In recent years, distributed generation, as clean natural energy generation and cogeneration system of high thermal efficiency, has increased due to the problems of global warming and exhaustion of fossil fuels. Many of the distributed generations are set up in the vicinity of the customer, with the advantage that this decreases transmission losses. However, output power generated from natural energy, such as wind power, photovoltaics, etc., which is distributed generation, is influenced by meteorological conditions. Therefore, when the distributed generation increases by conventional control techniques, it is expected that the voltage change of each node becomes a problem. Proposed in this paper is the optimal control of distribution voltage with coordination of distributed installations, such as the load ratio control transformer, step voltage regulator (SVR), shunt capacitor, shunt reactor, and static var compensator. In this research, SVR is assumed to be a model with tap changing where the signal is received from a central control unit. Moreover, the communication infrastructure in the supply of a distribution system is assumed to be widespread. The genetic algorithm is used to determine the operation of this control. In order to confirm the validity of the proposed method, simulations are carried out for a distribution network model with distributed generation (photovoltaic generation).

This paper presents an output power smoothing method by a simple coordinated control of DC-link voltage and pitch angle of a wind energy conversion system (WECS) with a permanent magnet synchronous generator (PMSG). The WECS adopts an AC-DC-AC converter system with voltage-source converters (VSC). The DC-link voltage command is determined according to output power fluctuations of the PMSG. The output power fluctuationsin low- and high-frequency domains are smoothed by the pitch angle control of the WECS, and the DC-link voltage control, respectively. By using the proposed method, the wind turbine blade stress is mitigated as the pitch action in high-frequency domain is reduced. In addition, the DC-link capacitor size is reduced without the charge/discharge action in low-frequency domain. A chopper circuit is used in the DC-link circuit for stable operation of the WECS under-line fault. Effectiveness of the proposed method is verified by the numerical simulations.

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.

Recently, smart grids are attracting attention. Already, a smart grid based on an AC grid is proposed. However, no study on research is presented or published on a smart grid based on a dc grid. This paper presents an ac/dc hybrid smart power system. The proposed system has advantages of both dc and ac grids. The proposed power system consists of a wind generator and several controllable loads. The controllable loads have different capacities. Therefore, by applying power consumption control with the droop characteristic, the dc bus voltage is maintained within the acceptable range. As controllable loads, electric water heater and electric vehicle are assumed. Effectiveness of the proposed method is verified by numerical simulation results.