Modeling smart grids as complex systems through the implementation of intelligent hubs

ICINCO 2010The electrical system is undergoing a profound change of state, which will lead to what is being called the smart grid. The necessity of a complex system approach to cope with ongoing changes is presented: combining a systemic approach based on complexity science with the classical views of electrical grids is important for an understanding the behavior of the future grid. Key issues like different layers and inter-layer devices, as well as subsystems are discussed and proposed as a base to create an agent-based system model to run simulations

Agent based modeling of energy networks

Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed

Attributes of Big Data Analytics for Data-Driven Decision Making in Cyber-Physical Power Systems

Big data analytics is a virtually new term in power system terminology. This concept delves into the way a massive volume of data is acquired, processed, analyzed to extract insight from available data. In particular, big data analytics alludes to applications of artificial intelligence, machine learning techniques, data mining techniques, time-series forecasting methods. Decision-makers in power systems have been long plagued by incapability and weakness of classical methods in dealing with large-scale real practical cases due to the existence of thousands or millions of variables, being time-consuming, the requirement of a high computation burden, divergence of results, unjustifiable errors, and poor accuracy of the model. Big data analytics is an ongoing topic, which pinpoints how to extract insights from these large data sets. The extant article has enumerated the applications of big data analytics in future power systems through several layers from grid-scale to local-scale. Big data analytics has many applications in the areas of smart grid implementation, electricity markets, execution of collaborative operation schemes, enhancement of microgrid operation autonomy, management of electric vehicle operations in smart grids, active distribution network control, district hub system management, multi-agent energy systems, electricity theft detection, stability and security assessment by PMUs, and better exploitation of renewable energy sources. The employment of big data analytics entails some prerequisites, such as the proliferation of IoT-enabled devices, easily-accessible cloud space, blockchain, etc. This paper has comprehensively conducted an extensive review of the applications of big data analytics along with the prevailing challenges and solutions

Towards the next generation of smart grids: semantic and holonic multi-agent management of distributed energy resources

The energy landscape is experiencing accelerating change; centralized energy systems are being decarbonized, and transitioning towards distributed energy systems, facilitated by advances in power system management and information and communication technologies. This paper elaborates on these generations of energy systems by critically reviewing relevant authoritative literature. This includes a discussion of modern concepts such as ‘smart grid’, ‘microgrid’, ‘virtual power plant’ and ‘multi-energy system’, and the relationships between them, as well as the trends towards distributed intelligence and interoperability. Each of these emerging urban energy concepts holds merit when applied within a centralized grid paradigm, but very little research applies these approaches within the emerging energy landscape typified by a high penetration of distributed energy resources, prosumers (consumers and producers), interoperability, and big data. Given the ongoing boom in these fields, this will lead to new challenges and opportunities as the status-quo of energy systems changes dramatically. We argue that a new generation of holonic energy systems is required to orchestrate the interplay between these dense, diverse and distributed energy components. The paper therefore contributes a description of holonic energy systems and the implicit research required towards sustainability and resilience in the imminent energy landscape. This promotes the systemic features of autonomy, belonging, connectivity, diversity and emergence, and balances global and local system objectives, through adaptive control topologies and demand responsive energy management. Future research avenues are identified to support this transition regarding interoperability, secure distributed control and a system of systems approach

A systematic literature review on the use of artificial intelligence in energy self-management in smart buildings

Buildings are one of the main consumers of energy in cities, which is why a lot of research has been generated around this problem. Especially, the buildings energy management systems must improve in the next years. Artificial intelligence techniques are playing and will play a fundamental role in these improvements. This work presents a systematic review of the literature on researches that have been done in recent years to improve energy management systems for smart building using artificial intelligence techniques. An originality of the work is that they are grouped according to the concept of "Autonomous Cycles of Data Analysis Tasks", which defines that an autonomous management system requires specialized tasks, such as monitoring, analysis, and decision-making tasks for reaching objectives in the environment, like improve the energy efficiency. This organization of the work allows us to establish not only the positioning of the researches, but also, the visualization of the current challenges and opportunities in each domain. We have identified that many types of researches are in the domain of decision-making (a large majority on optimization and control tasks), and defined potential projects related to the development of autonomous cycles of data analysis tasks, feature engineering, or multi-agent systems, among others.European Commissio

