How to Optimize the Management of Science and Technology Funds in Colleges and Universities Based on the Policy of Streamlining Administration,Delegating Powers,Improving Regulation,and Strengthening Services

To advance the field of science and technology,we need to revitalize the development of science and technology through innovation.The development of science and technology has many beneficial implications on the revitalization of the country.For this reason,universities in China should give full attention to their role as the main propeller of science and technology.“Streamlining administration,delegating powers,improving regulation,and strengthening services”is a policy issued by the Chinese government for the management of science and technology funds in colleges and universities.Based on the policy of“streamlining administration,delegating powers,improving regulation,and strengthening services,”colleges and universities must optimize the management of science and technology funds for their efficient use.In this paper,we analyzed the importance of the policy and put forward an effective management strategy,aiming to improve the management of science and technology funds in colleges and universities.

通过Powerize.com免费获取工商金融情报

Powerize.com is well known for providing free business and financial information on the Web.The unique information integrated service of Powerize.com,its approaches to free information and fee based information as well as its searching modes are discussed.The author suggests that information experts pay more attention to recommending such kinds of services to Internet users in China in order to let more and more Internet users obtain free information via such kinds of services.

Key technologies of artificial intelligence in electric power customer service

As the demand for customer service continues to increase,more companies are attempting to apply artificial intelligence technology in the field of customer service,enabling intelligent customer service,reducing customer service pressure,and reducing operating costs.Currently,the existing intelligent customer service has a limited degree of intelligence and can only answer simple user questions,and complex user expressions are difficult to understand.To solve the problem of low accuracy of multi-round dialogue semantic understanding,this paper proposes a semantic understanding model based on the fusion of a convolutional neural network(CNN)and attention.The model builds an“intention-slot”joint model based on the“encoding–decoding”framework and uses hidden semantic information that combines intent recognition and slot filling,avoiding the problem of information loss in traditional isolated tasks,and achieving end-to-end semantic understanding.Additionally,an improved attention mechanism based on CNNs is introduced in the decoding process to reduce the interference of redundant information in the original text,thereby increasing the accuracy of semantic understanding.Finally,by applying the model to electric power intelligent customer service,we verified through an experimental comparison that the proposed fusion model improves the performance of intent recognition and slot filling and can improve the user experience of electric power intelligent customer services.

A collaborative approach to integrated energy systems that consider direct trading of multiple energy derivatives

The cooperative model of a multi-subject Regional Integrated Energy System(RIES)is no longer limited to the trading of traditional energy,but the trading of new energy derivatives such as Green Certificates(GC),Service Power(SP),and CO_(2) will be more involved in the energy allocation of the cooperative model.This study was conducted for the multi-entity RIES cooperative model considering the trading of electronics,GC,SP,and CO_(2).First,a cooperative framework including wind-photovoltaic generation system(WG),combined heat and power system(CHP),and power-carbon-hydrogen load(PCH)is proposed,and the mechanism of energy derivatives trading is also analyzed.Then,the sub-models of each agent in the cooperative model are established separately so that WG has the capability of GC generation,CHP has the capability of GC and CO_(2) absorption,and PCH can realize the effective utilization of CO_(2).Then,the WG–CHP–PCH cooperative model is established and equated into two sub-problems of cooperative benefit maximization and transaction payment negotiation,which are solved in a distributed manner by the alternating directed multiplier method(ADMM).Finally,the effectiveness of the proposed cooperative model and distributed solution is verified by simulation.The simulation results show that the WG–CHP–PCH cooperative model can substantially improve the operational efficiency of each agent and realize the efficient redistribution of energy and its derivatives.In addition,the dynamic parameter adjustment algorithm(DP)is further applied in the solving process to improve its convergence speed.By updating the step size during each iteration,the computational cost,the number of iterations,and the apparent oscillations are reduced,and the convergence performance of the algorithm is improved.

Design of Robust Var Reserve Contract for Enhancing Reactive Power Ancillary Service Market Efficiency

In a deregulated Var market, market power issue is more serious than in an energy market since reactive power cannot be transmitted over long distances. This letter designs a multi-timescale Var market framework, where market power that may arise in the hourly-ahead Var support service market due to system configuration deficiency and market structure flaws can be eliminated by day-ahead contract-based Var reserve service market. Settlement of day-ahead Var reserve contract is formulated as a two-stage robust optimization (TSRO) model considering worst case of uncertainty realization and potential market power that may arise in hourly-ahead market. TSRO with integer recourses is then solved by a new column and constraint generation algorithm. Results show a robust Var reserve contract can fully eliminate market power, and prevent suppliers from manipulating market prices.

