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ELM-Fuzzy Method for Automated Decision-Making in Price Directed Electricity Markets

Alamaniotis, Miltiadis; Karagiannis, Georgios

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Authors

Miltiadis Alamaniotis



Abstract

Among many domains application of information technologies has also transformed electricity markets. Price directed markets refer to the driving the electricity consumption by controlling the electricity prices in real time. This paper frames itself in such an electricity market, where consumers receive the prices and they respond with their demand for the next hour in real time. Response is performed by a smart meter that is equipped with tailored algorithms that make decisions based on the preferences of the customer. In this paper, a responding method is proposed that is based on Extreme Learning Machine (ELM) and Fuzzy Logic Inference. The synergism of the two tools allows the automated decision making where the interference of the human customer is minimal. The proposed method, called ELM-Fuzzy, is presented and tested on a set of real-world data. Results demonstrate the efficiency of the ELM-Fuzzy method to make fast and optimal decisions aiming at reducing the electricity expenses of the customer.

Citation

Alamaniotis, M., & Karagiannis, G. (2019, September). ELM-Fuzzy Method for Automated Decision-Making in Price Directed Electricity Markets. Presented at 2019 16th International Conference on the European Energy Market (EEM), Ljubljana, Slovenia

Presentation Conference Type Conference Paper (published)
Conference Name 2019 16th International Conference on the European Energy Market (EEM)
Start Date Sep 18, 2019
End Date Sep 20, 2019
Online Publication Date Nov 28, 2019
Publication Date 2019
Deposit Date Oct 30, 2020
Publicly Available Date Aug 12, 2021
Publisher Institute of Electrical and Electronics Engineers
DOI https://doi.org/10.1109/eem.2019.8916549
Public URL https://durham-repository.worktribe.com/output/1139958

Files

Accepted Conference Proceeding (167 Kb)
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© 2019 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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