电厂优化配煤的不确定性机会约束非线性规划方法

动力配煤是适合中国国情的一种洁净煤技术，可以改善燃煤电厂的经济效益和燃烧性能。动力配煤技术的关键在于优化求解，然而煤质参数是不确定的和可变的，电厂优化配煤决策必须处理这些不确定性。文中建立了一个不确定性机会约束非线性规划模型(inexact chance-constrained nonl- inear programming, ICCNLP)来处理不确定条件下电厂优化配煤问题。ICCNLP可有效处理以区间或概率密度分布表征的不确定性，并评估为实现系统成本最小而需承担的违反约束的风险水平，如超出硫排放标准的风险。结果表明，ICCNLP可得到稳定和可行的区间解，决策者可根据实际情况，在解区间内调整决策变量值，从而得到多个决策替代方案。

Inexact Chance-constrained Nonlinear Programming Method for Coal Blending in Power Plants

Coal blending is a kind of clean coal combustion technology suitable for China, and it can improve economic and combustion performance of power plants. The key of this technology lies in the optimization calculations. However, decisions about coal blending must deal with uncertainty and variability in coal properties, so a hybrid inexact chance- constrained nonlinear programming (ICCNLP) model was developed for coal blending problems under uncertainty. The ICCNLP could directly handle uncertainties presented as both intervals and probability density distributions, and assess the risk of violating various constraints, such as the probability of exceeding the sulfur emission standard, for accomplishing a minimizing system cost. The results indicate that feasible and stable interval solutions will be obtained and some decision alternatives can be generated by adjusting decision variable values within their solution intervals according to applicable conditions.