Decentralized Optimal Dispatch of Photovoltaic Inverters in Residential Distribution Systems
Decentralized Optimal Dispatch of Photovoltaic Inverters in Residential Distribution Systems
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DOI：
10.1109/tec.2014.2357997
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发表时间：
2014-12-01
影响因子：
4.9
通讯作者：
Giannakis, Georgios B.
中科院分区：
文献类型：
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作者：
Dall'Anese, Emiliano;Dhople, Sairaj V.;Giannakis, Georgios B.
本文开发了计算住宅光伏 (PV) 逆变器最佳有功功率和无功功率设定点的分散方法。众所周知，传统的光伏逆变器控制器旨在以单位功率因数提取最大功率，无法实现电压调节和网络损耗最小化等次要性能目标。最佳潮流技术可用于选择哪些逆变器将提供辅助服务，并根据明确的性能标准和经济目标计算其最佳有功功率和无功功率设定点。本文利用稀疏性促进正则化技术和半定松弛技术的进步，展示了如何通过减少计算负担和最优性保证来解决此类问题。为了实现大规模实施，引入了一种基于所谓的乘法器交替方向方法的新颖算法框架，通过该算法框架可以将这种设置中的最优潮流类型问题系统地分解为子问题，这些子问题可以由公用事业公司和客户拥有的光伏系统在信息交换有限的情况下以分散的方式解决。由于计算负担在多个设备之间分担，并且可以规避所有对所有通信的要求，因此所提出的优化方法可以有利地扩展到大型配电网络。
Decentralized methods for computing optimal real and reactive power setpoints for residential photovoltaic (PV) inverters are developed in this paper. It is known that conventional PV inverter controllers, which are designed to extract maximum power at unity power factor, cannot address secondary performance objectives such as voltage regulation and network loss minimization. Optimal power flow techniques can be utilized to select which inverters will provide ancillary services and to compute their optimal real and reactive power setpoints according to well-defined performance criteria and economic objectives. Lever-aging advances in sparsity-promoting regularization techniques and semidefinite relaxation, this paper shows how such problems can be solved with reduced computational burden and optimality guarantees. To enable large-scale implementation, a novel algorithmic framework is introduced-based on the so-called alternating direction method of multipliers-by which optimal power flow-type problems in this setting can be systematically decomposed into subproblems that can be solved in a decentralized fashion by the utility and customer-owned PV systems with limited exchanges of information. Since the computational burden is shared among multiple devices and the requirement of all-to-all communication can be circumvented, the proposed optimization approach scales favorably to large distribution networks.