scholarly journals Per-Phase and 3-Phase Optimal Coordination of Directional Overcurrent Relays Using Genetic Algorithm

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1699
Author(s):  
Ronald C. Matthews ◽  
Trupal R. Patel ◽  
Adam K. Summers ◽  
Matthew J. Reno ◽  
Shamina Hossain-McKenzie
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Distributed Storage ◽  
Renewable Energy Sources ◽  
Computation Time ◽  
Discrete Control ◽  
Mixed Integer ◽  
First Case ◽  
Three Phase ◽  
Optimal Coordination

Penetration of the power grid by renewable energy sources, distributed storage, and distributed generators is becoming increasingly common. Increased utilization of these distributed energy resources (DERs) has given rise to additional protection coordination concerns, particularly where they are utilized in an unbalanced manner or where loading among phases is unbalanced. Digital relays such as the SEL-751 (produced by Schweitzer Engineering Laboratories, Pullman, WA, USA) series have the capability of being set on a per-phase basis. This capability is underutilized in common practice. Additionally, in optimization algorithms for determining relay settings, the time-overcurrent characteristics (TOCs) of relays are generally not treated as variables and are assigned before running the optimization algorithm. In this paper, TOC options themselves are treated as discrete variables to be considered in the optimization algorithm. A mixed integer nonlinear programming problem (MINLP) is set up where the goal is to minimize relay operating times. A genetic algorithm (GA) approach is implemented in MATLAB where two cases are considered. In the first case, the TOC and Time dial setting (TDS) of each relay is set on a three-phase basis. In the second case, per-phase settings are considered. Relay TDSs and TOCs are both considered as simultaneous discrete control variables. Despite the stochastic nature of using per-phase settings for unbalanced systems is found to generally allow for shorter operating times. However, for relatively balanced systems, it is best to use three-phase settings if computation time is of importance.

scholarly journals An Adaptive Test Sheet Generation Mechanism Using Genetic Algorithm

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Huan-Yu Lin ◽  
Jun-Ming Su ◽  
Shian-Shyong Tseng
Keyword(s):  
Genetic Algorithm ◽  
Computation Time ◽  
Mixed Integer ◽  
Selection Strategy ◽  
Integer Programming Problem ◽  
Test Sheet ◽  
Test Items ◽  
Adaptive Test ◽  
Time Series Approach ◽  
Assessment Requirements

For test-sheet composition systems, it is important to adaptively compose test sheets with diverse conceptual scopes, discrimination and difficulty degrees to meet various assessment requirements during real learning situations. Computation time and item exposure rate also influence performance and item bank security. Therefore, this study proposes an Adaptive Test Sheet Generation (ATSG) mechanism, where a Candidate Item Selection Strategy adaptively determines candidate test items and conceptual granularities according to desired conceptual scopes, and an Aggregate Objective Function applies Genetic Algorithm (GA) to figure out the approximate solution of mixed integer programming problem for the test-sheet composition. Experimental results show that the ATSG mechanism can efficiently, precisely generate test sheets to meet the various assessment requirements than existing ones. Furthermore, according to experimental finding, Fractal Time Series approach can be applied to analyze the self-similarity characteristics of GA’s fitness scores for improving the quality of the test-sheet composition in the near future.

scholarly journals Comparative Analysis of Distributive Optimized Clustering Techniques in Cognitive Radio Networks

2018 ◽  
Vol 7 (3.27) ◽  
pp. 504 ◽  
Author(s):  
R Ganesh Babu ◽  
Dr V.Amudha
Keyword(s):  
Genetic Algorithm ◽  
Comparative Analysis ◽  
Cognitive Radio ◽  
Convergence Rate ◽  
Optimization Algorithm ◽  
Computation Time ◽  
Radio Networks ◽  
Optimization Techniques ◽  
Dynamic Clustering ◽  
Clustering Techniques

In this paper we study and compare the performance of Distributed Firefly Optimized Clustering (DFOC) with Distributed Swarm Optimized Clustering (DSOC) optimization techniques used for the dynamic clustering. Proposed Distributed Firefly Optimized Clustering (DFOC) is an optimization algorithm  based on the function of attractiveness of firefly behavior. All the cognitive nodes move towards the brighter firefly with random velocity to form an organized cluster with least computation time. In the existing DSOC method each particle’s best position and velocity are evaluated according to the objective function until an optimum global best position is reached. The convergence rate of DSOC is similar to Genetic Algorithm (GA). The proposed DFOC, the SU power is reduced to 7.34% for 100 numbers of SUs.compared to DSOC.  

scholarly journals A Genetic Algorithm for a Two-Machine Flowshop with a Limited Waiting Time Constraint and Sequence-Dependent Setup Times

