基于一致性算法的混合多端直流自律分散控制

HAN Minxiao

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基于一致性算法的混合多端直流自律分散控制

更新时间：2025-08-13

- 基于一致性算法的混合多端直流自律分散控制
- Automation of Electric Power Systems Vol. 40, Issue 12, Pages: 130-136(2016)
- 作者机构：
  
  华北电力大学电气与电子工程学院,北京市,102206
- 作者简介：
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- Published：2016
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HAN Minxiao. [J]. Automation of electric power systems, 2016, 40(12): 130-136.
DOI：

HAN Minxiao. [J]. Automation of electric power systems, 2016, 40(12): 130-136. DOI：

摘要

提出了基于一致性算法的混合多端直流自律分散控制。一致性算法广泛应用于多代理系统中，其作用是使各代理仅需相邻通信即可获取全局信息，是实现自律分散控制的基础。因此，在混合多端直流每个端子设置一个代理构成多代理系统。每个代理包含两个功能模块:全局信息获取模块应用一致性算法获取节点总注入功率与参与优化控制的换流站数目；优化控制模块在获取全局信息的基础上，计算本换流站满足特定目标函数的功率和电压参考值。首先在MATLAB中对一致性算法进行了仿真验证，结果表明一致性算法既能保证收敛性，又可在功率变化情况下及时获取全局信息。然后以混合多端直流的损耗优化为例说明基于一致性算法的自律分散控制可应用的场景，在PSCAD中的仿真结果表明所提出的控制策略能够应用到系统的损耗优化中，显著降低了混合多端直流的损耗。

Abstract

A consensus algorithm based decentralized autonomous control of hybrid multi-terminal direct current(MTDC)system is proposed. Consensus algorithm has been widely used in multi-agent systems to obtain global information only communicating with neighbouring agents

which is the foundation of global optimization control. Therefore

each terminal is equipped with an agent to constitute a multi-agent system

and each agent contains two function modules. Global information discovery module obtains total injected power and the number of converters participating optimization control. Optimization control module calculates power and voltage reference based on the discovered global information. First

the consensus algorithm is verified in MATLAB

the results show that the consensus algorithm can guarantee convergence and obtain global information in power fluctuation situation. Then

the power losses optimization of a hybrid MTDC system is used as an example to illustrate the feasible application of consensus algorithm based decentralized autonomous control. The simulation results in PSCAD manifest that the proposed control strategy can be applied in system losses optimization and effectively decrease the hybrid MTDC losses. This work is supported by National Natural Science Foundation of China(No. 51177044)and State Grid Corporation of China(No. XT71-14-042).

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