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Due to the growing demand on renewable energy, photovoltaic (PV) generation systems have increased considerably in recent years. However, the power output of PV systems is affected by different weather conditions. Accurate forecasting of PV power output is important for system reliability and promoting large-scale PV deployment. This paper proposes algorithms to forecast power output of PV systems based upon weather classification and support vector machines (SVM). In the process, the weather conditions are divided into four types which are clear sky, cloudy day, foggy day, and rainy day. In this paper, a one-day-ahead PV power output forecasting model for a single station is derived based on the weather forecasting data, actual historical power output data, and the principle of SVM. After applying it into a PV station in China (the capability is 20 kW), results show the proposed forecasting model for grid-connected PV systems is effective and promising. [ABSTRACT FROM PUBLISHER]

With the rapid development of China high-speed railway, the low frequency oscillation (LFO) of electrical quantities appears more often recently and leads to some severe problems of train operation. To improve the traction line-side converter control and suppress the phenomenon economically and effectively, a model-based predictive direct power control (MPDPC) approach is proposed in this paper. The approach adopts a discrete-time model of traction line-side converter in d–q reference frame to predict the future values of the input active and reactive power. The optimal switching state is selected by minimizing a cost function of power to evaluate the power errors at the next sampling time. Through the theoretical analysis and simulations, the performance of MPDPC is compared with traditional transient direct current control (TDCC) that is widely adopted in China Railway High-Speed 3 electric-multiple-unit. The real-time online simulations based on Real-Time Laboratory (RT-LAB) are also realized to further validate the results. Moreover, two vehicle-grid cascade simulation systems are constructed, and the LFO suppressing capability of MPDPC and TDCC is compared. Finally, the steady-state characteristic, dynamic characteristic, and LFO suppressing capability of MPDPC are demonstrated through the analysis of key performance indexes. [ABSTRACT FROM AUTHOR]

Long-term electricity consumption forecasting has been a hot issue due to its importance in power systems planning. Recently, system dynamics (SD) have been considered a potential method for electricity consumption forecasting. However, traditional SD methods are failed in forecasting future power systems toward low-carbon, due to the complex influencing factors and the simple SD model structure. In this study, a novel method combining SD and the ImPACT equation is proposed to solve the above problem. First, a new influencing factor system including emerging factors is established to consider the development of future power system. Subsequently, the ImPACT equation is employed to decompose the electricity consumption into four subsystems. By doing this, the linkage between factors and electricity consumption can be better revealed, which helps to improve the forecasting accuracy. Next, models for quantifying the correlation between subsystems and factors are established using SD. Finally, the proposed method is verified by forecasting the power consumption of China in the future year 2030 to 2050. Furthermore, various scenarios are set to analyze the changing trend of future power consumption by different influencing factors. The results of this article can provide important basic information for power supply and power grid planning. [ABSTRACT FROM AUTHOR]

As a new energy vehicle, fuel cell vehicles (FCVs) have the advantages of pollution-free and zero-emission, which have attracted wide attention from all over the world. By predicting the ownership of FCVs, decision-makers can grasp the future development potential of FCVs, so that the national government can adopt corresponding policies and measures. To this end, based on analyzing the development trend of FCVs, this article proposes an FCVs ownership prediction method based on the generalized Bass model. From the perspective of technology, application, and market conditions of FCVs, this article first analyzes the development trend of FCVs in the future, which provides the basis for the establishment of the ownership prediction method and the estimation of model parameters. Then, considering the influence of levelized cost of driving (LCD) reduction and hydrogen refueling stations (HRSs) constructions, a prediction method of FCVs ownership based on the generalized Bass model is proposed, and the model parameters are estimated by Grey Verhulst model, electric vehicles data, and liquefied natural gas vehicles data. Through the proposed method, the ownership of FCVs in China from 2021 to 2070 is predicted and the results show that the ownership of FCVs in China will reach about 1.43 million in 2030 and about 10.41 million in 2040. Finally, through sensitivity analysis, this article discusses the influence of external factors such as policy, LCD, and HRSs on the market diffusion of FCVs, and puts forward corresponding suggestions. [ABSTRACT FROM AUTHOR]