scholarly journals Solving economic dispatch and unit commitment problem in smart grid system using eagle strategy based crow search algorithm

2019 ◽  
Vol 14 (3) ◽  
pp. 1087
Author(s):  
Rachid HABACHI ◽  
Achraf Touil ◽  
Abdellah Boulal ◽  
Abdelkabir Charkaoui ◽  
Abdelwahed Echchatbi
Keyword(s):  
Smart Grid ◽  
Unit Commitment ◽  
Search Algorithm ◽  
Economic Dispatch ◽  
Minimum Cost ◽  
Grid System ◽  
Unit Commitment Problem ◽  
Commitment Problem ◽  
Smart Grid System ◽  
Eagle Strategy

<p><span lang="EN-US">The economic dispatch problem of power plays a very important role in the exploitation of electro-energy systems to judiciously distribute power generated by all plants. The Unit commitment problem (UCP) is mainly finding the minimum cost schedule to a set of generators by turning each one either on or off over a given time horizon to meet the demand load and satisfy different operational constraints. This research article integrates the crow search algorithm as a local optimizer of Eagle strategy to solve economic dispatch and unit commitment problem in smart grid system.</span></p>

scholarly journals Comparative study of metaheuristics methods applied to smart grid network in Morocco

2020 ◽  
Vol 11 (1) ◽  
pp. 487
Author(s):  
Rachid Habachi ◽  
Achraf Touil ◽  
Abdellah Boulal ◽  
Abdelkabir Charkaoui ◽  
Abdelwahed Echchatbi
Keyword(s):  
Smart Grid ◽  
Unit Commitment ◽  
Search Algorithm ◽  
Economic Dispatch ◽  
Minimum Cost ◽  
Unit Commitment Problem ◽  
Commitment Problem ◽  
Smart Grid System ◽  
Local Optimizer ◽  
Eagle Strategy

The economic dispatch problem of power plays a very important role in the exploitation of electro-energy systems to judiciously distribute power generated by all plants. The Unit commitment problem (UCP) is mainly finding the minimum cost schedule to a set of generators by turning each one either on or off over a given time horizon to meet the demand load and satisfy different operational constraints, This research article integrates the crow search algorithm (CSA) as a local optimizer of Eagle strategy (ES) to solve economic dispatch and unit commitment problem in smart grid system of two electricity networks: a testing system 7 units and the Moroccan  network.. The results obtained by ES- CSA are compared with various results obtained in the literature. Simulation results show that using ES-CSA can lead to finding stable and adequate power generated that can fulfill the need of both the civil and industrial areas<em>.</em>

Ant Lion Optimizer for Solving Unit Commitment Problem in Smart Grid System

2017 ◽  
Vol 8 (1) ◽  
pp. 129 ◽  
Author(s):  
Izni Nadhirah Sam’on ◽  
Zuhaila Mat Yasin ◽  
Zuhaina Zakaria
Keyword(s):  
Renewable Energy ◽  
Smart Grid ◽  
Unit Commitment ◽  
Energy Resources ◽  
Grid System ◽  
Renewable Energy Resources ◽  
Unit Commitment Problem ◽  
Commitment Problem ◽  
Ant Lion ◽  
Smart Grid System

<p>This paper proposed the integration of solar energy resources into the conventional unit commitment. The growing concern about the depletion of fossil fuels increased the awareness on the importance of renewable energy resources, as an alternative energy resources in unit commitment operation. However, the present renewable energy resources is intermitted due to unpredicted photovoltaic output. Therefore, Ant Lion Optimizer (ALO) is proposed to solve unit commitment problem in smart grid system with consideration of uncertainties .ALO is inspired by the hunting appliance of ant lions in natural surroundings. A 10-unit system with the constraints, such as power balance, spinning reserve, generation limit, minimum up and down time constraints are considered to prove the effectiveness of the proposed method. The performance of proposed algorithm are compared with the performance of Dynamic Programming (DP). The results show that the integration of solar energy resources in unit<em> commitment scheduling can improve the total operating cost significantly. </em></p>

scholarly journals Eagle Strategy based Crow Search Algorithm for solving Unit Commitment Problem

