Power distribution systems should meet demands such as high reliability, efficiency, and penetration of renewable energy generators (REGs) in a smart grid. In general, power distribution systems are radial in nature. One-way power flow is the advantage of a radial system. However, the introduction of REGs causes bidirectional power flow. Furthermore, there are limits to improvements in reliability and efficiency in a radial system. Therefore, the upgrading of primary feeders from a radial to a loop configuration has been considered in the Korea Smart Distribution Project. An advanced power distribution system (APDS), in which primary feeders operate in a loop configuration, has been explored in this paper. First, the design scheme of a conventional power distribution system configuration that adopts distribution automation is introduced. Subsequently, an upgrading scheme of loop configuration using normally opened tie switches and a tie switch selection algorithm for loss minimization are described. Finally, the advantages of the upgraded configuration are reported through case studies. It is observed that the APDS configuration can integrate more REGs from the viewpoint of voltage regulation. An advanced distribution system allowing greater use of REGs will be a major contribution to smart grid implementation.

We propose an algorithm to set the parameters of volt–var curves to improve the performance of distributed generation. Specifically, we optimally set the volt–var curves of the smart inverter for proper control of the distributed generation output. To improve the overall distribution system performance, we consider the minimization of voltage deviation, system loss, and peak of reactive power in an objective function, thereby providing optimal volt–var curve parameters. The proposed algorithm overcomes various limitations of existing studies. First, we use distribution system factors in a multiobjective optimization function to adjust volt–var curve parameters that deviate from the default settings. Second, we consider the service transformers that affect the system voltage according to the photovoltaic generation output in the test model during optimization. Third, we analyze the system improvement according to the number of parameters to be optimized. Fourth, we analyze the implementation of the optimized volt–var curve according to the practical periods when the smart inverter settings can be updated. Fifth, we evaluate different suitable volt–var curves for multiple photovoltaic generators grouped using clustering. Using the proposed algorithm, the distribution system operator can set the optimal volt–var curve according to the system conditions and requirements. We conducted simulations of the proposed method using OpenDSS, a quasistatic time-series simulation, on a test model reflecting the characteristics of a South Korean distribution system. The simulation results confirm that the overall system performance increases when the optimal volt–var curve settings obtained from the proposed algorithm are used.

This paper proposes a method to improve the performance of a distribution system by optimizing volt–var function of a smart inverter to alleviate the voltage deviation problem due to distributed generation connection. In order to minimize voltage deviation and line losses which represent the performance of a distribution system, this paper proposes an algorithm that optimally sets the parameters of the volt–var function. In the process of optimizing the parameters of the volt–var function, the algorithm proposed in this paper considers minimizing the contribution of the reactive power in order not to affect the output of the distributed generation. In order to apply to the field, the distribution system in South Korea considering the configuration and operation regulation was selected as a test model for algorithm verification. As a result, the system performance was successfully improved by optimally setting the volt–var function of the smart inverter which is an effective way to solve the over-voltage problem caused by distributed generation connection. This paper verified the proposed method through OpenDSS, a quasi-static time-series simulation, for the test model considering the characteristics of the distribution system in South Korea.

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.

Losses in energy storage systems (ESSs) are considered operational costs and it is critical to improve efficiency in order to expand their use. We proposed a method of improving efficiency through the operation algorithm of an ESS, consisting of multiple energy storage units (ESUs). Since the ESS used for frequency adjustment maintains a fast response characteristics, we have created a lookup table of efficient ESU operating combinations using genetic algorithms in advance to maintain a fast response time. In addition, the charge/discharge energy balance between the plurality of ESUs is maintained, and the deterioration is prevented from being concentrated in some ESUs. The proposed algorithm was reviewed based on three case studies. The first case study examined whether the lookup table obtained using the genetic algorithm well identified the optimal solution. The second compared the system that optimally distributes the output to ESUs to achieve ESS efficiency for frequency regulation with the system that uniformly distributes the output to ESUs. The third analyzed the impact of efficiency enhancement on the operation of an ESS for frequency regulation through a one-month simulation. The findings confirmed that when the entire system output is optimally allocated to the ESUs, the system’s economic efficiency can be improved by reducing the loss while maintaining the accumulative charge/discharge balance.