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Demand side real-time pricing (RTP) is a crucial measure of demand response (DR) in electricity markets. As an ideal retail tariff mechanism, price volatility risk of RTP can be rationally allocated among market participants by integrating various RTP-related hedge contracts. Based on RTP researches and experiences around the world, combining with random electricity price model, RTP-related hedge contracts are priced with Monte-Carlo simulation method. Furthermore, based on conditional value at risk (CVaR) method, a decision model, whose object is maximizing customer's utilities of electricity purchasing, is introduced. Optimal hedged load percentage for different risk preference customers can be obtained by solving the model. Numerical results are finally used to prove the effectiveness of the proposed model, which is beneficial to customer's selectively hedging against price volatility risk of RTP and enhancing interactions between load serving entity (LSE) and its customers.