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To accelerate the evolutionary process and increase the probability to find the optimal solution, the following methods are proposed to improve the conventional quantum genetic algorithm: an improved method to determine the rotating angle, the self-adaptive rotating angle strategy, adding the quantum mutation operation and quantum disaster operation. The efficiency and accuracy to search the optimal solution of the algorithm are greatly improved. Simulation test shows that the improved quantum genetic algorithm is more effective than the conventional quantum genetic algorithm to solve some optimization problems.

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A decentralised load frequency control (LFC) for multi-area power systems with communication delays is studied. Active disturbance rejection control (ADRC) method is adopted to handle the communication delays. First the conventional ADRC is tuned via the bandwidth method and it is shown that the achievable performance for delayed systems is no better than proportional-integral-derivative (PID) controllers. Then a modified ADRC structure is discussed and it is shown that the achievable performance is limited by the controller bandwidth. In order to improve the performance, a method to tune the parameters of ADRC is proposed via the internal model control method. Simulation results show that the proposed method is easy to apply and can achieve good damping performance.

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