In this paper a hybrid Active DC line conditioner for fluctuations and ripples reduction in voltage and current of DC power systems is proposed. Malfunctions in operation of equipments and systems which are supplied by low quality distribution power systems are one of the main effects of DC voltage ripple. In the proposed configuration a hybrid system including series and shunt Active line conditioners for ripple reduction of load voltage and source current is used. Simulation and experimental results are provided to show the performance of the proposed configuration in different states.

This article investigates the problem of simultaneous attitude and vibration control of a flexible spacecraft to perform high precision attitude maneuvers and reduce vibrations caused by the flexible panel excitations in the presence of external disturbances, system uncertainties, and actuator faults. Adaptive integral sliding mode control is used in conjunction with an attitude actuator fault iterative learning observer (based on sliding mode) to develop an Active fault tolerant algorithm considering rigid-flexible body dynamic interactions. The discontinuous structure of fault-tolerant control led to discontinuous commands in the control signal, resulting in chattering. This issue was resolved by introducing an adaptive rule for the sliding surface. Furthermore, the utilization of the sign function in the iterative learning observer for estimating actuator faults has not only enhanced its robustness to external disturbances through a straightforward design, but has also led to a decrease in computing workload. The strain rate feedback control algorithm has been employed with the use of piezoelectric sensor/actuator patches to minimize residual vibrations caused by rigid-flexible body dynamic interactions and the effect of attitude actuator faults. Lyapunov's law ensures finite-time overall system stability even with fully coupled rigid-flexible nonlinear dynamics. Numerical simulations demonstrate the performance and advantages of the proposed system compared to other conventional approaches.

After extreme events such as floods, thunderstorms, blizzards and hurricanes there will be devastating effects in the distribution networks which may cause a partial or complete blackout. Then, the major concern for the system operators is to restore the maximum critical loads as soon as possible by available generation units. In order to solve this problem, this paper provides a restoration strategy by using Distributed Generations (DGs). In this strategy, first, the shortest paths between DGs and critical loads are identified. Then, the best paths are determined by using a decision-making method, named PROMOTHEE-II to achieve the goals. The uncertainties for the output power of DGs are also considered in different scenarios. The IEEE 123-node distribution network is used to show the performance of the suggested method. The simulation results clearly show the efficiency of the proposed strategy for critical loads restoration in distribution networks.

One of the major issues in the planning stage for distribution networks is the optimal design of microgrids (MGs). One of the important goals in the design of MGs is supplying the load with the highest reliability and the lowest cost. Construction of MGs in the distribution systems may have many benefits such as local control strategy in order to minimize the interaction between different MGs, prevent the fault propagation and finally, increase the reliability of the system for consumers and distribution companies. Therefore, in this paper, with the aim of improving reliability and cost, three different approaches to constructing multi-microgrid (MMG) systems in the Active distribution network (ADN) are proposed and compared. In this way, by determining the location and capacity of energy storage systems (ESSs) as well as clustering of ADN based on the mentioned objectives and proposed optimization algorithms, in different scenarios, using the Monte Carlo (MC) algorithm and the Forward-backward load flow, the objective function is calculated. Then, with the repetition and various suggestions made by the optimization algorithm, the optimal value of the objective function is obtained and the results of the designed approaches are compared. To simulate and demonstrate the effectiveness of the proposed method, the 119-bus test distribution system is used.

One of the obvious reasons for most disorders in network service provisioning is network path congestion. Congestion avoidance in today's networks is too costly and sometimes impossible. With the introduction of SDN, centralizing the equipment's control plane has become possible. This paper presents an enhanced method named ESV-DBRA to avoid congestion in multi-tenant SDN networks. At first, ESV-DBRA monitors the traffic load and delay of all network paths for each tenant individually. Then, by merging the parameters obtained from the monitoring, the Service Level Agreements (SLA), and a novel proposed cost function, it calculates the cost of the network paths per tenant. As a result, traffic for each tenant is routed through the path/paths at the lowest possible cost from the tenant's perspective. Next, the bandwidth quotas will be calculated and assigned to the tenants over their optimal routes. Afterward, whenever congestion is likely to occur in a path, ESV-DBRA automatically changes the route or bandwidth of the tenants' traffic related to this path to avoid congestion. Related algorithms are also proposed.Eventually, simulations show that the proposed method effectively increases bandwidth utilization by 10.76%.