Tarek Medalel Masaud

A probabilistic forecasting model for accurate estimation of PV solar and wind power generation

Wind and Solar power are the most promising and rapidly developing renewable energy technologies that exist in our world today. They are also termed variable energy resources since their natural resources, wind speed and solar irradiance, are intermittent in nature. This variability is a critical factor when estimating the annual energy of wind and solar sources. Capital and operational costs associated with their implementation are highly affected when inaccurate estimations are carried out. This paper presents a new forecasting model for solar irradiance and wind speed by utilizing historical hourly data to outline an annual eight-segment probabilistic model of wind and solar. The proposed methodology employs a probabilistic approach to estimate the hourly wind speeds and solar irradiance for a year. The model is used to estimate the annual energy produced by a 42.5 MW wind farm and a 1.5 MW PV array. The results are compared with a four-season estimation approach, which have shown a substantial improvement in the estimation accuracy of the total energy produced.

Optimal allocation of SCIG and DFIG based distributed generation considering load uncertainty and line outage: A comparative study

Voltage Stability is one of the factors considered in determining the reliability and efficiency of the operation of the power grid. Unstable voltage variation and voltage collapse can be caused by variation of demand and line outage which might lead to shortage of active and reactive power. Integration of distributed generation (DG) in power systems to improve voltage stability is a commonly used method in the operation of power networks. For efficient utilization of DGs, the investigation of optimal allocation of grid connected DG units is vital research challenge to evaluate the impact of DG on the grid voltage stability. This paper presents a comparative study of the optimal placement for squirrel cage induction generator (SCIG) and doubly fed induction generator (DFIG) based distributed generators with an objective function of enhancing voltage profile. The probabilistic load flow that accounts for load variation has been considered. In addition, the impact of line outage on the system voltage is tackled in the study.

Impact of aggregated EVs charging station on the optimal scheduling of battery storage system in islanded microgrid

In islanded microgrid scheme, optimal scheduling of energy storage system (ESS), and effective coordination between local resources are crucial and challenging optimization tasks. Demand management tools such as flexible load management have a significant influence on the optimal scheduling of ESS in islanded microgrid applications. This paper presents an optimization model to investigate the impact of aggregated electric vehicles (EVs) charging stations as a flexible load on the optimal scheduling of energy storage for islanded microgrid applications. Mixed Integer Linear Programming (MILP) is used to formulate the proposed optimization model and solved using CPLEX tool. Numerical simulations demonstrated the effectiveness of the conducted study.

Placement and sizing of parallel reactive power compensation in the presence of distributed generation for line loss reduction

This paper investigates the problem of placement and sizing of large scale utility owned distributed generator (DG units) and parallel reactive power compensation to achieve a high loss reduction in large-scale primary distribution networks. The paper adopts a probabilistic approach to detect the candidate line to install DG (Line with the highest losses). In addition, a method to quantify reactive power compensation requirements for DG installation based on a desired line loss reduction percentage is proposed. IEEE 5-Bus test system is used as a test system in this study. Simulation results have demonstrated the effectiveness of the proposed methodology.

Modeling and analysis of self-excited induction generator for wind energy conversion

Self-Excited Induction Generators (SEIG) have recently emerged for wind energy conversion in remote and rural areas due to many advantages as standalone induction generator over Grid Connected Induction Generators. However, poor voltage and frequency regulation under varying load and speed is the prime disadvantage of standalone SEIG. Steady state analysis for such machines is important to understand their behavior under varying operating conditions. This paper presents a detailed d-q model of SEIG using Matlab/Simulink which contributes to the development of SEIG modeling with a limited complexity. From the generalized d-q model, the effect of different constraints such as, variation of prime mover speed, and excitation capacitor size, on the SEIG output built up process have been addressed and analyzed. The variation of the magnetizing inductance and the non-linearity is also considered.