A review of prosumers’ behaviours in smart grids and importance of smart grid management

Purpose: The concept of the smart grid is relatively new. The first aim of the study is to understand the behaviour of prosumers in smart grids. The other goal is to raise awareness of the management tasks and risks of smart grids by highlighting the relevant issues of some business networks (PPP projects, outsourcing, strategic alliances etc.). Methodology: Systemized literature review was used in the paper. Results: The discussed management problems of various business networks indicate that management challenges can also be expected in smart grids, so it is worth preparing in time. Conclusion: We found a lack of empirical research about the behaviour of prosumers and believe that studying the electric power grid of the future from a management perspective, that is, examining the possible behaviours and decisions of various actors, can provide valuable and useful information for smart grid design and safe operation insurance

FAIR Metadata Standards for Low Carbon Energy Research—A Review of Practices and How to Advance

The principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) have been put forward to guide optimal sharing of data. The potential for industrial and social innovation is vast. Domain-specific metadata standards are crucial in this context, but are widely missing in the energy sector. This report provides a collaborative response from the low carbon energy research community for addressing the necessity of advancing FAIR metadata standards. We review and test existing metadata practices in the domain based on a series of community workshops. We reflect the perspectives of energy data stakeholders. The outcome is reported in terms of challenges and elicits recommendations for advancing FAIR metadata standards in the energy domain across a broad spectrum of stakeholders

An event-based resource management framework for distributed decision-making in decentralized virtual power plants

The Smart Grid incorporates advanced information and communication technologies (ICTs) in power systems, and is characterized by high penetration of distributed energy resources (DERs). Whether it is the nation-wide power grid or a single residential building, the energy management involves different types of resources that often depend on and influence each other. The concept of virtual power plant (VPP) has been proposed to represent the aggregation of energy resources in the electricity market, and distributed decision-making (DDM) plays a vital role in VPP due to its complex nature. This paper proposes a framework for managing different resource types of relevance to energy management for decentralized VPP. The framework views VPP as a hierarchical structure and abstracts energy consumption/generation as contractual resources, i.e., contractual offerings to curtail load/supply energy, from third party VPP participants for DDM. The proposed resource models, event-based approach to decision making, multi-agent system and ontology implementation of the framework are presented in detail. The effectiveness of the proposed framework is then demonstrated through an application to a simulated campus VPP with real building energy data

Smart City Ontologies and Their Applications: A Systematic Literature Review

The increasing interconnections of city services, the explosion of available urban data, and the need for multidisciplinary analysis and decision making for city sustainability require new technological solutions to cope with such complexity. Ontologies have become viable and effective tools to practitioners for developing applications requiring data and process interoperability, big data management, and automated reasoning on knowledge. We investigate how and to what extent ontologies have been used to support smart city services and we provide a comprehensive reference on what problems have been addressed and what has been achieved so far with ontology-based applications. To this purpose, we conducted a systematic literature review finalized to presenting the ontologies, and the methods and technological systems where ontologies play a relevant role in shaping current smart cities. Based on the result of the review process, we also propose a classification of the sub-domains of the city addressed by the ontologies we found, and the research issues that have been considered so far by the scientific community. We highlight those for which semantic technologies have been mostly demonstrated to be effective to enhance the smart city concept and, finally, discuss in more details about some open problems

