With the power system in China had been divided into five major power grid, different stakeholders have been formed, so there is internal competition in the five major power grid. Furthermore, the pollution caused by power industry become seriously. So optimal economic scheduling of electric power system is very important. By optimization, the grid can not only increase revenue by reduce costs, but also can reduce pollution. However, power system optimal dispatch is a complicated and multi-object problem. In this paper, elite group guided quantum-inspired evolutionary algorithm has been adopted. The elite group at each iteration is composed of a certain number of individuals with better fitness values in the current population, all the individuals in the elite group cooperate together to affect quantum-inspired gates to produce off spring. As a weighted state preference can push the genes of individuals to evolve toward state '1'. Simulation results show that the new algorithm is effective.
[1]
S. Soares,et al.
Nonlinear Medium-Term Hydro-Thermal Scheduling With Transmission Constraints
,
2014,
IEEE Transactions on Power Systems.
[2]
A.G. Bakirtzis,et al.
Simulation of Optimal Medium-Term Hydro-Thermal System Operation by Grid Computing
,
2009,
IEEE Transactions on Power Systems.
[3]
Peter B. Luh,et al.
An optimization-based algorithm for scheduling hydrothermal power systems with cascaded reservoirs and discrete hydro constraints
,
1997
.
[4]
Bai Xiaomin,et al.
Optimal scheduling of large hydro-thermal power system
,
1991
.