Distributed state estimation (DSE) allows networked microgrids to achieve global state awareness with conservation of local information privacy by peer-to-peer message exchange implemented with Internet of Things protocols over heterogeneous communications. This paper presents a secure DSE (SDSE) method for networked microgrids to enhance system resiliency by addressing false data injection threat in distributed microgrid agent nodes. The designated SDSE applies a trust-based diffusion algorithm using adaptive combination policy, which allows agents to adapt their combination coefficients to exclude misbehaving nodes from the network. The results demonstrate that proposed SDSE algorithm addresses emerging data integrity and security problems in critical energy delivery infrastructure and SCADA environment.

This paper presents a cloud-based and hybrid wireless mesh communication framework for bilevel, nested, distributed optimization of networked clusters of microgrids. The proposed optimization framework implements a diffusion-based, fully distributed algorithm on local wireless network and a quasi-distributed approach on wide-area internet-based cloud. The lower level of the bilevel optimization implements a distributed optimal economic dispatch solution for intramicrogrid among distributed energy resources, and the upper level implements a global optimal dispatch for intermicrogrid energy exchange. To demonstrate industrial applicability of the proposed framework, the IEC 61850 interoperability protocol is adopted to achieve a certain delay performance so that the distributed optimization convergence is guaranteed. First, hardware-based prototype intelligent electronic devices are developed using embedded systems. Then, the bilevel nested optimization algorithm is implemented for integration of networked microgrids. Finally, experimental results are demonstrated from a real-time smart grid testbed featuring realistic microgrids. The results demonstrate that the proposed framework meets communication requirements for distributed optimization of networked microgrids.

As intermittent generation profiles introduce more stress due to the sudden imbalance in supply and demand, power systems are becoming more dependent on online aggregated support of networked utility-independent private microgrids. During the aggregation process, microgrid operators’ preferences and bidding behaviors are priority. New aggregation approaches are required considering the individual behaviors of the networked and geographically dispersed independent microgrids. In this paper, we present a novel bidding behavior modeling and an auction architecture consisting of a central aggregator and networked microgrid agents. The bidding behavioral states of the microgrid agents are formalized as partially observable Markov processes for the belief updates and short-term policy determination in order to maximize the individual profit. A reverse auction model is adopted to enable competitive negotiations between the central aggregator and networked microgrid agents. The auction and aggregation processes were implemented in a power system control area along with an automatic generation control (AGC) scheme to contribute frequency control. The proposed AGC and auction mechanism were verified with an industrial multi-agent framework in a laboratory-based real-time application.

Emerging Software Defined Networking (SDN) technology provides excellent flexibility to large-scale networks in terms of control, management, security, and maintenance. In this paper, we propose an SDN-based communication infrastructure for Smart Grid distribution networks among substations. A Smart Grid communication infrastructure consists of a large number of heterogenous devices that exchange real-time information for monitoring the status of the grid. We then investigate how SDN-enabled Smart Grid infrastructure can provide resilience to active distribution substations with self-recovery. Specifically, by introducing redundant and wireless communication links that can be used during the emergencies, we show that SDN controllers can be effective for restoring the communication while providing a lot of flexibility. Furthermore, to be able to effectively evaluate the performance of the proposed work in terms of various fine-grained network metrics, we developed a Mininet-based testing framework and integrated it with ns-3 network simulator. Finally, we conducted experiments by using actual Smart Grid communication data to assess the recovery performance of the proposed SDN-based system. The results show that SDN is a viable technology for the Smart Grid communications with almost negligible delays in switching to backup wireless links during the times of link failures in reliable fashion.