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.

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.

Battery energy storage systems (BESS) can alleviate the unstable effects of intermittent renewable energy systems, such as solar and wind power systems. In addition, a BESS can level the load of the existing utility grid. The penetration rate of this type of system is expected to increase in the future power grid, i.e., the microgrid. In this paper, a modeling technique is proposed that allows users to customize the photovoltaic (PV) battery hybrid systems. A dynamic power system computer-aided design/electromagnetic transients including DC system (PSCAD/EMTDC) model of a PV battery hybrid system is presented in this paper. Dynamic modeling of PV arrays, BESS, maximum power point tracking (MPPT) algorithms, and bidirectional converters are provided as well. The PV model, battery model, and MPPT control model are designed using a user-defined model (UDM) for custom electromagnetic transient simulation. A control method for stabilizing the output of the PV battery hybrid system is proposed. Finally, a PSCAD/EMTDC simulation is conducted to verify the effectiveness of the operating algorithm.

This paper describes a method to estimate conservation voltage reduction (CVR) factors using data measured in power distribution systems. A direct method is proposed to estimate CVR factors using only data measured at the moment of the transformer tap change. The mean absolute deviation (MAD) direct method is proposed to consider direct methods and load variations. The proposed methods do not necessitate intentional tap changes for testing purposes. Instead, the voltage and load changes that occur when the tap changes, for voltage regulation purposes, are measured and utilized in the CVR factor calculation. The proposed methods were tested using data obtained from the Korea Electric Power Corporation (KEPCO) system, and the results revealed that CVR factors for both active power and reactive power could be estimated using data measured in power distribution systems. Results of the CVR factor estimation for the active power revealed that the highest CVR factors occurred in winter, during which a large quantity of heating loads exist. In addition, the estimated CVR factors for the reactive power were higher than the estimated CVR factors for the active power because reactive power is more sensitive to voltage changes.

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.

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.