Enhancing the powering ability of triboelectric nanogenerator through output signal’s management strategies

As a new branch of efficient and low-cost mechanical energy conversion technology,triboelectric nanogenerator(TENG)is a potential solution to provide a long-term power supply for the Internet of Things(IoT)sensors and portable electronic devices.However,due to inherent working properties of TENG itself such as extremely high internal impedance,pulse,and alternating current(AC)output,TENG can not directly supply power to loads such as batteries efficiently.Based on these,we describe TENG’s performance from a new perspective of powering ability.It consists of two aspects:the ability to transport charge effectively and the ability to output high power quality current steadily.In order to push forward the developments and applications of TENG,it is necessary to improve its power supply capacity from different perspectives.Fortunately,in recent years,a variety of output signal’s management strategies aiming at effectively managing the generated electricity and significantly improving powering ability of TENG have obtained significantly progress.Herein,this paper discusses the working mechanisms and different load characteristics of TENG at first to clarify the electric performance of TENG.Then,on basis of theoretical analysis,the output signal’s management strategies are elaborated from four aspects:improving the cycle output electricity of TENG,increasing the surface charge density of TENG,improving the power quality of TENG-based energy harvesting system,promoting the application of TENG through integrated circuit(IC)technology and TENG network,and the relevant principles and applications are discussed systematically.Finally,the advantages and disadvantages of the above output signal’s management strategies are summarized and discussed,and the future development of the output signal’s management strategies for TENG is prospected.

Comprehensive evaluation model of wind power accommodation ability based on macroscopic and microscopic indicators

This article explores and establishes comprehensive evaluation index system of wind power accommodation ability considering microscopic index and macroscopic index, and the index system includes conventional evaluation indexes such as forecast deviation, simultaneity factor and anti-peak rate, also newly introduced evaluation indexes such as installed capacity, power adequacy and accommodation space. Bayesian weight modified method is used for solving index weights of 8 wind power accommodation indexes. The paper puts forward a comprehensive evaluation model of wind power accommodation ability based on improved radar chart method, and this model changes traditional radar chart fan-shaped sector to quadrilateral evaluation region, and increasing angle bisector can solve the problem that evaluation results are not unique. It constructs new area and perimeter vectors of radar chart, which make the evaluation results give consideration to level of aggregation and balance degree of evaluation objectives, and case study results show that this model has a certain practical value.