An algorithm for linguistic risk assessment of uncertain factors in generation planning

Abstract

AbstractThis paper presents an efficient computational algorithm for evaluating the risks of uncertain factors in generation planning. Uncertainty in a multiobjective risk assessment problem can be divided into (a) uncertainty of the possible conditions to be evaluated; (b) uncertainty in multiobjective decision making; and (c) uncertainty in risk which is obtained using imprecise information.The proposed method basically consists of two phases: (1) the aggregation of risks with respect to all of the objectives for each uncertain factor; and (2) the linguistic expression of the aggregated risk of each uncertain factor. In the first phase, uncertainty in possible conditions is treated as fuzziness in planning parameters, and uncertainty in multiobjective decision making is also treated as fuzziness in decision making.Furthermore, the statistical trend of risk with respect to an objective for each uncertain factor can be extracted from uncertain risks obtained using imprecise information. In this method, both classes of fuzziness and the statistical trend of risk for each uncertain factor can be integrated into the risk of each uncertain factor, and then the risks of each uncertain factor with respect to all the objectives can be aggregated by extension principle in fuzzy sets theory. In the second phase based on the linguistic approximation technique, the aggregated risk of each uncertain factor can be represented by natural language. The proposed method can realize an effective and flexible decision support for evaluating the risks of uncertain factors in generation planning. The effectiveness and feasibility of the proposed method are demonstrated on a typical power system model.