Renewable energy resource policies are being promoted to solve global resource depletion and environmental problems. Accordingly, as the connection between renewable energy resources and the distribution system has increased, various problems such as degradation in the quality of the power produced and voltage fluctuations have occurred. In this study, to solve the voltage problem, we propose a decentralized real-time volt/var control of the distributed generations (DGs) in a distribution system. The proposed control scheme aims to maintain the voltage for a point of common coupling (PCC) within a specified range, and the proposed control is applied in two stages. The proposed control scheme compensates for the disadvantages of a conventional control scheme and shows a new control structure. The proposed control scheme was applied to the test distribution system using MATLAB and was verified to be more effective than the conventional control scheme.
Photovoltaic (PV)–battery hybrid systems, which are composed of PV arrays, batteries, and bidirectional inverters, can level the loads of traditional utility grids. Their objective is to supply predetermined active and reactive power to the power grid. This paper presents an operation method for PV–battery hybrid systems by estimating PV generation. Using the PV installation information, the maximum PV generation on a clear day was predicted and compared with historical data. The PV generation was estimated using historical data from 2007 to 2010. The method aims to reduce the peak load of the power system using the estimated load and PV generation of the next day. With the given weather information and load pattern for the next day, the charge and discharge set points of the battery can be determined by considering the initial SoC (State of Charge) and capacity of the battery. To compensate for the estimation error of the load and PV output, an operational margin was considered. This method can maximize system operation efficiency by fully utilizing the battery. The effectiveness of the operation method was validated through simulation studies. It was confirmed that the peak load could be reduced by 30% using the proposed algorithm.
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