559 research outputs found

    Crossing Roads of Federated Learning and Smart Grids: Overview, Challenges, and Perspectives

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    Consumer's privacy is a main concern in Smart Grids (SGs) due to the sensitivity of energy data, particularly when used to train machine learning models for different services. These data-driven models often require huge amounts of data to achieve acceptable performance leading in most cases to risks of privacy leakage. By pushing the training to the edge, Federated Learning (FL) offers a good compromise between privacy preservation and the predictive performance of these models. The current paper presents an overview of FL applications in SGs while discussing their advantages and drawbacks, mainly in load forecasting, electric vehicles, fault diagnoses, load disaggregation and renewable energies. In addition, an analysis of main design trends and possible taxonomies is provided considering data partitioning, the communication topology, and security mechanisms. Towards the end, an overview of main challenges facing this technology and potential future directions is presented

    Sustainable consumption: towards action and impact. : International scientific conference November 6th-8th 2011, Hamburg - European Green Capital 2011, Germany: abstract volume

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    This volume contains the abstracts of all oral and poster presentations of the international scientific conference „Sustainable Consumption – Towards Action and Impact“ held in Hamburg (Germany) on November 6th-8th 2011. This unique conference aims to promote a comprehensive academic discourse on issues concerning sustainable consumption and brings together scholars from a wide range of academic disciplines. In modern societies, private consumption is a multifaceted and ambivalent phenomenon: it is a ubiquitous social practice and an economic driving force, yet at the same time, its consequences are in conflict with important social and environmental sustainability goals. Finding paths towards “sustainable consumption” has therefore become a major political issue. In order to properly understand the challenge of “sustainable consumption”, identify unsustainable patterns of consumption and bring forward the necessary innovations, a collaborative effort of researchers from different disciplines is needed

    Self-organizing Coordination of Multi-Agent Microgrid Networks

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    abstract: This work introduces self-organizing techniques to reduce the complexity and burden of coordinating distributed energy resources (DERs) and microgrids that are rapidly increasing in scale globally. Technical and financial evaluations completed for power customers and for utilities identify how disruptions are occurring in conventional energy business models. Analyses completed for Chicago, Seattle, and Phoenix demonstrate site-specific and generalizable findings. Results indicate that net metering had a significant effect on the optimal amount of solar photovoltaics (PV) for households to install and how utilities could recover lost revenue through increasing energy rates or monthly fees. System-wide ramp rate requirements also increased as solar PV penetration increased. These issues are resolved using a generalizable, scalable transactive energy framework for microgrids to enable coordination and automation of DERs and microgrids to ensure cost effective use of energy for all stakeholders. This technique is demonstrated on a 3-node and 9-node network of microgrid nodes with various amounts of load, solar, and storage. Results found that enabling trading could achieve cost savings for all individual nodes and for the network up to 5.4%. Trading behaviors are expressed using an exponential valuation curve that quantifies the reputation of trading partners using historical interactions between nodes for compatibility, familiarity, and acceptance of trades. The same 9-node network configuration is used with varying levels of connectivity, resulting in up to 71% cost savings for individual nodes and up to 13% cost savings for the network as a whole. The effect of a trading fee is also explored to understand how electricity utilities may gain revenue from electricity traded directly between customers. If a utility imposed a trading fee to recoup lost revenue then trading is financially infeasible for agents, but could be feasible if only trying to recoup cost of distribution charges. These scientific findings conclude with a brief discussion of physical deployment opportunities.Dissertation/ThesisDoctoral Dissertation Systems Engineering 201

    Vulnerability and resilience of cyber-physical power systems: results from an empirical-based study

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    Power systems are undergoing a profound transformation towards cyber-physical systems. Disruptive changes due to energy system transition and the complexity of the interconnected systems expose the power system to new, unknown and unpredictable risks. To identify the critical points, a vulnerability assessment was conducted, involving experts from power as well as information and communication technologies (ICT) sectors. Weaknesses were identified e.g.,the lack of policy enforcement worsened by the unreadiness of involved actors. The complex dynamics of ICT makes it infeasible to keep a complete inventory of potential stressors to define appropriate preparation and prevention mechanisms. Therefore, we suggest applying a resilience management approach to increase the resilience of the system. It aims at a better ride through failures rather than building higher walls. We conclude that building resilience in cyber-physical power systems is feasible and helps in preparing for the unexpected

    Utility Metrics Specifications. OpenIoT Deliverable D422

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    This deliverable specifies the utility metrics that are considered and used in the scope of the OpenIoT project. These utility metrics are recorded as part of the implementation of the Utility Manager component of the OpenIoT platform, while they have also been used to drive the utility based optimization mechanisms of the project. In particular we provided the following contributions: We provide an analysis and summary of utility metrics for different data providers and environments, including physical sensors, sensor networks, and virtual sensors. These metrics can be used to measure utility for interconnected objects. We proposed utility functions that use metrics in order to compute valuation and cost functions. These functions can be used by utility-based optimization techniques. The utility based schemes proposed provide means and algorithms that can help selecting virtual sensors for efficient data collection. We describe utility metrics, tailored specifically for the OpenIoT use cases, indicating the relevant parameters (e.g. location, bandwidth, availability, privacy), and cost and valuation functions (if applicable)

    Minimizing residential distribution system operating costs through intelligently scheduled plug-in hybrid electric vehicle charging

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    Rising fuel prices and environmental concerns are threatening the stability of current electrical grid systems. These factors are pushing the automobile industry towards more effcient, hybrid vehicles. Current trends show petroleum is being edged out in favor of electricity as the main vehicular motive force. The proposed methods create an optimized charging control schedule for all participating Plug-in Hybrid Electric Vehicles in a distribution grid. The optimization will minimize daily operating costs, reduce system losses, and improve power quality. This requires participation from Vehicle-to-Grid capable vehicles, load forecasting, and Locational Marginal Pricing market predictions. Vehicles equipped with bidirectional chargers further improve the optimization results by lowering peak demand and improving power quality

    Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts

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    The climate changes that are visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this book presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications such as hybrid and microgrid power systems based on energy internet, blockchain technology, and smart contracts, we hope that they are of interest to readers working in the related fields mentioned above
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