| Issue |
E3S Web Conf.
Volume 115, 2019
2019 The 2nd International Conference on Electrical Engineering and Green Energy (CEEGE 2019)
|
|
|---|---|---|
| Article Number | 01007 | |
| Number of page(s) | 5 | |
| Section | Electronical Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/201911501007 | |
| Published online | 02 September 2019 | |
Selection of Optimal Variant of Hybrid System under Conditions of Uncertainty
TU-Sofia, EPF-Sliven, Bulgaria
* Corresponding author: misho.ivanov@abv.bg
The aim of the study is to select an optimal variant of a hybrid system under conditions of uncertainty according to selected criteria. The problems of the study are the different options for building the hybrid system and choosing an adequate criterion for choosing the optimal variant. The study covers analysis of three variants of building up a hybrid system for supplying of autonomous electric load. The three variants are: introduction of an active user for equalizing the load schedule; introduction of additional generating source for covering the peak portion of the load schedule; covering the peak portion of the load by using an additional generating source and diesel generator. An optimal variant is selected under the conditions of uncertainty according to two criteria: minimum discounted expenses and loss of power. To this effect, the method of Mathematical hierarchical game theory analysis is applied. As a result of the study, the appropriate criteria for choosing an optimal variant for building a hybrid system are obtained. The results obtained allow to set a different degree of significance of the formulated basic criteria in the computational algorithm for decision making for the construction of the hybrid system.
© 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, 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.