Research On Intelligence Optimization Methods For Unit Commitment Scheme

Since genetic algorithms often cause premature convergence and do not give out global optimality in solving unit commitment (UC) scheme problems, while the simulated annealing algorithm shows better performance in accepting new solutions. By introducing annealing algorithm to the evaluation functions and the selection manipulation of genetic algorithms, the selection manipulation and the global convergence can be improved. Using decimal coding and without decoding, both the calculation error and time for calculation can be reduced. The result shows that this hybrid algorithm can improve the economic performance of UC scheme while various restrictions for security and reliability are still satisfied. In the environment of electricity market the reactive power and spinning reserve supporting by power plants are important ancillary services and are also effective measures to ensure the secure and stable operation of power system, improve power quality, reduce power losses and make the electric energy transaction smoothly carried out. These are new problems about UC scheme optimization under competitive markets. In this paper, the compensation cost of reactive power and spinning reserve supporting and automation generation control (AGC) is analyzed by economic measuring. The result shows that power plants should gain the synthetic economic compensation for providing the reactive power and other ancillary services in order to ensure the stable and secure operation for power system under competitive markets. Furthermore, new models and optimization methods for UC scheme under competitive markets are researched conveniently. Unit commitment scheme problem researched under competitive markets can helping power plants make good security and economic operating schedule. The aim model is based on maximizing profit considering of the affecting of reactive power and reserve, and subjected to the constraints such as the utilization of generator, power limiting, rate of the running up and down, system reserve and electricity markets transaction. The advantage of dual exponent programming, genetic algorithms and simulated annealing algorithms are synthesized to solving this UC scheme problem, and eight generators system is adopted for an example. The sample results show that unit commitment has take some places considering of income of reserve in competitive markets, that power plants will attach much importance to producing cost in order to get more profit, that UC scheme and its load distributing is affected directly by the power obtained by competing in power plant, and that the astringency performance of the synthetic optimization methods is better and suitable to solve UC scheme problem under competitive markets.