Aircraft DC Microgrid Control for Voltage and Loss Constraints
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Solution Overview
Problem
Existing optimal scheduling control technologies for aircraft energy systems are inadequate for multi-bus DC microgrids, leading to inefficiencies in bus voltage regulation, current distribution, and power allocation, particularly under severe load switching conditions.
Innovation Solution
A distributed optimization control method is developed, which establishes a multi-bus DC microgrid system model based on Kirchhoff's law and uses a distributed optimization control algorithm incorporating projection and penalty techniques to achieve bus voltage regulation and current distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If distributed optimization control algorithm is implemented, then bus voltage regulation and current distribution are improved, but computational complexity and control algorithm difficulty increase
Solution Approach 1:
The control system is divided into distributed control modules at each bus node, where each node independently executes the optimization algorithm based on local information and communicates with neighboring nodes. This segmentation reduces the computational burden on any single controller while achieving system-wide voltage regulation and current distribution optimization.
2Reliability
If projection and penalty techniques are used to enforce constraints, then constraint satisfaction is improved, but control algorithm complexity increases
Solution Approach 1:
The projection and penalty techniques provide continuous feedback mechanisms that guide the optimization algorithm toward feasible solutions. The penalty term adds a cost for constraint violations, while the projection operator ensures that control inputs remain within admissible ranges, creating a feedback loop that enforces constraints without requiring complex external monitoring systems.
3Measurement precision
If multi-bus DC microgrid model is used instead of single-bus model, then system accuracy is improved, but control difficulty increases
Solution Approach 1:
The multi-bus DC microgrid is segmented into independent control zones, with each bus having its own distributed controller that manages local power flow and voltage regulation. This segmentation allows the complex multi-bus system to be controlled through simpler local decisions rather than requiring centralized control of the entire system, making implementation more manageable.
Data Source
AI summary
A distributed optimization control method for an aircraft energy system considering loss includes the following steps: S1, based on characteristics of the actual near-space aircraft energy system and the near-space environment, the multi-bus DC microgrid system model is established for the near-space aircraft energy system according to Kirchhoff's law; S2, according to the energy scheduling requirement of the near-space aircraft energy system, the system control target is established; S3, according to the system control target, the optimal scheduling problem of the aircraft energy system considering operating loss is established; and S4, based on projection and penalty, the distributed optimization control algorithm is designed. The distributed optimization control method realizes bus voltage regulation and current distribution. The soft constraint of output current and line current of the DC/DC converter is realized by penalty, and the hard constraint of bus voltage is realized based on the projection operator.