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Published in:
Overview of Plug-in Electric Vehicles Technologies Read chapter Read first chapter

2015 | OriginalPaper | Chapter

5. Risk Averse Energy Hub Management Considering Plug-in Electric Vehicles Using Information Gap Decision Theory

Authors : Alireza Soroudi, Andrew Keane

Published in: Plug In Electric Vehicles in Smart Grids

Publisher: Springer Singapore

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Abstract

The energy hub is defined as the multi-input multi-output energy converter. It usually consists of various converters like thermal generators, combined heat and power (CHP), renewable energies and energy storage devices. The plug-in electric vehicles as energy storage devices can bring various flexibilities to energy hub management problem. These flexibilities include emission reduction, cost reduction, controlling financial risks, mitigating volatility of power output in renewable energy resources, active demand side management and ancillary service provision. In this chapter a comprehensive risk hedging model for energy hub management is proposed. The focus is placed on minimizing both the energy procurement cost and financial risks in energy hub. For controlling the undesired effects of the uncertainties, the Information gap decision theory (IGDT) technique is used as the risk management tool. The proposed model is formulated as a mixed integer linear programming (MILP) problem and solved using General Algebraic Modeling System (GAMS). An illustrative example is analyzed to demonstrate the applicability of the proposed method.

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previous chapter An Optimal and Distributed Control Strategy for Charging Plug-in Electrical Vehicles in the Future Smart Grid
next chapter Integration of Distribution Grid Constraints in an Event-Driven Control Strategy for Plug-in Electric Vehicles in a Multi-Aggregator Setting
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Metadata
Title
Risk Averse Energy Hub Management Considering Plug-in Electric Vehicles Using Information Gap Decision Theory
Authors
Alireza Soroudi
Andrew Keane
Copyright Year
2015
Publisher
Springer Singapore
Book
Plug In Electric Vehicles in Smart Grids

Print ISBN: 978-981-287-301-9

Electronic ISBN: 978-981-287-302-6

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-981-287-302-6_5

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