Authors:
Eduardo M. Gouveia
1
and
Paulo Moisés Costa
2
Affiliations:
1
Polytechnic Institute of Viseu, Portugal
;
2
Polytechnic Institute of Viseu and INESC Porto, Portugal
Keyword(s):
Power Flow, Fuzzy, Symmetric, Optimization.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Bioinformatics
;
Biomedical Engineering
;
Enterprise Information Systems
;
Forecasting
;
Information Systems Analysis and Specification
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Linear Programming
;
Mathematical Modeling
;
Methodologies and Technologies
;
Operational Research
;
Optimization
;
Simulation
;
Symbolic Systems
Abstract:
Power flow studies use computational tools for the planning and operation of electrical power systems purposes. The deterministic model is the most commonly used load flow approach. In this model, the input data and the results are crisp values. Therefore, to account for uncertainties, the most common approach used is the definition of scenarios, which are characterized by crisp values. This is an impractical way to solve the problem of the uncertainty in the data. A more practical way to lead with the uncertainties is the use of probabilistic power flows. On such approach, the uncertainties are modelled through the use of probability density functions (pdf). However, that approach may be inappropriate, namely when there is no available historical data in order to construct the pdf. On such cases, the fuzzy power flows (FPF) is an interesting alternative. In this paper, a methodology named Symmetric Fuzzy Power Flow is used. That methodology uses optimization models to solve power fl
ow problems considering the uncertainty treated as fuzzy numbers. A comparison between the proposed methodology and the classic ones is also provided.
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