Abstract
Mean-variance mapping optimization (MVMO) is an emerging metaheuristic optimization algorithm, whose evolutionary mechanism performs within a normalized search space. The most remarkable aspect of this mechanism resides in the application of a special mapping function to generate new values of the optimization variables based on their statistical significance throughout the search process. This paper concerns with the feasibility of the MVMO to tackle the problem of online optimal reactive power management in near-shore wind power plants. The main challenges reside in the restricted computing budget and mix-integer nature of the problem. To this aim, MVMO is configured to evolve a single solution throughout the search process, and a new mapping function is proposed to improve the global search capability. Numerical tests on a benchmark system proposed by the IEEE Working Group on Modern Heuristic Optimization as well as a real world wind power plant demonstrate the effectiveness of MVMO.
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