Impacts of load models and power factor control on optimal sizing of photovoltaic distributed generators in a distribution system

Abstract

This paper studies the impact of optimal sizing of photovoltaic distributed generators (PV-DGs) on a distribution system using different static load models (i.e., constant power, constant current, and constant impedance) and various power factor (PF) operations. A probabilistic approach with Monte Carlo simulation is proposed to obtain the optimal size of PV-DG. Monte Carlo simulation is applied to predict the solar radiation, ambient temperatures, and load demands. The objective is to minimize average system real power losses, with the power quality constraints not exceeding the limits, i.e. voltage and total harmonic voltage distortion (THDv) at the point of common coupling (PCC). A modified Newton method and a classical harmonic flow method are employed to calculate the power flow and THDv values, respectively. An actual 51-bus, medium-voltage distribution system in Thailand is employed as a test case. Results demonstrate that the proposed method performs well to provide the optimal size of PV-DG based on technical constraints. Further, the results show that the three static load models do not affect the optimal PV-DG size but the model has a different impact for various PF operations. PV-DGs may improve the voltage regulation and decrease the losses in distribution systems practically, but the THDv values could increase.

Examination of the Chance Constrained Optimal WT Penetration Level in Distorted Distribution Network with Wind Speed and Load Uncertainties

“…The probabilistic approaches, in which these uncertainties are taken into account, are inevitable for the evaluation of the stochastic behavior of distribution systems, to which the WTs are interfaced. In that manner, it is very important for stochastic approaches that the random variables in the problem have some probability distributions [12]. Since the consumptions and renewable power productions in distribution systems have probabilistic framework, these are included in the stochastically modeled approaches.…”

“…where c represents scale index and k WT v , shows the wind speed on the wind turbine at bus k of the distribution network. The wind turbine capacity depends on wind speed, and can be evaluated as [21]: In this study, the load uncertainty of the distribution network has been modelled by normal distribution [12]. The normal distribution pdf is given as follows:…”

“…The optimization outcomes can be represented by the probability distributions within the determined region by utilizing the probabilistic approaches. In this manner, Monte Carlo Simulation (MCS) is a well suited method for handling the probabilistic and harmonic related problems [12][13][14]. In [12], an optimization problem has been investigated by the MCS method with the consideration of confidence intervals for THD current limits in distribution system with background harmonics.…”

“…In this manner, Monte Carlo Simulation (MCS) is a well suited method for handling the probabilistic and harmonic related problems [12][13][14]. In [12], an optimization problem has been investigated by the MCS method with the consideration of confidence intervals for THD current limits in distribution system with background harmonics. Chance constrained programming plays important role in performing the planning of distorted distribution systems.…”

Penalty factor-based optimization algorithm for distributed generation sizing in distribution network

“…The works of Mouti et al [5] and Hengsritawat et al [18] are examples of studies on the optimal DG location and size optimization. In their analyses, these authors considered different modes of DG units in the system.…”