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Title: Joint optimization of generation and storage in the presence of wind
Authors: Liu, Fei
Giulietti, Monica
Chen, Bo
Issue Date: 2016
Publisher: © Institution of Engineering and Technology
Citation: LIU, F., GIULIETTI, M. and CHEN, B., 2016. Joint optimization of generation and storage in the presence of wind. IET Renewable Power Generation, 10 (10), pp. 1477-1487.
Abstract: We study an independent grid where the penetration of wind energy is high and exploit the joint planning of energy storage and a renewable energy source, as it can potentially result in a more economical and efficient energy system. More specifically, we consider an energy system that consists of a gas-fired plant, and a small wind farm with a capacity for energy storage. We assume that the gas-fired plant has a maximum generation capacity that is no more than the electricity demand. We first propose an optimization model with known wind speed and electricity demand. Then we gradually extend this deterministic model to take into account the stochastic nature of the renewable energy source and electricity demand. Furthermore, we consider the possibility of connecting our system to the National Grid, which we import from or export to when our system has an energy shortage or surplus in meeting the demand. Our results provide helpful insights in planning the joint deployment of generation capacity and energy storage, and show that the system operates more efficiently and economically when it is connected to the National Grid.
Description: This paper is a postprint of a paper submitted to and accepted for publication in IET Renewable Power Generation and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library.
Sponsor: Monica Giulietti acknowledges financial support from EPRSC project No. EP/K002228/1 (IMAGES).
Version: Accepted for publication
DOI: 10.1049/iet-rpg.2015.0547
URI: https://dspace.lboro.ac.uk/2134/21645
Publisher Link: http://dx.doi.org/10.1049/iet-rpg.2015.0547
ISSN: 1752-1416
Appears in Collections:Published Articles (Business School)

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