Hossein Sangrody

An initial study on load forecasting considering economic factors

This paper proposes a new objective function and quantile regression (QR) algorithm for load forecasting (LF). In LF, the positive forecasting errors often have different economic impact from the negative forecasting errors. Considering this difference, a new objective function is proposed to put different prices on the positive and negative forecasting errors. QR is used to find the optimal solution of the proposed objective function. Using normalized net energy load of New England network, the proposed method is compared with a time series method, the artificial neural network method, and the support vector machine method. The simulation results show that the proposed method is more effective in reducing the economic cost of the LF errors than the other three methods.

Study of sufficient number of optimal tilt angle adjustment to maximize residential solar panels yield

In this paper a comprehensive study is carried out on the optimal number of intervals for adjusting the optimal tilt angle of a solar panel. The tilt angle of solar panels is important for capturing solar radiation and it depends on the path of the sun in the location of the solar panel. A Bee Algorithm is used to compute the optimal tilt angle for a given period. The main goal is to show instead of using a tracking system, which is costly for residential usage, manual adjustment of the tilt angle of a solar panel for a certain number of times during a year is sufficient to receive most of the solar radiation. This study is performed for different locations across the US with different latitudes and longitudes. The optimal number of intervals for each location is computed and the effects of the changes in the longitude and latitude are investigated.

On the performance of forecasting models in the presence of input uncertainty

Nowadays, with the unprecedented penetration of renewable distributed energy resources (DERs), the necessity of an efficient energy forecasting model is more demanding than before. Generally, forecasting models are trained using observed weather data while the trained models are applied for energy forecasting using forecasted weather data. In this study, the performance of several commonly used forecasting methods in the presence of weather predictors with uncertainty is assessed and compared. Accordingly, both observed and forecasted weather data are collected, then the influential predictors for solar PV generation forecasting model are selected using several measures. Using observed and forecasted weather data, an analysis on the uncertainty of weather variables is represented by MAE and bootstrapping. The energy forecasting model is trained using observed weather data, and finally, the performance of several commonly used forecasting methods in solar energy forecasting is simulated and compared for a real case study.

Back-to-back converter control of grid-connected wind turbine to mitigate voltage drop caused by faults

Power electronic converters enable wind turbines, operating at variable speed, to generate electricity more efficiently. Among variable speed operating turbine generators, permanent magnetic synchronous generator (PMSG) has got more attentions due to low cost and maintenance requirements. In addition, the converter in a wind turbine with PMSG decouples the turbine from the power grid, which favors them for grid codes. In this paper, the performance of back-to-back (B2B) converter control of a wind turbine system with PMSG is investigated on a faulty grid. The switching strategy of the grid side converter is designed to improve voltage drop caused by the fault in the grid while maximum available active power of wind turbine system is injected to the grid and the DC link voltage in the converter is regulated. The methodology of the converter control is elaborated in details and its performance on a sample faulty grid is assessed through simulation.

Reliability assessment of distribution system using fuzzy logic for modelling of transformer and line uncertainties

Reliability assessment of distribution system, based on historical data and probabilistic methods, leads to an unreliable estimation of reliability indices since the data for the distribution components are usually inaccurate or unavailable. Fuzzy logic is an efficient method to deal with the uncertainty in reliability inputs. In this paper, the ENS index along with other commonly used indices in reliability assessment are evaluated for the distribution system using fuzzy logic. Accordingly, the influential variables on the failure rate and outage duration time of the distribution components, which are natural or human-made, are explained using proposed fuzzy membership functions. The reliability indices are calculated and compared for different cases of the system operations by simulation on the IEEE RBTS Bus 2. The results of simulation show how utilities can significantly improve the reliability of their distribution system by considering the risk of the influential variables.

Simulation and modeling of dielectric barrier impact on heterogeneous electric field

Non-pressurized air is extensively used as basic insulation medium in medium/high voltage equipments. An inherent property of air-insulated design is that the systems tend to become physically large. Application of dielectric barrier can increase the breakdown voltage and therefore decrease the size of the equipment. In this paper, the impact of dielectric barrier on breakdown voltage enhancement is investigated under both dc and ac applied voltages. For this purpose, two different kinds of dielectric materials as barrier are examined in high voltage electrode structures. Several simulations are carried out to investigate the effect of electric field uniformity factor on breakdown voltage enhancement with dielectric barrier in different structures. The impact of different parameters such as inter-electrodes gap, shape of electrodes, and dielectric materials on the break-down voltage are investigated with simulations and experiments for applied ac and dc voltages. Simulation studies and experimental results illustrate the effectiveness of dielectric barrier in the system.