71 research outputs found
Decentralized Coalition Formation with Agent-based Combinatorial Heuristics
A steadily growing pervasion of the energy distribution grid with communication technology is widely seen as an enabler for new computational coordination techniques for renewable, distributed generation as well as for bundling with controllable consumers. Smart markets will foster a decentralized grid management. One important task as prerequisite to decentralized management is the ability to group together in order to jointly gain enough suitable flexibility and capacity to assume responsibility for a specific control task in the grid. In self-organized smart grid scenarios, grouping or coalition formation has to be achieved in a decentralized and situation aware way based on individual capabilities. We present a fully decentralized coalition formation approach based on an established agent-based heuristics for predictive scheduling with the additional advantage of keeping all information about local decision base and local operational constraints private. Two closely interlocked optimization processes orchestrate an overall procedure that adapts a coalition structure to best suit a given set of energy products. The approach is evaluated in several simulation scenarios with different type of established models for integrating distributed energy resources and is also extended to the induced use case of surplus distribution using basically the same algorithm
Dynamic Data Driven Dimensioning of Balancing Power with k-Nearest Neighbors
This paper proposes a novel dynamic design for
control reserve dimensioning. In contrast to the current statistical
analytic design we present a data driven approach with methods
of computational intelligence. The chosen k-nearest neighbor
algorithm is one of the most sucessfully used methods in machine
learning. The model is able to predict complex nonlinear behavior
by assuming that similar observations have similar outcomes.
A condition for the success of this method is to determine
the salient features. Therefore the core of this paper is to
show the dependencies of the influencing parameters. Numerical
experiments on the basis of freely available data for the years
2011 until 2013 show that there are time and space patterns as
well as inter dependencies with the active power market
Applying Trust for Operational States of ICT-Enabled Power Grid Services
Digitalization enables the automation required to operate modern
cyber-physical energy systems (CPESs), leading to a shift from hierarchical to
organic systems. However, digitalization increases the number of factors
affecting the state of a CPES (e.g., software bugs and cyber threats). In
addition to established factors like functional correctness, others like
security become relevant but are yet to be integrated into an operational
viewpoint, i.e. a holistic perspective on the system state. Trust in organic
computing is an approach to gain a holistic view of the state of systems. It
consists of several facets (e.g., functional correctness, security, and
reliability), which can be used to assess the state of CPES. Therefore, a trust
assessment on all levels can contribute to a coherent state assessment. This
paper focuses on the trust in ICT-enabled grid services in a CPES. These are
essential for operating the CPES, and their performance relies on various data
aspects like availability, timeliness, and correctness. This paper proposes to
assess the trust in involved components and data to estimate data correctness,
which is crucial for grid services. The assessment is presented considering two
exemplary grid services, namely state estimation and coordinated voltage
control. Furthermore, the interpretation of different trust facets is also
discussed.Comment: Preprint of the article under revision for the ACM Transactions on
Autonomous and Adaptive Systems, Special Issue on 20 Years of Organic
Computin
Towards a foundation for holistic power system validation and testing
Renewable energy sources and further electrificationof energy consumption are
key enablers for decreasing green-house gas emissions, but also introduce
increased complexitywithin the electric power system. The increased
availability ofautomation, information and communication technology,
andintelligent solutions for system operation have transformed thepower system
into a smart grid. In order to support thedevelopment process of smart grid
solutions on the system level,testing has to be done in a holistic manner,
covering the multi-domain aspect of such complex systems. This paper
introducesthe concept of holistic power system testing and discuss first
stepstowards a corresponding methodology that is being developed inthe European
ERIGrid research infrastructure project.Comment: 2016 IEEE 21st International Conference on Emerging Technologies and
Factory Automation (ETFA
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