This article describes an intelligent simulation method for measuring price risk, which is still one of the important problems for various risk managements and need to be studied profoundly. To solve this problem, risk measured in terms of Value at Risk on electricity price is proposed by intelligent simulation. In this work, prices under various market scenarios are produced by intelligent model using fuzzy neural network (FNN). After that, the quantitative model for price risk analysis is built in the form of a function of the estimated probability distribution of price, where price VAR is determined from the distribution according to parameter set, i.e. confidence level. The proposed method is more realistic and effective than variance approach to provide the assessment of the potential loss of electricity price over some period of time.