Version 1
: Received: 9 November 2017 / Approved: 10 November 2017 / Online: 10 November 2017 (10:08:01 CET)
How to cite:
Pilz, M.; Al-Fagih, L.; Pfluegel, E. Energy Storage Scheduling with an Advanced Battery Model: A Game–Theoretic Approach. Preprints2017, 2017110069. https://doi.org/10.20944/preprints201711.0069.v1
Pilz, M.; Al-Fagih, L.; Pfluegel, E. Energy Storage Scheduling with an Advanced Battery Model: A Game–Theoretic Approach. Preprints 2017, 2017110069. https://doi.org/10.20944/preprints201711.0069.v1
Pilz, M.; Al-Fagih, L.; Pfluegel, E. Energy Storage Scheduling with an Advanced Battery Model: A Game–Theoretic Approach. Preprints2017, 2017110069. https://doi.org/10.20944/preprints201711.0069.v1
APA Style
Pilz, M., Al-Fagih, L., & Pfluegel, E. (2017). Energy Storage Scheduling with an Advanced Battery Model: A Game–Theoretic Approach. Preprints. https://doi.org/10.20944/preprints201711.0069.v1
Chicago/Turabian Style
Pilz, M., Luluwah Al-Fagih and Eckhard Pfluegel. 2017 "Energy Storage Scheduling with an Advanced Battery Model: A Game–Theoretic Approach" Preprints. https://doi.org/10.20944/preprints201711.0069.v1
Abstract
Energy storage systems will play a key role for individual users in the future smart grid. They serve two purposes: (i) handling the intermittent nature of renewable energy resources for a more reliable and efficient system, and (ii) preventing the impact of blackouts on users and allowing for more independence from the grid, while saving money through load-shifting. In this paper we investigate the latter scenario by looking at a neighbourhood of 25 households whose demand is satisfied by one utility company. Assuming the users possess lithium-ion batteries, we answer the question of how each household can make the best use of their individual storage system given a real-time pricing policy. To this end, each user is modelled as a player of a non-cooperative scheduling game. The novelty of the game lies in the advanced battery model, which incorporates charging and discharging characteristics of lithium-ion batteries. The action set for each player comprises day-ahead schedules of their respective battery usage. We analyse different user behavior and are able to obtain a realistic and applicable understanding of the potential of these systems. As a result, we show the correlation between the efficiency of the battery and the outcome of the game.
Keywords
game theory; smart grid; energy storage; battery modelling; demand-side management; load-shaping
Subject
Engineering, Energy and Fuel Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
