Abstract
Most optimization and decision problems in power systems include integer or binary variables, leading to combinatorial problems. In this paper, several approaches using metaheuristics and genetic algorithms are presented that deal with real problems of the power industry Most of these methodologies are now implemented in distribution management systems (DMS) used by several utilities.

Abstract
In this paper we present a complete methodology to perform state estimation studies in distribution networks. Due to the peculiarities of these networks the traditional state estimation concept was enlarged in different ways. It includes a load allocation study, as a way to cope with the reduced number of real time measurements in SCADA database. The algorithm estimates binary values of topology variables, due to incomplete or erroneous topology information in the control center and it is able to include data modeled by fuzzy numbers as a way to include fuzzy results of the load allocation procedure or fuzzy assessments from experts. Finally, the paper describes a methodology developed to tune the weights to be used in the state estimation based on a Takagi-Sugeno fuzzy inference system. The paper includes a case study based in the IEEE 24 bus system to highlight and illustrate its application in a variety of situations.

Abstract
This text describes a real-world DMS environment in which intelligent tools and techniques such as neural networks, fuzzy sets and meta-heuristics (like evolutionary computing and simulated annealing) have given a strong positive contribution.

Abstract
This paper presents a methodology developed within the SOLARGIS project - a Joule project - aiming at evaluating the potential of integrating renewable forms of energy for dispersed electricity production. With this project we also wanted to demonstrate the efficiency of GIS - Geographical Information Systems - as a tool to analyse the integration of renewable forms of energy. In this paper we present the methodologies developed to identify renewable resources in a given geographic region, to detect high potential areas for wind farm siting and to evaluate the efficiency and market of isolated systems to be used for dispersed rural electrification. In this last methodology we used fuzzy models to describe the uncertainties in demand and cost values.

Abstract
This paper presents a Monte-Carlo algorithm considering loads defined by fuzzy numbers. In this methodology states are sampled according to the probabilistic models governing the life cycle of system components while fuzzy concepts are used to model uncertainty related to future load behavior. This model can be used to evaluate generation/transmission power system reliability for long term planning studies as one uses the more adequate uncertainty models for each type of data. For each sampled state a Fuzzy Optimal Power Flow is run so that one builds its power not supplied membership function. The paper proposes new indices reflecting the integration of probabilistic models and fuzzy concepts and discusses the application of variance reduction techniques if loads are defined by fuzzy numbers. A case-study based on the IEEE 30 bus system illustrates this methodology.

Abstract
The new energy policies adopted by the European Union are set to help in the decarbonization of the energy system. In this context, the share of Variable Renewable Energy Sources is growing, affecting electricity markets, and increasing the need for system flexibility to accommodate their volatility. For this reason, legislation and incentives are being developed to engage consumers in the power sector activities and in providing their potential flexibility in the scope of grid system services. This work identifies energy and cross-sector Business Models (BM) centered on or linked to the provision of distributed flexibility to the DSO and TSO, building on those found in previous research projects or from companies' commercial proposals. These BM are described and classified according to the main actor. The remaining actors, their roles, the interactions among them, how value is created by the BM activities and their value propositions are also described.