This paper presents the improvements of the hosting capacity of photovoltaics (PVs) and electric vehicles (EVs) in a stand-alone microgrid (MG) with an energy storage system (ESS) by consider-ing a model predictive control (MPC) based energy management system. The system is configured as an MG, including PVs, an ESS, a diesel generator (DG), and several loads with EVs. The DG is controlled to operate at rated power and the MPC algorithm is used in a stand-alone MG, which supplies the energy demanded for several loads with EVs. The hosting capacity of the load in-cluding the EV and PVs can be expanded through the ESS to the terminal node of the microgrid. In this case, the PVs and the load can be connected in excess of the capacity of the diesel genera-tor, and each bus in the feeder complies with the voltage range required by the grid. The effec-tiveness of the proposed algorithm to resolve the hosting capacity is demonstrated by numerical simulations.

Microgrids based on renewable energy sources are presently requires control functions to enhance of power quality in the distribution system. In order to maintain the power generation/consumption balance and necessary for stable functioning such as voltage and frequency of microgrid, the traditional power systems always utilize necessary control actions. However, the present practice requires the independent power producers and/or developers who want to build a micrgrid to meet the power quality requirements. Therefore, this paper proposes an innovative supervisory power quality control scheme of a grid-off microgrid, especially voltage and frequency control, at a given location that manipulates dynamically the active and reactive power from the power conversion systems with taking into account their operating states and limits.

In recent years, the energy industry has increased the proportion of renewable energy sources, which are sustainable and carbon-free. However, the increase in renewable energy sources has led to grid instability due to factors such as the intermittent power generation of renewable sources, forecasting inaccuracies, and the lack of metering for small-scale power sources. Various studies have been carried out to address these issues. Among these, research on Virtual Power Plants (VPP) has focused on integrating unmanaged renewable energy sources into a unified system to improve their visibility. This research is now being applied in the energy trading market. However, the purpose of VPP aggregators has been to maximize profits. As a result, they have not considered the impact on distribution networks and have bid all available distributed resources into the energy market. While this approach has increased the visibility of renewables, an additional method is needed to deal with the grid instability caused by the increase in renewables. Consequently, grid operators have tried to address these issues by diversifying the energy market. As regulatory method, they have introduced real-time energy markets, imbalance penalty fees, and limitations on the output of distributed energy resources (DERs), in addition to the existing day-ahead market. In response, this paper proposes an optimal scheduling method for VPP aggregators that adapts to the diversifying energy market and enhances the operational benefits of VPPs by using two Mixed-Integer Linear Programming (MILP) models. The validity of the proposed model and algorithm is verified through a case study analysis.

The introduction of electrical vehicle charging infrastructure including electric vehicle (EV) charger renewable energy resource at the secondary feeder in a distribution system has been increased as one of countermeasure for global environmental issues. However, the electric vehicle charging (EVC) infrastructure may act as the peak load in the distribution system, which can adversely impact on the voltage stability when the electric vehicle is quickly charged. Therefore, to keep within the limit capacity of a secondary feeder and allowable limit for the feeder voltage, this paper proposes a stabilization method by an energy storage system (ESS) control strategy at the secondary feeder to not exceed the upper limit or fall below the lower limit. In addition, this paper presents an estimation method to keep the proper standard value of the state of charge (SOC). From the simulation results, the voltage stabilization operation by the ESS should make the feeder voltages of the distribution system (secondary feeder) introduced EVC infrastructure keep better voltage conditions. In addition, the estimation method was able to keep the proper standard value confirming that the SOC of the ESS when it is in standby can be kept within the proper reference range. Therefore, it is confirmed that this strategy is an effective tool to solve the voltage problems by ESS.

With the intention of keep the customer voltage within a nominal voltage boundary (the South Korea voltage regulation in range of 220 V ± 6% for a single phase), the SVR (step voltage regulator) method in the primary feeder has been seriously systematized for the scheduled tap time delay (from a minimum of 120 s to a maximum of 900 s). The voltage must be compensated for the primary feeder during the tap delay time of SVR. However, when RES (renewable energy resource) is connected with the primary feeder, the customer voltage could exceed the nominal voltage boundary. Therefore, in order to keep the secondary feeder voltage within the nominal voltage boundary at all the time, this paper proposed a novel voltage control method in the primary feeder using coordinated controls between ESS (energy storage system) and SVR. Through the simulations based on PSCAD/EMTDC which is analysis tool of power system, it is confirmed that the proposed algorithm can effectively control the customer voltage within allowable limitation.

A programmable direct current (DC) power supply with Real-time Digital Simulator (RTDS)-based photovoltaic (PV) Power Hardware-In-the-Loop (PHIL) simulators has been used to improve the control algorithm and reliability of a PV inverter. This paper proposes a supervisory control algorithm for a PV PHIL simulator with a non-RTDS device that is an alternative solution to a high-cost PHIL simulator. However, when such a simulator with the conventional algorithm which is used in an RTDS is connected to a PV inverter, the output is in the transient state and it makes it impossible to evaluate the performance of the PV inverter. Therefore, the proposed algorithm controls the voltage and current target values according to constant voltage (CV) and constant current (CC) modes to overcome the limitation of the Computing Unit and DC power supply, and it also uses a multi-rate system to account for the characteristics of each component of the simulator. A mathematical model of a PV system, programmable DC power supply, isolated DC measurement device, and Computing Unit are integrated to form a real-time processing simulator. Performance tests are carried out with a commercial PV inverter and prove the superiority of this proposed algorithm against the conventional algorithm.