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 new optimization model EPSO, Evolutionary Particle Swarm Optimization,. inspired in both Evolutionary Algorithms and in Particle Swarm Optimization algorithms: The fundamentals of the method are described, and an application to the problem of Loss minimization and Voltage control is presented, with very good results.

Abstract
This text presents an overview of the basic concepts of a Neuro-Fuzzy inference system for spatial Offer-and-Demand forecasting of electric power on a geographical basis, over GIS (Geographical Information Systems).

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
Power-to-Hydrogen (P2H) clean systems have been increasingly adopted for Virtual Power Plant (VPP) to drive system decarbonization. However, current models for the joint operation of VPP and P2H often disregard the full impact on grid operation or hydrogen supply to multiple consumers. This paper contributes with a VPP operating model considering a full Alternating Current Optimal Power Flow (AC OPF) while integrating different paths for the use of green hydrogen, such as supplying hydrogen to a Combined Heat and Power (CHP), industry and local hydrogen consumers. The proposed framework is tested using a 37-bus distribution grid and the results illustrate the benefits that a P2H plant can bring to the VPP in economic, grid operation and environmental terms. An important conclusion is that depending on the prices of the different hydrogen services, the P2H plant can increase the levels of self-sufficiency and security of supply of the VPP, decrease the operating costs, and integrate more renewables.