Application of microgrids in providing ancillary services to the utility grid
Alireza Majzoobi and
Amin Khodaei
Energy, 2017, vol. 123, issue C, 555-563
Abstract:
A microgrid optimal scheduling model is developed in this paper to demonstrate microgrid's capability in offering ancillary services to the utility grid. The application of localized ancillary services is of significant importance to grid operators as the growing proliferation of distributed renewable energy resources, mainly solar generation, is causing major technical challenges in supply-load balance. The proposed microgrid optimal scheduling model coordinates the microgrid net load with the aggregated consumers/prosumers net load in its connected distribution feeder to capture both inter-hour and intra-hour net load variations. In particular, net load variations for three various time resolutions are considered, including hourly ramping, 10-min based load following, and 1-min based frequency regulation. Numerical simulations on a test distribution feeder with one microgrid and several consumers/prosumers indicate the effectiveness of the proposed model and the viability of the microgrid application in supporting grid operation.
Keywords: Ancillary services; Frequency regulation; Load following; Microgrid; Optimal scheduling; Renewable energy (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (27)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544217301202
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:123:y:2017:i:c:p:555-563
DOI: 10.1016/j.energy.2017.01.113
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().