A Genetic Based Algorithm for Short-Term Thermal Generating Unit Commitment.(Dept.E)
نویسندگان
چکیده
منابع مشابه
Short Term Unit-Commitment Using Genetic Algorithms
Unit commitment is a complex decision-making process because of multiple constraints which must not be violated while nding the optimal or a near-optimal commitment schedule. This paper discusses the application of genetic algorithms for determining short term commitment order of thermal units in power generation. The objective of the optimal commitment is to determine the on/oo states of the u...
متن کاملShort-term Price-based Unit Commitment of Hydrothermal GenCos: A Pre-emptive Goal Programming Approach
The solution of single-objective unit commitment problems for generation companies participating in deregulated markets may not directly be implementable mainly because of neglecting some conflicting secondary objectives arising from policy-making at internal/external environment. Benefiting an efficient multi-objective approach to improve the applicability of price-based unit commitment soluti...
متن کاملA Genetic Algorithm for Choice-Based Network Revenue Management
In recent years, enriching traditional revenue management models by considering the customer choice behavior has been a main challenge for researchers. The terminology for the airline application is used as representative of the problem. A popular and an efficient model considering these behaviors is choice-based deterministic linear programming (CDLP). This model assumes that each customer bel...
متن کاملA Genetic-Algorithm Based Approach For Generating Fuzzy Singleton Models
Methods for generating fuzzy singleton models from input-output data have been proposed by many authors. This paper introduces a genetic algorithm (GA) based method to generate a fuzzy singleton model taking into account all the necessary constraints to guarantee an analytically inverted representation of the process dynamics which may be used as a fuzzy controller in Internal Model Control (IM...
متن کاملmachine learning for predictive management: short and long term prediction of phytoplankton biomass using genetic algorithm based recurrent neural networks
in the regulated nakdong river, algal proliferations are annually observed in some seasons, with cyanobacteria (microcystis aeruginosa) appearing in summer and diatom blooms (stephanodiscus hantzschii) in winter. this study aims to develop two ecological models forecasting future chlorophyll a at two time-steps (one-week and one-year forecasts), using recurrent neural networks tuned by genetic...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: MEJ. Mansoura Engineering Journal
سال: 2020
ISSN: 2735-4202
DOI: 10.21608/bfemu.2020.131358