2018 ◽  
Vol 12 (1) ◽  
pp. 17 ◽  
Author(s):  
Rachid Habachi ◽  
Achraf Touil ◽  
Abdelkabir Charkaoui ◽  
Abdelwahed Echchatbi
Keyword(s):  
Local Search ◽  
Unit Commitment ◽  
Search Algorithm ◽  
Optimization Strategy ◽  
Unit Commitment Problem ◽  
Spinning Reserve ◽  
Two Stage ◽  
Commitment Problem ◽  
Local Optimizer ◽  
Eagle Strategy

<p>Eagle strategy is a two-stage optimization strategy, which is inspired by the observation of the hunting behavior of eagles in nature. In this two-stage strategy, the first stage explores the search space globally by using a Levy flight; if it finds a promising solution, then an intensive local search is employed using a more efficient local optimizer, such as hillclimbing and the downhill simplex method. Then, the two-stage process starts again with new global exploration, followed by a local search in a new region. One of the remarkable advantages of such a combina-tion is to use a balanced tradeoff between global search (which is generally slow) and a rapid local search. The crow search algorithm (CSA) is a recently developed metaheuristic search algorithm inspired by the intelligent behavior of crows.This research article integrates the crow search algorithm as a local optimizer of Eagle strategy to solve unit commitment (UC) problem. The Unit commitment problem (UCP) is mainly finding the minimum cost schedule to a set of generators by turning each one either on or off over a given time horizon to meet the demand load and satisfy different operational constraints. There are many constraints in unit commitment problem such as spinning reserve, minimum up/down, crew, must run and fuel constraints. The proposed strategy ES-CSA is tested on 10 to 100 unit systems with a 24-h scheduling horizon. The effectiveness of the proposed strategy is compared with other well-known evolutionary, heuristics and meta-heuristics search algorithms, and by reported numerical results, it has been found that proposed strategy yields global results for the solution of the unit commitment problem.</p><p> </p>

scholarly journals Optimization Methodologies and Testing on Standard Benchmark Functions of Load Frequency Control for Interconnected Multi Area Power System in Smart Grids

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 980 ◽  
Author(s):  
Krishan Arora ◽  
Ashok Kumar ◽  
Vikram Kumar Kamboj ◽  
Deepak Prashar ◽  
Sudan Jha ◽  
...  
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Unit Commitment ◽  
Frequency Control ◽  
Load Frequency Control ◽  
Grid System ◽  
Unit Commitment Problem ◽  
Load Frequency ◽  
Fixed Dimension ◽  
Smart Grid System

In the recent era, the need for modern smart grid system leads to the selection of optimized analysis and planning for power generation and management. Renewable sources like wind energy play a vital role to support the modern smart grid system. However, it requires a proper commitment for scheduling of generating units, which needs proper load frequency control and unit commitment problem. In this research area, a novel methodology has been suggested, named Harris hawks optimizer (HHO), to solve the frequency constraint issues. The suggested algorithm was tested and examined for several regular benchmark functions like unimodal, multi-modal, and fixed dimension to solve the numerical optimization problem. The comparison was carried out for various existing models and simulation results demonstrate that the projected algorithm illustrates better results towards load frequency control problem of smart grid arrangement as compared with existing optimization models.

scholarly journals EADPSODV Technique for Solving UC Problem

2019 ◽  
Vol 8 (6) ◽  
pp. 2191-2195
Keyword(s):  
Energy Demand ◽  
Unit Commitment ◽  
Optimization Problems ◽  
Large Family ◽  
Minimum Cost ◽  
Ant Colony ◽  
Unit Commitment Problem ◽  
Robust Solution ◽  
Unit System ◽  
Commitment Problem

Unit Commitment problem (UC) is a large family of mathematical optimization problems usually either match the energy demand at minimum cost or maximize revenues from energy production. This paper proposes a new approach for solving Unit Commitment problem using the EADPSODV technique. In PSODV, the appropriate mutation factor is selected by applying Ant Colony search procedure in which internally a Genetic Algorithm (GA) is employed in order to develop the necessary Ant Colony parameters. In EADPSODV method the advantageous part is that, for determining the most feasible configuration of the control variables in the Unit Commitment. An initial observation and verification of the suggested process is carried on a 10-unit system which is extended to 40-unit system over a stipulated time horizon (24hr). The outcomes attained from the proposed EADPSODV approach indicate that EADPSODV provides effective and robust solution of Unit Commitment.

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