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

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

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Authors

M.E. Cruz Victorio



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.

Presentation Conference Type Conference Paper (Published)
Conference Name 14th IEEE PES PowerTech Conference
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
Public URL https://durham-repository.worktribe.com/output/1138865

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Accepted Conference Proceeding (2 Mb)
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