Road2CPS priorities and recommendations for research and innovation in cyber-physical systems

This document summarises the findings of the Road2CPS project, co-financed by the European Commission under the H2020 Research and Innovation Programme, to develop a roadmap and recommendations for strategic action required for future deployment of Cyber-Physical Systems (CPS). The term Cyber-Physical System describes hardware-software systems, which tightly couple the physical world and the virtual world. They are established from networked embedded systems that are connected with the outside world through sensors and actuators and have the capability to collaborate, adapt, and evolve. In the ARTEMIS Strategic Research Agenda 2016, CPS are described as ‘Embedded Intelligent ICT Systems’ that make products smarter, more interconnected, interdependent, collaborative, and autonomous. In the future world of CPS, a huge number of devices connected to the physical world will be able to exchange data with each other, access web services, and interact with people. Moreover, information systems will sense, monitor and even control the physical world via Cyber-Physical Systems and the Internet of Things (HiPEAC Vision 2015). Cyber-Physical Systems find their application in many highly relevant areas to our society: multi-modal transport, health, smart factories, smart grids and smart cities amongst others. The deployment of Cyber-Physical Systems (CPS) is expected to increase substantially over the next decades, holding great potential for novel applications and innovative product development. Digital technologies have already pervaded day-to-day life massively, affecting all kinds of interactions between humans and their environment. However, the inherent complexity of CPSs, as well as the need to meet optimised performance and comply with essential requirements like safety, privacy, security, raises many questions that are currently being explored by the research community. Road2CPS aims at accelerating uptake and implementation of these efforts. The Road2CPS project identifying and analysing the relevant technology fields and related research priorities to fuel the development of trustworthy CPS, as well as the specific technologies, needs and barriers for a successful implementation in different application domains and to derive recommendations for strategic action. The document at hand was established through an interactive, community-based approach, involving over 300 experts from academia, industry and policy making through a series of workshops and consultations. Visions and priorities of recently produced roadmaps in the area of CPS, IoT (Internet of Things), SoS (System-of-Systems) and FoF (Factories of the Future) were discussed, complemented by sharing views and perspectives on CPS implementation in application domains, evolving multi-sided eco-systems as well as business and policy related barriers, enablers and success factors. From the workshops and accompanying activities recommendations for future research and innovation activities were derived and topics and timelines for their implementation proposed. Amongst the technological topics, and related future research priorities ‘integration, interoperability, standards’ ranged highest in all workshops. The topic is connected to digital platforms and reference architectures, which have already become a key priority theme for the EC and their Digitisation Strategy as well as the work on the right standards to help successful implementation of CPSs. Other themes of very high technology/research relevance revealed to be ‘modelling and simulation’, ‘safety and dependability’, ‘security and privacy’, ‘big data and real-time analysis’, ‘ubiquitous autonomy and forecasting’ as well as ‘HMI/human machine awareness’. Next to this, themes emerged including ‘decision making and support’, ‘CPS engineering (requirements, design)’, ‘CPS life-cycle management’, ‘System-of-Systems’, ‘distributed management’, ‘cognitive CPS’, ‘emergence, complexity, adaptability and flexibility’ and work on the foundations of CPS and ‘cross-disciplinary research/CPS Science’

Cloud computing for energy management in smart grid - an application survey

The smart grid is the emerging energy system wherein the application of information technology, tools and techniques that make the grid run more efficiently. It possesses demand response capacity to help balance electrical consumption with supply. The challenges and opportunities of emerging and future smart grids can be addressed by cloud computing. To focus on these requirements, we provide an in-depth survey on different cloud computing applications for energy management in the smart grid architecture. In this survey, we present an outline of the current state of research on smart grid development. We also propose a model of cloud based economic power dispatch for smart grid