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.

Abstract
This paper describes the application of the specialized genetic algorithm of Chu-Beasley to solve the Distribution System Reconfiguration, DSR, problem considering different demand scenarios. This algorithm is an approach inspired in the natural selection and evolution of species. The reconfiguration problem of distribution networks taking into account different demand scenarios aims at identifying the most adequate radial topology of a distribution system assuming that this topology is used for all demand scenarios under study. This search is driven by the minimization of the cost of energy losses in the network along a full operation year. The performance of the algorithm is evaluated considering test systems having 33, 70, 84 and 136 buses and a real system with 417 buses. The obtained results confirm the robustness and efficiency of the developed approach and its potential to be used in distribution control centers.

Abstract
This paper describes a hybrid tool to perform Static Transmission Expansion Planning, STEP, studies and its application to the Garver6-Bus academic system and to the Southern Brazilian Transmission equivalent real system. The developed STEP tool integrates two phases as follows. The first one uses Constructive Heuristic Algorithms (CHA) to reduce the search space, and the second uses Particle Swarm Optimization (PSO) to identify the final solution. This hybridization between CHAs and PSO proved to be very effective and shows good performance to reduce the size of the STEP search space and to identify good quality solutions. These are relevant issues given the combinatorial nature of investment problems leading to the explosion of the number of alternative plans, one of the greatest difficulties faced in this planning problem.

Abstract
In a restructured electricity sector, day-ahead markets can be modeled as a game where some players - the producers - submit their proposals. To analyze the companies' behavior we have used the concept of Nash equilibrium as a solution in these multi-agent interaction problems. In this paper, we present new and crucial adaptations of two well-known mechanisms, the adjustment process and the relaxation algorithm, in order to achieve the goal of computing Nash equilibria. The advantages of these approaches are highlighted and compared with those available in the literature.

Abstract
Storage technologies are expected to assume an increasing relevance in the next few years, given the widespread number of available options, the possible applications and the reduction of investment costs. Therefore and apart from the well-known hydro pumping stations, the installation of storage is being considered as an increasingly viable option namely in distribution networks and also in end user installations. This paper reviews the recently passed Portuguese legislation on self-consumption and details a model to evaluate the economic interest of installing batteries together with PV panels according to several possible business models. The simulations suggest that the tariffs currently applied and the investment costs turn these options still not attractive so that a final simulation was developed to evaluate the break even value of the tariffs to turn the investments on storage paid in a reasonable horizon.

Abstract
This paper analyzes the impact of storage installations on grid electricity demand. Storage systems allow the decoupling of consumption from electricity generation and therefore have the potential to change the daily demand profile seen by the network in a significant way. This has far reaching consequences for many stakeholders, as changes in the net demand would for example impact electricity prices or change the requirements for peak generation. The developed approach considers the installation of storage devices to increase self-consumption of locally generated electricity in a residential and small commercial end users context as well as its application for electricity arbitrage. Assumptions about their implementation on a system level are described and their impact on overall electricity demand is determined considering the German case.