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As renewable energy penetration increases, the lack of flexibility in a multi-renewable power system can seriously affect its own economics and reliability. To address this issue, three objectives are considered in this study: power fluctuations on tie-line, operating cost, and curtailment rate of renewable energy. Presented also is an optimal day-ahead scheduling model based on the MREPS for distributed generations with flexibility constraints. The multi-objective particle swarm optimization (MOPSO) algorithm can be applied to obtain a set of Pareto non-dominated solutions for the day-ahead scheduling strategy with the proposed model. By using fuzzy comprehensive evaluation, the optimal compromise solution is determined in the set. The presented method sacrifices a small amount of economy and power fluctuation, but it can reduce the deviation between forecast and realized power fluctuations on the tie-line, while improving the utilization of renewable energy.

The friction between piston ring-cylinder liner is a major cause of energy losses in internal combustion engines. However, no experimental method is available to measure and analyze the fictional behavior. This paper focuses on the investigation of using acoustic emission (AE) to characterize the friction online. To separate the effect relating to friction sources, wavelets multi-resolution analysis is used to suppress interfering AE events due to valve impacts and combustion progress. Then a wavelet envelope indicator is developed to highlight AE contents from friction induced AE contents. The results show that the AE contents in the middle strokes correlate closely with viscous friction process as their amplitudes exhibit a continuous profile similar to piston speed. Furthermore, the AE envelope indicator proposed can distinguish the differences between two types of lubrication oils, showing superior performance of AE based online lubrication diagnosis.