TY - JOUR
T1 - Optimal Operation Management of a Regional Network of Microgrids Based On Chance-Constrained Model Predictive Control
AU - Bazmohammadi, Najmeh
AU - Tahsiri, Ahmadreza
AU - Anvari-Moghaddam, Amjad
AU - Guerrero, Josep M.
PY - 2018/8
Y1 - 2018/8
N2 - A regional network of microgrids includes a cluster of microgrids located in a neighbourhood area connecting together through power lines. In this study, the problem of operation management of networked-microgrids is considered. The main goal is to develop an efficient strategy to control local operation of each microgrid including the amount of energy to be requested from the main grid and the optimal charging/discharging patterns of batteries along with the transferred power among microgrids considering system's technical constraints. Accounting for system uncertainty due to the presence of renewable energy sources and variability of loads, the problem is formulated in the framework of chance-constrained model predictive control. Moreover, the Monte Carlo algorithm is adopted to generate discrete random scenarios to evaluate the solutions. Simulation studies have been exemplarily carried out in order to show the effectiveness of the proposed approach.
AB - A regional network of microgrids includes a cluster of microgrids located in a neighbourhood area connecting together through power lines. In this study, the problem of operation management of networked-microgrids is considered. The main goal is to develop an efficient strategy to control local operation of each microgrid including the amount of energy to be requested from the main grid and the optimal charging/discharging patterns of batteries along with the transferred power among microgrids considering system's technical constraints. Accounting for system uncertainty due to the presence of renewable energy sources and variability of loads, the problem is formulated in the framework of chance-constrained model predictive control. Moreover, the Monte Carlo algorithm is adopted to generate discrete random scenarios to evaluate the solutions. Simulation studies have been exemplarily carried out in order to show the effectiveness of the proposed approach.
KW - model predictive control
KW - microgrid
KW - chance-constrained
KW - optimization
UR - http://www.scopus.com/inward/record.url?scp=85051656420&partnerID=8YFLogxK
U2 - 10.1049/iet-gtd.2017.2061
DO - 10.1049/iet-gtd.2017.2061
M3 - Journal article
SN - 1751-8687
VL - 12
SP - 3772
EP - 3779
JO - IET Generation, Transmission & Distribution
JF - IET Generation, Transmission & Distribution
IS - 15
ER -