The real-time operation of the energy management system (RT-EMS) is one of the vital functions of Microgrids (MG). In this context, the reliability and smooth operation should be maintained in real time regardless of load and generation variations and without losing the optimum operation cost. This paper presents a design and implementation of a RT-EMS based on Multiagent system (MAS) and the fast converging T-Cell algorithm to minimize the MG operational cost and maximize the real-time response in grid-connected MG. The RT-EMS has the main function to ensure the energy dispatch between the distributed generation (DG) units that consist in this work on a wind generator, solar energy, energy storage units, controllable loads and the main grid. A modular multi-agent platform is proposed to implement the RT-EMS. The MAS has features such as peer-to-peer communication capability, a fault-tolerance structure, and high flexibility, which make it convenient for MG context. Each component of the MG has its own managing agent. While, the MG optimizer (MGO) is the agent responsible for running the optimization and ensuring the seamless operation of the MG in real time, the MG supervisor (MGS) is the agent that intercepts sudden high load variations and computes the new optimum operating point. In addition, the proposed RT-EMS develops an integration of the MAS platform with the Data Distribution Service (DDS) as a middleware to communicate with the physical units. In this work, the proposed algorithm minimizes the cost function of the MG as well as maximizes the use of renewable energy generation; Then, it assigns the power reference to each DG of the MG. The total time delay of the optimization and the communication between the EMS components were reduced. To verify the performance of our proposed system, an experimental validation in a MG testbed were conducted. Results show the reliability and the effectiveness of the proposed multiagent based RT-EMS. Various scenarios were tested such as normal operation as well as sudden load variation. The optimum values were obtained faster in terms of computation time as compared to existing techniques. The latency from the proposed system was 43% faster than other heuristic or deterministic methods in the literature. This significant improvement makes this proposed system more competitive for RT applications.

In this paper, a data-centric communication framework is proposed for multicast routable generic object-oriented substation event (GOOSE) messages (MRGM) over the wide area network (WAN) for effective substation-to-substation (SS2SS) and substation to control center (SS2CC) communications. In this structure, the IEC 61850 GOOSE message is transmitted over the WAN using the data distribution service (DDS) as a fast, reliable, and secure data-centric communication middleware. The main feature of this framework is its multicast capability, where several authorized subscribers can receive a published message simultaneously. This can significantly improve the system monitoring and control of the protection systems in modern smart grids, where intelligent schemes can be applied. The effectiveness of the proposed platform, in terms of total end-to-end delay between participants, is evaluated through experimental results obtained from the actual hardware-based test setup developed at the Florida International University (FIU) smart grid testbed. The results demonstrate that the latency between sending and receiving a GOOSE message among participants is within its maximum time span defined by the IEC 61850-90-5 working group for communications over the WAN.

The necessity of critical communication between intelligent electronic devices (IEDs) in different substations led to expanding the Generic Object-Oriented Substation Event protocol (GOOSE) from the local area network (LAN) to the wide area network (WAN). International Electrotechnical Commission (IEC) 61850-90-5 has extended GOOSE messages as routable GOOSE (R-GOOSE) messages by adding network and transport layers. Therefore, the communication’s end-to-end latency and reliability against cyberattacks should be addressed.

This paper proposes a supervisory control scheme for hybrid AC-DC microgrids to enhance the system loadability under unbalanced loading conditions by implementing a new power routing mechanism for AC/DC converters. The system is studied on grid-connected mode and the supervisory control strategy is aimed to maximize the system loadability at the point of common coupling (PCC). The supervisory control receives the measurements from the PCC and calculates active and reactive power mismatches for all three phases. Afterward these mismatches are assigned to all three-phase interlinking converters (ICs) to keep the power balance at the PCC. Balancing the three-phase loadings at the PCC not only enhances the system loadability index, but also decreases voltage deviations and energy losses in the microgrid. Numerical results obtained by implementing the proposed method on the modified IEEE 13 bus system show the validity of the proposed control strategy.