Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves

Abstract

This paper presents an optimization model for the optimal placement and sizing of wind turbines, considering their reactive power capacity, wind speed, and demand curves. The optimization model is nonlinear and is focused on minimizing power losses in AC distribution networks. Also, paired wind turbine and power conversion systems are treated via chargeability factor η at the peak hour. This factor represents the percentage of usage of the power conversion system in the nominal wind speed conditions, and allows to support reactive power dynamically during all periods of the day as a function of the distribution system requirements. In addition, an artificial neural network is used for short-term forecasting to deal with uncertainties in wind power generation. We assume that the number of wind power distributed generators could be from zero to three generators integrated into the system, considering unit power factors and reactive power injections to follow up the effect of reactive power compensation in the daily operation. The General Algebraic Modeling System (GAMS) is employed to solve the proposed optimization model.

Dynamic Reactive Power Compensation in Power Systems through the Optimal Siting and Sizing of Photovoltaic Sources

“…Additionally, a loadability factor was integrated, which is used in the power electronic interface to limit the PV's active power to the grid. Note that the main differences of this study regarding the reference [9] are: (i) the usage of real generation and demand curves in the Colombian power system context to characterize the demand and solar radiation behaviors; (ii) the inclusion of the sensitivity analysis in the optimization model regarding the numerical performance of the voltage profiles as a function of the number of PV plants integrated into the electrical grid; and (iii) the usage of the reactive power capabilities of the power electronic interface in photovoltaic applications which have not been previously explored in the relevant literature and was identified as an opportunity of research that this paper attempted to contribute to from the point of view of the exact mathematical optimization.…”

“…The Colombian system is not alien to this problem, since, in the case of highvoltage levels (i.e., ≥220 kV), the number of power losses oscillates between 1.5% to 1.8% of the total power generated; while in the case of the distribution grids, these percentages are between 6% to 18% [7]. To reduce the amount of energy wasted in electricity transmission and distribution activities, one of the main approaches studied by regulatory entities and academics corresponds to the inclusion of the renewable generation since it helps to: (i) reduce the harmful effects of greenhouse gas emissions in predominately thermal generation systems [8], (ii) improve the grid performance, i.e., voltage support and power loss minimization; and (iii) redistribute the power flow in lines, i.e., reduction of the power system stress, which helps make the system more robust regarding contingencies [9,10].…”

“…The problem of the optimal placement and sizing of wind power sources in power systems considering variable power factor have recently been studied by Gil-González, et al in [9], where the problem was formulated using a mixed-integer nonlinear programming (MINLP) model. The converter interfaces of the wind energy conversion system are used to provide reactive power to the grid when necessary via a nonlinear controller design [11].…”

“…Mathematical models of algebraic nature have also been proposed and solved in the GAMS software [19]. Moreover, it is possible to have adequate planning regarding the optimal location and dimensioning of DGs, as reported in [9]. An optimization methodology to size and locate the PV, WT, and capacitor banks considering the uncertainties of the demand caused by electric vehicles and the variations of irradiation, wind speed, and the usual load was presented in [20], where it was applied to a typical radial network.…”

“…In this paper, a model for the optimal location and sizing of PV plants in AC power systems considering reactive power injection was formulated. The proposed model generates the mixed-integer nonlinear programming (MINLP) model, which is solved using the GAMS software as a tool, as used in similar works [9]. Under the presented model, the PV can inject or absorb reactive power by employing the power electronics devices' reactive power management supply capability for integration with the power grid, according to the grid requirements.…”