Due to the intermittency and randomness of solar photovoltaic (PV) power, it is difficult for system operators to dispatch PV power stations. In order to find a precise expectation for day-ahead PV power generation, conventional models have taken into consideration the temperature, humidity, and wind speed data for forecasting, but these predictions were always not accurate enough under extreme weather conditions. Aerosol index (AI), which indicates the particulate matter in the atmosphere, has been found to have strong linear correlation with solar radiation attenuation, and might have potential influence on the power generated by PV panels. A novel PV power forecasting model is proposed in this paper, considering AI data as an additional input parameter. Based on seasonal weather classification, the back propagation (BP) artificial neural network (ANN) approach is utilized to forecast the next 24-h PV power outputs. The estimated results of the proposed PV power forecasting model coincide well with measurement data, and the proposed model has shown the ability of improving prediction accuracy, compared with conventional methods using ANN.Index Terms-Aerosol index (AI), artificial neural network (ANN) method, back propagation (BP) network, maximum absolute prediction error, photovoltaic (PV) power forecasting.

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LiMnPO 4 (LMP) is one of the most potential candidates for high energy density (≈700 W h kg -1 ) lithium ion batteries (LIBs). However, the intrinsically low electronic conductivity and lithium ion diffusion coefficient of LMP result in its low performance. To overcome these challenges, it is an effective approach to prepare nanometer-sized Fe-doping LMP (LFMP) materials through optimization of the preparation routes. Moreover, surface coating can improve the ionic and electronic conductivity, and decrease the interfacial side reactions between the nanometer particles and electrolyte. Thus, a uniform surface coating will lead to a significant enhancement of the electrochemical performance of LFMP. Currently, considerable efforts have been devoted to improving the electrochemical performance of LiFe 1-y Mn y PO 4 (0.5 ≤ y < 1.0) and some important progresses have been achieved. Here, a general overview of the structural features, typical electrochemical behavior, delithiation/ lithiation mechanisms, and thermodynamic properties of LiFe 1-y Mn y PO 4based materials is presented. The recent developments achieved in improvement of the electrochemical performances of LiFe 1-y Mn y PO 4 -based materials are summarized, including selecting the synthetic methods, nanostructuring, surface coating, optimizing Fe/Mn ratios and particle morphologies, cation/ anion doping, and rational designing of LFMP-based full cells. Finally, the critical issues at present and future development of LiFe 1-y Mn y PO 4 -based materials are discussed.of LIBs. [3,4] Investigation on the design and preparation of high performance cathode materials has received extensive attention from academic and industrial research worldwide. The first successful example of LiCoO 2 discovered by Goodenough and his co-workers in 1980 is a dominating cathode material in commercial portable electronic devices. [5] It displays medium specific capacity and high compaction density when it is employed as a cathode material in the fabrication of electrode, resulting in its high energy density. In order to improve the safety of LIBs, decrease the cost and to enhance specific capacity, researchers have been trying to find other efficient materials. Many oxide-based positive insertion materials, such as LiMn 2 O 4 , [6] LiMn 1.5 Ni 0.5 O 4 , [7] LiNi 0.8 Co 0.15 Al 0.05 O 2 [8]and LiMn 0.33 Co 0.33 Ni 0.33 O 2[9] were proposed as possible alternatives to the existing layered LiCoO 2 cathodes because of its own shortcomings, such as the toxicity and high cost of cobalt as well as its poor thermal stability. [10] Figure 1 illustrates crystal structures and discharge curves for some typical cathode materials, including layered LiCoO , spinel LiNi 0.5 Mn 1.5 O 4 and olivine LiFePO 4 , in which spinel and olivine materials show flat potential plateaus, while layered materials display sloping potential profiles. [11] Besides the transition metal oxides-based cathode materials, phospho-olivines introduced firstly by Goodenough and co-workers in 1997 as cathode materials for L...