TY - GEN
T1 - Efficient decentralized economic dispatch for microgrids with wind power integration
AU - Zhang, Yu
AU - Giannakis, Georgios B.
PY - 2014
Y1 - 2014
N2 - Decentralized energy management is of paramount importance in smart micro grids with renewables for various reasons including environmental friendliness, reduced communication overhead, and resilience to failures. In this context, the present work deals with distributed economic dispatch and demand response initiatives for grid-connected micro grids with high-penetration of wind power. To cope with the challenge of the wind's intrinsically stochastic availability, a novel energy planning approach involving the actual wind energy as well as the energy traded with the main grid, is introduced. A stochastic optimization problem is formulated to minimize the micro grid net cost, which includes conventional generation cost as well as the expected transaction cost incurred by wind uncertainty. To bypass the prohibitively high-dimensional integration involved, an efficient sample average approximation method is utilized to obtain a solver with guaranteed convergence. Leveraging the special infrastructure of the micro grid, a decentralized algorithm is further developed via the alternating direction method of multipliers. Case studies are tested to corroborate the merits of the novel approaches.
AB - Decentralized energy management is of paramount importance in smart micro grids with renewables for various reasons including environmental friendliness, reduced communication overhead, and resilience to failures. In this context, the present work deals with distributed economic dispatch and demand response initiatives for grid-connected micro grids with high-penetration of wind power. To cope with the challenge of the wind's intrinsically stochastic availability, a novel energy planning approach involving the actual wind energy as well as the energy traded with the main grid, is introduced. A stochastic optimization problem is formulated to minimize the micro grid net cost, which includes conventional generation cost as well as the expected transaction cost incurred by wind uncertainty. To bypass the prohibitively high-dimensional integration involved, an efficient sample average approximation method is utilized to obtain a solver with guaranteed convergence. Leveraging the special infrastructure of the micro grid, a decentralized algorithm is further developed via the alternating direction method of multipliers. Case studies are tested to corroborate the merits of the novel approaches.
KW - ADMM
KW - Microgrids
KW - economic dispatch
KW - renewable energy
KW - sample average approximation
UR - http://www.scopus.com/inward/record.url?scp=84903519062&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84903519062&partnerID=8YFLogxK
U2 - 10.1109/GREENTECH.2014.12
DO - 10.1109/GREENTECH.2014.12
M3 - Conference contribution
AN - SCOPUS:84903519062
SN - 9781479939336
T3 - IEEE Green Technologies Conference
SP - 7
EP - 12
BT - Proceedings - 2014 6th Annual IEEE Green Technologies Conference, GREENTECH 2014
PB - IEEE Computer Society
T2 - 2014 6th Annual IEEE Green Technologies Conference, GREENTECH 2014
Y2 - 3 April 2014 through 4 April 2014
ER -