Considering the floatability and uncertainties of Carbon Trade, this paper proposed a under Carbon Trade model called a two-stage inexact-stochastic programming (TISP) which was structured on the basis of Carbon emissions permits and the technologies and costs of carbon emission reduction. Then the balance of net benefit and CO2 emission permit of the system was sought through the optimization model. The paper showed the result about a significant index called µ. Firstly, when the model definedµ=40%, net system benefit achieved optimal and the benefit was higher under carbon trading than that under non-trading. Secondly, when the model definedµ<40%, the carbon reduction requirements of the coal-fired power plants could be met only by capture and storage (CS) reduction technology under the conditions of carbon trading or both the CS and chemical absorption (CA) reduction technology under the conditions of non-trading. Lastly, when the model definedµ>40%, all of the three power plants must develop the CA reduction technology processing on the premise of guaranteeing the CS technology. In a word, Carbon Trade would not only contribute to rationally allocating carbon reduction technologies but also help to establish a new trading markets including energy-use specification, carbon-emission criterion and pollutant-emission restriction. The final aim was to make the target of the carbon dioxide reduction come true as early as possible.%基于碳排放许可值、CO2减排技术与成本、碳交易参数的浮动性与不确定性,构建碳交易机制的区间两阶段不确定性随机规划模型(TISP),通过优化模型寻求系统净收益与CO2排放许可的平衡点,结果表明,当µ=40%时,系统的净收益为最优,且系统的净收益在碳交易模式下高于非交易模式下的净收益；当µ<40%时,燃煤电厂在碳交易模式下只需采用 CS 减排技术均能达到排放许可要求,在非交易模式下则同时采用CS和CA减排技术；当µ>40%时,3种发电方式在保证CS减排技术的前提下,均要增加CA减排技术的处理。碳交易机制有利于减排技术的合理分配及用能权、碳排放权和排污权交易市场的建立,尽快实现市场化节能碳减排目标。
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