Multi-Region Power Dispatch via Aggregation Models
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Solution Overview
Problem
The complexity of dispatching and controlling multi-region power systems is exacerbated by data ownership issues and computing capacity limitations among different regional power systems, making it difficult to coordinate and optimize power resource allocation across regions.
Innovation Solution
A method and system where each regional system operator obtains and reports basic operating parameters to establish a dispatching model using power flows of tie lines, which are then aggregated and solved by a cross-region system operator to achieve a reduced dispatching model, optimizing power allocation with minimal information interaction and eliminating the need for repeated iterations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complete system data is exchanged among regional operators, then coordination and optimization of multi-region power system can be achieved, but information exchange volume and computational complexity increase significantly
Solution Approach 1:
The multi-region power system is segmented into independent regional subsystems, each with its own dispatching model. Only essential boundary parameters (tie-line power flows) are exchanged between regions, rather than complete system data. This segmentation enables distributed optimization while minimizing information exchange volume.
Solution Approach 2:
A cross-region system operator acts as an intermediary to coordinate the aggregation models from different regional operators. The intermediary facilitates optimized power allocation across regions without requiring direct complete data exchange between all regional operators, reducing overall information exchange requirements.
2Reliability
If complete system data is collected from all regional operators, then centralized optimization can be performed, but computing capacity requirements become prohibitive
Solution Approach 1:
The centralized optimization problem is segmented into multiple regional dispatching models that can be solved independently. Each regional operator solves its own optimization problem using local data, significantly reducing the computational burden compared to solving one large centralized problem with all system data.
Solution Approach 2:
Instead of requiring complete system data for full centralized optimization, the method uses partial information (aggregation models with tie-line parameters) from each region to achieve coordinated optimization. This partial action approach achieves sufficient optimization accuracy without the prohibitive computational cost of complete data processing.
3Reliability
If regional operators maintain data privacy, then data security is protected, but cross-region coordination becomes difficult
Solution Approach 1:
Only the essential parameters needed for cross-region coordination (tie-line power flows and aggregation models) are extracted and exchanged between regional operators. Complete system data and sensitive information remain localized and private to each region, while sufficient information is shared to enable coordinated optimization.
Solution Approach 2:
Each regional operator maintains local control and data privacy for its own system, while exchanging only the specific boundary parameters necessary for cross-region coordination. This local quality approach allows each region to protect its sensitive data while still participating in coordinated multi-region optimization.
Data Source
AI summary
The disclosure provides a method and a system for dispatching a multi-region power system. The method includes: obtaining, by each regional system operator, basic operating parameters of the regional power system; establishing, by each regional system operator, a dispatching model of the regional power system based on the basic operating parameters; identifying, by each regional system operator, an aggregation model of the regional power system based on the dispatching model of the regional power system; reporting, by each regional system operator, the aggregation model to the cross-region system operator; establishing, by the cross-region system operator, a reduced dispatching model of the multi-region power system based on the aggregation model from each regional system operator; and solving, by the cross-region system operator, the reduced dispatching model to obtain a dispatching result of each regional power system.