A Joint Risk- and Security-Constrained Control Framework for Real-Time Energy Scheduling of Islanded Microgrids

High penetration of intermittent renewable energy sources (RES) and unexpected disruptions (e.g., natural disasters) are fundamental challenges which can threaten the secure operation of microgrids, especially during the islanded condition, with no support from the upstream grid. This paper introduc...

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Bibliographic Details
Published in:IEEE transactions on smart grid 2022-09, Vol.13 (5), p.3354-3368
Main Authors: Nikkhah, Saman, Sarantakos, Ilias, Zografou-Barredo, Natalia-Maria, Rabiee, Abbas, Allahham, Adib, Giaouris, Damian
Format: Article
Language:English
Subjects:
conic programming
Contingency
Costs
Distributed generation
Economic impact
Islanded microgrid (IMG)
Microgrids
Mixed integer
Natural disasters
Optimization
Predictive control
Real time operation
Real-time systems
Renewable energy sources
risk
Risk management
Scheduling
Security
Uncertainty
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Summary:High penetration of intermittent renewable energy sources (RES) and unexpected disruptions (e.g., natural disasters) are fundamental challenges which can threaten the secure operation of microgrids, especially during the islanded condition, with no support from the upstream grid. This paper introduces a hierarchical tri-layer min-max-min joint risk- and security-constrained model predictive control (RSC-MPC) framework for real-time energy scheduling of islanded microgrids (IMGs) under the influence of uncertainty and real-time time-varying contingency conditions. While the first layer processes a pre-scheduling day-ahead optimisation, the second layer detects the worst-case contingency conditions by maximising the load curtailment and the mismatch between pre-scheduling (i.e., first layer) and real-time operation. The third layer implements the corrective security measures to minimise the negative effect of contingency conditions while accounting to the cost associated with the risk of uncertainty in the forecasted inputs. The third layer also explores the economic effects of the RES' uncertainty on the proposed RSC-MPC, considering the risk and energy procurement cost as conflicting objectives. The computational efficiency of the proposed hierarchical control system in terms of accuracy and processing time is guaranteed through a mixed integer conic programming model. The proposed RSC-MPC is tested in different case studies and its efficiency is validated by numerical results.
ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2022.3171816