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Adaptive Electricity Scheduling in Micro Grids


Affiliations
1 Department of Electrical & Electronics Engineering, Dr. M.G.R. Educational & Research Institute, University, India
2 Department of EEE, Dr. M.G.R. Educational & Research Institute, University, India
     

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Micro grid (MG) is a promising component for future smart grid (SG) deployment. The balance of supply and demand of electric energy is one of the most important requirements of MG management. In this paper, we present a novel framework for smart energy management based on the concept of quality-of-service in electricity. Specifically, the resident electricity demand is classified into basic usage and quality usage. The basic usage is always guaranteed by the MG, while the quality usage is controlled based on the MG state. The micro grid control center (MGCC) aims to minimize the MG operation cost and maintain the outage probability of quality usage, below a target value, by scheduling electricity among renewable energy resources, energy storage systems, and macro grid. The problem is formulated as a constrained stochastic programming problem. The optimization technique is then applied to derive an adaptive electricity scheduling algorithm by introducing the QoSE virtual queues and energy storage virtual queues. The proposed algorithm is an online algorithm. We derive several “hard” performance bounds for the proposed algorithm, and evaluate its performance with trace-driven simulations. The simulation results demonstrate the efficacy of the proposed electricity scheduling Algorithm.

Keywords

Driver Circuit, Inductive Step Down Voltage, Transformer, Photo Voltaic Cell, Battery, Solar Panel.
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  • Adaptive Electricity Scheduling in Micro Grids

Abstract Views: 265  |  PDF Views: 5

Authors

Sanjay Kumar Rana
Department of Electrical & Electronics Engineering, Dr. M.G.R. Educational & Research Institute, University, India
Sachin Kumar
Department of Electrical & Electronics Engineering, Dr. M.G.R. Educational & Research Institute, University, India
Sandeep Sahoo
Department of Electrical & Electronics Engineering, Dr. M.G.R. Educational & Research Institute, University, India
Rahul Jha
Department of Electrical & Electronics Engineering, Dr. M.G.R. Educational & Research Institute, University, India
Rupesh Yadav
Department of Electrical & Electronics Engineering, Dr. M.G.R. Educational & Research Institute, University, India
Shiv Shankar Kumar
Department of Electrical & Electronics Engineering, Dr. M.G.R. Educational & Research Institute, University, India
S. T. Rama
Department of EEE, Dr. M.G.R. Educational & Research Institute, University, India
Balamurgan
Department of EEE, Dr. M.G.R. Educational & Research Institute, University, India

Abstract


Micro grid (MG) is a promising component for future smart grid (SG) deployment. The balance of supply and demand of electric energy is one of the most important requirements of MG management. In this paper, we present a novel framework for smart energy management based on the concept of quality-of-service in electricity. Specifically, the resident electricity demand is classified into basic usage and quality usage. The basic usage is always guaranteed by the MG, while the quality usage is controlled based on the MG state. The micro grid control center (MGCC) aims to minimize the MG operation cost and maintain the outage probability of quality usage, below a target value, by scheduling electricity among renewable energy resources, energy storage systems, and macro grid. The problem is formulated as a constrained stochastic programming problem. The optimization technique is then applied to derive an adaptive electricity scheduling algorithm by introducing the QoSE virtual queues and energy storage virtual queues. The proposed algorithm is an online algorithm. We derive several “hard” performance bounds for the proposed algorithm, and evaluate its performance with trace-driven simulations. The simulation results demonstrate the efficacy of the proposed electricity scheduling Algorithm.

Keywords


Driver Circuit, Inductive Step Down Voltage, Transformer, Photo Voltaic Cell, Battery, Solar Panel.



DOI: https://doi.org/10.36039/ciitaas%2F7%2F6%2F2015%2F106722.151-156