Machine Learning and Data-Driven Techniques for the Control of Smart Power Generation Systems:An Uncertainty Handling Perspective

Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy.Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties.The burgeoning era of machine learning(ML)and data-driven control(DDC)techniques promises an improved alternative to these outdated methods.This paper reviews typical applications of ML and DDC at the level of monitoring,control,optimization,and fault detection of power generation systems,with a particular focus on uncovering how these methods can function in evaluating,counteracting,or withstanding the effects of the associated uncertainties.A holistic view is provided on the control techniques of smart power generation,from the regulation level to the planning level.The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility,maneuverability,flexibility,profitability,and safety(abbreviated as the“5-TYs”),respectively.Finally,an outlook on future research and applications is presented.

Agents for Smart Power Grids

The future of electricity systems will compose of small-scale generation and distribution where end-users will be active participants with localized energy management systems that are able to interact on a free energy market. Software agents will most likely control power assets and interact together to decide the best and safest configuration of the power grid system. This paper presents a design of agents that can be deployed in real-time with capabilities that include optimization of resources, intensive computation, and appropriate decision-making. Jordan 51-bus system has been used for simulation with a total generation capacity of 4050 MW of which 230 MW represents renewable energy. The economic analyses demonstrated the use of smart grid technologies with 2016 generation—load profiles for nominal liquified gas (NLG) prices and ±20% sensitivity analysis. The results have shown variations in the range of 1% in the price of MWh with smart grid technologies. These variations are mainly driven by the fact that agents shift power generation to renewable power plants to produce maximum power at peak hours. As a result, there is a positive economic impact in both NLG ± 20% sensitivity analysis, due to the fact that agents coordinate to better displace expensive thermal generation with renewable generation. It is evident that renewable resources compensate for power at peak times and provide economic benefits and savings.

Application of Smart Power Strategy to Construct a More Effective Strategy to Denuclearize North Korea

The use of sanctions to coerce Pyongyang into abandoning its nuclear weapons and related programs is not working. North Korea continues to survive and expands its nuclear and missile capabilities. It is time for the US to construct a more successful North Korea strategy by applying a smart power strategy before the North Koreans can operationalize their nuclear ICBMs within the next several years. If and when that occurs, the US will inevitably consider the use of force to resolve the North Korean nuclear issue, but that will be too costly for the US and its allies. Washington must do all it can to avoid another war on the Asian mainland. The only practical uses of force are as defensive and enhanced deterrence measures to protect the US and its allies against North Korean nuclear and conventional provocations. Instead, the US should call for an immediate freeze of North Korea＇s nuclear and missile programs and demonstrate its willingness to co-exist with Pyongyang, Only by accepting co-existence with Pyongyang, Washington has an opportunity to persuade Beijing and Moscow to join its efforts with Seoul and Tokyo to denuclearize North Korea. It is time to engage North Korea by accepting it as it is and exercising strategic patience of a different kind to achieve US aims.

Research and Practice of Smart Power Consumption

As a vital part of a smart grid, smart power consumption enables real-time interaction between consumers and the grid. With improved management of the demand side and energy efficiency, smart power consumption plays an important role in emission reduction as well as the economic operation of the power grid. Meanwhile, it enhances the power grid to a larger scale infrastructure by the two-way transmission of energy and information. This paper introduces the research, practice and vision of smart power consumption in China.

‘Smart Power’ for ‘Sharing’ As an attitude of life

The Interst off Asia Essential Spring will be held from March 17th to 19th,2010,in Hong Kong Convention & Exhibition Centre. During this exhibition,the Interst off Asia Directions trend committee will present its apparel fabric trend forecast for next season's wardrobes,unfolding a story of ‘Smart Power’ of ‘Sharing’.

The Visualization Analysis of Research Hotspot and Frontier Technology of the Smart Power Distribution and Utilization Based on the Cite Space

In order to make an intensive study of the development of smart power distribution and utilization technology in China, their research hotspots and frontier technology are selected out through combining the informatics method, and using the CiteSpace which can take keyword cooccurrence analysis and draw the visualization graph. According to this result, we can infer the development trend of smart power distribution and utilization in the future, and providing reference for the researcher whose engage in this domain. The electric related literature was collected from the CNKI database in China. Under the smart power distribution and utilization domain, we also analyze the development of the power quality and the energy internet in detail.

Interaction Research on the Smart Power Consumption

Due to the rapid growth of the air conditioning load of the residents had bigger impact on power grid safety and power smooth operation, in order to improve energy conservation and reduce emissions of the residents, many countries had studied the home energy management system (HEMS) in the world. In this paper, based on the summary of the work of other countries, the HEMS research and practice situation of China were discussed, combined with the national development and reform commission (NDRC) project, the power consumption visualization?empirical research had been carried on in different cities in 2012, the interaction results show that the load can be reduced by an average of 6.67%, which proved that the electricity interactive was very interesting for long-term strategy of energy conservation and emissions reduction.

