PRICING FUZZY MODELS APPROACH FOR DECISION-MAKING IN POWER SYSTEMS ELECTRICITY TRANSACTIONS

The paper uses fuzzy set theory to obtain some fuzzy models which can be useful, each, as a decision - support to estimate an electrical energy (EE) price for consumers. In the same time, according to us, the paper can be a possible benchmark example of approximate reasoning, used as a fuzzy decision–support system. All three fuzzy tariff models developed in fuzzy environment, integrate some specific features of a deregulated electricity market, as in Romania in this transition period: i) in the market is only a single “seller―, SC Electrica SA (SCESA), i.e. a single-supplier of electrical energy; ii) because of this, the consumers interests, beginning with 1999, are protected by the National Authority of Settlements from Energy (NASE) through some (social) compulsions; iii) the average price of EE (/MWh) near our market place is, obviously, a real problem (in our case the markets are from: Russia, Ukraine, Bulgaria, Hungary, Serbia and Moldavia).Not being a competitive environment, the normal practice used in NASE rules as method of EE pricing are average costs, i.e. total costs divided by total sales. The fuzzy method shows how it is possible to perform sensitivity tests on the EE price function model (by changing the parameters of SCESA and NASE), until can obtain an acceptable and true price can be obtained. In this aim, the three fuzzy models use different rules for pricing: conservative, aggressive, and different order of words concerning the rules, and finally doing a comparation among prices and models. Though the paper will not exhaust all fuzzy rules, doubtlessly, create a way of fuzzy reasoning, as a modality to find an EE price.