Probabilistic interval prediction can be used to quantitatively analyse the uncertainty of wind energy. In this paper, a wind power interval prediction model based on chaotic chicken swarm optimization and extreme learning machine (CCSO-ELM) is proposed. Traditional optimization has limitations of low population diversity and a tendency to easily fall into local minima. To address these limitations, chaos theory is adopted in the chicken swarm optimization (CSO), which improves its performance and efficiency. In addition, the traditional cost function does not reflect the deviation degree of off-interval points; hence, an evaluation index considering the relative deviation of off-interval points is proposed in this paper. Finally, the new cost function is taken as the fitness function, the output layer weight of ELM is optimized using CCSO, and the lower upper bound estimation (LUBE) is adopted to output the prediction interval directly. The simulation result shows that the proposed method can effectively reduce the average bandwidth, improve the quality of interval prediction, and guarantee the interval coverage.

Large eddy simulations based on the CFD software OpenFOAM have been used to study the effect of Reynolds number and turbulence intensity on the flow and mixing characteristics of an argon thermal plasma jet. Detailed analysis was carried out with respect to four aspects: the average flow field, the instantaneous flow field, turbulence statistical characteristics and the self-similarity. It was shown that for the argon thermal plasma jet with low Reynolds number, increasing the turbulence intensity will increase the turbulent transport mechanism in the mixing layer rather than in the jet axis, leading to the faster development of turbulence. The effect of the turbulent transport mechanism increases with increasing Reynolds number. However, the characteristics of flow and mixing are not affected by turbulence intensity for high Reynolds number situations. It was also found that the mean axial velocity and mean temperature in the axis of the turbulent thermal plasma jet satisfy the self-similarity aspects downstream. In addition, decay constant K is 1.25, which is much smaller than that (5.7–6.1) of the turbulent cold gas jet and has nothing to do with the Reynolds number or turbulence intensity in the jet inlet.

Because of the complexity and severity of the marine environment, the probability of failure of offshore wind farms is much higher than that of onshore wind farms. The original control might fail under a single-machine and the network communication faults of wind turbines. In this study, centralized control is replaced with distributed control, the leader-follower distributed control strategy under two types of fault conditions is proposed to reduce the adverse effect of failure on the system and improve the tolerance of the system. First, the single-machine system is expanded into a wind turbine cluster system model based on Hamiltonian energy theory. Then, a leader-follower distributed control strategy is proposed to ensure the stable operation of wind turbines under a single-machine fault of the leader or follower unit. Next, considering communication failure, the leader-follower control strategy in the weakly connected topology is designed to make the system and the active power output stable. Finally, the simulation results confirm that the leader-follower control strategy system can enhance the stability and reliability of the system in the case of a unit shut down and network communication faults.

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With the implementation of low-carbon economy policy, clean energy (such as wind and solar energy) has been developing rapidly, and the percentage is increasing year by year; On the other hand, with a steadily growing percentage of residential electricity consumption and commercial electricity consumption, resulting in large electricity load difference between peak and valley, the load related requirements of modern steam power plants are noticeably changing. Whereas the past units being designed in base load now have to take part in peak load, and usually in a low load operation, unable to play its advantages of high efficiency in design load. In the article the current three main governing methods (i.e. nozzle governing, throttling governing and bypass governing) for steam turbine will be discussed and evaluated under economical criteria focused on the above described challenges for future power generating technologies. A new governing method is Nozzle governing with Overload Valve Regulation, which keeps the advantage that main steam pressure of the Nozzle governing steam turbine is higher under partial load conditions, and weakens the influence of the low efficiency of governing stage on high pressure turbine, effectively improves the efficiency of steam turbine unit under partial load conditions. In the turbine adopted the new governing method of Nozzle governing with Overload Valve Regulation, the first stage is governing stage, divided into several groups. Main steam from boiler goes through the main stop valve and main steam control valve in sequence, and then turns to the governing stage. When the load is below 85%THA, main steam control valve I, II and III are fully opened, main steam control valve IV is fully closed, and the unit is in sliding pressure operation. When the load is 85%THA, the main steam pressure can reach the rated pressure. With the load increasing, main steam control valve IV starts to open, but the main steam pressure maintains the rated pressure, adjusted to THA when main steam control valve IV is fully opened and the flowrate of governing stage reaches the maximum. In the load more than THA condition, the bypass valve starts to open, the main steam goes through the bypass steam room into the certain stage (as fourth), to meet the requirements of the super load, adjusted to VWO (about 108%THA) when the bypass valve is fully opened. Through the detailed description about the scheme set and calculation analysis about economy benefit of the new regulation technology of Nozzle governing with Overload Valve Regulation, it shows that with the annual load range of 40%THA–85%THA, the economy of turbine adopted the new regulation technology is better than bypass governing by about 21.6 kJ/kW.h. (CSPE)