چكيده به لاتين
The purpose of this thesis is to find the optimal location and size of DG units in distribution systems for power quality improvement. To achieve the defined goals, at first step, a novel objective function is proposed for optimization of DG units considering different technical constraints such as voltage limit, line loading limit, and etc. The related objective function consists total cost of DG units, purchased natural gas, power losses of distribution network, and predefined penalty for greenhouse gas emissions. The meta-heuristic algorithms including Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Imperialist Competitive Algorithm (ICA) are employed to find the optimal location and size of DG units. In this step, a new strategy is proposed to provide the cooling, and heating loads in the distribution system. At the next step, PSO algorithm as a robust technique is employed to optimize the DG units including linear and non-linear loads to minimize the Total Harmonic Distortion (THD) of network voltages. A new formulation is proposed to consider the load growth for available loads in the distribution system, the uncertainty of wind and solar power and load demand in the simulation procedure. Then, to mitigate the voltage sag problem in distribution systems, a new formulation is proposed for optimization of DG units. Different types of load models such as industrial, residential and commercial loads are considered in the system. To involve the voltage sag occurrence in distribution system, a penalty is considered for interruption of each type of available load. At the next step, a new formulation is proposed for optimal planning of smart distribution system including demand response. Furthermore, it is considered that PEVs participate in demand response programs to control the THD of different buses in the case study network. Finally, a new technique based on multi objective optimization is proposed to optimize the DG units in distribution systems. Multi Objective Particle Swarm Optimization (MOPSO) is applied to manage the active power losses, the total cost of DG units, voltage THD of buses, and emissions of greenhouse gases in the distribution network. The proposed methodology implements Pareto optimal solutions to solve the multi-objective problem with constraints. The simulation results show that the proposed algorithm which is a developed comprehensive and precise method for optimal utilization of DG units, can be implemented as a robust tool by the distribution network operator. The developed algorithm can be implemented for all networks, and different types of DG units can be added to the system as well as various parameters in case of objective function. The proposed algorithm is efficient in solving the optimization of DG units which considers the technical, economic and environmental constraints, and also different types of loads such as electrical, cooling, and heating load.
