Self Adaptive Safe Provisioning of Wireless Power Using DCOPs
| Jazyk: | angličtina |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Optimization
TS - Technical Sciences MCS - Monitoring & Control Services Electromagnetic waves Wireless power transfer (WPT) Large-scale network Radiation Exposure Environmental dynamics Distributed optimization Radiation Exposure Minimization Cocoa Energy transfer ICT Wireless Power Transfer Distributed constraint optimizations Constrained optimization Cybernetics Centralized optimization |
| Popis: | Wireless Power Transfer (WPT) technologies aim at getting rid of cables used by consumer devices for energy provision. As long distance WPT is becoming mature, the health impact of WPT becomes increasingly important to consider. In this paper we look at how to maximize the wireless power transfer to remote devices, while maintaining a safe level of electromagnetic radiation (EMR) for humans that are in the vicinity of the energy transmitters. Classically, this problem can be described as a centralized optimization problem of finding the optimal set of safe power levels at locations of human presence. Instead, we advocate to formulate this problem as an agent-based Distributed Constraint Optimization Problem (DCOP). As a solution to this problem we introduce CoCoA-WPT, a variant of the DCOP solver CoCoA. CoCoA-WPT provides a solution of similar quality to centralized solver even for a large scale network involving over a thousand nodes. Based on CoCoA-WPT, we propose a self-adaptive charging system: Transferring Energy Safely by Self-Adaptation (TESSA). TESSA keeps the charging network safe even when it is perturbed by environmental dynamics. We show that TESSA can reach on average up to 85% of the theoretical optimal maximum total transmitted power (calculated using centralized solution) while satisfying the EMR safety constraints. © 2017 IEEE. Axon AI; Dynamic Object Language Labs (DOLL); et al.; IEEE; IEEE Computer Society; NSF |
| Databáze: | OpenAIRE |
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