能源学 | 国际会议约稿信息2条

能源学

BigData4SmartEnergy 2018

International Workshop on Big Data Analysis for Smart Energy

全文截稿: 2017-11-05

开会时间: 2018-01-15

会议难度: ★★

CCF分类: 无

会议地点: Shanghai, China

网址：http://sigai.or.kr/workshop/bigcomp/2018/big-data-for-smart-energy/

The First International Workshop on Big Data Analysis for Smart Energy (BigData4SmartEnergy 2018) will be held on January 15, 2018, Shanghai, China, in conjunction with the 2018 IEEE International Conference on Big Data and Smart Computing (IEEE BigComp2018).

AI-based smart energy deals with the challenges of using big data and AI techniques for the efficient management of energy resources and facilities, the timely detection of energy problems and anomalies, and the effective prediction of energy demands and services in the future, hence has already become an important area of research in many countries. This workshop aims to create opportunities to share on-going works in smart energy industry and academia, to enhance collaboration between energy researchers and data scientists, and to foster new innovations of AI, big data, and smart computing technologies in such areas as smart energy platforms and infrastructure, monitoring and analysis of energy big data, customized demand forecast in smart cities, smart homes, and electric vehicles, new innovative energy services, and so on. Prospective authors are cordially invited to submit their original contributions covering completed or ongoing work in (but not limited to) the following areas:
-Innovative AI techniques for future energy services and monitoring
-Intelligent techniques for smart energy platforms and infrastructure
-Big data analytics for smart energy operations, measurement and control
-Real-time handling and storage of stream data for power facilities
-Intelligent monitoring and real-time analysis of power energy big data
-Data mining and metadata annotation of power energy big data
-Big data- and/or block chain-based security systems for energy services
-Evaluation, monitoring and visualization techniques for energy big data
-Intelligent asset management of transmission and distribution facilities
-Machine learning techniques for anomaly detection in power services
-Electricity demand prediction for smart homes and smart cities
-Smart grid and customized energy services demand prediction
-Energy ecosystems and related issues

能源学

Venice 2018

International Symposium on Energy from Biomass and Waste

全文截稿: 2018-02-28

开会时间: 2018-10-15

会议难度: ★★★

CCF分类: 无

会议地点: Venice, Italy

网址：http://www.venicesymposium.it/

The production of energy from alternative sources and its impact on climate change are among the main strategic tools implicated in the sustainable development of our society. Numerous types of biomass and wastes contribute towards the production of energy and reduction in the use of fossil fuels by means of biological, chemical and thermal processes. Existing biomass and waste to energy technologies are currently undergoing rapid development. Despite growing interest in the use of these technologies, in many countries their implementation remains limited.

The aim of the Venice 2018 Symposium is to focus on the advances made in the application of technologies for energy recovery from biomass and waste and to encourage discussion in these fields. The previous edition of the Symposium, held in 2016, was attended by over 500 scientists and operators from approximately 54 different countries.

The seventh edition of the Symposium will feature:
-Three days of scientific presentations
-One day of guided technical tours at biochemical and thermochemical plants
-Six parallel oral sessions, poster sessions and an exhibition by companies working in the field
-Expected attendance of over 600 delegates from tens of different countries worldwide

The conference will be held in the eminent meeting centre of the Scuola Grande di San Giovanni Evangelista, internationally renowned as one of the most relevant congress venue in Venice.

The Symposium is organized by the International Waste Working Group (IWWG) and Ordine degli Ingegneri della Provincia di Venezia, with the scientific support of the Universities of Padova, Hokkaido, Queensland, Rostock, Trento, Tsinghua and Hamburg University of Technology.