Restructuring and privatization in power systems have resulted in a fundamental transition of conventional distribution systems into modern multi-agent systems. In these structures, each agent of the distribution system would independently operate its local resources. In this regard, uncertainties associated with load demands and renewable energy sources could challenge the operational scheduling conducted by each agent. Therefore, this paper aims to develop a distributed operational management for multi-agent distribution systems taking into account the uncertainties of each agent. The developed framework relies on alternating direction method of multipliers (ADMM) to coordinate the operational scheduling of the agents in a distributed manner. Moreover, a robust optimization technique is employed to consider the worst-case realization associated with the operation of each agent. Finally, the proposed framework is implemented on IEEE 37-bus network to analyze its efficacy in distributed robust operational management of distribution systems with multi-agent structures.Index Terms-Energy Management, active distribution systems, distributed management, alternating direction method of multipliers (ADMM), robust optimization.

No abstract

The privatization of distribution systems has resulted in the development of multiple-microgrid (multiple-MG) systems where each microgrid independently operates its local resources. Moreover, the high integration of independent distributed energy sources could lead to operational issues such as grid congestion in future distribution systems. Therefore, this paper provides a transactive-based energy management framework to operate multiple-MG distribution systems; while, alleviating grid congestion in a decentralized manner. In this respect, alternating direction method of multipliers (ADMM) is considered to develop an operational framework that copes with distributed nature of multiple-MG systems. In this context, a novel procedure in the context of ADMM is proposed to distributedly determine transactive coordinator signals which address energy prices as well as power losses and grid congestions. Furthermore, each MG takes into account stochastic programming and the conditional value-at-risk index to handle the uncertainty of its operational scheduling. At last, the proposed framework is applied on IEEE 37-bus and 123-bus test grids to investigate its efficacy in distributed energy management of multiple-MG systems.

No abstract