Enhancing Smart Microgrid Resilience and Virtual Power Plant Profitability Through Hybrid IGWO-PSO Optimization With a Three-Phase Bidding Strategy
The increasing energy demand and rising fossil fuel prices are accelerating the transition to renewable energy, supported by government initiatives due to their environmental and economic advantages. However, challenges such as limited capacity and stability constraints hinder the widespread adoptio...
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2025-01-01
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| author | T. Yuvaraj T. Sengolrajan Natarajan Prabaharan K. R. Devabalaji Akie Uehara Tomonobu Senjyu |
| author_facet | T. Yuvaraj T. Sengolrajan Natarajan Prabaharan K. R. Devabalaji Akie Uehara Tomonobu Senjyu |
| author_sort | T. Yuvaraj |
| collection | DOAJ |
| description | The increasing energy demand and rising fossil fuel prices are accelerating the transition to renewable energy, supported by government initiatives due to their environmental and economic advantages. However, challenges such as limited capacity and stability constraints hinder the widespread adoption of distributed energy resources (DERs). Virtual Power Plants (VPPs) enhance market participation by aggregating DERs, while electric vehicles (EVs) contribute to environmental sustainability by reducing emissions. Additionally, integrating distribution static compensators (DSTATCOMs) within VPPs improves microgrid stability and reactive power support. This study proposes a two-stage optimization approach to enhance network resilience and VPP profitability in a radial distribution network (RDN). The first stage focuses on minimizing resilience-related costs and energy not supplied (ENS) during natural disasters, while the second stage optimizes VPP profit using a three-phase bidding strategy, which includes the day-ahead market, real-time market, and overall market. A hybrid improved grey wolf optimization-particle swarm optimization (IGWO-PSO) algorithm is developed to solve this complex optimization problem. To demonstrate the effectiveness of the proposed approach, IGWO-PSO is compared with other hybrid optimization algorithms. Validation on a modified IEEE 33-bus RDN confirms that the proposed model enhances VPP placement and sizing, leading to improved economic, operational, and resilience metrics. Furthermore, the model accounts for uncertainties in load demand, renewable generation, energy prices, and equipment availability, ensuring a robust and adaptable energy management strategy. |
| format | Article |
| id | doaj-art-5275a8d40fe0453b80d71a48e6398fb8 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-5275a8d40fe0453b80d71a48e6398fb82025-08-20T02:58:51ZengIEEEIEEE Access2169-35362025-01-0113807968082010.1109/ACCESS.2025.356546010979928Enhancing Smart Microgrid Resilience and Virtual Power Plant Profitability Through Hybrid IGWO-PSO Optimization With a Three-Phase Bidding StrategyT. Yuvaraj0https://orcid.org/0000-0002-8892-9417T. Sengolrajan1Natarajan Prabaharan2https://orcid.org/0000-0003-0686-5825K. R. Devabalaji3https://orcid.org/0000-0001-9868-6968Akie Uehara4https://orcid.org/0009-0002-2724-3638Tomonobu Senjyu5https://orcid.org/0000-0003-4494-6773Centre for Smart Energy Systems, Chennai Institute of Technology, Chennai, IndiaDepartment of Electrical and Electronics Engineering, Kongunadu College of Engineering and Technology (Autonomous), Tiruchirappalli, IndiaSchool of Electrical and Electronics Engineering, SASTRA Deemed University, Thanjavur, IndiaDepartment of Electrical and Electronics Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Missions Research Foundation, Chennai, IndiaFaculty of Engineering, University of the Ryukyus, Nishihara, JapanFaculty of Engineering, University of the Ryukyus, Nishihara, JapanThe increasing energy demand and rising fossil fuel prices are accelerating the transition to renewable energy, supported by government initiatives due to their environmental and economic advantages. However, challenges such as limited capacity and stability constraints hinder the widespread adoption of distributed energy resources (DERs). Virtual Power Plants (VPPs) enhance market participation by aggregating DERs, while electric vehicles (EVs) contribute to environmental sustainability by reducing emissions. Additionally, integrating distribution static compensators (DSTATCOMs) within VPPs improves microgrid stability and reactive power support. This study proposes a two-stage optimization approach to enhance network resilience and VPP profitability in a radial distribution network (RDN). The first stage focuses on minimizing resilience-related costs and energy not supplied (ENS) during natural disasters, while the second stage optimizes VPP profit using a three-phase bidding strategy, which includes the day-ahead market, real-time market, and overall market. A hybrid improved grey wolf optimization-particle swarm optimization (IGWO-PSO) algorithm is developed to solve this complex optimization problem. To demonstrate the effectiveness of the proposed approach, IGWO-PSO is compared with other hybrid optimization algorithms. Validation on a modified IEEE 33-bus RDN confirms that the proposed model enhances VPP placement and sizing, leading to improved economic, operational, and resilience metrics. Furthermore, the model accounts for uncertainties in load demand, renewable generation, energy prices, and equipment availability, ensuring a robust and adaptable energy management strategy.https://ieeexplore.ieee.org/document/10979928/Virtual power plantmicrogridsresilienceVPP profithybrid IGWO-PSO algorithmradial distribution network |
| spellingShingle | T. Yuvaraj T. Sengolrajan Natarajan Prabaharan K. R. Devabalaji Akie Uehara Tomonobu Senjyu Enhancing Smart Microgrid Resilience and Virtual Power Plant Profitability Through Hybrid IGWO-PSO Optimization With a Three-Phase Bidding Strategy IEEE Access Virtual power plant microgrids resilience VPP profit hybrid IGWO-PSO algorithm radial distribution network |
| title | Enhancing Smart Microgrid Resilience and Virtual Power Plant Profitability Through Hybrid IGWO-PSO Optimization With a Three-Phase Bidding Strategy |
| title_full | Enhancing Smart Microgrid Resilience and Virtual Power Plant Profitability Through Hybrid IGWO-PSO Optimization With a Three-Phase Bidding Strategy |
| title_fullStr | Enhancing Smart Microgrid Resilience and Virtual Power Plant Profitability Through Hybrid IGWO-PSO Optimization With a Three-Phase Bidding Strategy |
| title_full_unstemmed | Enhancing Smart Microgrid Resilience and Virtual Power Plant Profitability Through Hybrid IGWO-PSO Optimization With a Three-Phase Bidding Strategy |
| title_short | Enhancing Smart Microgrid Resilience and Virtual Power Plant Profitability Through Hybrid IGWO-PSO Optimization With a Three-Phase Bidding Strategy |
| title_sort | enhancing smart microgrid resilience and virtual power plant profitability through hybrid igwo pso optimization with a three phase bidding strategy |
| topic | Virtual power plant microgrids resilience VPP profit hybrid IGWO-PSO algorithm radial distribution network |
| url | https://ieeexplore.ieee.org/document/10979928/ |
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