Abstract-Since high penetration renewable sources are integrated into the future power system, energy storage systems are often installed to maintain the frequency stability in a microgrid. The operation mode of a microgrid may frequently change due to the intermittency of renewable sources, and energy storage systems will be charged/discharged accordingly to smooth and balance the generation of renewable sources. Thus, energy storage systems should be coordinated in a proper approach to ensure the supply-demand balance while increasing their profits and energy efficiency. To this end, a distributed optimal solution for energy storage systems to maintain the supplydemand balance while maximizing their welfare and energy efficiency is proposed to energy storage systems by enhancing the coordination through the communication under a multiagent system framework. Under this framework, each energy storage system is designated as an agent, and it only utilizes the local information to interact with the neighbouring agents. Additionally, since the participants in microgrid may not be willing to release their information about cost functions, or even the local gradient with other neighbouring agents, the proposed solution could be implemented without these private information to the individual agents. The simulation studies are carried out for IEEE 14-bus and 30-BESS systems to validate the effectiveness of the proposed distributed solution.

Abstract-This paper considers the optimal resource management problem for microgrids. Microgrids provide a promising approach to fulfil challenges of the integration of distributed renewable generations and energy storage systems. However, the resource management in a microgrid encounters the new difficulty, i.e. supply-demand imbalance, caused by the intermittence of renewable sources. Therefore, an optimal solution is proposed to the resource management by enhancing the communication and coordination under a multi-agent system framework. An agent is a participant, for instance, the distributed renewable generator/energy storage system of the microgrid. With this multi-agent system, the distributed optimal solution only utilizes the local information, and interacts with the neighbouring agents. Thus, single-node congestion is avoided since the requirement for a central control centre is eliminated, and it is robust against single-link/node failures. The analysis will show that the proposed solution can solve the resource management problem in an initialization-free manner. Additionally, the proposed strategy can maintain the supply-demand balance under a time-varying supply-demand deviation. The simulation studies are carried out for IEEE 14-bus and 162-bus power systems to validate the effectiveness of the proposed distributed solution.

No abstract

Abstract-This paper investigates the optimal resource management in a microgrid under various operating conditions. A two-level optimization system is proposed for the distributed optimal resource management based on a multi-agent system framework. The proposed strategy generates a reference of the optimal power output at the top-level through local communication. This strategy only requires the information among neighbouring participants without a central control coordination, and simultaneously accomplishes resource optimization in a finite-time while maintaining the supply-demand balance. The bottom-level control is responsible for the reference tracking of each corresponding participant in a microgrid. The convergent rate of the proposed algorithm is compared with other consensus-based algorithms through simulation studies. Simulation results in the IEEE 14-bus system and an actual islanded system are also presented to demonstrate the overall effectiveness of the proposed strategy.

In this paper, to reduce required capacities for information exchanges in microgrids, a novel distributed eventbased algorithm is proposed for optimal energy management in a microgrid. Aiming at optimally scheduling the energy supplier's generation, an objective function is formulated to minimize the total cost of maintaining the supply-demand balance with considering power losses. Regarding each participant as an agent, the proposed algorithm is implemented in a distributed manner based on a multi-agent system framework. Therefore, each agent only exchanges information with its neighbours through a local network. Additionally, comparing with the periodical communication of sampled-data mechanisms, the adopted event-based scheme achieves satisfactory performance by using significantly less communication between participants. As a result, it further facilitates the development of networked microgrids. Furthermore, concerning the privacy of participants, the proposed algorithm is implemented without exposing owners' private preferences. The effectiveness of the proposed distributed algorithm is validated through several simulation studies.

Abstract-This paper considers the optimal charging problem of plug-in electric vehicles (PEVs) on demand side management. PEVs provide a promising alternative solution to reduction of environmental pollution and fuel emission. With a large number of PEVs connected to the grid, a well-designed charging coordination approach is needed to release the impacts on the power system. A distributed cooperative control strategy of PEVs is proposed to meet system interests while respecting each PEV's charging constraint. The proposed strategy is distributed, which only needs to be interacted with the neighbouring agents. Our analysis shows that the proposed strategy solves the optimal charging problem of PEVs in an initialization-free approach, which avoids any procedure for initialization during PEVs' charging process. Furthermore, the proposed strategy is robust to the time-varying available charging power and plug-and-play operations. The simulation studies validate the effectiveness of the proposed distributed strategy.

No abstract

No abstract