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

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.