scholarly journals Analysis and Comparison for the Unit Commitment Problem in a Large-Scale Power System by Using Three Meta-Heuristic Algorithms

2017 ◽  
Vol 141 ◽  
pp. 423-427 ◽  
Author(s):  
Yuan-Kang Wu ◽  
Hong-Yi Chang ◽  
Shih Ming Chang
Keyword(s):  
Power System ◽  
Large Scale ◽  
Unit Commitment ◽  
Heuristic Algorithms ◽  
Unit Commitment Problem ◽  
Commitment Problem

scholarly journals Practical Robust Optimization Method for Unit Commitment of a System with Integrated Wind Resource

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Yuanchao Yang
Keyword(s):  
Power System ◽  
Large Scale ◽  
Unit Commitment ◽  
Optimization Method ◽  
Northwest China ◽  
Mixed Integer ◽  
Problem Solution ◽  
Unit Commitment Problem ◽  
Solution Approach ◽  
Commitment Problem

Unit commitment, one of the significant tasks in power system operations, faces new challenges as the system uncertainty increases dramatically due to the integration of time-varying resources, such as wind. To address these challenges, we propose the formulation and solution of a generalized unit commitment problem for a system with integrated wind resources. Given the prespecified interval information acquired from real central wind forecasting system for uncertainty representation of nodal wind injections with their correlation information, the proposed unit commitment problem solution is computationally tractable and robust against all uncertain wind power injection realizations. We provide a solution approach to tackle this problem with complex mathematical basics and illustrate the capabilities of the proposed mixed integer solution approach on the large-scale power system of the Northwest China Grid. The numerical results demonstrate that the approach is realistic and not overly conservative in terms of the resulting dispatch cost outcomes.

scholarly journals A meliorated Harris Hawks optimizer for combinatorial unit commitment problem with photovoltaic applications

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ayani Nandi ◽  
Vikram Kumar Kamboj
Keyword(s):  
Power Generation ◽  
Power System ◽  
Electric Power ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Electric Power System ◽  
Unit Commitment Problem ◽  
Spinning Reserve ◽  
Commitment Problem ◽  
Sine Cosine Algorithm

AbstractConventional unit commitment problem (UCP) consists of thermal generating units and its participation schedule, which is a stimulating and significant responsibility of assigning produced electricity among the committed generating units matter to frequent limitations over a scheduled period view to achieve the least price of power generation. However, modern power system consists of various integrated power generating units including nuclear, thermal, hydro, solar and wind. The scheduling of these generating units in optimal condition is a tedious task and involves lot of uncertainty constraints due to time carrying weather conditions. This difficulties come to be too difficult by growing the scope of electrical power sector day by day, so that UCP has connection with problem in the field of optimization, it has both continuous and binary variables which is the furthermost exciting problem that needs to be solved. In the proposed research, a newly created optimizer, i.e., Harris Hawks optimizer (HHO), has been hybridized with sine–cosine algorithm (SCA) using memetic algorithm approach and named as meliorated Harris Hawks optimizer and it is applied to solve the photovoltaic constrained UCP of electric power system. In this research paper, sine–cosine Algorithm is used for provision of power generation (generating units which contribute in electric power generation for upload) and economic load dispatch (ELD) is completed by Harris Hawks optimizer. The feasibility and efficacy of operation of the hybrid algorithm are verified for small, medium power systems and large system considering renewable energy sources in summer and winter, and the percentage of cost saving for power generation is found. The results for 4 generating units, 5 generating units, 6 generating units, 7 generating units, 10 generating units, 19 generating units, 20 generating units, 40 generating units and 60 generating units are evaluated. The 10 generating units are evaluated with 5% and 10% spinning reserve. The efficacy of the offered optimizer has been verified for several standard benchmark problem including unit commitment problem, and it has been observed that the suggested optimizer is too effective to solve continuous, discrete and nonlinear optimization problems.

Absolutely Stochastic Simulated Annealing Approach to Large Scale Unit Commitment Problem

2006 ◽  
Vol 34 (6) ◽  
pp. 619-637 ◽  
Author(s):  
Tomonobu Senjyu ◽  
Ahmed Yousuf Saber ◽  
Tsukasa Miyagi ◽  
Naomitsu Urasaki ◽  
Toshihisa Funabashi
Keyword(s):  
Simulated Annealing ◽  
Large Scale ◽  
Unit Commitment ◽  
Unit Commitment Problem ◽  
Scale Unit ◽  
Commitment Problem

scholarly journals A Cross-Entropy-Based Hybrid Membrane Computing Method for Power System Unit Commitment Problems

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 486 ◽  
Author(s):  
Min Xie ◽  
Yuxin Du ◽  
Peijun Cheng ◽  
Wei Wei ◽  
Mingbo Liu
Keyword(s):  
Power System ◽  
Membrane Computing ◽  
Unit Commitment ◽  
Economic Dispatch ◽  
Hybrid Membrane ◽  
Cross Entropy ◽  
Unit Commitment Problem ◽  
Commitment Problem ◽  
Dynamic Economic Dispatch ◽  
Computing Method

The cross-entropy based hybrid membrane computing method is proposed in this paper to solve the power system unit commitment problem. The traditional unit commitment problem can be usually decomposed into a bi-level optimization problem including unit start-stop scheduling problem and dynamic economic dispatch problem. In this paper, the genetic algorithm-based P system is proposed to schedule the unit start-stop plan, and the biomimetic membrane computing method combined with the cross-entropy is proposed to solve the dynamic economic dispatch problem with a unit start-stop plan given. The simulation results of 10–100 unit systems for 24 h day-ahead dispatching show that the unit commitment problem can be solved effectively by the proposed cross-entropy based hybrid membrane computing method and obtain a good and stable solution.

Sign in / Sign up

Export Citation Format

Share Document