Incorporating forecasting and peer-to-peer negotiation frameworks into a distributed model predictive control approach for meshed electric networks

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Monasterios, Pablo R. Baldivieso and Verba, Nandor and Morris, Euan A and Konstantopoulos, George C. and Gaura, Elena and McArthur, Stephen (2022) Incorporating forecasting and peer-to-peer negotiation frameworks into a distributed model predictive control approach for meshed electric networks. IEEE Transactions on Control of Network Systems, 9 (3). pp. 1556-1568. ISSN 2325-5870 (https://doi.org/10.1109/TCNS.2022.3158806)

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Abstract

The continuous integration of renewable energy sources into power networks is causing a paradigm shift in energy generation and distribution with regard to trading and control. The intermittent nature of renewable sources affects the pricing of energy sold or purchased. The networks are subject to operational constraints, voltage limits at each node, rated capacities for the power electronic devices, and current bounds for distribution lines. These economic and technical constraints, coupled with intermittent renewable injection, may pose a threat to system stability and performance. In this article, we propose a novel holistic approach to energy trading composed of a distributed predictive control framework to handle physical interactions, i.e., voltage constraints and power dispatch, together with a negotiation framework to determine pricing policies for energy transactions. We study the effect of forecasting generation and consumption on the overall network's performance and market behaviors. We provide a rigorous convergence analysis for both the negotiation framework and the distributed control. Finally, we assess the impact of forecasting in the proposed system with the aid of testing scenarios.

ORCID iDs

Monasterios, Pablo R. Baldivieso, Verba, Nandor, Morris, Euan A ORCID logoORCID: https://orcid.org/0000-0001-7799-1402, Konstantopoulos, George C., Gaura, Elena and McArthur, Stephen ORCID logoORCID: https://orcid.org/0000-0003-1312-8874;
  • Item type:Article
    ID code:79703
    Dates:
    Date
    Event
    1 September 2022
    Published
    15 March 2022
    Published Online
    21 February 2022
    Accepted
    Notes:© 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.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Faculty of Engineering
    Depositing user: Pure Administrator
    Date deposited:23 Feb 2022 16:09
    Last modified:02 Dec 2024 01:26
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/79703
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