MATEC Web Conf.
Volume 260, 20192018 7th International Conference on Power Science and Engineering (ICPSE 2018)
|Number of page(s)||5|
|Section||Electronics and Electrical Automation|
|Published online||25 January 2019|
Development of an Optimization Model to Manage Imbalances in Power Systems by Local Power Retail Companies
Professor, Department of Electrical Engineering and Information Systems, Graduate School of the University of Tokyo, 113-8656 Tokyo, Japan
The feed-in tariff (FIT) programs resulted in rapid growth of renewable power sources in various countries. In Japan, the program particularly triggered explosive growth of solar power generations because of its short lead-time and high tariff level. Although mass introduction of renewable power sources certainly contributes to reduce CO2 emissions, it causes serious instability issues in power systems. One of the most serious issues is management of imbalances resulting from forecast errors in solar power generations. These imbalances must be compensated so as to keep stable operation in power systems. On the other hand, local power retail companies are increasing nowadays in various countries including Japan. These companies are mainly procuring renewable power sources such as solar power systems.Taking these circumstances into consideration, this article aims at exploring measures to manage the imbalances of power systems by local power retail companies. For this purpose, we developed a model in mixed integer linear programming to operate power systems dealing with the imbalances. Evaluated results using the model indicated the followings; appropriate adoption of stationary or home batteries is shown to economically compensate the imbalances by local power retail companies.
© The Authors, published by EDP Sciences, 2019
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.