Abstract

     The main approach used to model uncertainties in microgrid planning is the Probabilistic Power Flow (PPF). However, this technique has a high computational cost due to the need to solve a system of nonlinear equations for different scenarios of microgrid operation. This paper aims to propose low-cost computational power flow algorithms to evaluate nodal voltages in islanded Direct Current (DC) microgrids under uncertainty. An approximated power flow is proposed based on the Admittance Summation Method for radial microgrids. In addition, iterative power flow algorithms, previously developed by the authors for Alternating Current (AC) microgrids, have been adapted for DC microgrids. The proposed iterative and approximated algorithms were combined with Monte Carlo Simulation to obtain a PPF method. The proposed methods were tested and validated in relation to the Newton-Raphson Method in DC radial microgrids with 33 and 906 nodes and in DC meshed microgrids with 33 e 144 nodes. The results showed that the developed methods have good accuracy and obtain considerable saving in the computational cost of the PPF.

Introduction

     A microgrid can be described as a cluster of loads and generators that can operate in an interconnected or islanded way from the electrical distribution network [1, 2]. The islanded operation occurs when there is a disturbance in the utility’s system and the microgrid is automatically disconnected from the Common Coupling Point (CCP). During the islanded operation, the microgrid loads are supplied by their own native generation. Therefore, it is expected that the reliability of the microgrid will be improved.

     An important aspect that has gained importance in the design of microgrids is the application of Direct Current (DC) microgrids and hybrid microgrids (DC and Alternating Current (AC)) [3, 4]. The use of DC voltage is motivated by the following facts: (i) increased DC loads (Light-Emitting Diode (LED) lamps, computers, printers, etc.); (ii) DC renewable Distributed Generation (DG) (solar photovoltaic and fuel cells); (iii) insertion of battery energy storage systems to increase the use of renewable DG. The DC microgrids can offer the following advantages when compared with AC microgrids [5],[6]: (i) minimization of conversion losses; (ii) greater power transfer capacity; (iii) elimination of the need for frequency synchronism. At this point, it is important to mention that the algorithms proposed in this paper are oriented towards DC microgrids, that is, hybrid AC-DC microgrids are not considered.

Conclusions

     This paper presented approximate and iterative power flow algorithms for islanded Direct Current microgrids with radial and meshed topologies. These algorithms were developed based on the combination of the following techniques: Admittance Summation Method, Current Summation Method, Gauss-Zbus Method, Modified Augmented Nodal Analysis and Superposition Principle. The proposed algorithms were embedded in a Probabilistic Power Flow, based on Monte Carlo Simulation, in order to demonstrate that these algorithms are suitable for planning studies under uncertainties. The tests results with large scale microgrids demonstrate that the proposed algorithms have good accuracy in relation to the Newton-Raphson Method in the evaluation of the voltage profile and losses. In addition, the proposed methods achieve significant reductions in the computational cost associated with the Probabilistic Power Flow. Future work associated with the proposed power flow algorithms is oriented to towards expanding these algorithms to model the following aspects related to DC microgrids: secondary control, voltage unbalance in bipolar configuration and networked (interconnected) microgrids.