheng Lan4Jie Feng5State Grid Sichuan Electric Power Research Institute, Chengdu 610041, ChinaState Grid Sichuan Electric Power Research Institute, Chengdu 610041, ChinaSchool of Mechanical Engineering, Sichuan University, Chengdu 610045, ChinaState Grid Sichuan Electric Power Research Institute, Chengdu 610041, ChinaState Grid Sichuan Electric Power Research Institute, Chengdu 610041, ChinaState Grid Sichuan Electric Power Research Institute, Chengdu 610041, ChinaIn the past, planning to develop an electricity generation capacity supply of consumable load, an acceptable level of reliability, and minimum cost has played significant roles. Due to technological development in energy and the support of energy policymakers to make the most of these clean and cheap resources, a significant amount of research has been conducted to make the most of such energy. Constraints such as low capacity, output power uncertainty, and sustainability problems have made using distributed energy sources costly and complex. Theoretically, capacity development planning in a power system is part of macro-energy planning. It is generally based on specific development policies in each country’s national interest. In addition to being economical, the purpose of this planning was to find the best capacity development plan commensurate with the amount of consumption so that the development plan does not go beyond the permissible limits of reliability, environmental issues, and other constraints. On the other hand, due to the considerable growth of divided production, especially energy sources, it is essential to use microgrids. Accordingly, in this research study, in the process of solving the problem of planning and providing load growth by the distributed generation units to maximize reliability and minimize investment costs, the creation of smaller networks was investigated. To optimize zoning, the weighted graph theory method, in which the weight of the edges is the apparent power passing through the lines, was adopted. In addition, reactive power reliability was included in the calculations to improve the economic aspects. Probabilistic modeling for the presence of renewable resources was employed to bring the model to reality. Since the above problem is very complex, a Seagull-based algorithm and chaos theory were utilized to solve this matter. Finally, the suggested method for the sample system is discussed in different scenarios, indicating an improvement in the system’s performance. According to the numerical results, the NSGA, SPEA, and MOPSO have mean values of 68.3%, 50.2%, and 48.3%, which are covered by the proposed optimization algorithm.https://www.mdpi.com/2076-3417/12/9/4743power system planningoptimizationreliabilitymicrogriduncertainty of renewable resourcesgraph theory
spellingShingle Zhigao Wang
Zhi Geng
Xia Fang
Qianqian Tian
Xinsheng Lan
Jie Feng
The Optimal and Economic Planning of a Power System Based on the Microgrid Concept with a Modified Seagull Optimization Algorithm Integrating Renewable Resources
Applied Sciences
power system planning
optimization
reliability
microgrid
uncertainty of renewable resources
graph theory
title The Optimal and Economic Planning of a Power System Based on the Microgrid Concept with a Modified Seagull Optimization Algorithm Integrating Renewable Resources
title_full The Optimal and Economic Planning of a Power System Based on the Microgrid Concept with a Modified Seagull Optimization Algorithm Integrating Renewable Resources
title_fullStr The Optimal and Economic Planning of a Power System Based on the Microgrid Concept with a Modified Seagull Optimization Algorithm Integrating Renewable Resources
title_full_unstemmed The Optimal and Economic Planning of a Power System Based on the Microgrid Concept with a Modified Seagull Optimization Algorithm Integrating Renewable Resources
title_short The Optimal and Economic Planning of a Power System Based on the Microgrid Concept with a Modified Seagull Optimization Algorithm Integrating Renewable Resources
title_sort optimal and economic planning of a power system based on the microgrid concept with a modified seagull optimization algorithm integrating renewable resources
topic power system planning
optimization
reliability
microgrid
uncertainty of renewable resources
graph theory
url https://www.mdpi.com/2076-3417/12/9/4743
work_keys_str_mv AT zhigaowang theoptimalandeconomicplanningofapowersystembasedonthemicrogridconceptwithamodifiedseagulloptimizationalgorithmintegratingrenewableresources
AT zhigeng theoptimalandeconomicplanningofapowersystembasedonthemicrogridconceptwithamodifiedseagulloptimizationalgorithmintegratingrenewableresources
AT xiafang theoptimalandeconomicplanningofapowersystembasedonthemicrogridconceptwithamodifiedseagulloptimizationalgorithmintegratingrenewableresources
AT qianqiantian theoptimalandeconomicplanningofapowersystembasedonthemicrogridconceptwithamodifiedseagulloptimizationalgorithmintegratingrenewableresources
AT xinshenglan theoptimalandeconomicplanningofapowersystembasedonthemicrogridconceptwithamodifiedseagulloptimizationalgorithmintegratingrenewableresources
AT jiefeng theoptimalandeconomicplanningofapowersystembasedonthemicrogridconceptwithamodifiedseagulloptimizationalgorithmintegratingrenewableresources
AT zhigaowang optimalandeconomicplanningofapowersystembasedonthemicrogridconceptwithamodifiedseagulloptimizationalgorithmintegratingrenewableresources
AT zhigeng optimalandeconomicplanningofapowersystembasedonthemicrogridconceptwithamodifiedseagulloptimizationalgorithmintegratingrenewableresources
AT xiafang optimalandeconomicplanningofapowersystembasedonthemicrogridconceptwithamodifiedseagulloptimizationalgorithmintegratingrenewableresources
AT qianqiantian optimalandeconomicplanningofapowersystembasedonthemicrogridconceptwithamodifiedseagulloptimizationalgorithmintegratingrenewableresources
AT xinshenglan optimalandeconomicplanningofapowersystembasedonthemicrogridconceptwithamodifiedseagulloptimizationalgorithmintegratingrenewableresources
AT jiefeng optimalandeconomicplanningofapowersystembasedonthemicrogridconceptwithamodifiedseagulloptimizationalgorithmintegratingrenewableresources