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Energy Distribution in a Smart Grid with Load Weight and Time Zone

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Proceedings of the Third International Conference on Computational Intelligence and Informatics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1090))

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Abstract

Energy generation and distribution according to the customer demand are major challenging tasks in the smart grid. In this paper, allocation and distribution of energy in the grid network based on load weight and time are proposed. Energy allocated to different levels in the grid based on load weight during high demand. Finally, based on the time zone and demand, the energy is distributed to the different categories of customers. Various test cases for high and low demand in peak and nonpeak hours with dynamic load are considered for investigation. The requests from three different types of load, i.e., shiftable, non-shiftable and shiftable with noncontinuous slots are considered. The proposed techniques give better flexibility in energy distribution to the customers by maintaining high fairness index. An adaptive shifting intelligent control is applied further to enhance the performance.

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References

  1. Yamamoto, S., T. Tazoe, H. Onda, H. Takeshita, S. Okamoto, and N. Yamanaka. 2013. Distributed Demand Scheduling Method to Reduce Energy Cost in Smart Grid. In IEEE Region 10 Humanitarian Technology Conference (R10-HTC), 148–1153.

    Google Scholar 

  2. Chao, H., and P. Hsiung. 2016. A Fair Energy Resource Allocation Strategy for Micro Grid. Microprocessors and Microsystems 42, 235–244.

    Google Scholar 

  3. Nunna, K., and S. Dolla. 2011. Demand Response in Smart Micro Grids. In IEEE PES Innovative Smart Grid Technologies—India (ISGT India), 131–136.

    Google Scholar 

  4. Rama chandran, B., S. Srivastava, C. Edrington, and D. Cartes. 2011. An Intelligent Auction Scheme for Smart Grid Market Using a Hybrid Immune Algorithm. IEEE Transactions on Industrial Electronics 58 (10): 4603–4612.

    Google Scholar 

  5. Nunna, H.K., and S. Dolla. 2012. Demand Response in Smart Distribution System with Multiple Microgrids. IEEE Transactions on Smart Grid 3 (4): 1641–1649.

    Google Scholar 

  6. Nunna, H.K., and S. Dolla. 2013. Energy Management in Micro Grids Using Demand Response and Distributed Storage a Multi-Agent Approach. IEEE Transactions on Power Delivery 28 (2): 939–947.

    Google Scholar 

  7. Nunna, H.K., and S. Dolla. 2013. Intelligent Demand Side Management in Smart-Micro Grid. In IEEE International Workshop on Intelligent Energy Systems (IWIES), 125–130.

    Google Scholar 

  8. Nunna, H.K., and S. Dolla. 2014. Responsive End-User-Based Demand Side Management in Multi Micro Grid Environment. IEEE Transactions on Industrial Informatics 10 (2): 1262–1272.

    Google Scholar 

  9. Yingjie, Z., M. Nicholas, Q. Xiangying, and W. Chen. 2014. The Fair Distribution of Power to Electric Vehicles: An Alternative to Pricing. In 5th IEEE International Conference on Smart Grid Communications.

    Google Scholar 

  10. Ardakanian, O., C. Rosenberg, and S. Keshav. 2013. Distributed Control of Electric Vehicle Charging, e-energy 13. In Fourth International Conference on Future Energy Systems, 101–112.

    Google Scholar 

  11. Pilloni, V., A. Floris, A. Meloni, and L. Atzor. 2016. Smart Home Energy Management Including Renewable Sources: A QoE-Driven Approach. IEEE Transactions on Industrial Informatics.

    Google Scholar 

  12. Hom Chaudhuri, B., and M. Kumar. 2011. Market Based Allocation of Power in Smart Grid. In American Control Conference.

    Google Scholar 

  13. Neely, M.J., A.S. Tehrani, and A.G. Dimakis. (2010) Efficient Algorithms for Renewable Energy Allocation to Delay Tolerant Consumers. In IEEE International Conference on Smart Grid Communications.

    Google Scholar 

  14. Smart Grids and Renewable—A Guide for Effective Deployment. 2013.

    Google Scholar 

  15. Rama Devi, Boddu, Manjubala Bisi, and Rashmi Ranjan Rout. 2017. Fairness Index of Efficient Energy Allocation Schemes in a Tree Based Smart Grid. Pakistan Journal of Biotechnology 14 (2): 120–127.

    Google Scholar 

  16. Rama Devi, Boddu. Dynamic Weight Based Energy Slots Allocation and Pricing with Load in a Distributive Smart Grid. Journal of Advance Research in Dynamical & Control Systems 11: 419–433.

    Google Scholar 

  17. MATLAB. https://www.mathworks.com/products/matlab.html. Dated: 24.11.2018.

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Correspondence to Boddu Rama Devi .

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Rama Devi, B., Srujan Raju, K. (2020). Energy Distribution in a Smart Grid with Load Weight and Time Zone. In: Raju, K., Govardhan, A., Rani, B., Sridevi, R., Murty, M. (eds) Proceedings of the Third International Conference on Computational Intelligence and Informatics . Advances in Intelligent Systems and Computing, vol 1090. Springer, Singapore. https://doi.org/10.1007/978-981-15-1480-7_9

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