Real-Time Scheduling for Energy Optimization: Smart Grid Integration with Renewable Energy

Authors

  • Chunhua Deming Research Fellow, NUS Graduate School (NUSGS), National University of Singapore, 119077, Singapore
  • Prasanna Pasam Developer IV Specialized, Supreme Tech Solutions, Vienna, Virginia, USA
  • Abhishekar Reddy Allam Software Developer, Compunnel Software Group Inc., 103 Morgan Lane STE 102, Plainsboro, NJ, USA
  • Rahimoddin Mohammed Software Engineer, Credit Risk, UBS, 1000 Harbor Blvd, Weehawken, NJ 07086, USA
  • SSMLG Gudimetla Naga Venkata IAM Engineer, HCL Global Systems Inc., Farmington Hills, Michigan- 48335, USA
  • Kanaka Rakesh Varma Kothapalli Consultant, Yotta Systems Inc., Morristown, New Jersey, 07960, USA

DOI:

https://doi.org/10.18034/apjee.v8i2.762

Keywords:

Real-time Scheduling, Energy Optimization, Smart Grid, Renewable Energy, Grid Integration, Scheduling Algorithms, Distributed Energy Resources, Power System Optimization

Abstract

This research investigates the scheduling of tasks in real-time to optimize energy use in the context of integrating renewable energy sources into the smart grid. The primary goals are to analyze the influence of fluctuations in renewable energy on grid synchronization, evaluate the efficiency of different optimization methods, and identify significant obstacles and corresponding remedies. Secondary data studies advanced forecasting methods, energy storage systems, and optimization techniques, including Linear Programming (LP), Dynamic Programming (DP), and metaheuristics. The significant findings show that renewable energy fluctuations affect power system stability. Advanced prediction methods and energy storage are essential in reducing these impacts. Optimization approaches enhance the scheduling efficiency, but the computational complexity and practical application constraints limit their effectiveness. Challenges such as frequency regulation, voltage management, and integrating Distributed Energy Resources (DERs) need specific solutions such as dynamic voltage support and grid modernization. The policy implications include supporting advanced technologies, encouraging real-time scheduling system research, and enhancing grid infrastructure to increase resilience. These measures are essential for integrating renewable energy, ensuring a reliable smart grid, and achieving a sustainable future.

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References

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Published

2021-11-05

How to Cite

Deming, C., Pasam, P., Allam, A. R., Mohammed, R., Venkata, S. G. N., & Kothapalli, K. R. V. (2021). Real-Time Scheduling for Energy Optimization: Smart Grid Integration with Renewable Energy. Asia Pacific Journal of Energy and Environment, 8(2), 77-88. https://doi.org/10.18034/apjee.v8i2.762

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