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Dynamic optimization is likely to play an important role in the reliability, quality, and efficiency of future power system, specifically for microgrid with renewable generation. This paper presents an improved hybrid optimization algorithm, called information exchange particle swarm optimization (IEPSO), to deal with the problem of dynamic optimal control in a microgrid with multiple distributed generations (DGs), such as wind power, small hydro, and energy storage. Based on the actual application of DG in Southwest China, we propose an optimization model for grid-connected microgrid that introduces a contribution rate of energy storage into the model and incorporates practical engineering constraints. The performance of different optimization control strategies for active and reactive power is investigated, and the results indicate that the IEPSO algorithm is efficient for dynamic optimization, and the dynamic contribution rate control strategy for energy storage is more effective than static strategy. [ABSTRACT FROM AUTHOR]

Several measurements of the radon concentration are performed by RAD7 in the University of South China. We find that 30-40 min is needed for RAD7 for tracing the concentration of the standard radon chamber. There are two reasons. The first is that the sufficient time of air cycle is needed for the radon concentration in internal cell of RAD7 equal to that of the environment; and the second is that the sufficient decay time is needed for the 218Po concentration in internal cell of RAD7 equal to that of the radon. We used a zeroth order approximation to describe the evolution of the environment radon concentration, and obtained a novel algorithm for quick and continuous tracing the change of radon concentration. The corrected radon concentration obtained through this method is in good agreement with the reference value. This method can be applied to develop and improve the instruments for tracing the change of radon concentration quickly. [ABSTRACT FROM AUTHOR]