|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|4968358||1365207||2017||5 صفحه PDF||سفارش دهید||دانلود کنید|
- Comparing the results from heuristic optimization algorithms requires appropriate metrics.
- Rough metrics are used very often in the power and energy area.
- A more significant metric based on first-order stochastic dominance is proposed.
- The effectiveness of this metric is shown for distribution system optimal reconfiguration.
In the recent research on power and energy system optimization, many deterministic and heuristic solvers have been proposed. Each proposal claims that the new solver is better than the previous ones on the basis of performance indicators, which are often limited to the best solution found or to simple statistics (mean, median, standard deviation). This paper introduces a new and more significant performance indicator based on the concept of first-order stochastic dominance. This indicator can generally compare the solutions of a given optimization problem for which the global optimum is not known. The optimal discrete distribution network reconfiguration for a real-scale system was taken as an example problem, to show the characteristics of the proposed indicator. The results obtained show the effectiveness of the proposed indicator to limit the acceptability of “better” solvers to the ones that actually exhibit enhanced performance with respect to incrementally improved benchmarks.
Journal: Sustainable Energy, Grids and Networks - Volume 9, March 2017, Pages 75-79