<p>This paper presents<strong> </strong>a terminal voltage control approach of a Switched Reluctance Generator (SRG) based wind turbine generating systems. The control process is employed using a closed loop stimulated by the error between the reference voltage and the generator output voltage due to load and wind speed variation. This error feeds the tuned Proportional Integral controller (PI).</p><p>Tuning of PI controller by conventional analysis methods is difficult by the existence of a significant non-linearity. A novel strategy method is presented here to determine optimum PI controller parameters of voltage control of SRG using Grasshopper Optimization Algorithm (GOA). This proposed approach is a simple and effective algorithm that is able to solve many optimization problems. The simplicity of algorithm provides high quality tuning of optimal PI controller parameters. The integral of time weighted squared error (ITSE) is used as the performance of the proposed GOA-PI controller. The effectiveness of the proposed strategy is tested with the three-phase 12/8 structure SRG. Outcomes indicate the supremacy of GOA over Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO) in terms of control performance measures.</p>

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Integrating uncertainties of the load demands and those associated with capacitor allocation in radial distribution feeders is the aim of the present paper. Modeling of the uncertainties accompanying the load parameters is important in relation to the problem of reactive power compensation in distribution systems using capacitors allocation. Interval mathematics provides a powerful tool for modeling uncertainties. The uncertainties related to load demand are modeled by solving the load flow using a developed interval backward/ forward sweep technique. The interval voltage outcomes are used in the governing equations of the capacitor allocation analysis. Interval distribution functions defining the real power losses and the voltage sensitivity are introduced to, sequentially, order the sensitive nodes that require compensation. A heuristic technique is formulated to determine the interval capacitor size, interval maximum cost saving, and the corresponding interval loss reduction. A significant improvement in the voltage profile is achieved using the proposed technique. Implementation of the technique is demonstrated using two realistic radial distribution feeders.