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burgeoning era of machine learning(ML)and data-driven control(DDC)techniques promises an improved alternative to these outdated methods.This paper reviews typical applications of ML and DDC at the level of monitoring,control,optimization,and fault detection of power generation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.

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.

Privacy-Preserving Prepayment Based Power Request and Trading in Smart Grid

Demand response has been intensively studied in recent years. It can motivate customers to change their consumption patterns according to the dynamic(time-varying) electricity price, which is considered to be the most cost-effective and reliable solution for smoothing the demand curve. However, many existing schemes, based on users' demand request in each period, require users to consume their requested electricity exactly, which sometimes causes inconvenience and losses to the utility, because customers cannot always be able to consume the accurate electricity demand due to various personal reasons. In this paper, we tackle this problem in a novel approach. Instead of charging after consumption, we adopt the prepayment mechanism to implement power request. Furthermore, we propose a trading market running by the control center to cope with the users' dynamic demand. It is noteworthy that both users' original demand and trading records are protected against potential adversaries including the curious control center. Through the numerical simulation, we demonstrate that our scheme is highly efficient in both computation and communication.

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.

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.

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。

数字孪生技术在电厂智慧化转型中的应用

阐述数字孪生技术在电厂智慧化转型中的应用,包括电厂建设过程中的信息查询智能化、电厂建设完成后的数字移交、电厂运维管理的智能化、电厂中的人员定位与实时联动。

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。

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。

内河水运基础设施及船舶技术发展现状与展望

我国交通运输事业已步入全面建设交通强国的新发展阶段,内河水运在综合交通运输体系中的比较优势尚未得到充分发挥,而“双循环”新发展格局及“双碳”战略的实施将要求内河水运及其核心要素的船舶技术必须实现创新发展。该文通过梳理提炼国内外内河水运以及船舶发展的现状与相关政策演变,分析创新技术研究进展与典型案例,对内河水运基础设施及船舶技术发展趋势进行展望:未来内河水运基础设施与数字、信息和网络技术深度融合,岸基控制中心作为关键性设施和船舶能源供给设施网联化;船舶则向着船型标准化、谱系化、智能化、少人化、能源绿色化及多元化、电力推进主流化等方向演进;船舶编队航行成为创新运输模式。文中所探索的内河水运基础设施及船舶技术的变革方向,可为建设新一代内河水运体系和研发先进船型提供参考。

基于智能电表数据的低压配电网拓扑与线路参数联合辨识

在低压配电网中,用户频繁地扩建和改接导致台账存在信息更新滞后、数据缺失等问题,难以获取当前运行状态下的拓扑及线路参数。针对无相角量测信息且含未知数量零注入功率“隐节点”的低压配电网,提出一种基于智能电表数据的低压配电网拓扑与线路参数联合辨识方法。基于低压配电网的电气特性以及辐射状网络的结构特点,推导出一种功率-电压比形式的线性逆潮流模型。通过线性回归求解得到阻抗距离矩阵,再利用无判定阈值形式的改进分组递归算法实现拓扑与线路参数的联合辨识。最后,在IEEE欧洲低压测试馈线和中国南京市某地区的实际低压配电网中对所提算法进行数值仿真,验证了所提算法的有效性。