کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5483110 1522312 2017 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Short-term scheduling of hydro-based power plants considering application of heuristic algorithms: A comprehensive review
ترجمه فارسی عنوان
برنامه ریزی کوتاه مدت نیروگاه های برق آبی با استفاده از الگوریتم های اکتشافی: یک بررسی جامع
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
Optimal generation scheduling of hydro-based power units has a significant place in electric power systems, which considerably has been dealt with as a subject of investigations for several years. Hydrothermal system is introduced as an important hydro-based power generation system. The objective of short-term hydrothermal scheduling (STHS) problem is obtaining the power generation schedule of the available hydro and thermal power units, which aims to minimize total fuel cost of thermal plants during a determined time period. Many conventional optimization procedures are first introduced for solving STHS problem. Recently, heuristic and meta-heuristic optimization methods, which are defined as an experience-based procedure, are implemented for obtaining optimal solution of generation planning of hydrothermal systems. This paper provides a comprehensive review on the application of heuristic methods to obtain optimal generation scheduling of hydrothermal systems, which compares the implemented procedures from different points of view. Optimal solutions obtained by employment of multiple heuristic and meta-heuristic optimization methods for different test instances are demonstrated and the introduced methods are compared in terms of convergence speed, attained optimal solutions, and constraints. Future research trends are discussed, which can be introduced as the subject of studies in the area of STHS problem.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Renewable and Sustainable Energy Reviews - Volume 74, July 2017, Pages 116-129
نویسندگان
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