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Energy Cost Saving Tips in Distributed Power Networks

Energy Cost Saving Tips in Distributed Power Networks

Alain Tcheukam Siwe, Hamidou Tembine
Copyright: © 2016 |Pages: 23
ISBN13: 9781522500728|ISBN10: 1522500723|EISBN13: 9781522500735
DOI: 10.4018/978-1-5225-0072-8.ch002
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MLA

Siwe, Alain Tcheukam, and Hamidou Tembine. "Energy Cost Saving Tips in Distributed Power Networks." Smart Grid as a Solution for Renewable and Efficient Energy, edited by Ayaz Ahmad and Naveed Ul Hassan, IGI Global, 2016, pp. 26-48. https://doi.org/10.4018/978-1-5225-0072-8.ch002

APA

Siwe, A. T. & Tembine, H. (2016). Energy Cost Saving Tips in Distributed Power Networks. In A. Ahmad & N. Hassan (Eds.), Smart Grid as a Solution for Renewable and Efficient Energy (pp. 26-48). IGI Global. https://doi.org/10.4018/978-1-5225-0072-8.ch002

Chicago

Siwe, Alain Tcheukam, and Hamidou Tembine. "Energy Cost Saving Tips in Distributed Power Networks." In Smart Grid as a Solution for Renewable and Efficient Energy, edited by Ayaz Ahmad and Naveed Ul Hassan, 26-48. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-5225-0072-8.ch002

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Abstract

This chapter studies energy cost saving strategies in power networks. A prosumer is a user that not only consumes electricity, but can also produce and store electricity. Three tips are considered: distributed power network architecture, peak energy shaving with the integration of prosumers' contribution and prosumers market. The proposed distributed power network architecture reduces significantly the transmission costs and can reduce significantly the global energy cost up to 42 percent. Different types of prosumer who use self-charging renewable energy systems, are able to intelligently buy energy from, or sell it, to the power grid. Therein, prosumers interact during the purchase or sale of electric power using a double auction with negotiation mechanism. Using a two-step combined learning and optimization scheme, each prosumer can learn its optimal bidding strategy and forecast its energy production, consumption and storage. Our simulation results show that the integration of prosumers can reduce peak hour costs up to 17 percent and 6 percent for eligible prosumers.

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