Fault-Tolerant Optimization and Control of a Microgrid Operation in Networked Microgrids

Networked microgrid operation and control is supported by fault-tolerant optimization. In networked microgrids, the microgrid failure or dysconnectivity from the network is obvious and must be rectified and restored in real-time. For this purpose, we need advanced algorithms for fault-tolerant optimization and its control in networked microgrids operation. We have introduced a multi-objective genetic algorithm (MOGA) to solve the multi-objective optimization problem. Genetic algorithms being meta-heuristic techniques are used to solve formulated complex optimization problems; fault-tolerant optimization problems (FTOP). A fault-tolerant optimization problem (FTOP) has the possibility of partial components of the system failing or generating errors during the operation of networked microgrids. For this problem, we have determined the best possible solution which is obtained even in the presence of failure or errors as well. We have minimized the total cost of the system and provision of a consistent supply of energy in case of failure of a microgrid in the networked microgrids to get stable and reliable energy. FTOP problems mostly occur in critical and uncertain systems like microgrids in which reliable power is the demand from the customers with continuous availability.