Optimal bidding strategy of microgrid with uncertainty of res in day ahead electricity market

1Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Microgrid is the most efficient way of integrating renewable generating sources in the low voltage network. This paper proposes a mathematical model for bidding power in low voltage grid connected microgrid system in an electricity market having pump storage plant. The optimization problem has been modeled and simulated using the CONOPT solver in GAMS environment interfaced with MATLAB. The storage units have been used to counter the impact due to uncertainty of the solar power and the load demand. The optimal bidding prices have been obtained for various renewable generating units in case of over and under production situations. Penalty factors have been imposed to manage the power imbalance which also helps in overall reduction of the operational cost. Pumped storage unit has been taken to obtain optimal bidding and minimized operational cost of the system.

References Powered by Scopus

Some aspects of stability in microgrids

386Citations
N/AReaders
Get full text

Microgrid supervisory controllers and energy management systems: A literature review

365Citations
N/AReaders
Get full text

Optimal bidding strategy for microgrids considering renewable energy and building thermal dynamics

356Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Impact of optimal sized pump storage unit on microgrid operating cost and bidding in electricity market

10Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Kumar, D., Verma, Y. P., & Khanna, R. (2019). Optimal bidding strategy of microgrid with uncertainty of res in day ahead electricity market. International Journal of Recent Technology and Engineering, 8(3), 3964–3971. https://doi.org/10.35940/ijrte.C5343.098319

Readers' Seniority

Tooltip

Professor / Associate Prof. 2

67%

PhD / Post grad / Masters / Doc 1

33%

Readers' Discipline

Tooltip

Engineering 2

67%

Business, Management and Accounting 1

33%

Save time finding and organizing research with Mendeley

Sign up for free