Price Forecast Methodologies Comparison for Microgrid Control with Multi-Agent Systems

Cruz Victorio, M.E.; Kazemtabrizi, B.; Shahbazi, M.

doi:10.1109/powertech46648.2021.9494970

Price Forecast Methodologies Comparison for Microgrid Control with Multi-Agent Systems

Cruz Victorio, M.E.; Kazemtabrizi, B.; Shahbazi, M.

Authors

M.E. Cruz Victorio

Dr Behzad Kazemtabrizi behzad.kazemtabrizi@durham.ac.uk
Associate Professor

Dr Mahmoud Shahbazi mahmoud.shahbazi@durham.ac.uk
Associate Professor

Abstract

Multi-Agent systems offer a way to control distributed generation in microgrids, reliability and cost minimisation capabilities can be improved by price forecast methodologies that can be deployed without the need of external control signals. This paper presents and compares two suitable electricity price forecast methodologies for use in distributed control of Microgrids’ resources using Multi-Agents: Markov Chain Monte Carlo simulations with heuristic and numerical optimisation and price prediction with Non-linear Auto Regressive Artificial Neural Networks with different internal architectures. The methods are evaluated using MAPE and RMSE functions for the UK electricity market data. It was found that the proposed heuristic model has less error than the Neural Networks only when the price data contains outliers.

Citation

Cruz Victorio, M., Kazemtabrizi, B., & Shahbazi, M. (2021). Price Forecast Methodologies Comparison for Microgrid Control with Multi-Agent Systems. . https://doi.org/10.1109/powertech46648.2021.9494970

Conference Name	14th IEEE PES PowerTech Conference
Conference Location	Madrid, Spain
Start Date	Jun 28, 2023
End Date	Jul 2, 2021
Acceptance Date	Feb 28, 2021
Online Publication Date	Jul 29, 2021
Publication Date	2021
Deposit Date	May 17, 2021
Publicly Available Date	Jul 3, 2021
Publisher	Institute of Electrical and Electronics Engineers
DOI	https://doi.org/10.1109/powertech46648.2021.9494970

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