S. Rajamand,
Volume 18, Issue 2 (6-2022)
Abstract
Fair distribution of generated power has a significant impact on the performance of the power system. Many methods have been proposed for the safe and secure operation of power systems under the uncertainties of distributed generators and system load. In this paper, we present an optimal power distribution algorithm for distributed generators against uncertainties and load changes of direct-current and alternating-current transmission systems. In this optimal algorithm, considering the stable-state constraints for all uncertainties is performed. In order to establish these constraints at the lowest cost, the adaptive droop coefficients are employed to optimize the power sharing, reloading and modifying the power coefficient of each distributed generator in the power system. Simulation results show the efficiency of the proposed method to improve the performance of the system and reduce the total cost. The voltage/power deviation from reference value in the proposed method is about 1-1.5% where in the conventional droop control, it is more than 2-3%. In addition, in the same uncertainty of the load/distributed generator power in the test system, proposed method requires 20% less power redistribution compared to the conventional droop method. Also, total cost increasing (due to uncertainty increasing) in the conventional droop method is higher than the proposed method (about 10-15%) which shows the robustness of the suggested method against uncertainty changes.
Shankarshan Prasad Tiwari, Ebha Koley,
Volume 18, Issue 4 (12-2022)
Abstract
In recent years, DC microgrid has attracted considerable attention of the research community because of the wide usage of DC power-based appliances. However, the acceptance of DC microgrid by power utilities is still limited due to the issues associated with the development of a reliable protection scheme. The high magnitude of DC fault current, its rapid rate of rising and absence of zero crossing hinders achieving reliable protection in DC microgrid. Further, the intermittency associated with the non-conventional distributed generators demands adaptiveness under varying weather conditions. In this paper, the above-mentioned issues are addressed by developing a bagging tree-based protection approach for a multi-terminal DC microgrid. The proposed scheme addresses the intermittency associated with renewable sources. It performs the functions of mode detection, fault detection/classification, and faulty section identification using local information of current and voltage signals only. The same avoids the communication network related drawbacks like data loss and latency.
Nguyen Cong Chinh,
Volume 20, Issue 3 (9-2024)
Abstract
This paper presents an intelligent meta-heuristic algorithm, named improved equilibrium optimizer (IEO), for addressing the optimization problem of multi-objective simultaneous integration of distributed generators at unity and optimal power factor in a distribution system. The main objective of this research is to consider the multi-objective function for minimizing total power loss, improving voltage deviation, and reducing integrated system operating costs with strict technical constraints. An improved equilibrium optimizer is an enhanced version of the equilibrium optimizer that can provide better performance, stability, and convergence characteristics than the original algorithm. For evaluating the effectiveness of the suggested method, the IEEE 69-bus radial distribution system is chosen as a test system, and simulation results from this method are also compared fairly with many previously existing methods for the same targets and constraints. Thanks to its ability to intelligently expand the search space and avoid local traps, the suggested method has become a robust stochastic optimization method in tackling complex optimization tasks.
