2,904 research outputs found
Reliability assessment of microgrid with renewable generation and prioritized loads
With the increase in awareness about the climate change, there has been a
tremendous shift towards utilizing renewable energy sources (RES). In this
regard, smart grid technologies have been presented to facilitate higher
penetration of RES. Microgrids are the key components of the smart grids.
Microgrids allow integration of various distributed energy resources (DER) such
as the distributed generation (DGs) and energy storage systems (ESSs) into the
distribution system and hence remove or delay the need for distribution
expansion. One of the crucial requirements for utilities is to ensure that the
system reliability is maintained with the inclusion of microgrid topology.
Therefore, this paper evaluates the reliability of a microgrid containing
prioritized loads and distributed RES through a hybrid analytical-simulation
method. The stochasticity of RES introduces complexity to the reliability
evaluation. The method takes into account the variability of RES through Monte-
Carlo state sampling simulation. The results indicate the reliability
enhancement of the overall system in the presence of the microgrid topology. In
particular, the highest priority load has the largest improvement in the
reliability indices. Furthermore, sensitivity analysis is performed to
understand the effects of the failure of microgrid islanding in the case of a
fault in the upstream network
Efficient Decentralized Economic Dispatch for Microgrids with Wind Power Integration
Decentralized energy management is of paramount importance in smart
microgrids 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 microgrids 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 microgrid 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 microgrid, 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.Comment: To appear in IEEE GreenTech 2014. Submitted Sept. 2013; accepted Dec.
201
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