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This paper proposes an optimal voltage regulation scheme (OVRS) for distribution systems with rich photovoltaic (PV). Various regulation devices are optimally controlled in a coordinated manner: PV inverter, D-STATCOM, step voltage regulator (SVR), and on-load-tap-changer (OLTC). A data structure algorithm is proposed to split the distribution system into layered zones considering the radial structure of the system. The solution process of the proposed scheme is accomplished by a meta-heuristic optimizer. OVRS addresses the voltage violations while yielding a coordinated operation of the various control devices. The proposed OVRS involves three control levels to completely prevent voltage violations. In the first control level, the PV inverter and D-STATCOM mitigate rapidly the local voltage deviation through injecting/absorbing optimized reactive power. The second control level is a decentralized-based control scheme that utilizes the voltage control devices in each zone to handle the voltage violations if any. For each zone, the control devices in the upper-stream zones (parent zones) are managed by the third control level to ensure cooperative control actions. The simulation results on the 119-bus distribution system, with clear, low fluctuation, and high fluctuation of solar radiation profiles, demonstrate the effectiveness of the proposed OVRS. [ABSTRACT FROM AUTHOR]

Although the wind farms based on squirrel cage induction generators (SCIG) is cheaper than the wind farms based on doubly fed induction generators (DFIG), it is always in desperate need for reactive power compensation. Nevertheless, the wind farms based on DFIG are expensive compared with the SCIG wind farm, it features by its ability to control the active power independent of reactive power. However, combined wind farm (CWF) has been developed to collect the benefits of SCIG and DFIG wind turbines in the same wind farm. In this article, artificial neural network (ANN) is used to evaluate gain parameters of static synchronous compensator (STATCOM) in order to improve the stability performance of CWF. The impact of tuned STATCOM on the performance of CWF during gust wind speed and during three-phase fault is comprehensively investigated. The performance of CWF with STATCOM tuned by ANN is compared with its performance when the STATCOM tuned by the multiobjective genetic algorithm (MOGA) and whale optimization algorithm (WOA). The results show that the performance of CWF can be enhanced using STATCOM tuned by ANN more than MOGA and WOA. [ABSTRACT FROM AUTHOR]