Distributed generators (DGs) have emerged as an advanced technology for satisfying growing energy demands and significantly mitigating the pollution caused by emissions. Microgrids (MGs) are attractive energy systems because they offer the reliable integration of DGs into the utility grid. An MG-based approach uses a self-sustained system that can operate in a grid-tied mode under normal conditions, as well as in an islanded mode when grid disturbance occurs. Islanding detection is essential; islanding may injure utility operators and disturb electricity generation and supply because of unsynchronized re-closure. In MGs, an energy management system (EMS) is essential for the optimal use of DGs in intelligent, sustainable, reliable, and integrated ways. In this comprehensive review, the classification of different operating modes of MGs, islanding detection techniques (IDTs), and EMSs are presented and discussed. This review shows that the existing IDTs and EMSs can be used when operating MGs. However, further development of IDTs and EMSs is still required to achieve more reliable operation and cost-effective energy management of MGs in the future. This review also highlights various MG challenges and recommendations for the operation of MGs, which will enhance the cost, efficiency, and reliability of MG operation for next-generation smart grid applications.

The electric vehicle (EV) is considered a premium solution to global warming and various types of pollution. Nonetheless, a key concern is the recharging of EV batteries. Therefore, this study proposes a novel approach that considers the costs of transportation loss, buildup, and substation energy loss and that incorporates harmonic power loss into optimal rapid charging station (RCS) planning. A novel optimization technique, called binary lightning search algorithm (BLSA), is proposed to solve the optimization problem. BLSA is also applied to a conventional RCS planning method. A comprehensive analysis is conducted to assess the performance of the two RCS planning methods by using the IEEE 34-bus test system as the power grid. The comparative studies show that the proposed BLSA is better than other optimization techniques. The daily total cost in RCS planning of the proposed method, including harmonic power loss, decreases by 10% compared with that of the conventional method.

This paper portrays the development of a concession-investment optimization model for optimizing the winning potential of a concession-bid from the prospective promoters' viewpoints by taking into account imprecise investment parameters. A financial performance measure has been developed to quantify bid-winning potential. Fuzzy set theory is embedded into a genetic algorithm to optimize bid-winning prospects of concession schemes under uncertainty. The fuzzy vertex method accomplishes propagation of uncertainty in cash flows arising from imprecision in estimation of investment parameters. Genetic algorithm solves the optimization routine. The developed model yields global near-optimal solution of bid-winning potential with contributing values of concessionary items: concession length, base price, and equity level under uncertain investment environment. A numerical example demonstrates model capabilities. The model results would help promoters devise a profitable, yet competitive, financial proposal.Griffith Sciences, Griffith School of EngineeringNo Full Tex