Knowledge-infused and Consistent Complex Event Processing over Real-time and Persistent Streams

Emerging applications in Internet of Things (IoT) and Cyber-Physical Systems (CPS) present novel challenges to Big Data platforms for performing online analytics. Ubiquitous sensors from IoT deployments are able to generate data streams at high velocity, that include information from a variety of domains, and accumulate to large volumes on disk. Complex Event Processing (CEP) is recognized as an important real-time computing paradigm for analyzing continuous data streams. However, existing work on CEP is largely limited to relational query processing, exposing two distinctive gaps for query specification and execution: (1) infusing the relational query model with higher level knowledge semantics, and (2) seamless query evaluation across temporal spaces that span past, present and future events. These allow accessible analytics over data streams having properties from different disciplines, and help span the velocity (real-time) and volume (persistent) dimensions. In this article, we introduce a Knowledge-infused CEP (X-CEP) framework that provides domain-aware knowledge query constructs along with temporal operators that allow end-to-end queries to span across real-time and persistent streams. We translate this query model to efficient query execution over online and offline data streams, proposing several optimizations to mitigate the overheads introduced by evaluating semantic predicates and in accessing high-volume historic data streams. The proposed X-CEP query model and execution approaches are implemented in our prototype semantic CEP engine, SCEPter. We validate our query model using domain-aware CEP queries from a real-world Smart Power Grid application, and experimentally analyze the benefits of our optimizations for executing these queries, using event streams from a campus-microgrid IoT deployment.Comment: 34 pages, 16 figures, accepted in Future Generation Computer Systems, October 27, 201

Increasing security of supply by the use of a local power controller during large system disturbances

This paper describes intelligent ways in which distributed generation and local loads can be controlled during large system disturbances, using Local Power Controllers. When distributed generation is available, and a system disturbance is detected early enough, the generation can be dispatched, and its output power can be matched as closely as possible to local microgrid demand levels. Priority-based load shedding can be implemented to aid this process. In this state, the local microgrid supports the wider network by relieving the wider network of the micro-grid load. Should grid performance degrade further, the local microgrid can separate itself from the network and maintain power to the most important local loads, re-synchronising to the grid only after more normal performance is regained. Such an intelligent system would be a suitable for hospitals, data centres, or any other industrial facility where there are critical loads. The paper demonstrates the actions of such Local Power Controllers using laboratory experiments at the 10kVA scale

Assessing the market for solar photovoltaic (PV) microgrids in Malawi

Access to energy is widely acknowledged as an enabler for development, and a lack of energy is a barrier to economic empowerment. Currently just 12% of the Malawian population have access to the national electricity grid, with rural electrification at only 5.3%. Solar photovoltaic (PV) microgrids offer increased access levels over pico-solar systems and solar-home systems, and are a successful rural electrification method in many areas of Africa. This paper addresses the research question of: "what is the market potential for solar microgrids in Malawi?" through a multidisciplinary methodology and outlines necessary steps to overcome the key risks and barriers for implementation nationally. Case studies of existing initiatives in Kenya and Rwanda have been used to inform a system and business design appropriate to Malawi. The market potential of PV microgrids in Malawi has been identified and quantified through a novel approach combining microgrid optimisation software HOMERPro with Geographic Information Systems tools. The methodology also includes an energy ecosystem mapping exercise to identify and frame influencing parameters affecting microgrid implementation nationally. The findings show that solar microgrids are cost competitive with diesel microgrids in all locations in Malawi, although the addition of dispatchable diesel generation may provide economic benefits in larger, more urban systems. To implement solar microgrids would cost approximately $210 per person and average operational expenses of$17 per person per year. It was determined that 42% of Malawians may be most cost effectively served by existing infrastructure, 37% would be best served by microgrids and 21% would be best served by solar-home systems

Smarter City: Smart Energy Grid based on Blockchain Technology

The improvement of the Quality of Life (QoL) and the enhancement of the Quality of Services (QoS) represent the main goal of every city evolutionary process. It is possible making cities smarter promoting innovative solutions by use of Information and Communication Technology (ICT) for collecting and analysing large amounts of data generated by several sources, such as sensor networks, wearable devices, and IoT devices spread among the city. The integration of different technologies and different IT systems, needed to build smart city applications and services, remains the most challenge to overcome. In the Smart City context, this paper intends to investigate the Smart Environment pillar, and in particular the aspect related to the implementation of Smart Energy Grid for citizens in the urban context. The innovative characteristic of the proposed solution consists of using the Blockchain technology to join the Grid, exchanging information, and buy/sell energy between the involved nodes (energy providers and private citizens), using the Blockchain granting ledger

China Maritime Report No. 12: Sansha City in China\u27s South China Sea Strategy: Building a System of Administrative Control

China established Sansha City in 2012 to administer the bulk of its territorial and maritime claims in the South China Sea. Sansha is headquartered on Woody Island. The city’s jurisdiction includes the Paracel Islands, Zhongsha Islands, and Spratly Islands and most of the waters within China’s “ninedash line.” Sansha is responsible for exercising administrative control, implementing military-civil fusion, and carrying out the day-to-day work of rights defense, stability maintenance, environmental protection, and resource development. Since 2012, each level of the Chinese party-state system has worked to develop Sansha, improving the city’s physical infrastructure and transportation, communications, corporate ecosystem, party-state institutions, and rights defense system. In effect, the city’s development has produced a system of normalized administrative control. This system ultimately allows China to govern contested areas of the South China Sea as if they were Chinese territory.https://digital-commons.usnwc.edu/cmsi-maritime-reports/1011/thumbnail.jp

Multi-agent systems for power engineering applications - part 1 : Concepts, approaches and technical challenges

This is the first part of a 2-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part 1 of the paper examines the potential value of MAS technology to the power industry. In terms of contribution, it describes fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications. As well as presenting a comprehensive review of the meaningful power engineering applications for which MAS are being investigated, it also defines the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part 2 of the paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented