Voltage Regulation Planning Based on Optimal Grid-Connected Renewable Energy Allocation Using Nature-Inspired Algorithms to Reduce Switching Cycles of On-Load Tap Changing Transformer

Article


Ali, Hamid K., Haidar, Ahmed M. A., Julai, Norhuzaimin and Helwig, Andreas. 2023. "Voltage Regulation Planning Based on Optimal Grid-Connected Renewable Energy Allocation Using Nature-Inspired Algorithms to Reduce Switching Cycles of On-Load Tap Changing Transformer." Electric Power Components and Systems. 52 (1), pp. 146-171. https://doi.org/10.1080/15325008.2023.2215783
Article Title

Voltage Regulation Planning Based on Optimal Grid-Connected Renewable Energy Allocation Using Nature-Inspired Algorithms to Reduce Switching Cycles of On-Load Tap Changing Transformer

ERA Journal ID4535
Article CategoryArticle
AuthorsAli, Hamid K., Haidar, Ahmed M. A., Julai, Norhuzaimin and Helwig, Andreas
Journal TitleElectric Power Components and Systems
Journal Citation52 (1), pp. 146-171
Number of Pages26
Year2023
PublisherTaylor & Francis
Place of PublicationUnited States
ISSN0731-356X
1532-5008
1532-5016
Digital Object Identifier (DOI)https://doi.org/10.1080/15325008.2023.2215783
Web Address (URL)https://www.tandfonline.com/doi/full/10.1080/15325008.2023.2215783
AbstractDue to the non-deterministic and probabilistic qualities of renewable energy resources (RER), integrating these resources has posed a challenge for energy companies and government policy planners. Hybrid power systems require frequent voltage regulation to address the changes in renewable generation and facilitate voltage management. This leads to an increment in the operating time of the tap changer in the power transformer, thus resulting in accelerated degradation of the on-load tap changer (OLTC) device. The primary focus of this paper is to optimally manage the penetration level of renewable generation while maintaining the minimum time for proper operation of voltage regulation devices. Accordingly, the major contribution of this paper is to address the switching cycle issues of the on-load tap-changing transformer. Initially, a framework is proposed to optimize the location and size of renewable power generation using a multi-objective cuckoo search optimization algorithm. The main goal here is to reduce power losses and tap changer operations while improving the system voltage profile under different levels of renewable energy penetration. The optimization problem takes into consideration the fluctuating nature of wind speed and solar irradiance for sunny and cloudy days over 24 h. The framework has been applied to the IEEE 57-bus and 118-bus systems with different load levels. The performance of the proposed approach has been benchmarked by comparing it with the genetic optimization algorithm to identify the higher potential buses for renewable generation allocation. The cuckoo search algorithm (CSA) shows outstanding results in reducing the number of switching cycles to about (37 – 43) % whereas the genetic algorithm (GA) only (17 – 18). In this sense, the number of changes in tap position when using the CSA is 1956 for sunny days and 1763 for cloudy days compared to GA 2558 for sunny days and 2547 for cloudy days. The voltage profiles for both algorithms are maintained in the range of (1.06 and 0.94) per unit. The results affirm the effectiveness of the proposed approach in determining the optimal placement and size of RER with voltage profile improvement and reduction in the switching cycles of OLTC.
KeywordsCuckoo Search Algorithm; optimal voltage regulatio; renewable energy resources; on-load tap changer; multi-objective optimization; genetic algorithm
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020400803. Electrical energy generation (incl. renewables, excl. photovoltaics)
400805. Electrical energy transmission, networks and systems
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Byline AffiliationsUniversity of Malaysia, Sarawak, Malaysia
School of Engineering
University College of Southern Queensland
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