Open AccessOptimal operation management of a regional network of microgrids based on chance‐constrained model predictive control
Author(s) -
Bazmohammadi Najmeh,
Tahsiri Ahmadreza,
AnvariMoghaddam Amjad,
Guerrero Josep M.
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.2061
Subject(s) - microgrid , computer science , monte carlo method , renewable energy , model predictive control , grid , mathematical optimization , energy management , control (management) , control engineering , energy (signal processing) , engineering , mathematics , artificial intelligence , statistics , geometry , electrical engineering
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.