A photovoltaic (PV) system's output power fluctuates according to the weather conditions. Fluctuating PV power causes frequency deviations in the power utilities when the penetration is large. Usually, an energy storage system (ESS) is used to smooth the PV output power fluctuations and then the smoothed power is supplied to the utility. In this paper, a simple fuzzy-based frequency-control method is proposed for the PV generator in a PV-diesel hybrid system without the smoothing of PV output power fluctuations. By means of the proposed method, output power control of a PV generator considering the conditions of power utilities and the maximizing of energy capture are achieved. Here, fuzzy control is used to generate the PV output power command. This fuzzy control has average insolation, change of insolation, and frequency deviation as inputs. The proposed method is compared with a maximum power point tracking control-based method and with an ESS-based conventional control method. The numerical simulation results show that the proposed method is effective in providing frequency control and also delivers power near the maximum PV power level.

In recent years, introduction of an alternative energy source such as solar energy is expected. However, insolation is not constant and the output of a photovoltaic (PV) system is influenced by meteorological conditions. In order to predict the power output for PV systems as accurately as possible, an insolation estimation method is required. This paper proposes the power output forecasting of a PV system based on insolation forecasting at 24 hours ahead by using weather reported data, fuzzy theory, and neural network (NN). If the suitable training data is not selected, the training process of NN tends to be unstable. The proposed technique for application of NN is trained by power output data based on fuzzy theory and weather reported data. Since the fuzzy model determines the insolation forecast data, NN will train the power output smoothly. The validity of the proposed method is confirmed by comparing the forecasting abilities on the computer simulations.

A photovoltaic (PV) system's power output is not constant and fluctuates depending on weather conditions. Fluctuating power causes frequency deviations and reduction in reliability of the isolated power utility or microgrid when large output power from several PV systems is penetrated in the utility. In this paper, to overcome these problems, a simple coordinated control method for leveling the fluctuations of combined power output from multiple PV systems is proposed. The conflicting objective of output power leveling and acquisition power increase is achieved by means of the proposed method. Here, output power command is generated in two steps: central and local. Fuzzy reasoning is used to generate the central leveling output power command considering insolation, variance of insolation, and absolute average of frequency deviation. In local step, a simple coordination is maintained between central power command and local power commands by producing a common tuning factor. Power converters are used to achieve the same output power as local command power employing PI control law for each of the PV generation systems. The proposed method is compared with the method where a modified maximum power point tracking control is used for smoothing the short-term change in each of the PV system's output. Simulation results show that the proposed method is effective for leveling output power fluctuations and feasible to reduce the frequency deviations of the isolated power utility to maintain reliability.

Energy storage systems (ESSs) are essential in future power systems because they can improve power usage efficiency. In this paper, a novel coordinated control algorithm is proposed for distributed battery ESSs (BESSs). The neighboring BESSs of a simulation system are grouped and controlled by a main control center. The main control center sends charging or discharging operation signals to each BESS. The primary objective of the proposed coordinated control scheme is to mitigate voltage and frequency deviations. In order to verify the proposed algorithm, the BESSs are connected to a distribution system of the Korea Electric Power Corporation. The results are compared with those obtained using uncoordinated control scheme with on-load tap changer considering aspects of power quality (voltage and frequency variation). The simulation results show that the voltage and frequency deviations are reduced with the proposed coordinated control algorithm.

The increased penetration of distributed generation (DG), renewable energy utilization, and the introduction of the microgrid concept have changed the shape of conventional electric power networks. Most of the new power system networks are transforming into the DG model integrated with renewable and non-renewable energy resources by forming a microgrid. Islanding detection in DG systems is a challenging issue that causes several protection and safety problems. A microgrid operates in the grid-connected or stand-alone mode. In the grid-connected mode, the main utility network is responsible for a smooth operation in coordination with the protection and control units, while in the stand-alone mode, the microgrid operates as an independent power island that is electrically separated from the main utility network. Fast islanding detection is, therefore, necessary for efficient and reliable microgrid operations. Many islanding detection methods (IdMs) are proposed in the literature, and each of them claims better reliability and high accuracy. This study describes a comprehensive review of various IdMs in terms of their merits, viability, effectiveness, and feasibility. The IdMs are extensively analysed by providing a fair comparison from different aspects. Moreover, a fair analysis of a feasible and economical solution in view of the recent research trend is presented.

The lifespan of a battery in battery energy storage systems (BESSs) is affected by various factors such as the operating temperature of the battery, depth of discharge, and magnitudes of the charging/discharging currents supplied to or drawn from the battery. In this study, the optimal location and size of a BESS are found for voltage regulation in a distribution system while increasing the lifespan of the battery. Various factors that affect the lifespan of a battery are considered and modelled. The problem is formulated as a multi‐objective optimisation problem with two‐objective functions. The first objective function calculates the energy losses in the system, whereas the second objective function represents the total investment cost of the distributed generator (DG) and BESS installations. Wind and solar DGs with uncertainties in their output powers are also considered with the BESSs. An elitist non‐dominated sorting genetic algorithm‐II with a utopian point method is used to solve the optimisation problem. Furthermore, an IEEE 906 bus European low‐voltage test feeder and eight test cases are considered for this study. The results show reduced losses and cost, improvement in the voltage profile, and extended lifespan of the batteries.