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Investigation of an optimized energy resource allocation algorithm for a community based virtual power plant
Okpako, O. Rajamani, Haile S. Pillai, Prashant Anuebunwa, U.R. Swarup, K.S.
Okpako, O.
Rajamani, Haile S.
Pillai, Prashant
Anuebunwa, U.R.
Swarup, K.S.
Publication Date
2016-09-01
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© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Abstract
Recently, significant advances in renewable energy generation have made it possible to consider consumers as prosumers. However, with increase in embedded generation, storage of electrical energy in batteries, flywheels and supercapacitors has become important so as to better utilize the existing grid by helping smooth the peaks and troughs of renewable electricity generation, and also of demand. This has led to the possibility of controlling the times when stored energy from these storage units is fed back to the grid. In this paper we look at how energy resource sharing is achieved if these storage units are part of a virtual power plant. In a virtual power plant, these storage units become energy resources that need to be optimally scheduled over time so as to benefit both prosumer and the grid supplier. In this paper, a smart energy resources allocation algorithm is presented for a virtual power plants using genetic algorithms. It is also proposed that the cause of battery depreciation be accounted for in the allocation of discharge rates. The algorithm was tested under various pricing scenarios, depreciation cost, as well as constraint. The results are presented and discussed. Conclusions were drawn, and suggestion for further work was made.
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Accepted manuscript
Citation
Okpako O, Rajamani H-S, Pillai P et al (2016) Investigation of an optimized energy
resource allocation algorithm for a community based virtual power plant. In: 2016 IEEE PES
PowerAfrica Conference. 28 Jun-3 Jul 2016, Livingstone, Zambia.
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Conference paper