In solving the transmission line maintenance scheduling optimization problem(TMSOP) under electric marketing circumstances,a chance-constrained bi-level programming model and a hybrid intelligent algorithm are put forward.

Study on Chance-Constrained Programming Model of Resource Distribution and Convey in Stochastic Environments;

A chance-constrained programming model taking interruptible load into consideration for the requirement of spinning reserve in power system

A model is established for ILM in the framework of chance-constrained programming aiming at maximizing the expected profit.

On the basis of considering the risk reference of interruptible consumers and the impact of different power supply interruption duration on consumer interruption cost, a chance constrained programming based pricing model for interruptible loads is established, and by means of the approach that embeds Monte Carlo stochastic simulation into genetic algorithm the proposed model is solved.

This paper discusses a distribution network with many venders,many retailers and multi-product suppliers,presents the stochastic programming model for the minimum total cost of the distribution network,in which the demand and the production are random variables,and converts chance constrained programming model to their definitive equivalents.

A chance constrained programming model is built to the stochastic optimal power flow problem(S-OPF)considering load probabilistic distributions.

A stochastic chance-constrained programming model is put forward for human resources program,which uses the maximum of oil output as objective and takes both cost and human requirement into account,and the process of its hybrid intelligent algorithm is provided at the same time.

Because of randomicity of load and spot price, which construct a stochastic vector, a mathematical model is set up based on stochastic chance-constrained programming(CCP).