Asynchronous Vector Clocks for Microgrid State Estimation
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Solution Overview
Problem
Existing distributed systems face challenges in executing distributed control algorithms asynchronously due to communication delays and system failures, which hinder efficient data exchange and state estimation in microgrids.
Innovation Solution
The implementation of asynchronous communication networks in microgrid systems, where microgrid control systems use diffusion strategies and peer-to-peer iterative communication to perform state estimation, allowing them to operate without synchronizing to a common time source and adapt to communication delays through trust matrices and vector clocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If synchronous communication is used between agent nodes, then data exchange consistency is improved, but system complexity and communication overhead increase
Solution Approach 1:
The patent inverts the conventional approach by using asynchronous communication instead of synchronous communication for distributed control algorithms. Agent nodes operate independently without waiting for responses from other nodes, eliminating the need for complex synchronization protocols while maintaining data consistency through local state tracking and iterative convergence.
Solution Approach 2:
The system dynamically adapts to varying communication conditions by allowing agent nodes to proceed at different rates. Each node independently determines when to execute algorithm steps based on local data availability and convergence criteria, rather than following a rigid synchronous schedule, thus reducing communication overhead and system complexity.
2Device complexity
If asynchronous communication is used between agent nodes, then system complexity is reduced, but data exchange consistency deteriorates
Solution Approach 1:
The patent implements feedback mechanisms where agent nodes continuously monitor local state variables and convergence criteria. Each node exchanges data with neighboring nodes and adjusts its computations based on received information, ensuring that the distributed algorithm converges to a consistent solution despite asynchronous communication patterns.
Solution Approach 2:
Each agent node independently manages its own execution timeline and data processing without relying on centralized coordination. Nodes autonomously determine when to perform computational steps based on local data availability and algorithm convergence requirements, maintaining consistency through self-regulated asynchronous operation.
3Measurement precision
If synchronous communication network is used, then algorithm execution accuracy is improved, but communication delays and system failures cause asynchrony
Solution Approach 1:
The patent segments the distributed control algorithm into independent computational steps that can be executed asynchronously by different agent nodes. Each node processes local measurements and exchanges intermediate results with neighbors, allowing the algorithm to maintain accuracy while tolerating communication delays and failures through modular, independent execution units.
4Reliability
If agent nodes wait for all iterations from other nodes before determining next iteration, then data consistency is improved, but execution time increases
Solution Approach 1:
The patent applies preliminary action by having agent nodes prepare and exchange data packets in advance containing iteration results and convergence indicators. Nodes can begin subsequent computational steps using preliminary data from neighbors before receiving final confirmed data, reducing waiting time while maintaining consistency through validation checks on the preliminary information.
Data Source
AI summary
Systems, methods, techniques and apparatuses of asynchronous communication is distributed systems are disclosed. One exemplary embodiment is a method determining, with a plurality of agent nodes structured to communicate asynchronously in a distributed system, a first set of iterations including an iteration determined by each of the plurality of agent nodes; determining, with a first agent node of the plurality of agent nodes, a local vector clock; receiving, with the first agent node, a first iteration of the first set of iterations and a remote vector clock determined based on the first iteration; updating, with the first agent node, the local vector clock based on the received remote vector clock; and determining a first iteration of a second set of iterations based on the first set of iterations after determining all iterations of the first set of iterations have been received based on the local vector clock.