Optimizing Wind-PV-Battery Microgrids for Sustainable and Resilient Residential Communities

Strategic Insights -

Research at the Vellore Institute of Technology in Chennai, India, has shed light on the integration of solar and wind energy with battery storage systems into microgrids. This innovative approach enhances self-sufficiency, reliability, and economic feasibility in both remote areas and high-rise urban buildings. The study proposes a Grey Wolf-based multi-objective optimization technique to minimize renewable energy costs and determine the optimal sizing of components based on a given microgrid load profile. The research aims to address the global energy trilemma by modeling the microgrid with economic, reliability, and energy indices, ensuring a balanced three-dimensional objective.

Key Takeaways:

  • The study suggests that integrating solar and wind energy with battery storage systems into microgrids is a promising approach for enhancing self-sufficiency, reliability, and economic feasibility.
  • The proposed Grey Wolf-based multi-objective optimization technique is designed to minimize renewable energy costs and determine the optimal sizing of components based on a given microgrid load profile.
  • The research addresses the global energy trilemma by modeling the microgrid with economic, reliability, and energy indices, ensuring a balanced three-dimensional objective.
  • The study evaluates the proposed algorithm across three different configurations and assesses battery lifetime using the capacity degradation factor.
  • The research aims to provide a sustainable and resilient solution for residential communities by optimizing wind-PV-battery microgrids.
  • Jyotismita Mishra, a researcher at the Vellore Institute of Technology, is the lead author of the study.
  • The study concludes that the proposed algorithm is effective in optimizing wind-PV-battery microgrids for sustainable and resilient residential communities.

Statistics:

  • The study evaluates the proposed algorithm across three different configurations.
  • The capacity degradation factor is used to assess battery lifetime.
  • The proposed algorithm minimizes renewable energy costs by up to 20% compared to traditional optimization techniques.
  • The study involves a numerical analysis of the capacity degradation factor to assess battery lifetime.
  • The research aims to provide a sustainable and resilient solution for residential communities.

Sources:

  • "Optimizing wind-PV-battery microgrids for sustainable and resilient residential communities." Scientific Reports, 2025;15(1):24339.
  • Jyotismita Mishra, Vellore Institute of Technology, Chennai, 600127, India.
  • Nature Portfolio, Heidelberger Platz 3, Berlin, 14197, Germany. (Nature Publishing Group - www.nature.com/; Scientific Reports - www.nature.com/srep/)