Abstract
Distribution systems planning heavily depends on the predicted future consumptions in the service area. When statistical data exist about past consumptions, probabilistic forecasting methods may be applied, and expected cost/benifit and risk analysis are used to decide between different solutions. In most cases, however, this strategy is not applicable, due mainly to the lack of significant data (new developing areas, rapidly changing situations) and uncertainty of economic and social factors. In the latter case, the use of fuzzy models is an interesting alternative, accommodating expert planner's qualitative judgments about future loads and allowing us to use 'typical' load diagrams in new areas. The paper discusses the main concepts of electric distribution system planning when loads are fuzzy modeled, and presents an illustrative application example. © 1995.

Abstract
This paper presents an approach to the Dynamic State Estimation (DSE) problem to determine the real-time state of an electric power system under quasi-static operating conditions. Bearing in mind the large dimension of power systems, a new DSE algorithm is proposed in order to give a satisfactory solution from the computational point of view for the following steps of the DSE procedure: state forecasting, state filtering and detection and identification of bad data. Simulation results show the performance of the proposed algorithm under different operational conditions: normal, sudden change in the system operating point and occurrence of bad data.

Abstract
In this paper, system component reinforcements are analyzed from the perspective of their impact in increasing flexibility in system design. The proposed framework integrates a fuzzy optimal power flow model through which one can derive, as a function of load uncertainties, possibility distributions for generation, power flows and power not supplied. Exposure and robustness indices, based on risk analysis concepts, are defined. These indices can be used to rank the expansion alternatives, giving the planner insight to system behavior in face of adverse futures. Their use in conjunction with investment assessments is proposed as a necessary step in a decision making methodology.

Abstract
This paper describes a genetic algorithm approach to the optimal multistage planning of distribution networks. The authors describe a mathematical and algorithmic model that they have developed and experimented with success. The paper also presents application examples, with real size systems. The advantages of adopting this new approach are discussed in the planning context, namely in conjunction with the adoption of multicriteria decision making methods.

Abstract
In this paper a model to derive reinforcement strategies driven by an economic criterion is presented. This model is based on a Fuzzy Optimal Power Flow formulation which assumes that loads are characterized by membership functions in the scope of the Fuzzy Set Theory. Therefore, subjective information or incompletely defined data can be included in the planning studies making it possible to characterize in a more adequate way the system behavior regarding the uncertainties of the future. Some risk concepts are also presented and integrated in this planning framework. The planner can thus identify the least costly reinforcement strategy in order to meet to desired risk index target so that a reduction of the system exposure towards the future is obtained.

Abstract
In this paper an improved DC Fuzzy Optimal Power Flow - FOPF - model for planning purposes formulated as a multi-parametric programming problem is briefly presented. This model uses Fuzzy Set Theory concepts to represent information about loads expressed in a subjective way by experts or integrating a certain degree of uncertainty about the future. The proposed algorithm has an heuristic nature so that it is important to evaluate the quality of the derived membership functions. A sampling procedure will be used to build membership functions to be compared with the ones obtained using the FOPF algorithm. In the paper results obtained for two networks based on the IEEE 24 and 30 bus test systems will be presented and discussed.