Matlab Code to Assess the Reliability of the Smart Power Distribution System Using Monte Carlo Simulation

Reliability of power systems is a key aspect in modern power system planning, design, and operation. The ascendance of the smart grid concept has provided high hopes of developing an intelligent network that is capable of being a self-healing grid, offering the ability to overcome the interruption problems that face the utility and cost it tens of millions in repair and loss. In this work, we develop a MATLAB code to examine the effect of the smart grid applications in improving the reliability of the power distribution networks via Monte Carlo Simulation approach. The system used in this paper is the IEEE 34 test feeder. The objective is to measure the installations of the Automatic Reclosers (ARs) as well as the Distributed Generators (DGs) on the reliability indices, SAIDI, SAIFI, CAIDI and EUE, and make comparisons with results from a previous study done by the authors using another approach. The MATLAB code should provide close results to the output of the previous research to verify its effectiveness.

Smart Power Substation Development in China

Over the past decade,China has undertaken substation intellectualization of more than 2000 substation operations in three stages.Much experience has been achieved during this developmental period.In this paper,the status of smart substation development in China is systematically presented,as well as future directions of the smart substation,such as adoption of the hierarchical protection and control system.

Community Smart Grid Utilizing Dynamic Demand Response and Tidal Power for Grid Stabilization

Conventional electricity generation is one of the largest contributors to climate change. Renewable energy sources are a promising part of the solution but uncertainty combined with a lack of controllability prevents renewable sources of power from being direct substitutes of conventional energy sources. This shift towards a higher penetration of renewable energy into the electric grid can be realized with the implementation of a more sophisticated smart grid, which uses dynamic demand response to alter demand on following generation. Research on renewable energy penetration of the grid predominately focuses on wind and solar power resources but demand cannot always match availability from these sources and therefore greatly increases the need for energy storage. Tidal power differs from solar and wind. It’s a predictably renewable resource which makes it extremely valuable even on a relatively small scale. Introduction of tidal power in a high penetration micro-grid can serve to stabilize the grid and reduce the amount of storage required. Widely different time scale for wind, solar and tidal power availability results in low cross correlations and therefore increases stability. This research describes an incremental approach to migrating a grid-tie island towards the formation of a smart-micro grid. The system will include a high penetration of three distributed generation systems, wind, solar and tidal and utilize commercially available energy storage and a smart-home management controller. Dynamic demand response through load balancing is implemented to minimize interactions with the electric grid. A second component of this work is to determine the optimum tidal generation capacity for the micro grid such that needed storage capacity from batteries or the utility grid is minimized.

Power-Aware Data Management Based on Hybrid RAM-NVM Memory for Smart Bracelet

Wearable devices become popular because they can help people observe health condition.The battery life is the critical problem for wearable devices. The non-volatile memory(NVM) attracts attention in recent years because of its fast reading and writing speed, high density, persistence, and especially low idle power. With its low idle power consumption,NVM can be applied in wearable devices to prolong the battery lifetime such as smart bracelet. However, NVM has higher write power consumption than dynamic random access memory(DRAM). In this paper, we assume to use hybrid random access memory(RAM)and NVM architecture for the smart bracelet system.This paper presents a data management algorithm named bracelet power-aware data management(BPADM) based on the architecture. The BPADM can estimate the power consumption according to the memory access, such as sampling rate of data, and then determine the data should be stored in NVM or DRAM in order to satisfy low power. The experimental results show BPADM can reduce power consumption effectively for bracelet in normal and sleeping modes.

校企合作模式下基于OBE理念的实践类课程设计

基于成果导向教育(OBE)的课程设计理念,设计了“智慧电力工程训练营”实践课程的整体教学模式。该课程通过与ABB集团合作的形式,构建了具有实际工程意义的综合设计内容,并按照反向设计原则,对各个知识点进行综合整理,设计出2周的课程教学结构和课堂教学模式,逐步实现学生的最终学习目标。在此基础上,通过教学评价体系综合评定每位学生的最终成绩。该课程的教学模式及其实施路径对于本科实践类课程设计具有较好的借鉴和推广价值。

Power Quality Data Compression Based on Iterative PCA Algorithm in Smart Distribution Systems

To reduce the stress of data transmission and storage for power quality (PQ) in smart distribution systems and help PQ analysis, a multichannel data compression based on iterative PCA (principal component analysis) algorithm is introduced. The proposed method uses PCA to reduce the redundancy of data to achieve the purpose of compressing data. In order to improve the calculating speed, an iterative method is proposed to compute the principal components of the covariance matrix. The correctness and feasibility of the proposed method are verified by field PQ data tests. Compared with discrete wavelet transform (DWT) method, the proposed method has good performance on compression ratio and reconstruction accuracy.

Performance of joint dual links dynamic power control and smart antenna for TDMA/TDD cellular mobile communications

Interference cancellation is made available by using smart antenna at cellular base stations. Well distributed cumulative probability of signal to interference plus noise power ratio appears to be vital for cellular mobile multimedia communications. A scenario of dual links dynamic power control combined to a solution of smart antenna is proposed to adjust the instant transmission power in terms of the disparity from the favorite range. Simulation results show that this method is quite effective to improve the cumulative distribution probability performance. Meanwhile, accompanying low power consumption is also obtained at both base stations and mobile stations.

