Abstract
A new probabilistic approach for microgrids (MGs) optimal energy management considering ac network constraints is proposed in this paper. The economic model of an energy storage system (ESS) is considered in the problem. The reduced unscented transformation (RUT) is applied in order to deal with the uncertainties related to the forecasted values of load demand, market price, and available outputs of renewable energy sources (RESs). Moreover, the correlation between market price and load demand is taken into account. Besides, the impact of the correlated wind turbines (WT) on MGs' energy management is studied. An enhanced JAYA (EJAYA) algorithm is suggested to achieve the best solution of the considered problem. The effective performance of the presented approach is verified by applying the suggested strategy on a modified IEEE 33-bus system. It can be observed that for dealing with probabilistic problems, the suggested RUT-EJAYA shows accurate results such as those of Monte Carlo (MC) while the computational burden (time and complexity) is lower.
| Original language | English |
|---|---|
| Article number | 8771129 |
| Journal | IEEE Systems Journal |
| Volume | 14 |
| Issue number | 2 |
| Pages (from-to) | 2703-2712 |
| Number of pages | 10 |
| ISSN | 1932-8184 |
| DOIs | |
| Publication status | Published - Jun 2020 |
| Externally published | Yes |
Bibliographical note
Funding Information:Manuscript received January 1, 2019; revised May 12, 2019; accepted July 3, 2019. Date of publication July 24, 2019; date of current version June 3, 2020. The work of J. P. S. Catalão was supported by FEDER funds through COMPETE 2020 and by Portuguese funds through FCT, under POCI-01-0145-FEDER-029803 (02/SAICT/2017). (Corresponding authors: Miadreza Shafie-khah; João P. S. Catalão).
Publisher Copyright:
© 2007-2012 IEEE.
Keywords
- EJAYA algorithm
- microgrid (MG) energy management
- reduced unscented transformation (RUT)
- uncertainty