Optimal placement of dispatchable and non-dispatchable distributed generation of different technologies

The penetration of distributed generation (DG) in the grid is a challenge for traditional electric power systems. Power injections from DG units alter the network power flow and improve power, energy losses and the voltage profile of the system. The assignment of a suitable size and number of DG units plays a large part in maximizing these benefits. This paper investigates various DG technologies (such as biomass, micro∗turbine, solar, wind, combined heat and power (CHP) and fuel cells) and; applies various optimization techniques; these techniques are categorized into analytical optimization and heuristic optimization. The analytical optimization techniques used in this paper are allocation using voltage (bus) stability index (VSI) and a power (line) stability index (PSI). The heuristic techniques are Multiobjective Genetic Algorithm (MOGA), Particle Swarm Optimization (PSO) and Biogeography Based Optimization (BBO). In addition, the paper discusses non-dispatchable and dispatchable DG. Single and multiobjective optimization techniques are proposed to determine the allocation of DG units in radial distribution systems while; considering objective functions namely, minimizing the power losses, minimizing the energy losses, minimizing the total cost and maximizing the voltage stability index (VSI). These techniques are applied to a standard IEEE 69 radial distribution system and implemented using MATLAB R2014b.