Abstract
In 20th century, many countries have liberalized their electricity market. This power markets liberalization has directed generation companies as well as wholesale buyers to undertake a greater intense risk exposure compared to the old centralized framework. In this framework, electricity price prediction has become crucial for any market player in their decision-making process as well as strategic planning. In this study, a prototype asymmetric-based neuro-fuzzy network (AGFINN) architecture has been implemented for short-term electricity prices forecasting for ISO New England market. AGFINN framework has been designed through two different defuzzification schemes. Fuzzy clustering has been explored as an initial step for defining the fuzzy rules while an asymmetric Gaussian membership function has been utilized in the fuzzification part of the model. Results related to the minimum and maximum electricity prices for ISO New England, emphasize the superiority of the proposed model over well-established learning-based models.
Highlights
IntroductionEnergy markets have experienced considerable changes. The energy liberalization in many countries dissolved a centralized integrated market and transformed it into a deregulated competitive one
During the past decades, energy markets have experienced considerable changes
In order to evaluate the performance of AGFINN NF models, all studies were carried out based on the same New England electricity price datasets
Summary
Energy markets have experienced considerable changes. The energy liberalization in many countries dissolved a centralized integrated market and transformed it into a deregulated competitive one. The aim of an electricity market is to reduce the electricity cost through this liberalization framework From this point of view, electricity could be considered as a “commodity” like other “trading” products in market. As electrical energy cannot be stored, a continuous stable condition between power generation and demand is always required. This energy “commodity” is a typical day-ahead market that does not permit for continuous trading like other financial markets. This is due to the fact that system operators need in advance information for checking the power schedule is in line with any transmission constraints. MCP is considered as the price for the entire system, in Energies 2020, 13, 1209; doi:10.3390/en13051209 www.mdpi.com/journal/energies
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