Probabilistic load elasticity analysis in low voltage distribution networks with high penetration of photovoltaic micro generation. (December 2019)

• Record Type: Journal Article
• Authors: Camilo, Fernando M.; Castro, Rui; Almeida, M.E.; Fernão Pires, V.
• Is Part Of: International journal of electrical power & energy systems. Volume 113(2019)
• Page Start: 782
• Page End: 791
• Publication Date: 2019-12
• Subjects: Load modelling -- ZIP models -- Monte-Carlo simulation -- Unbalanced network -- Voltage profile; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2019.06.002
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: We investigate load modeling in an LV network with a high penetration of PV. We use an unbalanced power flow algorithm, capable of handling load models. Monte Carlo approach is applied for the stochastic computations. The obtained probabilistic results are compared to the traditional load modeling. Abstract: Microgeneration PV units connected to the LV distribution network is contributing to a paradigm change on the planning and operation. The proliferation of electric and electronic devices in residential houses, principally nonlinear loads, can be observed and is a result of the evolution of technology. These nonlinear devices may generate a number of harmonics, therefore disturbing and degrading the power quality of the network. This paper intends to give a contribution to the subject by investigating the static load modelling in a LV radial distribution network. For this purpose, a three-phase unbalanced power flow algorithm is used, with the capability of handling static load models variations, through the well-known concept of elasticity. The research is made by using stochastic variations, typifying the residential load segment. The Monte Carlo approach is applied for the stochastic computations, considering the uncertainty in the composition of loads. The obtained probabilistic results are compared to the typical load modelling through ZIP models. The obtained results indicate that overvoltages may occur in summer days at around noon, independently of the behaviour of the loads. On the other hand, voltages at the lower acceptable band can be expected at night during winter, when the peak load occurs.