Prosumer collectives: a review

he authors would like to acknowledge the Smart Grid Forum for funding this research. They also acknowledge the aligned GREEN Grid research project, funded by the Ministry of Business Innovation and Employment (MBIE), with co-funding from Transpower and the Electricity Engineers’ Association. We also acknowledge our reviewers, John Hancock and Gerry Carrington.The widespread growth globally of micro-generation (particularly PV) means that consumers are interacting with electricity systems in new ways, becoming ‘energy prosumers’ – both producing and consuming energy. We define an energy prosumer as “a consumer of energy who also produces energy to provide for their needs, and who in the instance of their production exceeding their requirements, will sell, store or trade the surplus energy”. Growing prosumerism has the potential to create challenges for grid management, particularly if local generation becomes concentrated within a part of a lines network, which can particularly occur with the establishment of prosumer collectives. For this report we reviewed international and NZ articles and reports on this phenomenon, to understanding how and why consumers were adopting microgeneration, and ways in which prosumer collectives are emerging. In considering how people become prosumers, we found it useful to differentiate between ‘active prosumers’ whose decision to adopt microgeneration is self-directed and purposeful, and ‘passive prosumers’ whose entry is the result of external influences or the by-product of other decisions. The shift to becoming a prosumer creates many opportunities for people to become more actively engaged with the role of energy in their lives, which opens the door for collective engagement. We reviewed different forms of prosumer collectives in the UK, North America, Europe and Australasia. From these we identified that different models of prosumer collectives are emerging depending on whether the collective was initiated by a community or third party, and whether the microgeneration facility is on a focal site (e.g. a wind turbine cluster) or multiple sites (e.g. PV on many houses in a community). A further influence is the emergence of new business models and smart technologies that enable prosumers to manage energy production and consumption on a personal and collective level. Some businesses now offer peer-to-peer platforms that enable power-sharing within a microgrid, as well as supporting spatially dispersed collective engagement. For example, prosumers who have surplus power can sell or exchange it directly with others. We identified and named five models of collective prosumerism: multi-site community initiatives; focal-site community initiatives; multi-site third-party initiatives; focal-site third-party initiatives; and dispersed-site third-party initiatives. The common theme is that multiple non-traditional players are consciously engaging with each other in generating and sharing energy and/or the proceeds of energy generation. We identify a range of drivers, barriers and enablers to collective prosumerism. The decreasing cost of microgeneration and storage is a significant driver, along with aspirations for greater independence, control, sustainability and community cohesion. Both community and third-party developments are largely initiated by organisations that have not traditionally been part of the electricity industry. If the industry ignores or attempts to suppress this emerging interest by consumers in collective prosumerism, it may find itself becoming increasingly irrelevant in the lives of electricity users

A Generic Ontology for Prosumer-Oriented Smart Grid

http://www.emse.fr/~picard/publications/gillani13endm.pdfInternational audienceThe concept of Smart Grid (SG) has comprehensively overhauled the scene of electric power grid and the integration of Prosumers , where an entity can consume and produce simultaneously extempo- rised in a complete paradigm shift. This requires a detailed knowl- edge base model at each entity level that can react according to con- textual changes. This paper outlines a generic and layered ontology design for such complex Prosumer oriented SG, which enables the autonomous in- tegration and real-time management of distributed and heteroge- neous sources. It details the relevant layer to the right granularity with keen insight into distributed co-ordination and semantic het- erogeneity. It also presents an inductive based reasoning on such ontology to make it thoroughly elucidative

