The efficient operation of electrical distribution systems is critical in modern industry, as it directly impacts the reliability, stability, and cost-effectiveness of delivering electricity to consumers. Capacitors are included in radial distribution systems to improve voltage profile and minimize losses by providing reactive power. Consequently, losses are reduced as the reactive power flow component is compensated. Furthermore, re-configuration of the distribution network, which involves altering the open/closed status of switches, is a vital approach that affects the steady flow of electricity through the network. Network reconfiguration and Optimal capacitor placement are essential techniques for enhancing the performance of the distribution networks. This study utilizes the Cuckoo Search Algorithm (CSA) to solve the problems of network reconfiguration and Optimal capacitor placement. The primary objective is to minimize power losses while ensuring that the voltage profile and reliability of the distribution system satisfy industry-level standards. The proposed method was tested on the IEEE 33 bus network. Five different scenarios were considered. The simulations were conducted in MATLAB software. The acquired improvements in the power loss reduction and voltage profile corroborate the effectiveness of this novel approach. Compared to previously explored methods, the results of the proposed scheme for solving Optimal capacitor placement and network reconfiguration individually were found to be more effective in terms of reducing power loss (3.12% and 4.02%, respectively).

In this paper, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) based approach is presented for distribution system reconfiguration. In contrast to the conventional GA based methods, the proposed approach does not require weighting factors for conversion of multi-objective function into an equivalent single objective function. In order to illustrate the performance of the proposed method, 33-bus and 69-bus distribution networks have been employed which have led to the desired results.

Optimal capacitor placement, considering power system loss reduction, voltage profile improvement, line reactive power decrease and power factor correction, is of particular importance in power system planning and control. The distribution system operator calculates the Optimal place, number and capacity of capacitors based on two major purposes: active power loss reduction and return on investment maximization. In this paper, the optimization problem of various values of economic amount of reactive power is formulated, then after evaluation of objective function and implementation of optimization algorithm for each value, the optimum capacity of capacitors and their arrangement in load nodes of power system are extracted. Also, using the proposed objective function, the threshold price of reactive power selling can be calculated, thus the investment of capacitor installation will be beneficial for distribution system operator.

This paper investigates an Optimal adaptive controller based on reinforcement learning while considering orbital perturbations. The controller can achieve mission goals, online without any model. reconfiguration capabilities provide great flexibility in achieving formation flying mission goals. In reconfiguration, it is desired that spacecrafts migrate from the current formation to a new formation, thus achieving mission goals. Orbital perturbations, difficulties in extracting exact mathematical models, and unknown system dynamics make the Optimal reconfiguration problem challenging. Due to the digital nature of spacecraft computer systems, controllers have to be implemented digitally. Accordingly, this paper introduces an adaptive Optimal digital controller for a discounted generalized cost function. The stability of the proposed controller is proven by the Lyapunov method. Then, using the Q-learning method, an algorithm is presented so that the controller can find the Optimal control gains in a model-free fashion. Finally, numerical simulations of a formation flying mission scenario, confirm the effectiveness of this method.

A novel approach is presented for the reconfiguration of satellite constellations based on Lambert’s theorem. The reconfiguration problem in this article, is considered with the constraint of overall fuel cost minimization. Hence, orbital maneuvers required for the operation of reconfiguration are designed in such a way that, transferring globally the satellites to the desired configuration of constellation will be possible at minimal cost. Also, the introduced method of orbital transfer for implementing the reconfiguration phase of satellite constellation has no limitation on the shape and orientation of initial and target orbits such as: co-planarity, coaxiality, circularity and/or the existence of a common point.Moreover, a method is offered for modeling the cost function of reconfiguration problem in which the two important tasks of Optimal orbital transfer of satellites to the target configuration of constellation and Optimal assignment of each satellite to a specific terminal position or final orbit will be done in one single step. For this purpose and in order to achieve globally Optimal solution of the reconfiguration problem of constellation the hybrid PSO/GA is used. Finally, two different scenarios of reconfiguration of satellite constellation will be modeled once by the presented approach and once by considering determined positions of flight and deployment for the satellites. The obtained results indicate the superiority of the idea presented in this article.

Due to the growth and expansion of cities and the unchanged distribution network, an important issue for electricity distribution companies is customer satisfaction with the quality of received power. It is clear that with the expansion of load centers, the amount of line power flow increases, that creates problems such as voltage drop and increased losses. Distribution network reconfiguration is one of the solutions for network administrators to prevent these problems. With increasing power consumption, environmental issues, and government constraints for power generation, have raised challenges in the distribution system. The solution is a smart grid implementation. In this paper are considered reconfiguration, distributed resources (PV and Wind systems) and energy storage systems (ESS) to achieve smart grid. The effect of scattered products on the reduction of losses, the effect of capacitive banks on improving the voltage profile and reducing losses, and the problem of reconfiguration on the performance indicators of the distribution system and the reduction of losses are investigated and proposed as a multi-objective function. The objective functions used include reducing total voltage deviations, reducing total system losses, increasing the security margin of lines, reducing the energy purchased from the main network, and reducing the energy variance from the main network. Several scenarios for examining the methods for improving the target functions have been investigated and the simulation results have been shown. The use of reconfiguration has a significant impact on the losses and voltage profiles, and distributed sources also have a positive impact on all sectors and affect the power of the network. With the activation of ESSs in the smart distribution network, the economic objective function is reduced and the grid has the ability to sell electricity to the main network. In the future work, the linearization of the proposed model and mathematical optimization methods can be used.

Optimal reconfiguration and capacitor placement are used to reduce power losses and keep the voltage within its allowable interval in power distribution systems considering voltage, current, and radial condition constraints. It is needed to solve two nonlinear discrete optimization problems simultaneously, so an intelligent algorithm is used to reach an optimum solution for network power losses. An effective method and a new optimization algorithm using 'improved binary PSO' is presented and discussed to minimize power losses in distribution network by simultaneous network reconfiguration and capacitor placement. The proposed model uses binary strings which represent the state of the network switches and capacitors. The algorithm is applied and tested on 16- and 33-bus IEEE test systems to find the optimum configuration of the network with regard to power losses. Five different cases are considered, and the effectiveness of the proposed technique is also demonstrated with improvements in power loss reduction compared to other previously researched methods, through MATLAB under steady-state conditions.