Smart deployment of energy storage and renewable energy sources for improving distribution system efficacy
Climate change, global warming, the depletion of fossil fuels, and rising energy demand are the main forces behind the increase in renewable energy sources. However, the unpredictability of power output from these renewable energy sources presents distribution system integration issues such as limit...
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| Format: | Article |
| Language: | English |
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AIMS Press
2022-11-01
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| Series: | AIMS Electronics and Electrical Engineering |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/electreng.2022024?viewType=HTML |
| _version_ | 1797958248959049728 |
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| author | Samarjit Patnaik Manas Ranjan Nayak Meera Viswavandya |
| author_facet | Samarjit Patnaik Manas Ranjan Nayak Meera Viswavandya |
| author_sort | Samarjit Patnaik |
| collection | DOAJ |
| description | Climate change, global warming, the depletion of fossil fuels, and rising energy demand are the main forces behind the increase in renewable energy sources. However, the unpredictability of power output from these renewable energy sources presents distribution system integration issues such as limited feeder capacity, unstable voltage, and network power loss. This study analyses the African vulture optimisation algorithm to determine the best allocation of distribution generators, with an emphasis on reducing the ageing of distribution transformers and delaying investment in feeders. The optimization technique provides faster global convergence and outperforms existing bio-inspired algorithms verified with benchmark uni-modal functions as a result of a larger crossover between the exploration and exploitation phases. The key aim is to decrease active power loss while simultaneously enhancing security margin and voltage stability. The IEEE 69-bus RDS system is utilised to validate the case studies for appropriate allocation of photovoltaic, wind turbine generation, and battery energy storage systems units, as well as offering the ideal energy management approach. During simulation, uncertainty on the characteristics of renewable energy source is accounted for. The results demonstrate the efficacy of the proposed algorithm with a substantial improvement in voltage profile, the benefit of lower CO2 emissions, an increase in security margin of up to 143%, and the advantage of extending the feeder investment deferral period by more than 50 years. In addition, the distribution transformer ageing acceleration factor improves significantly in the case of an increase in load demand. |
| first_indexed | 2024-04-11T00:16:21Z |
| format | Article |
| id | doaj.art-5c9e06df3679409bad08f29e1b4a4511 |
| institution | Directory Open Access Journal |
| issn | 2578-1588 |
| language | English |
| last_indexed | 2024-04-11T00:16:21Z |
| publishDate | 2022-11-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Electronics and Electrical Engineering |
| spelling | doaj.art-5c9e06df3679409bad08f29e1b4a45112023-01-09T01:28:24ZengAIMS PressAIMS Electronics and Electrical Engineering2578-15882022-11-016439741710.3934/electreng.2022024Smart deployment of energy storage and renewable energy sources for improving distribution system efficacySamarjit Patnaik0Manas Ranjan Nayak1Meera Viswavandya21. Department of Electrical Engineering, Biju Patnaik University of Technology, Rourkela 769015, Odisha, India1. Department of Electrical Engineering, Biju Patnaik University of Technology, Rourkela 769015, Odisha, India2. Department of Electrical Engineering, Odisha University of Technology and Research, Bhubaneswar 751029, Odisha, IndiaClimate change, global warming, the depletion of fossil fuels, and rising energy demand are the main forces behind the increase in renewable energy sources. However, the unpredictability of power output from these renewable energy sources presents distribution system integration issues such as limited feeder capacity, unstable voltage, and network power loss. This study analyses the African vulture optimisation algorithm to determine the best allocation of distribution generators, with an emphasis on reducing the ageing of distribution transformers and delaying investment in feeders. The optimization technique provides faster global convergence and outperforms existing bio-inspired algorithms verified with benchmark uni-modal functions as a result of a larger crossover between the exploration and exploitation phases. The key aim is to decrease active power loss while simultaneously enhancing security margin and voltage stability. The IEEE 69-bus RDS system is utilised to validate the case studies for appropriate allocation of photovoltaic, wind turbine generation, and battery energy storage systems units, as well as offering the ideal energy management approach. During simulation, uncertainty on the characteristics of renewable energy source is accounted for. The results demonstrate the efficacy of the proposed algorithm with a substantial improvement in voltage profile, the benefit of lower CO2 emissions, an increase in security margin of up to 143%, and the advantage of extending the feeder investment deferral period by more than 50 years. In addition, the distribution transformer ageing acceleration factor improves significantly in the case of an increase in load demand.https://www.aimspress.com/article/doi/10.3934/electreng.2022024?viewType=HTMLphotovoltaicdistribution transformer ageingbattery energy storage systemwind turbine generationafrican vulture optimisationfeeder investment deferral |
| spellingShingle | Samarjit Patnaik Manas Ranjan Nayak Meera Viswavandya Smart deployment of energy storage and renewable energy sources for improving distribution system efficacy AIMS Electronics and Electrical Engineering photovoltaic distribution transformer ageing battery energy storage system wind turbine generation african vulture optimisation feeder investment deferral |
| title | Smart deployment of energy storage and renewable energy sources for improving distribution system efficacy |
| title_full | Smart deployment of energy storage and renewable energy sources for improving distribution system efficacy |
| title_fullStr | Smart deployment of energy storage and renewable energy sources for improving distribution system efficacy |
| title_full_unstemmed | Smart deployment of energy storage and renewable energy sources for improving distribution system efficacy |
| title_short | Smart deployment of energy storage and renewable energy sources for improving distribution system efficacy |
| title_sort | smart deployment of energy storage and renewable energy sources for improving distribution system efficacy |
| topic | photovoltaic distribution transformer ageing battery energy storage system wind turbine generation african vulture optimisation feeder investment deferral |
| url | https://www.aimspress.com/article/doi/10.3934/electreng.2022024?viewType=HTML |
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