Optimal operation of the battery energy storage system (BESS) is very important to reduce the running cost of a microgrid. Rolling horizon-based scheduling, which updates the optimal decision based on the latest information, is widely applied to microgrid operation. In this paper, the optimal scheduling of a microgrid, considering the energy cost, demand charge, and the battery wear-cost, is formulated as a mixed integer linear programming (MILP) problem. This paper also deals with two practical and important issues when applying the rolling-horizon strategy to BESS scheduling. First, to mitigate the high dependency of the load forecast on the latest information, a confidence weight parameter method is proposed. Second, a new target state of charge (SOC) assignment method is proposed to avoid the depletion of BESS and to reduce the wear-cost of the battery. In addition to the optimal scheduling, a novel real-time control scheme is proposed to mitigate the effect of the forecast uncertainty. The performance of the proposed methods is tested with data measured from a campus microgrid.

Maximum Power Point Tracking (MPPPT) techniques are employed in PV systems to make full utilization of PV array output power which depends on solar irradiation and temperature. Recently, many MPPT algorithms and control schemes of PV system have been proposed, but different control methods and different PID controller parameters lead to different output efficiency and dynamic response. Therefore, in this paper, a PSCAD/EMTDC user defined module of the solar array is established to easily simulate its inherent characteristics with the basic specification data. Moreover, we also compare the advantages and weakness of the existing MPPT control methods by simulations to give a reference to the Grid-Connected Photovoltaic System (GCPS) designers.

Direct Current (DC) microgrids are expected to become larger due to the rapid growth of DC energy sources and power loads. As the scale of the system expends, the importance of voltage control will be increased to operate power systems stably. Many studies have been performed on voltage control methods in a DC microgrid, but most of them focused only on a small scale microgrid, such as a building microgrid. Therefore, a new control method is needed for a middle or large scale DC microgrid. This paper analyzes voltage drop problems in a large DC microgrid and proposes a cooperative voltage control scheme with a distributed generator (DG) and a grid connected converter (GCC). For the voltage control with DGs, their location and capacity should be considered for economic operation in the systems. Accordingly, an optimal DG allocation algorithm is proposed to minimize the capacity of a DG for voltage control in DC microgrids. The proposed methods are verified with typical load types by a simulation using MATLAB and PSCAD/EMTDC.

Since the penetration level of wind energy is continuously increasing, the negative impact caused by the fluctuation of wind power output needs to be carefully managed. This paper proposes a novel real-time coordinated control algorithm based on a wavelet transform to mitigate both short-term and long-term fluctuations by using a hybrid energy storage system (HESS). The short-term fluctuation is eliminated by using an electric double-layer capacitor (EDLC), while the wind-HESS system output is kept constant during each 10-min period by a Ni-MH battery (NB). State-of-charge (SOC) control strategies for both EDLC and NB are proposed to maintain the SOC level of storage within safe operating limits. A ramp rate limitation (RRL) requirement is also considered in the proposed algorithm. The effectiveness of the proposed algorithm has been tested by using real time simulation. The simulation model of the wind-HESS system is developed in the real-time digital simulator (RTDS)/RSCAD environment. The proposed algorithm is also implemented as a user defined model of the RSCAD. The simulation results demonstrate that the HESS with the proposed control algorithm can indeed assist in dealing with the variation of wind power generation. Moreover, the proposed method shows better performance in smoothing out the fluctuation and managing the SOC of battery and EDLC than the simple moving average (SMA) based method.

The optimal state of charge (SoC) balancing control for series-connected lithium-ion battery cells is presented in this paper. A modified SoC balancing circuit for two adjacent cells, based on the principle of a bidirectional Cuk converter, is proposed. The optimal SoC balancing problem is established to minimize the SoC differences of cells and the energy loss subject to constraints of the normal SoC operating range, the balancing current, and current of cells. This optimization problem is solved using the sequential quadratic programming algorithm to determine the optimal duties of PWM signals applied to the SoC balancing circuits. An algorithm for the selection of the initial points for the optimal problem-solving process is proposed. It is applied in cases where the cost function has no decreasing part. Experimental tests are conducted for seven series-connected Samsung cells. The optimal SoC balancing control and SoC estimation algorithms are coded in MATLAB and embedded in LabVIEW to control the SoC balancing in real time. The test results show that the differences between the SoCs of cells converges to the desired range using the proposed optimal SoC balancing control strategy.

This paper proposes an adaptive protection method using sensitivity analysis that examines the effect of changed network topologies (CNTs) on the operation time of protective devices (PDs) for a base network topology (BNT) in a distribution network. In this study, BNT refers to the topological structure of the distribution network maintained over the long-term, whereas CNT is the changed structure maintained for a relatively short term for field workings, fault restoration, or real-time reconfiguration. The main purpose is to consider the PD's operating speed and the number of controls for changing the settings and to calculate the optimal setting values for two terms while including the CNT in the BNT over a long duration. For this purpose, we used two approaches: First, a sensitivity index, defined as the increase in the operation time of the PD for the BNT when each CNT is included in the BNT, is used to determine the CNT’s inclusion priority. Second, an objective function (OF) is used to evaluate the maximum acceptable number of CNTs based on the priorities derived from the sensitivity analysis. This OF aims to minimize the weighted sum of the average operation time and the number of setting changes for the PDs. Case studies on the test systems were conducted, and the effectiveness of the proposed method was verified by comparing it with existing adaptive protection methods.