Smart Meter Phase Assignment Optimization
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Solution Overview
Problem
In low-voltage distribution networks, imbalanced current distribution among phases leads to inefficiencies, safety risks, and increased power losses due to unclear customer phase connections and varying consumption patterns, resulting in overheating, technical losses, and voltage fluctuations.
Innovation Solution
A method for assigning smart meters to phases based on electrical load patterns to minimize residuals and mean crest factors, ensuring balanced load distribution and reducing peak demand, using a greedy algorithm or multi-objective optimization to iteratively assign meters and optimize phase connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If customers are connected to phases based on purchased power or statistical profiles, then connection simplicity is maintained, but phase balance deteriorates leading to increased technical power losses
Solution Approach 1:
The patent changes the connection parameter from static (purchased power or statistical profile) to dynamic (real-time electrical load pattern). By continuously monitoring and adjusting phase connections based on actual consumption patterns, the system achieves both operational simplicity and energy efficiency, reducing technical power losses while maintaining easy connection management.
Solution Approach 2:
The patent implements a feedback mechanism where electrical load patterns are continuously monitored and used to adjust phase assignments. This closed-loop system ensures that customers are dynamically reassigned to phases based on real-time consumption data, maintaining phase balance and minimizing energy losses without complicating the connection process.
2Ease of operation
If customers with similar load patterns are connected to the same phase, then connection management is simplified, but phase balance deteriorates causing overloads and overheating
Solution Approach 1:
The patent applies asymmetry by intentionally distributing customers with similar load patterns across different phases rather than concentrating them on one phase. This asymmetric distribution strategy prevents phase imbalances, overloads, and overheating while maintaining simple connection management through automated load pattern analysis and dynamic reassignment.
Solution Approach 2:
The system dynamically changes phase assignment parameters based on real-time load pattern analysis. By continuously monitoring electrical consumption patterns and adjusting phase connections accordingly, the system maintains reliable phase balance while keeping connection management straightforward through automated decision-making algorithms.
3Device complexity
If more customers are connected to a single phase based on existing topology, then device complexity is reduced, but current imbalance increases leading to efficiency problems
Solution Approach 1:
The patent enables the distribution network to self-optimize by automatically analyzing electrical load patterns and dynamically reassigning customers to appropriate phases. This self-service mechanism maintains simple network topology while improving distribution efficiency, as the system autonomously balances phases based on real-time consumption data without requiring complex manual intervention or infrastructure changes.
Solution Approach 2:
The patent introduces dynamics into the previously static phase assignment process. By continuously monitoring electrical load patterns and dynamically adjusting phase connections, the system maintains simple network topology while achieving optimal distribution efficiency. The dynamic reassignment adapts to changing consumption patterns without increasing physical infrastructure complexity.
Data Source
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AI summary
A method for assigning a plurality of smart meters to phases of a distribution feeder comprising three phases, each smart meter having an electrical load pattern associated therewith, the method comprising: for each smart meter of the plurality of smart meters, assigning the smart meter to one phase of the three phases that minimizes one of: a sum of residuals of all pairs of phases of the three phases resulting from assigning the electrical load pattern of the smart meter to the one phase; and a sum of mean crest factors of the three phases resulting from assigning the electrical load pattern of the smart meter to the one phase. Also a device for assigning a plurality of smart meters to phases of a distribution feeder comprising three phases. And a method for assigning a plurality of smart meters to phases of a distribution feeder comprising three phases, each smart meter having an electrical load pattern associated therewith, the method comprising: running a multi-objective optimization algorithm for assigning each smart meter to a phase of the three phases; wherein the multi-objective optimization algorithm minimizes: a sum of residuals of all pairs of phases of the three phases upon assigning all smart meters to phases of the three phases; and a sum of mean crest factors of the three phases upon assigning all smart meters to phases of the three phases; and wherein upon assigning all smart meters to phases of the three phases the sum of residuals and the sum of mean crest factors are non-dominated in a Pareto front.