Abstract
Power transformers are important equipment of a substation from the generation, transmission, and distribution of electricity to end users. The costs associated with purchasing a power transformer in the voltage class of 500 kV (100 MVA) are a few million. The fines imposed by regulatory agencies are significant when there is unavailability of equipment for any defect or failure. Therefore, energy companies have been struggling in preventive and predictive maintenance in order to maintain this equipment in an effective maintenance program, avoiding the occurrence of failures. There are various techniques that are utilized for diagnosis and analysis of transformer failure, but little has been discussed about mechanisms that assist in decision making when it is necessary to overload the transformer, especially in emergency situations. In this paper, we present a framework that unifies the step of fault diagnosis of power transformers with the process of decision making, considering the current operating conditions as well as the life of the equipment. The assistance to the decision-making methodology is based on risk analysis with indicators derived from the failure rate and Arrhenius theory. The validation of the method is performed with a case study using data from a utility.

Abstract
In the smart grid environment, reserve services (RS) are also expected from the demand side, taking into account the flexibility and availability of loads connected into the grid. This paper proposes a method to calculate the availability of thermal domestic loads for the provision of upward RS, considering some aspects regarding the constructive characteristics of the appliances, as well as the consumer habits and comfort preferences. A case study comprising 500 consumers with three types of domestic thermal loads (electric water heaters, air-conditioners, and refrigerators) will be used to illustrate the method.

Abstract
The smart grid concept increases the observability and controllability of the distribution system, which creates conditions for bi-directional control of Distributed Energy Resources (DER). The high penetration of Renewable Energy Resources (RES) in the distribution grid may create technical problems (e.g., voltage problems, branch congestion) in both transmission and distribution systems. The flexibility from DER can be explored to minimize RES curtailment and increase its hosting capacity. This paper explores the use of the Monte Carlo Simulation to estimate the flexibility range of active and reactive power at the boundary nodes between transmission and distribution systems, considering the available flexibility at the distribution grid level (e.g., demand response, on-load tap changer transformers). The obtained results suggest the formulation of an optimization problem in order to overcome the limitations of the Monte Carlo Simulation, increasing the capability to find extreme points of the flexibility map and reducing the computational effort.

Abstract
This paper presents a new and efficient methodology for voltage control and network reconfiguration of distribution networks using fuzzy rules, EPSO and graph theory. A simpler representation of the network is built through a graph, were all the network loops are identified, both closed and open loops. This information is incorporated into the EPSO operators to create feasible solutions for the topological problem, avoiding convergence problems and reducing the computational burden. The initial EPSO population is created from the initial feasible solution, using appropriated heuristics to create feasible and possibly better initial solutions. At the same time a heuristic based strategy is used to perform local voltage control actions. Finally a fuzzy inference based algorithm is employed to achieve the optimal transformer and capacitor bank tap position. The proposed methodology was tested in a 13-bus test system, and in a real distribution system with 3200 buses.

Abstract
This paper aims at presenting a Home Energy Management System ( HEMS) module capable of scheduling electric water heater ( EWH) appliances in order to optimize the PV self-consumption. A multi-period optimization model is presented. Laboratory tests were conducted to validate the model and to demonstrate the capability of this HEMS module to address recent challenges of self-consumption in a domestic environment. A commercial EWH device developed by Bosch communicating with the HEMS module is used to perform the tests.

Abstract
This paper describes the application of the clonal selection algorithm to the reconfiguration problem of distribution networks considering non-uniform demand levels. The Clonal Algorithm, CLONALG, is a combinatorial optimization technique inspired in the immunologic bio system and it aims at reproducing the main properties and functions of this system. The reconfiguration problem of distribution networks with non-uniform demand levels is a complex problem that aims at identifying the most adequate radial topology of the network that complies with all technical constraints in every demand level while minimizing the cost of active losses along an extended operation period. This work includes results of the application of the Clonal algorithm to distribution systems with 33, 84 and 136 buses. These results demonstrate the robustness and efficiency of the proposed approach.