Dynamic Optimal Power Flow Including Energy Storage with Adaptive Operation Costs
Author
Ju, Chengquan
Wang, Peng
Date of Issue
2015Conference Name
IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society
School
School of Electrical and Electronic Engineering
Interdisciplinary Graduate School
Interdisciplinary Graduate School
Research Centre
Energy Research Institute
Version
Accepted version
Abstract
In past few years, the developing technology of energy storage has greatly catalyzed the evolution of energy management in power systems. The availability of storage techniques makes it possible to integrate large-scale energy storages, mitigating supply/demand variation and fluctuations brought by renewables. This paper proposes an optimal power flow (OPF) model considering energy storage with adaptive operation costs to optimize power generation and storage scheduling in multiple time periods. The objective of the proposed model is to minimize the total generation cost of generators and the operation cost of energy storages. The operation cost coefficients of energy storage are auto-adjusted according to state of charge (SOC) and time-of-use (TOU) cost of generators, specifying the dynamic characteristics of energy storage. The effectiveness of the proposed OPF model is validated by the IEEE 14-bus system that in optimal scheduling the operation of energy storage is not only price-sensitive but also responsive to the ramping load change.
Subject
Optimal power flow
Energy storage
Energy storage
Type
Conference Paper
Rights
© 2015 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. The published version is available at: [http://dx.doi.org/10.1109/IECON.2015.7392323].
http://dx.doi.org/10.1109/IECON.2015.7392323
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