Arquitecturas de datos basadas en Internet de las Cosas y su aplicación

El internet de las cosas (IoT por sus siglas en inglés) se presenta como nuevo paradigma de los sistemas de información, capaz de ayudar en numerosos retos a los que se enfrenta nuestra sociedad: desde la lucha contra el cambio climático hasta el progreso por la consecución del derecho a una vida digna y feliz. Este nuevo paradigma plantea no solo posibilidades sino numerosos retos tecnológicos que deberán ser abordados aplicando el método científico, para el beneficio global. La privacidad de los datos y la seguridad de las comunicaciones adquieren nuevas problemáticas en un marco tan dinámico como el IoT, donde los datos fluyen rápidamente de productores a consumidores, son procesados por agentes intermediarios y su valor incrementado gracias a relaciones entre datos de distintos orígenes. Las características intrínsecas de los datos, ligadas frecuentemente a los propios dispositivos que los generan (como la precisión o la frecuencia de actualización), deben acompañar a estos datos en su viaje a través de Internet, aportando un contexto imprescindible para su correcta interpretación y utilización. La búsqueda de dichos datos en las inmensas colecciones donde se almacenan, así como la comprensión de los mismos es un reto, donde el volumen exige la utilización de técnicas de procesado automatizado e incluso la aplicación de técnicas basadas en inteligencia artificial. La distribución y transporte de estos grandes volúmenes de datos pueden suponer problemas para las redes de distribución, lo que unido a posibles exigencias de baja latencia en la respuesta, nos fuerzan a diseñar y aplicar novedosas estrategias para el procesado de dichos datos de forma local o próxima a donde han sido producidos. Finalmente, la capacidad de interconectar plataformas y sistemas de manera fácil, rápida y segura mediante arquitecturas modulares y flexibles, supone una necesidad, más que una ventaja competitiva, en una nueva economía dirigida por los datos. Estos problemas, atacados de forma individual, ofrecen interesantes escenarios de investigación y mejora, pero considerados de forma conjunta revelan una realidad aún más interesante, donde se hace evidente que el total de las partes es más que la suma de las mismas, revelando relaciones y sinergias entre los diseños de arquitecturas e interfaces, el modelado de los datos, la seguridad e incluso la distribución y orquestación de tareas. Este trabajo de tesis doctoral explora estos aspectos de una manera holística, integrando tecnologías y estándares existentes en el diseño y construcción de arquitecturas de datos para IoT seguras e interoperables, considerando modelado y representación ontológica de los datos y explorando también la distribución y orquestación de tareas entre el borde y la nube. Como resultado, se presentan tres contribuciones principales, orientadas a la exploración de las arquitecturas interoperables y seguras, la distribución y orquestación de tareas entre el borde y la nube y finalmente sobre la representación de conceptos de seguridad y privacidad de los datos en este nuevo paradigma. En estas contribuciones se ofrecen diversos escenarios y bancos de prueba de las mismas, demostrando su relevancia y valor de cara al desarrollo y avance de estas tecnologías.  The Internet of Things (IoT) is presented as a new information systems paradigm, capable of helping with a number of the difficult challenges faced by our modern society. From the fight against climate change to progress towards achieving the right to a dignified and happy life, this new paradigm poses not only possibilities but also numerous technological challenges. Data privacy and security face new problems in such a dynamic environment as the IoT, where data flows rapidly from producers to consumers, is processed by intermediaries and its value increases thanks to relationships between data from different sources. Where the search for said data and its understanding is a challenge and where huge data volumes require the use of automated processing and the application of artificial intelligence techniques. Where the volume of data can strain the distribution networks and the latency requirements can be high, novel strategies must be applied for the processing of said data locally or close to where it is produced. Where the ability to easily, quickly and securely interconnect platforms and systems represents a competitive advantage in a new data-driven economy. These problems, when tackled individually, offer interesting research and improvement scenarios, but when considered as a whole they reveal an even more interesting reality, where it becomes evident that the total of the parts is more than the sum of them, revealing relationships and synergies between architecture and interface designs, data modeling, security, and even the distribution and orchestration of tasks. This doctoral thesis explores these aspects in a holistic way, integrating existing technologies and standards in the design and construction of secure and interoperable data architectures for IoT, considering ontological data modeling and representation and exploring task distribution and orchestration between edge and the cloud. As a result of this work, three main contributions are presented, oriented to the exploration of interoperable and secure architectures, the distribution and orchestration of tasks between the edge and the cloud and finally on the representation of security and data privacy concepts in this new paradigm. These contributions offer various scenarios and test benches for them, demonstrating their relevance and value for the development and advancement of these technologies

Integrated topological representation of multi-scale utility resource networks

PhD ThesisThe growth of urban areas and their resource consumption presents a significant global challenge. Existing utility resource supply systems are unresponsive, unreliable and costly. There is a need to improve the configuration and management of the infrastructure networks that carry these resources from source to consumer and this is best performed through analysis of multi-scale, integrated digital representations. However, the real-world networks are represented across different datasets that are underpinned by different data standards, practices and assumptions, and are thus challenging to integrate. Existing integration methods focus predominantly on achieving maximum information retention through complex schema mappings and the development of new data standards, and there is strong emphasis on reconciling differences in geometries. However, network topology is of greatest importance for the analysis of utility networks and simulation of utility resource flows because it is a representation of functional connectivity, and the derivation of this topology does not require the preservation of full information detail. The most pressing challenge is asserting the connectivity between the datasets that each represent subnetworks of the entire end-to-end network system. This project presents an approach to integration that makes use of abstracted digital representations of electricity and water networks to infer inter-dataset network connectivity, exploring what can be achieved by exploiting commonalities between existing datasets and data standards to overcome their otherwise inhibiting disparities. The developed methods rely on the use of graph representations, heuristics and spatial inference, and the results are assessed using surveying techniques and statistical analysis of uncertainties. An algorithm developed for water networks was able to correctly infer a building connection that was absent from source datasets. The thesis concludes that several of the key use cases for integrated topological representation of utility networks are partially satisfied through the methods presented, but that some differences in data standardisation and best practice in the GIS and BIM domains prevent full automation. The common and unique identification of real-world objects, agreement on a shared concept vocabulary for the built environment, more accurate positioning of distribution assets, consistent use of (and improved best practice for) georeferencing of BIM models and a standardised numerical expression of data uncertainties are identified as points of development.Engineering and Physical Sciences Research Council Ordnance Surve