Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques

Highlights: • The recent planning methods for distributed generation are critically reviewed. • A comprehensive review and comparison of analytical techniques is provided. • The obtained insights can guide future deployment of distributed generation. - Abstract: The rapid development of distributed generation in different forms and capacities is transforming the conventional planning of distribution networks. Despite the benefits offered by renewable distributed generation technologies, several economic and technical challenges can result from the inappropriate integration of distributed generation in existing distribution networks. Therefore, the optimal planning of distributed generation is of paramount importance to ensure that the performance of distribution network can meet the expected power quality, voltage stability, power loss reduction, reliability and profitability. In this paper, we firstly discuss several conventional and metaheuristic methodologies to address the optimal distributed generation planning problem. Metaheuristic algorithms are often used as they offer more flexibility, particularly for multi-objective planning problems without the pursuit of globally optimized solution. Analytical techniques are considered suitable for modeling power system mechanisms and validating numerical methods. Then, this paper conducts a comprehensive review and critical discussion of state-of-the-art analytical techniques for optimal planning of renewable distributed generation. The analytical techniques are discussed in detail in six categories, i.e. exact loss formula, loss sensitivity factor, branch current loss formula, branch power flow loss formula, equivalent current injection and phasor feeder current injection. In addition, a comparative analysis of analytical techniques is presented to show their suitability for distributed generation planning in terms of various optimization criteria. Finally, we present conclusive remarks along with a set of recommendations and future challenges for optimal planning of distributed generation in modern power distribution networks.