Simulated annealing-based optimal wind-thermal coordination scheduling

The rise of environmental protection and the progressive exhaustion of traditional fossil energy sources have increased the interests in integrating wind energy sources into existing power systems. Development of better wind-thermal coordination algorithms is necessary to determine the optimal proportion of wind generator capacity that can be integrated into the system for operating an isolated hybrid power system reliably and efficiently. A stochastic searching technique, which utilises a simulated annealing (SA) approach combined with an efficient constrained dynamic economic dispatch (CDED) method, is developed to coordinate the wind and thermal generation scheduling in isolated power systems with large integration of wind capacity. The SA algorithm is used for the scheduling of the generating units, whereas a direct search method routine carries out the ramp rate CDED when considering wind power generation. Several technique constraints are applied to determine the maximum proportion of wind generator capacity that can be integrated into the system. A constraint satisfaction technique for generating feasible neighbouring solution is also developed to improve the SA solution process. Numerical experiments are included to understand the wind generator capacity in the operating cost analysis and to provide valuable information for both the operational and planning problems.