Security Constrained Unit Commitment Problem Employing Artificial Computational Intelligence for Wind-Thermal Power System

2015 ◽  
pp. 261-275
Author(s):  
K. Banumalar ◽  
B. V. Manikandan ◽  
K. Chandrasekaran
Keyword(s):  
Power System ◽  
Computational Intelligence ◽  
Unit Commitment ◽  
Thermal Power ◽  
Unit Commitment Problem ◽  
Thermal Power System ◽  
Commitment Problem

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.

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.

Extreme Ray Feasibility Cuts for Unit Commitment with Uncertainty

2020 ◽  
Author(s):  
Chao Li ◽  
Muhong Zhang ◽  
Kory Hedman
Keyword(s):  
Power System ◽  
Transmission Lines ◽  
Unit Commitment ◽  
Deterministic Model ◽  
Dual Cone ◽  
Scheduling Problems ◽  
Unit Commitment Problem ◽  
Commitment Problem ◽  
Industry Practice ◽  
Extreme Rays

The unit commitment problem with uncertainty is considered one of the most challenging power system scheduling problems. Different stochastic models have been proposed to solve the problem, but such approaches have yet to be applied in industry practice because of computational challenges. In practice, the problem is formulated as a deterministic model with reserve requirements to hedge against uncertainty. However, simply requiring a certain level of reserves cannot ensure power system reliability as the procured reserves may be nondispatchable because of transmission limitations. In this paper, we derive a set of feasibility cuts (constraints) for managing the unit commitment problem with uncertainty. These cuts eliminate unreliable scheduling solutions and reallocate reserves in the power system; they are induced by the extreme rays of a polyhedral dual cone. This paper shows that, with the proposed reformulation, the extreme rays of the dual cone can be characterized by combinatorial selections of transmission lines (arcs) and buses (nodes) of the power system. As a result, the cuts can then be characterized using engineering insights. The unit commitment problem with uncertainty is formulated as a deterministic model with the identified extreme ray feasibility cuts. Test results show that, with the proposed extreme ray feasibility cuts, the problem can be solved more efficiently, and the resulting scheduling decision is also more reliable.

scholarly journals Firefly algorithm with multiple workers for the power system unit commitment problem

2016 ◽  
Vol 24 ◽  
pp. 4773-4789 ◽  
Author(s):  
Banumalar KOODALSAMY ◽  
Manikandan BAIRAVAN VEERAYAN ◽  
Chandrasekaran KOODALSAMY ◽  
Sishaj Pulikottil SIMON
Keyword(s):  
Power System ◽  
Firefly Algorithm ◽  
Unit Commitment ◽  
Unit Commitment Problem ◽  
Commitment Problem
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