The microgrid and demand response (DR) are important technologies for future power grids. Among the variety of microgrid operations, the multi-agent system (MAS) has attracted considerable attention. In a microgrid with MAS, the agents installed on the microgrid components operate optimally by communicating with each other. This paper proposes an operation algorithm for the individual agents of a test microgrid that consists of a battery energy storage system (BESS) and an intelligent load. A microgrid central controller to manage the microgrid can exchange information with each agent. The BESS agent performs scheduling for maximum benefit in response to the electricity price and BESS state of charge (SOC) through a fuzzy system. The intelligent load agent assumes that the industrial load performs scheduling for maximum benefit by calculating the hourly production cost. The agent operation algorithm includes a scheduling algorithm using day-ahead pricing in the DR program and a real-time operation algorithm for emergency situations using emergency demand response (EDR). The proposed algorithm and operation strategy were implemented both by a hardware-in-the-loop simulation test using OPAL-RT and an actual hardware test by connecting a new distribution simulator.

This letter proposes a new scheme of smooth operation transition for the stand-alone power system which is composed of engine generator and battery energy storage system (BESS) with photo voltaic panels. The proposed scheme offers smooth operation transition of BESS controller from the current control to the voltage control and vice versa. The feasibility of proposed scheme was verified through experiments with a scaled prototype.

This paper proposes a half-bridge voltage balancer with a new controller for bipolar DC distribution systems. The proposed control scheme consists of two cascaded Proportional Integral (PI) controls rather than one PI control for balancing the pole voltage. In order to confirm the excellence of voltage balancing performance, a typical bipolar DC distribution system including a half-bridge voltage balancer with proposed controller was analyzed by computer simulations. Experiments with a scaled prototype were also carried out to confirm the simulation results. The half-bridge voltage balancer with proposed controller shows better performance than the half-bridge voltage balancer with one PI control for balancing the pole voltage.

This paper proposes a new DC output voltage control for a battery energy storage system (BESS) with a lithium-ion battery based on the state of charge (SoC). The proposed control scheme was verified through computer simulations for a typical stand-alone DC microgrid, which consists of a BESS, photovoltaic (PV) panel, engine generator (EG), and DC load. A scaled hardware prototype for a stand-alone DC microgrid was set up in the lab, in which the proposed control scheme was loaded in a DSP controller. The experimental results were compared with the simulation results for performance verification. The proposed control scheme provides relatively lower variation of the DC grid voltage than the conventional droop control.

This paper presents a neural network (NN) torque observer that is used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator. Therefore, the response of PMSM (permanent magnet synchronous machine) follows that of the nominal plant. The load torque compensation method is composed of a neural deadbeat observer. To reduce of the noise effect, the post-filter, which is implemented by MA process, is proposed. The parameter compensator with RLSM (recursive least square method) parameter estimator is suggested to increase the performance of the load torque observer and main controller. The proposed estimator is combined with a high performance neural torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation and experiment, are shown in this paper