• Energy Research

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.

In this paper, the VVO (Volt/Var optimization) is proposed using simplified linear equations. For fast computation, the characteristics of voltage control devices in a distribution system are expressed as a simplified linear equation. The voltage control devices are classified according to the characteristics of voltage control and represented as the simplified linear equation. The estimated voltage of distribution networks is represented by the sum of the simplified linear equations for the voltage control devices using the superposition principle. The voltage variation by the reactive power of distributed generations (DGs) can be expressed as the matrix of reactance. The voltage variation of tap changing devices can be linearized into the control area factor. The voltage variation by capacitor banks can also be expressed as the matrix of reactance. The voltage equations expressed as simplified linear equations are formulated by quadratic programming (QP). The variables of voltage control devices are defined, and the objective function is formulated as the QP form. The constraints are set using operating voltage range of distribution networks and the control ranges of each voltage control device. In order to derive the optimal solution, mixed-integer quadratic programming (MIQP), which is a type of mixed-integer nonlinear programming (MINLP), is used. The optimal results and proposed method results are compared by using MATLAB simulation and are confirmed to be close to the optimal solution.

The voltage and reactive power control (Volt/VAR Control, VVC) in distribution networks has become a challenging issue with the increasing utilization of distributed generations (DGs). In this paper, a heuristic-based coordinated voltage control scheme that considers distribution voltage control devices, i.e., on-load tap changers (OLTC) and step voltage regulators (SVR), as well as reactive power control devices, i.e., DGs, are proposed. Conventional voltage control methods using non-linear node voltage equations require complex computation. In this paper, the formulation of simplified node voltage equations accounting for changes in tap position of distribution voltage control devices and reactive power changes of reactive power control devices are presented. A heuristic coordinated voltage control scheme using the proposed simplified node voltage equations is proposed. A coordinated voltage control scheme to achieve voltage control for nominal voltage and conservative voltage reduction (CVR) is presented. The results of the proposed schemes are compared with the results from the quadratic optimization method to confirm that the proposed schemes yields suitably similar results. Furthermore, a tap scheduling method is proposed to reduce the number of tap changes while controlling network voltage. The tap position is readjusted using a voltage control performance index (PI). Simulation results confirm that when using this method the number of tap changes is reduced. The proposed scheme not only produces reasonable performance in terms of control voltage of networks but also reduces the number of tap changes made by OLTC. The proposed control method is an alternative candidate for a system to be applied to practical distribution networks due to its simplified calculations and robust performance.

This paper proposes a fault location method for power distribution networks using phasor measurement units (PMU) and short circuit analysis. In order to improve the problems of the existing studies, we focused on several approaches as follows. First, in order to minimize the number of PMU installations, a fault location estimation of lateral feeders through short circuit analysis was presented. Second, unbalanced faults and impacts of photovoltaic (PV) were considered. The proposed method consists of two stages. In Stage 1, the fault location was estimated for the main feeder using PMU installed at the start and end points of the main feeder. Symmetrical components of voltage and current variation were calculated by considering the impact of PVs interconnected to the lateral feeders. If the result of Stage 1 indicated a connection section of lateral feeder on the main feeder, Stage 2 would be performed. In Stage 2, the fault location was estimated for the lateral feeder by comparing the results of the short circuit analysis and measurements of PMUs. The short circuit analysis was based on an unbalanced power flow that considered dynamic characteristics of the PV inverter. The proposed method was verified through various fault situations in a test system. For the applicability of the proposed algorithm to the actual system, a noise test was also performed.

In this study, we propose a voltage estimation method for the radial distribution network with distributed generators (DGs) using high-precision measurements (HPMs). The proposed method uses the section loads center for voltage estimation because individual loads are not measured in the distribution system. The bus voltage was estimated through correction of the section load center by using an HPM at the end of the main feeder. The correction parameter of the section load center was calculated by comparing the initial voltage estimates and the measurements of the HPMs. After that, the voltage of the main feeder was re-estimated. Finally, the bus voltage in the lateral feeder was estimated based on the voltage estimates in the main feeder and the current measurements in the lateral feeder. The accuracy of the proposed algorithm was verified through case studies by using test systems implemented in MATLAB, Simulink, and Python environments. In order to verify the utilization of the proposed method to the practical system, a test with injection of approximately 5% of normally distributed random noise was performed. Through the results of the case studies, when an HPM is installed at the end of the main feeder, it demonstrated that the voltage estimation accuracy can be greatly improved by the proposed method. Compared with the existing methods, the proposed method was less affected by PV and showed robustness to measurement noise.

As the numbers of microgrids (MGs) and prosumers are increasing, many research efforts are proposing various power sharing schemes for multiple MGs (MMGs). Power sharing between MMGs can reduce the investment and operating costs of MGs. However, since MGs exchange power through distribution lines, this may have an adverse effect on the utility, such as an increase in peak demand, and cause local overcurrent issues. Therefore, this paper proposes a power sharing scheme that is beneficial to both MGs and the utility. This research assumes that in an MG, the energy storage system (ESS) is the major controllable resource. In the proposed power sharing scheme, an MG that sends power should discharge at least as much power from the ESS as the power it sends to other MGs, in order to actually decrease the total system demand. With these assumptions, methods for determining the power sharing schedule are proposed. Firstly, a mixed integer linear programming (MILP)-based centralized approach is proposed. Although this can provide the optimal power sharing solution, in practice, this method is very difficult to apply, due to the large calculation burden. To overcome the significant calculation burden of the centralized optimization method, a new method for determining the power sharing schedule is proposed. In this approach, the amount of power sharing is assumed to be a multiple of a unit amount, and the final power sharing schedule is determined by iteratively finding the best MG pair that exchange this unit amount. Simulation with a five MG scenario is used to test the proposed power sharing scheme and the scheduling algorithm in terms of a reduction in the operating cost of MGs, the peak demand of utility, and the calculation burden. In addition, the interrelationship between power sharing and the system loss is analyzed when MGs exchange power through the utility network.

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.

As the interconnection of renewable-energy-based distributed generations (DGs) to the distribution system increases, the local and temporary voltage and current problems, which are difficult to resolve with the existing operation method, are becoming serious. In this study, we propose a short-term operational method that can effectively resolve voltage and current violations caused by instantaneous output fluctuations of DGs in a system with a high hosting capacity of renewable energy sources. To achieve the objectives, a modified heuristic network reconfiguration method, and a method determining the maximum power output limit of individual DGs are proposed. We propose a cooperative method for controlling the power output fluctuations of renewable-energy-based DGs, which includes voltage control, network reconfiguration, and power curtailment. The proposed algorithm was verified through case studies by using a test system implemented in MATLAB environments. It can effectively resolve violations caused by DGs while minimizing the number of switching operations and power curtailment. The proposed method is an appropriate operation method to be applied to the real system as it can cope with the instantaneous output fluctuation of DGs, which was not dealt with in the existing operation method.