Decentralized Load Balancing for Distribution Feeders
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Solution Overview
Problem
Existing distribution feeder systems are slow to react to changing load conditions due to centralized approaches that rely on delayed data processing and complex statistical calculations, leading to obsolete balancing decisions and high costs.
Innovation Solution
A decentralized peer-to-peer methodology using intelligent electronic devices (IEDs) with peer communication via GOOSE messages to determine balanced load points and generate permissive close signals in real-time, allowing for efficient load balancing and safe reconnection of line sections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a centralized approach with delayed data processing is used, then system complexity is reduced, but responsiveness to changing load conditions deteriorates
Solution Approach 1:
The patent segments the centralized data processing function into distributed intelligent electronic devices (IEDs) located at each switch. Each IED independently performs load point determination and permissive close logic calculations using locally available data, eliminating the need for centralized processing and enabling real-time responsiveness to load changes.
Solution Approach 2:
Each intelligent electronic device serves itself by autonomously determining load points and generating permissive close signals based on local measurements and peer-to-peer communication. This self-service capability eliminates dependency on centralized control, enabling immediate local decision-making without waiting for centralized processing.
2Measurement precision
If complex statistical calculations are performed, then measurement precision is improved, but processing time increases
Solution Approach 1:
The patent applies partial action by using simplified deterministic calculations instead of complete statistical analysis. Each IED uses real-time load measurements and predetermined load budgets to determine load points, performing only the necessary calculations needed for immediate decision-making rather than comprehensive statistical processing.
Solution Approach 2:
The patent replaces complex statistical calculation mechanisms with simpler deterministic logic based on real-time measurements and predefined thresholds. This substitution maintains sufficient measurement precision for operational decisions while dramatically reducing processing time and computational requirements.
3Device complexity
If centralized processing is used, then device complexity is reduced, but productivity decreases
Solution Approach 1:
The patent segments the load balancing function across multiple independent intelligent electronic devices distributed throughout the system. Each device simultaneously performs load point determination and permissive close logic calculations, enabling parallel processing that dramatically increases overall productivity compared to sequential centralized processing.
Solution Approach 2:
The patent implements preliminary action by pre-configuring load budgets and permissive close logic within each intelligent electronic device. This allows devices to immediately execute load balancing decisions using pre-prepared calculation frameworks and local data, eliminating delays associated with centralized computation and coordination.
Data Source
AI summary
Balanced load points and permissive close switch determinations may be made using a decentralized peer-to-peer methodology for a distribution feeder that includes switches and line sections between adjacent switches, each switch being a switching point of the distribution feeder. In particular, a balanced load point may be determined by determining a first load at a first switch and a second load at a second switch coupled to the first switch via a first line section, communicating the first load and a first load budget from the first switch to the second switch, determining a third load on the first line section based on the first load and the second load, and determining a second load budget at the second switch based on the first load budget and the third load, all substantially in real time.