The inevitable inconsistency among individual cells will reduce the available capacity of the series battery pack and even cause safety hazards due to overcharge and overdischarge. To address this problem of series battery pack inconsistency, this paper proposes a dual target equalization control strategy based on a dual multi-winding flyback converter. The benefits of the suggested topology include easy control and quick equalization; By merging the battery charging and discharging operations, the dual target equalization control technique has the effect of reducing the balancing time and increasing the equalization efficiency. The dual objective control strategy, in comparison to the single objective control strategy, diminishes the process of equalization time by about 36.1% during discharge and improves the SOC (State of Charge) by 0.2%; during charging, it reduces the equalization time by 42.7% and strengthens the SOC by 0.21%. The excellence and efficacy of the suggested equalization topology and control method are confirmed by the simulation results.

This paper constructs a centralized noncooperative game model of power sales with grid's risk avoidance and its renewable energy power's investment and production strategy considering renewable energy power production quotas and green power certificate system based on a method which combines the nonlinear programming theory and the Nash equilibrium for the complete information static game, is investigated. The result of the investigation shows that there exists a unique optimal renewable energy power's investment and production strategy (i.e., the optimal renewable energy utilization rates and the optimal power production quantities) for the proposed model. Moreover, it's proven that an increase in the risk-aversion coefficient of the grid would improve the optimal power price and the demand for the optimal total power production quantity based on which the risk-neutral duopoly oligopoly energy suppliers would seize the opportunity to raise investment costs in renewable energy technologies and improve the optimal renewable energy utilization rates for boosting the optimal power production quantities from their own perspective. Finally, numerical verifications for the unique optimal renewable energy power's investment and production strategy and the corresponding optimal revenue functions for the proposed model is realized on the integrated simulation platform of MATLAB and V-REP by utilizing the gradient-like optimization method.

As a vital important parameter of lithium-ion batteries (LIBs), accurately estimating the state of charge (SOC) holds significant importance in ensuring the reliable and stable operation of power storage equipment. To enhance the accuracy of SOC estimation, an adaptive high-degree unscented Kalman filter (AHUKF) approach is put forward. Firstly, a model of LIBs is established and the corresponding parameters are identified using the adaptive forgetting factor regression least-squares (AFFRLS) approach. The adaptive forgetting factor can augment the features of novel data and gradually diminish the influence of historical data. Subsequently, the AHUKF approach is proposed to strengthen the exactness and consistency of SOC estimation for LIBs. Finally, the effectiveness and robustness of the AHUKF approach are validated through simulation consequences attained under the FUDS and DST conditions.

Electrical power data has the advantages of wide coverage, strong real-time and high authenticity, consequently, electrical power data can represent consumption level to some extent. To reflect the consumption level accurately, the paper constructs a electrical power consumption index system based on a combination of entropy weight method (EWM) and analytic hierarchy process (AHP). Firstly, the paper studies the basic types and classifications of consumption of a province in China and then divides consumption into eight categories and each category is subdivided into various industries. Secondly, the paper picks up the effective electricity indicators that can characterize consumption, on this basis, it analyzes the correlation between electrical power data and consumption data, then establishes a multi-factor consumption index system based on electrical power data, applying the EWM and AHP to the mathematical model of consumption index, and puts forward the implementation steps. Finally, the method is respectively applied to various industries and total industry in the province of China, and the consumption index and electrical power data are empirically studied, which shows that the proposed method is effective and practical.

In the student-centered cultivation model, innovation ability and engineering skills of solving complex engineering problems is generally considered to be the key goal, which is usually broken down into small independent tasks arranged in different courses to support it from varying ways. However, at the implementation level, the actual training effect is not quite satisfactory due to the weak relationship between different courses and the lack of motivation for teachers to communicate with each other. In this paper, we propose a set of blended learning courses focusing on cultivating innovation ability throughout the undergraduate study period. Based on our design, the blended learning courses integrate MOOC, private course, comprehensive curriculum project, discipline competition and other types of courses, aiming to comprehensively improve undergraduates' innovation ability and engineering skills. These courses are arranged in different semesters and majors according to their general knowledge and specialization. After six years of practice for at least 3 generations of undergraduate students who have completed a whole training plan, we have collected a large number of data and made detailed analysis. It shows that undergraduates who participate in the complete learning process of the blended courses have obvious advantages in professional course scores, scholarship and award proportion.

Due to the inverter used, DG can not only integrate the active power into power grid but also support the grid with reactive power. This paper proposes an optimal configuration methodology of renewable DG so as to maximize the penetration level of DG considering the temporal characteristics of active-reactive power (P-Q). Further, the uncertainty output of the wind generator, photovoltaic and small hydropower is taken into account by forming typical scenarios based on the cluster analysis of historical data. Simulation on a modified IEEE33-bus distribution system show that a significant increase in maximum penetration can obtain by considering the reactive power of DGs.