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Hierarchical and Decentralized Stochastic Energy Management for Smart Distribution Systems With High BESS Penetration

机译:具有高BESS渗透率的智能配电系统的分层和分散式随机能量管理

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摘要

In this paper, we propose a hierarchical and decentralized stochastic energy management scheme for smart distribution systems with high battery energy storage system (BESS) penetration. An energy management problem is formulated based on a two-layer hierarchical architecture for the joint optimization of distribution system operator (DSO) and customers. In the lower layer, the stochastic energy management problem of individual BESS is formulated as a Markov decision process to minimize the electricity cost. In the upper layer, the solutions of individual BESS stochastic energy management problems are used for the energy management of smart distribution systems to minimize the line losses while maintaining the voltage levels within required range. Considering the partial communications among households, this problem can be transformed into a decentralized partially observable Markov decision process with stochastic controllers. Accordingly, an energy management scheme based on exhaustive backups is proposed to solve the formulated problem in a decentralized manner. To reduce the computational complexity caused by high BESS penetration, a heuristic search and pruning method is further proposed. The case study results based on IEEE 5-bus test feeder and IEEE European low voltage test feeder indicate that the proposed scheme can reduce the electricity costs of both DSO and customers, while having the voltage levels regulated. Also, the computational complexity is much lower for a smart distribution system with high BESS penetration, in comparison with existing BESS energy management schemes.
机译:在本文中,我们为具有高电池储能系统(BESS)渗透率的智能配电系统提出了一种分层的分散式随机能量管理方案。基于两层层次结构的能源管理问题用于配电系统运营商(DSO)和客户的联合优化。在较低的层中,将单个BESS的随机能源管理问题表述为马尔可夫决策过程,以最大程度地减少电费。在上层,将单个BESS随机能源管理问题的解决方案用于智能配电系统的能源管理,以最大程度地减少线路损耗,同时将电压水平维持在所需范围内。考虑到家庭之间的部分通信,该问题可以转化为具有随机控制器的分散的,部分可观察的马尔可夫决策过程。因此,提出了一种基于穷举的能源管理方案,以分散的方式解决提出的问题。为了降低由于高BESS渗透而导致的计算复杂性,进一步提出了一种启发式搜索和修剪方法。基于IEEE 5总线测试馈线和IEEE欧洲低压测试馈线的案例研究结果表明,该方案可以在调节电压水平的同时降低DSO和客户的电力成本。而且,与现有的BESS能源管理方案相比,具有高BESS渗透率的智能配电系统的计算复杂度要低得多。

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