智能电厂安全防范系统联动研究

发电厂中的安防子系统较多,但数据资源共享和关联程度不够,信息孤岛现象显著。本文通过安防子系统联动的研究,实现各安全功能模块的协调和配合,保证各功能模块间的互联互享互通。通过三维可视化平台,利用灵活的联动配置方式,实现对现场复杂环境、重要设备及人员安全的联合防护,有效提升发电厂安全管理效率和应急响应能力。

引领世界新一轮农业革命、筑牢粮食安全体系的中国式农业强国路径

农业强大是工业强大、国家强大、社会稳定的基石,只有农业强起来、粮食安全有保障,才能稳住经济大局,国家才有应变局、开新局的底气。当今世界因粮食危机引发政治危机的事件屡见不鲜,揭示了农业科技水平及农产品生产供给能力在国家安全中占据“基础地位”和“核心地位”。在当今世界刚刚开启第三次农业革命的时代背景下,本研究提出了推进科技创新是摆脱粮食危机的关键,以科技创新推动中国农业现代化、加速推进生态型智慧农业,以多学科交叉融合打造特色生态型农业模式。党的二十大部署了“加快建设农业强国”任务,中国要走以“绿水青山就是金山银山”为价值观的生态型智慧农业发展之路。本研究剖析了世界粮食危机的根源,评析了新时代中国粮食稳产增产的保障措施,阐释了科技创新在保障国家粮食安全中的重要地位,勾勒了中国未来农业“生态与智慧融合一体”的特色发展路径。

基于人工蜂群算法的配电网无功优化调度研究

为了改善现有无功功率调度时算法执行效率,解决模型易陷入局部极值问题,提出一种基于改进人工蜂群算法模型。在分析等式和不等式约束的情况下,建立最小化实际功率损耗、电压偏差和电压稳定增强的无功功率调度目标函数。提出一种基于邻域半径选择的改进人工蜂群算法,设计一种新的邻域选择机制和改进的搜索策略。实验阶段,以IEEE39总线电力系统为例,对所提算法有效性和执行效率进行验证。与线性规划(LP)、粒子群优化(PSO)算法和基础人工蜂群(ABC)算法相比,改进ABC算法比其他算法执行效率更优,且解的质量更高。该模型为配电网电力调度及稳定性运行的发展提供了一定借鉴作用。

燃煤电厂中煤场的防碰撞系统研究

通过对安全防护需求的图像处理及雷达扫描技术建模研究,开发了基于图像处理与雷达信号相融合的防碰撞系统。通过计算测试分析,在多干扰噪声情况下系统最大误差为42 mm,处于合理误差范围内,完全满足实际工程需要,这对实际燃煤电厂内煤场的设备运行安全提供了一定的技术保障,同时实现了人与其他设备的安全防护要求。

应对粮食危机视角下国家粮食安全体系构筑策略研究

农业是国家安全和社会稳定的基石,只有农业强起来,粮食安全有保障才能稳住国家经济大局。当今世界粮食危机频发,继而引发严重的政治危机,只有牢牢把控粮食生产的可持续性才能消除粮食危机。笔者剖析了世界粮食危机的根源,分析了我国粮食安全的风险因素及时代化特征,从加大种植结构的管控力度防止耕地“非农化”“非粮化”、培育新型农业人才、“藏粮于地、藏粮于技”推进高标准农田建设、攻关主粮种子选育技术、多渠道改造和利用盐碱地、提升农业机械化水平、选育抗病性能的新品种等7个方面提出了保障粮食安全和化解粮食风险的策略,为构筑国家粮食安全体系提供理论依据和解决方案。

面向智算融合网络的自主防御范式研究

随着数字经济时代算力供给模式的变革,以算力为核心的新型网络基础设施已成为实现算力资源共享、支撑数字经济转型的重要动力.在算力网络中,多元异构用户终端通过多种方式高频接入网络以随时随地获取算力服务,网络的开放性和动态性增大,算力网络将面临更严峻的安全挑战.然而,基于传统网络的安全防御模式通常针对具体安全问题静态式增补安全防护组件,无法主动适配用户需求灵活调整防御策略,难以应对算力网络中的安全风险.因此,本文面向新型算力网络安全需求,将安全功能作为网络内部属性,基于智算融合网络提出一种多维协同自主防御范式.结合智算融合网络“三层”“三域”的设计思想,在“三层”中,以广义服务层定义安全固有服务,以映射适配层智慧适配安全功能,以融合组件层执行安全策略;在“三域”中,以实体域先导资源适配,以知识域驱动安全服务流程,以感控域实施具体安全技术,构建“检测”“溯源”“防御”三维一体的完整基础管控流程,其中安全策略与技术可根据场景扩展性与业务安全性进行灵活调整.最终,通过仿真实验对所提范式有效性进行了验证,为未来智算融合安全的进一步研究和应用提供参考.