No abstract

This paper proposes the performance improvement of radial distribution network with distributed generation (DG) integration using extended particle swarm optimization (PSO) algorithm. High-performance distribution network is a network that has a low power loss, better voltage profile, and loading balance among feeders. The effort to improve the performance of the distribution network is network configuration optimization. The optimization has become an important issue with the presence of DG in distribution networks. In this study, network configuration optimization is based on an extended PSO algorithm. The methodology has been tested in two models of IEEE radial distribution networks. The results showed that the optimal configuration of the distribution network is able to reduce power loss and to improve the voltage profile of the network significantly.

No abstract

No abstract

This paper proposes a reconfiguration methodology that aims for achieving the minimum active power loss of radial distribution networks with integration of distributed energy resources (DER) in order to improve the distribution system performance. The problems of power system operations and planning schemes will be arising due to the presence of DER to the distribution systems, such losses will rise and the increase of the voltage at which there are many DER. One of the popular efforts to improve the performance of the distribution system is network reconfiguration. In this study, reconfiguration method proposed is based on an extended fuzzy multi-objective approach. Multi-objective function are considered for minimization of the active power loss, deviation of bus voltage, and load balancing among the feeders, while subject to a radial network structure in which all loads must be energized. In this case, all objectives may be simultaneously weighted. The implementation of the extended fuzzy multi-objective for reconfiguration of distribution network with integration of DER on IEEE 77-bus distribution network and Yogyakarta 60-bus distribution network are described. The simulation results show that a 1.80% of efficiency improvement is achieved for IEEE 77-bus network, and a 0.11% of Yogyakarta 60-bus network efficiency improvement is achieved by the method.

To concentrate the rays to the focal point and stabilize the temperature on the receiver were one of the complex works of the two-stage solar concentrator. This paper offers a new method of Fuzzy cascade controller system based on tuning up the optimization at Genetic Algorithm-simple additive weighting (GA-SAW) on the dual parabolic dish concentrator with Compound Parabolic Concentrator. The model and computation of three degrees of freedom robotic arm movement with the ray tracing method were used as the concentrator position predictor. In this research, the acquired fuzzy controller result had an average settling time 0.497 sec, and average rise time 0.277 sec faster than a conventional PID controller. This research was able to overcome the disturbance which was diffused rays, so there was a better output with the power and heat flux increased up to 62.49%. The monte carlo ray tracing method from Tonatiuh Software was used to investigate and movement validation of the dual parabola concentrator by showed the flux distribution on the receiver's absorber. In the last stage, an experiment with a prototype had been conducted as a response verification of the controller system which produce a receiver temperature output as high as 121ºC. The final result showed that the controller system managed to optimize the temperature on the receiver's absorber and generate a stable thermoelectric output with power of 1.01 Watt.

No abstract

No abstract