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Economical Operation of Thermal Generating Units Integrated with Smart Houses

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PRICAI 2012: Trends in Artificial Intelligence (PRICAI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7458))

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Abstract

This paper presents an economic optimal operation strategy for thermal power generation units integrated with smart houses. With the increased competition in retail and power sector reasoned by the deregulation and liberalization of power market make optimal economic operation extremely important. Moreover, the energy consumption is multiplying due to the proliferation of all-electric houses. Which is why, controllable loads such as electric water heater, heat pump (HP) and electric vehicles (EV) have great potentials to be introduced in a smart-grid oriented environment. The presented strategy models thermal power generators with controllable loads (HP and EV) in a coordinated manner in order to reduce the production cost as a measure of supply side optimization. As of demand side, the electricity cost is minimized by means of reducing the interconnection point (IP) power flow. Particle swarm optimization (PSO) is applied to solve both of the optimization problems in efficient way. A hypothetical power system (with practical constraints and configurations) is tested to validate the performance of the proposed method.

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References

  1. Chakraborty, S., Senjyu, T., Saber, A.Y., Yona, A., Funabashi, T.: Optimal Thermal Unit Commitment Integrated with Renewable Energy Sources Using Advanced Particle Swarm Optimization. IEEJ Trans. on Electrical and Electronics Eng. 4(5), 609–617 (2009)

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© 2012 Springer-Verlag Berlin Heidelberg

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Chakraborty, S., Ito, T., Senjyu, T. (2012). Economical Operation of Thermal Generating Units Integrated with Smart Houses. In: Anthony, P., Ishizuka, M., Lukose, D. (eds) PRICAI 2012: Trends in Artificial Intelligence. PRICAI 2012. Lecture Notes in Computer Science(), vol 7458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32695-0_3

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  • DOI: https://doi.org/10.1007/978-3-642-32695-0_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32694-3

  • Online ISBN: 978-3-642-32695-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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