Review of Energy Transition Policies in Singapore, London, and California

The paper contains the online supplementary materials for "Data-Driven Prediction and Evaluation on Future Impact of Energy Transition Policies in Smart Regions". We review the renewable energy development and policies in the three metropolitan cities/regions over recent decades. Depending on the geographic variations in the types and quantities of renewable energy resources and the levels of policymakers' commitment to carbon neutrality, we classify Singapore, London, and California as case studies at the primary, intermediate, and advanced stages of the renewable energy transition, respectively

The Application of PSO-AFSA Method in Parameter Optimization for Underactuated Autonomous Underwater Vehicle Control

In consideration of the difficulty in determining the parameters of underactuated autonomous underwater vehicles in multi-degree-of-freedom motion control, a hybrid method that combines particle swarm optimization (PSO) with artificial fish school algorithm (AFSA) is proposed in this paper. The optimization process of the PSO-AFSA method is firstly introduced. With the control simulation models in the horizontal plane and vertical plane, the PSO-AFSA method is elaborated when applied in control parameter optimization for an underactuated autonomous underwater vehicle. Both simulation tests and field trials were carried out to prove the efficiency of the PSO-AFSA method in underactuated autonomous underwater vehicle control parameter optimization. The optimized control parameters showed admirable control quality by enabling the underactuated autonomous underwater vehicle to reach the desired states with fast convergence

A LSSVR Interactive Network for AUV Motion Control

In view of the requirements on control precision of autonomous underwater vehicles (AUVs) in different operations, the improvement of AUV motion control accuracy is the focus of this paper. In regard to the unsatisfying robustness of traditional control methods, an interactive network based on Least Square Support Vector Regression (LSSVR) is therefore put forward. The network completed the identification of the strong nonlinear AUV dynamic characteristics based on the LSSVR theory and by virtue of the interactions between the offline and online modules, it achieved offline design and online optimization of the AUV control law. In addition to contrastive numerical simulations and sea trials with the classic S-plane method in AUV velocity and heading control, the LSSVR network was also tested in path following and long-range cruise. The precision and robustness and of the proposed network were verified by the high-accuracy control results of the aforesaid simulations and trials. The network can be of practical use in AUV control especially under unfamiliar water conditions with access to a limited number of control samples or little information of the operation site

Conducting Polymer Nanostructures: Template Synthesis and Applications in Energy Storage

Conducting polymer nanostructures have received increasing attention in both fundamental research and various application fields in recent decades. Compared with bulk conducting polymers, conducting polymer nanostructures are expected to display improved performance in energy storage because of the unique properties arising from their nanoscaled size: high electrical conductivity, large surface area, short path lengths for the transport of ions, and high electrochemical activity. Template methods are emerging for a sort of facile, efficient, and highly controllable synthesis of conducting polymer nanostructures. This paper reviews template synthesis routes for conducting polymer nanostructures, including soft and hard template methods, as well as its mechanisms. The application of conducting polymer mesostructures in energy storage devices, such as supercapacitors and rechargeable batteries, are discussed