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Weather-Driven Priority Charging for Battery Storage Systems in Hybrid Renewable Energy Grids

Dhrumil Bhatt, Siddharth Penumatsa, Nirbhay Singhal

TL;DR

This work tackles the challenge of integrating volatile renewable generation into a resilient grid by proposing a large-scale, interconnected battery storage network governed by weather-informed, priority-based charging. It introduces a Stability Driven Priority Algorithm for short-term grid stability and a Health Efficiency Priority Algorithm to minimize battery degradation via a SoC/SoH ranking, guided by real-time forecasts from weather and load data. Experimental results show that the approach reduces degradation by about 2.2% over two years and prevents storage units from hitting zero state of charge, thereby improving reliability and longevity of storage in hybrid grids. The framework demonstrates practical potential for more resilient, weather-adaptive renewable energy infrastructures, with future work including advanced load-prediction models and expansion to additional renewables.

Abstract

The integration of renewable energy into the power grid is often hindered by its fragmented infrastructure, leading to inefficient utilization due to the variability of energy production and its reliance on weather conditions. Battery storage systems, while essential for stabilizing energy supply, face challenges like sub-optimal energy distribution, accelerating battery degradation, and reducing operational efficiency. This paper presents a novel solution to these challenges by developing a large-scale, interconnected renewable energy network that optimizes energy storage and distribution. The proposed system includes strategically placed battery storage facilities that stabilize energy production by compensating for fluctuations in renewable output. A priority charging algorithm, informed by real-time weather forecasting and load monitoring, ensures that the most suitable battery systems are charged under varying conditions. Within each storage facility, a secondary priority charging algorithm minimizes battery degradation by ranking batteries based on critical parameters such as state of health (SoH) and state of charge (SoC) and deciding which to charge. This comprehensive approach enhances the efficiency and longevity of battery storage systems, offering a more reliable and resilient renewable energy infrastructure.

Weather-Driven Priority Charging for Battery Storage Systems in Hybrid Renewable Energy Grids

TL;DR

This work tackles the challenge of integrating volatile renewable generation into a resilient grid by proposing a large-scale, interconnected battery storage network governed by weather-informed, priority-based charging. It introduces a Stability Driven Priority Algorithm for short-term grid stability and a Health Efficiency Priority Algorithm to minimize battery degradation via a SoC/SoH ranking, guided by real-time forecasts from weather and load data. Experimental results show that the approach reduces degradation by about 2.2% over two years and prevents storage units from hitting zero state of charge, thereby improving reliability and longevity of storage in hybrid grids. The framework demonstrates practical potential for more resilient, weather-adaptive renewable energy infrastructures, with future work including advanced load-prediction models and expansion to additional renewables.

Abstract

The integration of renewable energy into the power grid is often hindered by its fragmented infrastructure, leading to inefficient utilization due to the variability of energy production and its reliance on weather conditions. Battery storage systems, while essential for stabilizing energy supply, face challenges like sub-optimal energy distribution, accelerating battery degradation, and reducing operational efficiency. This paper presents a novel solution to these challenges by developing a large-scale, interconnected renewable energy network that optimizes energy storage and distribution. The proposed system includes strategically placed battery storage facilities that stabilize energy production by compensating for fluctuations in renewable output. A priority charging algorithm, informed by real-time weather forecasting and load monitoring, ensures that the most suitable battery systems are charged under varying conditions. Within each storage facility, a secondary priority charging algorithm minimizes battery degradation by ranking batteries based on critical parameters such as state of health (SoH) and state of charge (SoC) and deciding which to charge. This comprehensive approach enhances the efficiency and longevity of battery storage systems, offering a more reliable and resilient renewable energy infrastructure.
Paper Structure (19 sections, 7 equations, 5 figures)

This paper contains 19 sections, 7 equations, 5 figures.

Table of Contents

  1. Introduction
  2. Literature Review
  3. Integrated Systems: Combining Weather and Load Forecasting
  4. Priority Charging
  5. Challenges and Gaps in Research
  6. Methodology
  7. Stability Driven Priority Algorithm
  8. Priority Charging Logic
  9. Load Distribution and Discharge Logic
  10. Weather Forecasting
  11. Load Monitoring and Prediction
  12. Health Efficiency Priority Algorithm
  13. Experimental Setup
  14. System Components
  15. Renewable Energy Sources
  16. ...and 4 more sections

Figures (5)

  • Figure 1: This figure illustrates the central base station wirelessly interconnected with the hybrid energy system, which integrates solar panels and wind turbines as the primary energy generation sources, connected to centralized battery storage units that store excess power for later use and load centers, representing towns or cities.
  • Figure 2: Given above is the logic flow for the combined priority charging and health efficiency algorithm
  • Figure 3: System stability over time with and without algorithm
  • Figure 4: System degradation over time with and without the algorithm
  • Figure :