In power systems, reliability evaluations mainly depend on the precise forecasting of the reliability parameters of the internal components. Nonetheless, the procedure of calculating the reliability parameters such as failure rate and repair rate parameters is based on the failure statistics and measurements which can cause much inherent uncertainty and thus affecting the reliability indices of the system. Therefore, the main purpose of this work is to suggest a sufficient and easy-implemented approach based on scenario production to capture the uncertainty of the reliability parameters including the failure rate and repair rate variables. Here, the scenario generation process is constructed using the roulette wheel mechanism along with the probability density function of the random variables. Then, the proposed scenario based approach makes use of a scenario reduction mechanism to avoid high computational burden. This aspect of the proposed stochastic framework makes it useful for the optimization applications which require iterative analysis. In order to see the feasibility and satisfying performance of the proposed framework, an IEEE standard test system is used as the case study.
Economic dispatch (ED) problem is a significant and precious strategy in the power engineering to preserve the balance between the load and generation in an economic way. The practical ED incorporates a non-convex objective function with several equality and inequality nonlinear constraints. As a result, solving the practical ED requires a powerful optimizer to reach the most economic dispatch solution. This paper suggests a newly introduced algorithm called Krill Herd (KH) to solve the practical ED problem considering the valve-loading effects, prohibited operating zone, spinning reserve and multi-fuel option, optimally. Also, a new modification method based on the Levy Flight movement is suggested to increase the convergence of the KH algorithm. The suggested algorithm is applied to two small size and one large size test system to demonstrate its high search ability.
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