In this paper, a Microgrid (MG) test model based on the 14-busbar IEEE distribution system is proposed. This model can constitute an important research tool for the analysis of electrical grids in its transition to Smart Grids (SG). The benchmark is used as a base case for power flow analysis and quality variables related with SG and holds distributed resources. The proposed MG consists of DC and AC buses with different types of loads and distributed generation at two voltage levels. A complete model of this MG has been simulated using the MATLAB/Simulink environmental simulation platform. The proposed electrical system will provide a base case for other studies such as: reactive power compensation, stability and inertia analysis, reliability, demand response studies, hierarchical control, fault tolerant control, optimization and energy storage strategies.

Microgrids (MG) treat local energy supply issues effectively and from a point of view of the distribution grid, may be a power supply or virtual load. Despite holding a myriad of benefits, MGs also bear a set of challenges, including a higher fault rate. Currently, many articles focus on control techniques; however, little has been written about the techniques of control, hierarchical control, and fault-tolerant control (FTC) applied to MGs, which is the motive of this bibliographic revision on control systems. A brief comparison of the different approaches in the field of present-day research is carried out primarily addressing hierarchical control and fault tolerance. The objective of this investigation is to attract the interest of researchers to the field of control and fault tolerance applied to MGs, such as: modeling, testbed, benchmark systems, control and hierarchical control strategies, fault diagnosis and FTC.

This work presents a novel methodology for the optimal location of reclosers in electric distribution systems. The proposal uses a multicriteria analysis to evaluate the reliability indicators for this level 3 (distribution) by generating scenarios from pseudo-random variables. The reliability indicators considered in the study are the System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI), Customer Average Interruption Duration Index (CAIDI), and Average Energy Not Supplied (AENS). It is employed a deterministic random generation in a defined range associated with each analysis variable (failure rate by elements and loads, failure duration, number of customers per load point, mean power consumed at each load point, etc.) The reliability indicators (criteria) are calculated for every possible location of a recloser in the candidate primary sections, thus obtaining the decision matrix, normalized and weighted by the CRITIC method to find the optimal location according to a minimum criterion. This analysis is repeated N times through the generation of scenarios using the Montecarlo method, establishing the probability of occurrence of each winning alternative and choosing the final optimal location of the first recloser within the distribution system. The methodology also proposes the switching coordination repeating the previously described analysis for locating a second recloser considering that the first was already a winning alternative within the generation of “many” scenarios. The scope of the proposed methodology is the number of reclosers that it is desired to analyze considering cost constraints and is general for any distribution system. The analysis is carried out with comprehensive programming in the Matlab software environment. The results successfully respond to the maneuver and switching tests with the joint criterion of minimizing all reliability indicators for level 3 (distribution). With this proposal, knowledge gaps in reliability studies are solved. The absence of data is completed with generations of pseudo-random variables, and the optimal location of the reclosers responds to all reliability criteria in distribution with weighting alternatives. The novel proposed methodology is validated with an exhaustive search analysis where all possible single or multiple reconnection scenarios are analyzed. The winning location alternative found coincides with the one determined by the proposed methodology in more than 90% of the generated random scenarios.

This article proposes an analysis of energy losses in distribution circuits with asymmetric topologies, starting from mathematical comparisons of the parameters of electrical losses among the three constructive approaches for distribution networks (monophasic, biphasic and three-phase). Approximations, that allow us to know asymmetric loss factors, will be established in order to develop appropriate criteria of designs in distribution networks that feed transformers purely monophasic, depending on the charge states, caliber of drivers and distances of the lines; thus minimizing the losses of energy due to unbalanced construction concept. These obtained factors provide a tool for the optimum design of more efficient networks, either to correct inefficient systems with high levels of losses, which are already in operation, or for new electrical investments projects pointing to the development of future smart grids with high energy efficiency.

This paper presents a new hybrid strategy which allows the dynamic identification of AC/DC microgrids (MG) by using algorithms such as Auto-Regressive with exogenous inputs (ARX) and Petri Nets (PN). The proposed strategy demonstrated in this study serves to obtain a dynamic model of the DC MG in isolated or connected modes. Given the non-linear nature of the system under study, the methodology divides the whole system in a bank of linearized models at different stable operating points, coordinated by a PN state machine. The bank of models obtained in state space, together with an adequate selection of models, can capture and reflect the non-linear dynamic properties of the AD/DC MGs and the different systems that it composes. The performance of the proposed algorithm has been tested using the Matlab/Simulink simulation platform.

In this work, a mathematical model called optimization by swarm of particles (PSO), was implemented to optimally solve the location and sizing of capacitor banks in a micro-grid of electrical distribution. The proposed method is based on particle swarm optimization (PSO) and the solution will be obtained with dynamic programming, implementing an algorithm that will be developed entirely in MATLAB. The algorithm calculates the optimal solution satisfying the necessary requirements to guarantee the operation of the electrical system. As a case study, a model of a micro-grid which is typically of 5 bars will be used. However, the algorithm was implemented in a general way and it can respond correctly to multi-bar systems. As a final analysis we made a comparison of the system data without compensating and the compensated system data, highlighting an improvement in the voltage profiles, minimization of the losses in the lines, minimization of the total losses of the system, improvement of the power factor, decrement in the maximum voltage deviation and average voltage deviation, complying with a minimum possible cost restriction criterion.