Colombo (2021) Effects of surfactants/ stabilizing agents on the microstructure and properties of porous geopolymers by direct foaming,

The low carbon transition requires the high growth of renewable generation penetration in energy systems to ultimately achieve net-zero carbon target. To ensure the reliable operation of energy systems with high intermittent renewable output, it is critical to have sufficient flexible resources to avoid curtailment. Therefore, the integrated power-natural gas-heating energy systems with power to gas (P2G) and gas storage has attracted great research interest especially on the combined operation method to enhance the flexibility provision between each other. In this paper, taking heating demand, P2G and gas storage into consideration, a multi-objective optimal operation strategy of integrated power-natural gas-heating energy systems is presented to obtain the maximum economic and environmental benefits. Furthermore, a novel model of flexibility metric is proposed based on redundant linepack and gas storage. Case studies without P2G and with P2G are carried out on integrated IEEE 39-bus power and Belgian 20-node gas system. Simulation results demonstrate that P2G not only can be beneficial for operation of the integrated energy systems in terms of total operational cost decline from M$2.510 to M$2.503, CO2 emission reduction from 62,860 ton to 62,240 ton and wind curtailment decrease from 25.58% to 4.22% but also has significant effect on flexibility improvement of a 71.72% increase.

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Orbital angular momentum (OAM) mode-division multiplexing (MDM) is a key technique to achieve ultra-high-capacity optical fiber communications. However, the high nonlinear impairment from optoelectronic devices, such as spatial light modulators, modulators, and photodiodes, is a long-standing challenge for OAM-MDM. In this paper, an equalizer based on a probabilistic neural network (PNN) is presented to mitigate the nonlinear impairment for an OAM-MDM fiber communication system with 32 GBaud Nyquist pulse amplitude modulation-8 (PAM8) intensity-modulation direct-detection (IM-DD) signals. PNN equalizer can calculate the distribution of the nonlinearity using Bayesian decision theory and thus mitigate the stochastic nonlinear impairment of the received signal. Experimental results show that compared with the convolutional neural network (CNN) equalizer, the PNN equalizer improves the receiver sensitivity by 0.6dB and 2dB for two OAM modes with l = + 3 and l = + 4 at the 20% FEC limit, respectively. Moreover, compared with Volterra or CNN equalizers, the PNN equalizer can reduce the computation complexity significantly, which has great potential to mitigate the nonlinear signal distortions in high-speed IM-DD OAM-MDM fiber communication systems.

In the ship design, there are strict vibration-proof requirements for precision instruments. Therefore, a ship repulsive magnetic levitation damping device is designed to achieve vibration reduction. And one self-tuning predictive control method is proposed to achieve the stable levitation of this device. Firstly, a predictive control (MPC) method with state constraints and input constraints is adopted to realise the stable suspension of the floater. The MPC can solve the problem of position imbalance of the magnetic levitation system under the external complex disturbances. Secondly, a self-tuning MPC method based on recursive least square is proposed to solve the problem caused by the fixed parameters of the traditional predictive controller. At the beginning of each control cycle, the recursive least-squares (RLS) method is used to estimate the parameters of the system. Thus, the optimal control model could be obtained for the current situation. Then, this model is applied to the predictive controller to solve the problem of parameter fixation in the traditional predictive control. Finally, the simulation results show that it can improve the accuracy, dynamic response and anti-interference performance obviously.