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

Cruz Victorio, M. E. and Kazemtabrizi, B. and Shahbazi, M. (2021) 'Price Forecast Methodologies Comparison for Microgrid Control with Multi-Agent Systems.', 14th IEEE PES Power Tech Conference Madrid / Virtual, 28 Jun - 02 Jul 2021.

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.

Item Type:Conference item (Paper)
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:https://www.powertech2021.com/
Publisher statement:© 2021 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.
Date accepted:28 February 2021
Date deposited:18 May 2021
Date of first online publication:02 July 2021
Date first made open access:03 July 2021

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