No abstract

No abstract

Despite photovoltaics being a new type of green energy technology, the output of the photovoltaic industry has been declining year by year since 2018. Thus, China’s photovoltaic industry must adapt to transformations from original extensive growth to the pursuit of high-quality energy. In order to accurately predict the installed capacity of photovoltaics in China, based on an extensive literature review and expert consultation, this paper is the first to construct a set of influencing factors that affect the photovoltaic industry, and we selected the main influencing factors as the predictive model’s input through the grey correlation analysis method. Then, we provide a novel grid investment forecast named the CEEMD-ABC-LSSVM predictive model (a least squares support vector machine algorithm based on complete total empirical mode decomposition and an artificial bee colony algorithm). This algorithm is based on the traditional LSSVM algorithm. The ABC algorithm is used to optimize the parameters, while CEEMD decomposes the original time series to obtain multiple components. While maintaining the data information, the data are expanded and the training is fully carried out. Next, in the empirical analysis, by comparing the prediction results of LSSVM, ABC-LSSVM, and the EMD-ABC-LSSVM algorithm, we demonstrate that the CEEMD-ABC-LSSVM model has strong generalization capabilities and achieves good Chinese PV growth based on the predicted effects of the installed capacity. Finally, the CEEMD-ABC-LSSVM model was used to predict the installed PV capacity in China from 2019 to 2035. We find that China’s installed PV capacity will surpass 4000 GW around 2035. As this installed capacity will increase year by year, China’s PV industry development will maintain steady overall growth.

No abstract

Various countries in the world are vigorously developing energy-saving industries and attaching importance to the improvement of household energy efficiency, but it is difficult to evaluate user power consumption characteristics due to insufficient information and large data granularity. It is, however, possible to evaluate the energy efficiency of household users via non-intrusive load monitoring (NILM). This paper explores the energy efficiency assessment of residential users and proposes a household energy efficiency assessment method based on NILM data. An energy efficiency assessment index of residents is provided by analyzing factors that affect residents’ energy efficiency. This index is clear, operable, and easy to obtain and quantify. Based on NILM information, clustering, and comprehensive evaluation, as well as combining the entropy weight method with the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), a user’s energy efficiency can be evaluated and analyzed. Some case studies are provided to verify the validity of the proposed method based on non-intrusive information, to analyze the characteristics and deficiencies of the user’s energy consumption, and to give corresponding energy recommendations.

No abstract

In this paper, a structure-reconfigurable resonant DC-DC (direct current -direct current) converter is presented. By controlling the state of the auxiliary switch, the converter could change the resonant structure to acquire a high efficiency and wide voltage gain range simultaneously. The characteristics of the LLC (inductor-inductor-capacitor) resonant converter are firstly analyzed. Based on this, through introducing additional resonant elements and adopting the topology morphing method, the proposed converter can be formed. Moreover, a novel parameter selection method is discussed to satisfy both working states. Then, a detailed loss analysis calculation is conducted to determine the optimal switching point. In addition, an extra resonant zero point is generated by the topology itself, and the inherent over-current protection is guaranteed. Finally, a 500 W prototype is built to demonstrate the theoretical rationality. The output voltage is constant at 400 V even if the input voltage varies from 160 to 400 V. A peak efficiency of 97.2% is achieved.Energies 2019, 12, 2905 2 of 25 efficiency is another requirement to be met. To sum up, DC-DC converters with a high efficiency and wide voltage gain range have considerable research significance.Energies 2019, 12, x FOR PEER REVIEW 2 of 25 high conversion efficiency is another requirement to be met. To sum up, DC-DC converters with a high efficiency and wide voltage gain range have considerable research significance.

No abstract