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Decentralised conic optimisation of reactive power considering uncertainty of renewable energy sources

机译：考虑可再生能源不确定性的无功分散圆锥优化

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摘要

This study proposes a decentralised reactive power optimisation of capacitors in distribution system with uncertain renewable energy sources (RES). The optimisation problem is modelled as minimising the active power loss and installed capacitors costs, subject to power flow constraints and other operation conditions. In view of the non-linear power flow equality constraints with uncertain power of the RES, the optimisation problem is hard to be solved efficiently due to the non-linear and stochastic issues. To this end, the discrete probability model of RES has been utilised to build the multi-scenario deterministic formulation of the stochastic problem, which further changes to a mixed integer conic optimisation (CO) model by relaxing the non-linear power flow equations. Besides, in keeping with the growing complexity of modern distribution system, a decentralised CO algorithm for large-scale problem is developed to separate the problem into smaller subproblems. The sufficient conditions which guarantee the exactness of the conic relaxed power flow equalities in subproblems are discussed as well. Simulations verify the effectiveness of the proposed algorithm.
机译：这项研究提出了具有不确定可再生能源（RES）的配电系统中电容器的分散无功优化。优化问题的模型是，根据功率流约束和其他操作条件，将有功功率损耗和安装的电容器成本降至最低。考虑到具有不确定功率的RES的非线性潮流相等约束，由于非线性和随机问题，难以有效地解决优化问题。为此，RES的离散概率模型已用于构建随机问题的多情景确定性公式，通过放宽非线性潮流方程，可将其进一步更改为混合整数圆锥优化（CO）模型。此外，为了适应现代配电系统日益增长的复杂性，针对大型问题开发了一种分散式CO算法，以将问题分为较小的子问题。还讨论了在子问题中保证圆锥松弛功率流相等的准确性的充分条件。仿真验证了所提算法的有效性。

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