In addition to the great benefits of Distributed generation (DG) resources to power systems, there are some disadvantages. In spite of some benefits like decrease of received power from transmission grid, increment of DGs penetration can lead to voltage increase in distribution networks during off peak. Hence the recent efforts have been made to handle problems to increase the penetration of these resources. The use of energy storage systems (ESSs) is one of the ways to prevent defects may arise from use of DGs in power systems and can help to increase penetration of DGs in power systems. ESSs can save energy during off peak and deliver it to the network in peak hours; hence, these equipment can reduce power losses and prevent voltage deviation during off peak by increasing load due to ESS charging.In this paper, first DG allocation and ESS placement are introduced then simultaneous placement of DG and ESS to reduce power losses in the distribution network are described. The proposed models are solved using genetic algorithm as optimization tool. The obtained results show that simultaneous placement could increase DG penetration compared to the separate allocation of these devices and provide further reduce of the losses in the distribution network.

Without capacity mechanisms, generation investment in the deregulated power system tends towards boom and bust cycles. Due to lack of significant demand response to electricity price, the cycles may jeopardize supply adequacy or even leads to a black-out in the bust periods. In this paper, encouragement of investment in Distributed generations, which is designed by the regulatory body is proposed to reduce the generation investment cycles. The traditional long-term model of generation investment dynamic is modified to model and consider the regulatory policies. Moreover, an optimization model of regulatory policies is also proposed in order to preserve the supply adequacy in power system. Particle swarm optimization algorithm is employed to solve the optimization problem. The proposed model is implemented in MATLAB software. The simulation results indicate the efficiency of the proposed model in improving the boom and bust cycles and preserving supply adequacy.

The operation of Fuel Cell Distributed generation (FCDG) systems in distribution systems is introduced by modeling, controller design, and simulation study of a Solid Oxide Fuel Cell (SaFe) Distributed generation (DG) system. The physical model of the fuel cell stack and dynamic models of power conditioning units are described. Then, suitable control architecture based on fuzzy logic control for the overall system is presented in order to active power control and power quality improvement. A MATLAB/Simulink simulation model is developed for the SOFC DG system by combining the individual component models and the controllers designed for the power conditioning units.Simulation results are given to show the overall system performance including active power control and voltage regulation capability of the distribution system.