Feeder Hosting Capacity Optimization for Faster PV Interconnection
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Solution Overview
Problem
Current technologies for calculating feeder hosting capacity (FHC) are not optimized, leading to limitations in accommodating renewable energy (RE) penetration due to issues like voltage rise, thermal overloading, and protection malfunctions.
Innovation Solution
The use of swarm optimization-based intelligent scenario selection for faster and better convergence of FHC, which involves local and global search experiences, calculating max voltage nodes, and solving unbalance load flow, short circuit, and harmonics analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional FHC calculation methods are used, then calculation simplicity is maintained, but calculation speed and accuracy deteriorate
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing voltage sensitivity factors for different feeder configurations and load conditions. This allows the FHC calculation to quickly retrieve and use pre-computed data instead of performing full power flow analyses for every scenario, significantly improving calculation speed while maintaining accuracy.
Solution Approach 2:
The patent replaces conventional iterative numerical methods with a swarm-based optimization algorithm that uses intelligent search strategies. This substitution transforms the calculation approach from brute-force iteration to a more efficient search methodology, achieving faster convergence and improved calculation performance.
2Quantity of substance
If higher RE penetration is accommodated, then renewable energy utilization is improved, but voltage rise and thermal overloading worsen
Solution Approach 1:
The patent changes key parameters including voltage limits, thermal limits, and protection criteria to accurately reflect system capabilities. By using updated parameters and conducting comprehensive analyses, the system determines optimized FHC values that enable higher RE penetration while maintaining safe operating conditions and preventing harmful effects.
Solution Approach 2:
The patent implements feedback mechanisms by continuously monitoring voltage levels, thermal conditions, and protection system responses during FHC calculations. This feedback allows the swarm-based optimization to adjust RE placement and sizing decisions to avoid voltage rise and thermal overloading while maximizing RE penetration capacity.
3Measurement precision
If comprehensive analysis of all scenarios is performed, then accuracy is improved, but computational burden and time consumption worsen
Solution Approach 1:
The patent extracts and focuses computational resources on the most critical scenarios and feeder sections that have the greatest impact on FHC. By identifying and prioritizing key analysis areas, the system achieves accurate results without the need to perform exhaustive analysis of every possible scenario, significantly reducing calculation time.
Solution Approach 2:
The patent performs preliminary identification of critical feeders, load zones, and RE placement scenarios before conducting detailed FHC calculations. This preliminary sorting and prioritization allows the system to focus computational efforts on the most impactful areas, achieving high accuracy while minimizing unnecessary calculations and time consumption.
Data Source
AI summary
Provided are embodiments of systems, devices and methods for improved optimization of FHC using a swarm optimization based intelligent scenario selection from local search (small step) and global search (large step) experiences for faster and better FHC.