Microgrids can be considered as controllable units from the utility point of view because the entities of microgrids such as distributed energy resources and controllable loads can effectively control the amount of power consumption or generation. Therefore, microgrids can make various contracts with utility companies such as demand response program or ancillary services. Another advantage of microgrids is to integrate renewable energy resources to low-voltage distribution networks. Battery energy storage systems (BESSs) can effectively compensate the intermittent output of renewable energy resources. This paper presents intelligent control schemes for BESSs and autonomous energy management schemes of microgrids based on the concept of multi-agent systems. The proposed control scheme consists of two layers of decision-making procedures. In the bottom layer, intelligent agents decide the optimal operation strategies of individual microgrid entities such as BESSs, backup generators and loads. In the upper layer, the central microgrid coordinator (MGCC) coordinates multiple agents so that the overall microgrid can match the load reduction requested by the grid operator. The proposed control scheme is applied to Korea Power Exchange's Intelligent Demand Response Program.

Microgrids are autonomous low-voltage power distribution systems that contain multiple distributed energy resources (DERs) and smart loads that can provide power system operation flexibility. To effectively control and coordinate multiple DERs and loads of microgrids, this paper proposes a distributed intelligent management system that employs a multi-agent-based control system so that delicate decision-making functions can be distributed to local intelligent agents. This paper presents the development of a hardware-in-the-loop simulation (HILS) system for distributed intelligent management system for microgrids and its promising application to an emergency demand response program. In the developed HILS system, intelligent agents are developed using microcontrollers and ZigBee wireless communication technology. Power system dynamic models are implemented in real-time simulation environments using the Opal-RT system. This paper presents key features of the data communication and management schemes based on multi-agent concepts. The performance of the developed system is tested for emergency demand response program applications.

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In the future, the individual entities of microgrids such as distributed generators and smart loads may need to determine their power generation or consumption in more economic ways. Intelligent agents can help the decision-making procedure of the entities by intelligent algorithms and state-of-the-art communication with central controller and other local agents. This paper presents the development of atable-top microgrid control system using multi-agent systems and also the demonstration of demand response programs during power shortage. In our table-top system, agents are implemented using microcontrollers and Zigbee wireless communication technology is applied for efficient data communication in the multi-agent system. The power system models of distributed generators and loads are implemented in the real-time simulator using Opal-RT system. The whole test system that includes real-time system simulation and agent hardware is implemented in the hardware-in-the-loop simulation framework. The performance of the developed system is tested for emergency demand response cases

Grid codes in many countries require low-voltage ride-through (LVRT) capability to maintain power system stability and reliability during grid fault conditions. To meet the LVRT requirement, wind power systems must stay connected to the grid and also supply reactive currents to the grid to support the recovery from fault voltages. This paper presents a new fault detection method and inverter control scheme to improve the LVRT capability for full-scale permanent magnet synchronous generator (PMSG) wind power systems. Fast fault detection can help the wind power systems maintain the DC-link voltage in a safe region. The proposed fault detection method is based on on-line adaptive parameter estimation. The performance of the proposed method is verified in comparison to the conventional voltage measurement method defined in the IEC 61400-21 standard.