时 间：2014-12-18（星期四） 14：30~17：00

地 点：皇冠新体育app报告厅（新9教三楼）

举办单位：皇冠新体育app

欢迎广大师生参加！

专家简介：

1.夏小华，南非比勒陀利亚大学终身教授、************，南非A级教授，南非科学院院士，南非工程院院士，IEEE Fellow，IEEE南非控制分会主席，《Automatica》杂志副主编。IFAC非线性控制技术委员会副主席。曾获中国教育部跨世纪人才计划、“霍英东教育基金杰出青年研究奖”一等奖。中国国务院政府特殊津贴获得者。主要研究领域为智能控制理论与应用、复杂系统控制理论与应用。在《Automatica》、《International Journal of Control》、《IEEE Transactions on Automatic Control》等上发表高水平研究文章100余篇。

2. Mr. Lijun Zhang obtained both his Bachelor’s and Master’s degree in Engineering at Wuhan University, Wuhan, China in 2010 and 2012, respectively. He is currently a lecturer and Ph.D candidate at the University of Pretoria, South Africa. His research interests include energy modeling and optimisation, optimal operation control and monitoring of power and industrial systems. He is working on mining system energy efficiency projects for his PhD degree.

3. Mr. Xianming Ye obtained both his Bachelor’s and Master’s degree in Engineering at Wuhan University, Wuhan, Hubei, China in 2008 and 2010, respectively. He is currently a PhD candidate in Electrical Engineering at University of Pretoria, South Africa since September 2010. He is a certified measurement and verification professionals since 2011. His research interests include: energy efficiency and demand side management, optimal metering design for measurement and verification and clean development mechanism programmes.

报告摘要:

1．Challenges and Benefits of Coal Quality Monitoring and Efficient Pumping for Coal Washing Plants

Market demand for cleaner coal to promote efficient coal utilization and reduce pollutant mission is increasing nowadays due to economic concerns and tighter environmental regulations. Meanwhile, energy cost takes a large proportion in the total cost for raw coal processing. Coal washing/beneficiation plants, therefore are forced to produce high quality coal in an energy-efficient way in order to meet market demand and reduce their operating cost. This talk presents a state-of-the-art medium density control system that makes use of the latest coal quality monitoring devices and a demand side management (DSM) approach to improve energy efficiency of pumping systems used. Through simulations carried out, the necessity and advantages of the control system designed are affirmed. Challenges for the measurement devices are also revealed and discussed. Energy and cost efficiencies of the pumping system are addressed by a DSM approach: a pump-storage-system (PSS) and its corresponding optimal operation strategy. Numerical analysis shows that electricity cost and energy consumption can be reduced by 51.8% and 50.28% respectively under TOU tariff with a 1 m3 secondary tank and a 160 m3 reservoir at the top of the plant. Economic viability of the DSM strategy is also investigated, which shows that an annual 36.47% reduction of overall cost can be achieved with a payback period of 2.56 years. Implementation barriers of the PSS proposed are also discussed.

2．Optimal measurement and verification plan: a lighting case study

Measurement and verification (M&V) is an indispensable process in various incentive energy efficiency and demand side management (EEDSM) programmes as a function to accurately and reliably measure and verify the project performance in terms of energy or cost savings. In practice, different types of unavoidable uncertainties that are coupled with the M&V process need to be handled, namely measurement uncertainty, modelling uncertainty, and sampling uncertainty. Particularly for large-scale lighting projects that require long-term continuous measurements, the desired sampling effort contributes to a significant increase to the M&V cost. In order to deal with the inherent trade-off between the M&V accuracy and M&V cost, three metering cost minimisation (MCM) models are developed, namely spatial MCM model, longitudinal MCM model, and the combined spatial and longitudinal MCM model, to assist the design of optimal M&V metering plans, by which the minimal metering cost is achieved with the satisfaction of the required measurement and sampling accuracy. The advantages of the proposed MCM models are demonstrated by a case study of a lighting retrofit project that is going to be implemented in a fleet of public hospitals.