A new method for optimal FTU placement in distribution network under consideration of power service reliability

Modern distribution network with high penetration of intermittent renewable sources and the so-called prosumers requires more reliable distribution automation(DA) system for safe operation and control. The design of optimal feeder terminal units(FTU)placement is critical and economical for the effective DA application. Previously proposed solutions of optimal FTU placement aiming to ensure the accuracy of state estimation(SE), typically include the following two main shortcomings: 1) only to obtain the optimal FTU placement in quantity, and the analysis of FTU location is not considered yet; 2) few consider the uncertainty of intermittent power injections in the analysis of state estimation. In this paper, a modified methodology of FTU placement is proposed not only aiming to ensure the accuracy of state estimation with the minimum number of meters, but also finding those specific FTU locations to guarantee the power service reliability. Moreover, the uncertainty models of those intermittent power injections are also considered by using probability density function(PDF). The resultant optimization problem is addressed by using the covariance matrix adaptation evolution strategy(CMA-ES). Case studies demonstrate the feasibility and effectiveness of the proposed methodology.

Reliability prediction and its validation for nuclear power units in service

In this paper a novel method for reliability prediction and validation of nuclear power units in service is proposed. The equivalent availability factor is used to measure the reliability, and the equivalent availability factor deducting planed outage hours from period hours and maintenance factor are used for the measurement of inherent reliability. By statistical analysis of historical reliability data, the statistical maintenance factor and the undetermined parameter in its numerical model can be determined. The numerical model based on the main- tenance factor predicts the equivalent availability factor deducting planed outage hours from period hours, and the planed outage factor can be obtained by using the planned maintenance days. Using these factors, the equivalent availability factor of nuclear power units in the following 3 years can be obtained. Besides, the equivalent availability factor can be predicted by using the historical statistics of planed outage factor and the predicted equivalent avail- ability factor deducting planed outage hours from period hours. The accuracy of the reliability prediction can be evaluated according to the comparison between the predicted and statistical equivalent availability factors. Furthermore, the reliability prediction method is validated using the nuclear power units in North American Electric Reliability Council （NERC） and China. It is found that the relative errors of the predicted equivalent availability factors for nuclear power units of NERC and China are in the range of-2.16% to 5.23% and -2.15% to 3.71%, respectively. The method proposed can effectively predict the reliability index in the following 3 years, thus providing effective reliability management and mainte- nance optimization methods for nuclear power units.

Energy Management and Operational Control Methods for Grid Battery Energy Storage Systems

Energy storage is one of the key means for improving the flexibility,economy and security of power system.It is also important in promoting new energy consumption and the energy Internet.Therefore,energy storage is expected to support distributed power and the micro-grid,promote open sharing and flexible trading of energy production and consumption,and realize multi-functional coordination.In recent years,with the rapid development of the battery energy storage industry,its technology has shown the characteristics and trends for large-scale integration and distributed applications with multi-objective collaboration.As a grid-level application,energy management systems(EMS)of a battery energy storage system(BESS)were deployed in real time at utility control centers as an important component of power grid management.Based on the analysis of the development status of a BESS,this paper introduced application scenarios,such as reduction of power output fluctuations,agreement to the output plan at the renewable energy generation side,power grid frequency adjustment,power flow optimization at the power transmission side,and a distributed and niohile energy storage system at the power distribution side.The studies and application status of a BESS in recent years were reviewed.The energy management,operation control methods,and application scenes of large-scale BESSs were also examined in the study.

RE-ENGINEERING TRANSFORMER MAINTENANCE PROCESSES TO IMPROVE CUSTOMIZED SERVICE DELIVERY

The outage of a transformer in a power generation system will generally result in a shutdown of the entire system. Consequentially, large amounts of revenue are lost to the plant owner with a substantial negative impact on the civil community and industrial customers. This paper analyzes the current maintenance practices （i.e., an as-is process model） of a transformer manufacturing company, which provides maintenance services to power generation plants and reports the major weaknesses in current business practices. The maintenance weaknesses include isolated processes and paper based information communication. These inefficient processes result in service delays, cost increases, and inappropriate responses to customers＇ specific requests and complaints. To improve the efficiency and flexibility of the entire transformer maintenance service system, an e-integration approach is implemented with three key tasks. First, the current business processes are re-engineered to provide an improved （to-be） business model. Then, we replace paper based documentation methods with an electronic filing system for efficient and cost-effective information exchange. Afterward, the improved process model is implemented as an Internet based system to enhance the interactions among the transformer manufacturer, end-users, and service contractors for customized maintenance services. The case study demonstrates that implementing the e-integration approach increases the efficiency and effectiveness of the customized maintenance services.