Voltage optimization in power distribution systems

Alternative energy sources have been introduced into the existing energy production sources to effectively support various solution methods and their applicability in order to be able to respond to the increasing energy need day by day. There is wind which is one of renewable energy resources at the beginning of the list. It uses Wind Turbine(WT) to generate energy from wind. The main focus of this study is an efficient operation of the power distribution systems with WTs. It is known that the outputs of WTs depend on many factors such as the climate, season, wind direction etc. A real data-set of WT output will be used for this purpose. The system which will be used for simulations is 33-node balanced test system. Will be used its' base case loads, scale the WT output data, and integrate into the test system. It is known that optimization problems may be either solved numerically or analytically. Numerical methods may be classified as derivative based ones and non-derivative based ones. Derivative based optimization models provide faster solutions however in some cases, it is not easy to obtain solution due to non-availability of the derivative information, and they may cause some convergence problems. This study aims to use one of the recently developed population based method: Sine-Cosine algorithm (SCA). Generally, population-based optimization techniques start the optimization process with a set of random solutions. Then these are evaluated for the objective functions of the models. These candidate solutions are then improved by applying some evolutionary techniques. Some of well-known techniques are crossover, mutation etc. In this study is aimed to propose an optimization model is developed to keep voltage deviation in a reliable range using Sine Cosine algorithm, taking outputs of wind turbines into consideration. It is a model that will take switched capacitors, tap positions of regulators and reactive power supply of the inverters of WTs into consideration. It is applied this optimization model to a balanced 33-node system. The daily optimal voltage profiles are created by changing tap positions of the regulators, bank switched capacitors, and reactive power outputs of the inverters of WTs.