This article describes the physicochemical properties of chitosan-coated liposomes containing skin-protecting agents, coenzyme Q10 and alpha-lipoic acid (CCAL). CCAL had a spherical shell-core structure and liposomes inverted the surface charge from negative to positive after coating with chitosan. Compared with the uncoated liposome, CCAL had higher zeta potential, larger droplet size and long-term stability. Fourier transform infrared spectroscopy (FTIR) study showed that the driving force for chitosan coating the liposomes was enhanced via hydrogen bonding and ionic bond force between the chitosan and the alpha-lipoic acid. While the encapsulation efficiency (EE) of alpha-lipoic acid also increased by interacting with the chitosan shell. In vitro antioxidant activity study showed an excellent hydroxyl radical scavenging activity of CCAL. In vitro release study displayed a sustained drug release, and in vitro penetration studies promoted the accumulation of drugs in rabbit skin.

The purpose of this paper is to investigate the short-term wind power forecasting. STWPF is a typically complex issue, because it is affected by many factors such as wind speed, wind direction, and humidity. This paper attempts to provide a reference strategy for STWPF and to solve the problems in existence. The two main contributions of this paper are as follows. (1) In data preprocessing, each encountered problem of employed real data such as irrelevant, outliers, missing value, and noisy data has been taken into account, the corresponding reasonable processing has been given, and the input variable selection and order estimation are investigated by Partial least squares technique. (2) STWPF is investigated by multiscale support vector regression (SVR) technique, and the parameters associated with SVR are optimized based on Grid-search method. In order to investigate the performance of proposed strategy, forecasting results comparison between two different forecasting models, multiscale SVR and multilayer perceptron neural network applied for power forecasts, are presented. In addition, the error evaluation demonstrates that the multiscale SVR is a robust, precise, and effective approach.

Recently, the coordination of EVs’ charging and renewable energy has become a hot research all around the globe. Considering the requirements of EV owner and the influence of the PV output fluctuation on the power grid, a three-objective optimization model was established by controlling the EVs charging power during charging process. By integrating the meshing method into differential evolution cellular (DECell) genetic algorithm, an improved differential evolution cellular (IDECell) genetic algorithm was presented to solve the multiobjective optimization model. Compared to the NSGA-II and DECell, the IDECell algorithm showed better performance in the convergence and uniform distribution. Furthermore, the IDECell algorithm was applied to obtain the Pareto front of nondominated solutions. Followed by the normalized sorting of the nondominated solutions, the optimal solution was chosen to arrive at the optimized coordinated control strategy of PV generation and EVs charging. Compared to typical charging pattern, the optimized charging pattern could reduce the fluctuations of PV generation output power, satisfy the demand of EVs charging quantity, and save the total charging cost.

Islands are the main platforms for exploration and utilization of marine resources. In this paper, an island hybrid renewable energy microgrid devoted to a stand-alone marine application is established. The specific microgrid is composed of wind turbines, tidal current turbines, and battery storage systems considering the climate resources and precious land resources. A multi-objective sizing optimization method is proposed comprehensively considering the economy, reliability and energy utilization indexes. Three optimization objectives are presented: minimizing the Loss of Power Supply Probability, the Cost of Energy and the Dump Energy Probability. An improved multi-objective grey wolf optimizer based on Halton sequence and social motivation strategy (HSMGWO) is proposed to solve the proposed sizing optimization problem. MATLAB software is utilized to program and simulate the optimization problem of the hybrid energy system. Optimization results confirm that the proposed method and improved algorithm are feasible to optimally size the system, and the energy management strategy effectively matches the requirements of system operation. The proposed HSMGWO shows better convergence and coverage than standard multi-objective grey wolf optimizer (MOGWO) and multi-objective particle swarm optimization (MOPSO) in solving multi-objective sizing problems. Furthermore, the annual operation of the system is simulated, the power generation and economic benefits of each component are analyzed, as well as the sensitivity.

The establishment of isolated microgrid is of great significance in solving power supply problems in offshore islands or remote mountainous areas. Aiming at the isolated microgrid containing photovoltaic, photothermal, wind, diesel, and energy storage, a three-objective sizing optimization model of the microgrid is proposed considering comprehensive economy cost, deficiency of power supply probability (DPSP), and renewable energy discard rate (REDR). The three-objective sizing optimization model was solved by the improved multiobjective grey wolf optimization algorithm. An island was taken as an example to optimize the sizing of the microgrid, and the rationality of the proposed three-objective model was verified. The feasibility of the improved multiobjective grey wolf optimization (IMOGWO) was verified by comparing with the multiobjective grey wolf optimization (MOGWO). Three representative solution sets and a set of compromise solution sets are obtained by simulation, and the results satisfied the load demand. And the DPSP and the REDR are reduced by 7.55% and 6.29% by using the IMOGWO. The designed and analyzed hybrid renewable energy system model might be applicable to around the world having similar climate conditions.