Hierarchical dispatch of multiple microgrids using nodal price: an approach from consensus and replicator dynamics
A hierarchical approach for the energy management of geographically close microgrids connected through a dedicated AC power network is proposed in this paper. The proposed approach consists of a two-layer energy management system (EMS) for networked microgrids. In the lower layer, each microgrid sol...
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doaj-b0b8d6c6ab884e5591bf966d4d70db0a2021-04-23T16:13:54ZengIEEEJournal of Modern Power Systems and Clean Energy2196-54202019-01-01761573158410.1007/s40565-019-0538-18964537Hierarchical dispatch of multiple microgrids using nodal price: an approach from consensus and replicator dynamicsMiguel A. Velasquez0Oscar Torres-Perez1Nicanor Quijano2Angela Cadena3Universidad de los Andes,Department of Electrical and Electronics Engineering,Bogotá,ColombiaUniversidad de los Andes,Department of Electrical and Electronics Engineering,Bogotá,ColombiaUniversidad de los Andes,Department of Electrical and Electronics Engineering,Bogotá,ColombiaUniversidad de los Andes,Department of Electrical and Electronics Engineering,Bogotá,ColombiaA hierarchical approach for the energy management of geographically close microgrids connected through a dedicated AC power network is proposed in this paper. The proposed approach consists of a two-layer energy management system (EMS) for networked microgrids. In the lower layer, each microgrid solves its own economic dispatch problem through a distributed model predictive control approach that respects capacity limits and ramp-rate constraints of distributed generation. In the upper layer, the energy trading in the network of microgrids decides how to optimally trade the energy based on the marginal cost information from the lower layer in order to improve global optimization objectives, e.g., social welfare. In order to solve the trading problem, a consensus-based algorithm and a replicator dynamics algorithm are proposed assuming that the marginal cost function of the microgrid is known and linear. It is shown that both algorithms converge to the same solution, which is equivalent to the minimization of operation costs. The consensus-based algorithm is extended in order to tackle more general marginal cost functions and trading network constraints. Moreover, the effect of ramp constraints and network limits is studied. Simulations show the effectiveness of the proposed algorithms for three interconnected microgrids with different characteristics.https://ieeexplore.ieee.org/document/8964537/ConsensusEconomic dispatchHierarchical controlNetworked microgridsRamp limitsReplicator dynamics |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Miguel A. Velasquez Oscar Torres-Perez Nicanor Quijano Angela Cadena |
spellingShingle |
Miguel A. Velasquez Oscar Torres-Perez Nicanor Quijano Angela Cadena Hierarchical dispatch of multiple microgrids using nodal price: an approach from consensus and replicator dynamics Journal of Modern Power Systems and Clean Energy Consensus Economic dispatch Hierarchical control Networked microgrids Ramp limits Replicator dynamics |
author_facet |
Miguel A. Velasquez Oscar Torres-Perez Nicanor Quijano Angela Cadena |
author_sort |
Miguel A. Velasquez |
title |
Hierarchical dispatch of multiple microgrids using nodal price: an approach from consensus and replicator dynamics |
title_short |
Hierarchical dispatch of multiple microgrids using nodal price: an approach from consensus and replicator dynamics |
title_full |
Hierarchical dispatch of multiple microgrids using nodal price: an approach from consensus and replicator dynamics |
title_fullStr |
Hierarchical dispatch of multiple microgrids using nodal price: an approach from consensus and replicator dynamics |
title_full_unstemmed |
Hierarchical dispatch of multiple microgrids using nodal price: an approach from consensus and replicator dynamics |
title_sort |
hierarchical dispatch of multiple microgrids using nodal price: an approach from consensus and replicator dynamics |
publisher |
IEEE |
series |
Journal of Modern Power Systems and Clean Energy |
issn |
2196-5420 |
publishDate |
2019-01-01 |
description |
A hierarchical approach for the energy management of geographically close microgrids connected through a dedicated AC power network is proposed in this paper. The proposed approach consists of a two-layer energy management system (EMS) for networked microgrids. In the lower layer, each microgrid solves its own economic dispatch problem through a distributed model predictive control approach that respects capacity limits and ramp-rate constraints of distributed generation. In the upper layer, the energy trading in the network of microgrids decides how to optimally trade the energy based on the marginal cost information from the lower layer in order to improve global optimization objectives, e.g., social welfare. In order to solve the trading problem, a consensus-based algorithm and a replicator dynamics algorithm are proposed assuming that the marginal cost function of the microgrid is known and linear. It is shown that both algorithms converge to the same solution, which is equivalent to the minimization of operation costs. The consensus-based algorithm is extended in order to tackle more general marginal cost functions and trading network constraints. Moreover, the effect of ramp constraints and network limits is studied. Simulations show the effectiveness of the proposed algorithms for three interconnected microgrids with different characteristics. |
topic |
Consensus Economic dispatch Hierarchical control Networked microgrids Ramp limits Replicator dynamics |
url |
https://ieeexplore.ieee.org/document/8964537/ |
work_keys_str_mv |
AT miguelavelasquez hierarchicaldispatchofmultiplemicrogridsusingnodalpriceanapproachfromconsensusandreplicatordynamics AT oscartorresperez hierarchicaldispatchofmultiplemicrogridsusingnodalpriceanapproachfromconsensusandreplicatordynamics AT nicanorquijano hierarchicaldispatchofmultiplemicrogridsusingnodalpriceanapproachfromconsensusandreplicatordynamics AT angelacadena hierarchicaldispatchofmultiplemicrogridsusingnodalpriceanapproachfromconsensusandreplicatordynamics |
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1721512452035706880 |