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Household level distributed energy management system integrating renewable energy sources and electric vehicles.

Gosselin, Daniel and Jiang, Jing and Sun, Hongjian (2017) 'Household level distributed energy management system integrating renewable energy sources and electric vehicles.', in IEEE 85th Vehicular Technology Conference (VTC2017-Spring) : 4–7 June 2017, Sydney, Australia ; proceedings. Piscataway: IEEE, pp. 1-5.

Abstract

To reduce the burden on data communication in smart girds, household level distributed energy management systems have become increasingly vital due to their capability of distributed intelligence and scheduling devices. This paper studies the optimal management of storage and electric vehicles at a household level when subject to financial constraints. A model using a real-time pricing structure is used to minimise the final consumer cost, whilst responding to power consumption limits set by the supplier. Implementation of the limits and pricing structure allow the supplier to better balance changes and discrepancies in both demand values and generation values. Using real data, models for solar generation, household load demand, and the pricing structure are proposed and integrated into the overall model for the household system. The model for the household system optimises the power taken from the grid and the power stored for the lowest end cost to the user. A series of laboratory evaluations are run to compare the effects of the electric vehicle, solar generation and limits on the household, and considerations are made to the financial and practical implications of these effects. Evaluation results show important benefits from soft limiting household consumption. This allows a more robust and efficient smart grid system that creates better communication between the supplier and the consumer.

Item Type:Book chapter
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1109/vtcspring.2017.8108626
Publisher statement:© 2017 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:05 March 2017
Date deposited:21 March 2017
Date of first online publication:16 November 2017
Date first made open access:No date available

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