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Ju-Yong Lee
Keyword(s):  
Genetic Algorithm ◽  
Waiting Time ◽  
Computation Time ◽  
Time Constraint ◽  
Setup Times ◽  
Mixed Integer ◽  
Sequence Dependent ◽  
Sequence Dependent Setup ◽  
Dependent Setup Times ◽  
Sequence Dependent Setup Times

This study considers a two-machine flowshop with a limited waiting time constraint between the two machines and sequence-dependent setup times on the second machine. These characteristics are motivated from semiconductor manufacturing systems. The objective of this scheduling problem is to minimize the total tardiness. In this study, a mixed-integer linear programming formulation was provided to define the problem mathematically and used to find optimal solutions using a mathematical programming solver, CPLEX. As CPLEX required a significantly long computation time because this problem is known to be NP-complete, a genetic algorithm was proposed to solve the problem within a short computation time. Computational experiments were performed to evaluate the performance of the proposed algorithm and the suggested GA outperformed the other heuristics considered in the study.

Research on Distributed Database Query Optimization Based on Genetic Algorithm

2013 ◽  
Vol 380-384 ◽  
pp. 2850-2853
Author(s):  
Yan Qin Li ◽  
Cai Tian Zhang
Keyword(s):  
Genetic Algorithm ◽  
Query Optimization ◽  
Optimization Algorithm ◽  
Distributed Storage ◽  
Cost Model ◽  
Distributed Database ◽  
Optimization Method ◽  
Performance Comparison ◽  
Database Query ◽  
Genetic Method

In order to improve the performance of the query optimization for the distribute database, an improved query optimization algorithm was proposed based on the genetic algorithm. The query execution cost model based on the genetic algorithm was proposed in this paper. The distributed database was emerged in the 70's of the last century and developed with the progress of the computer technology and network technology, the distributed database was the database system which is distributed storage dispersedly in physics and with centralized processing in mathematic logic. Because the storage points were not uniform, the structure of the distributed database is much more complicated than the centralized database. Both the genetic algorithm and the dynamic exhaustive planning algorithm were taken in the query simulation for the performance comparison. The result shows that the genetic query optimization method in this paper has better performance in the distributed database query application. The case study and the simulation result show that the algorithm can get a satisfactory optimization result in a few iterations and the query optimization algorithm based on the genetic method has nice performance of the query optimization property, and the consumption and costs of the query is reduced to the minimum. The method which this paper proposed has good application performance and is valuable to put into practice.

scholarly journals Feasible Islanding Operation of Electric Networks with Large Penetration of Renewable Energy Sources considering Security Constraints

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 537 ◽  
Author(s):  
Seyed Arash Alavi ◽  
Valentin Ilea ◽  
Alireza Saffarian ◽  
Cristian Bovo ◽  
Alberto Berizzi ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Renewable Energy Sources ◽  
Optimal Solution ◽  
Computation Time ◽  
Mixed Integer ◽  
Energy Sources ◽  
Distribution Grid ◽  
Electric Networks ◽  
Emergency Situations ◽  
The One

The high penetration of Renewable Energy Sources into electric networks shows new perspectives for the network’s management: among others, exploiting them as resources for network’s security in emergency situations. The paper focuses on the frequency stability of a portion of the grid when it remains islanded following a major fault. It proposes an optimization algorithm that considers the frequency reaction of the relevant components and minimizes the total costs of their shedding. The algorithm predicts the final frequency of the island and the active power profiles of the remaining generators and demands. It is formulated as a Mixed-Integer Non-Linear Programming problem and the high computation time due to a large-size problem is mitigated through a simplified linear version of the model that filters the integer variables. The algorithm is designed to operate on-line and preventively compute the optimal shedding actions to be engaged when islanding occurs. The algorithm is validated for a typical distribution grid: the minimum amount of shedding actions is obtained while the most frequency reactive resources are maintained in operation to assure a feasible frequency. Finally, time-domain simulations show that the optimal solution corresponds to the one at the end of the network’s transients following the islanding.

Two-Layer Optimize Algorithm for Microgrid Economic Dispatch

2014 ◽  
Vol 672-674 ◽  
pp. 1336-1341
Author(s):  
Yan Ding ◽  
Rong Jia ◽  
Kai Song Dong ◽  
Zhen Li ◽  
Wei Cheng Shen ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Integer Programming ◽  
Mixed Integer Programming ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Lower Layer ◽  
Economic Dispatch ◽  
Mixed Integer ◽  
Integer Programming Problem ◽  
Short Time

To deal with the super short-time energy management of microgrid, a mixed-integer programming optimization algorithm combined with genetic algorithm is proposed. Firstly, this paper introduced the short-time economic dispatch mathematical model of microgrid. Secondly, a two-layer optimize algorithm is been developed. The lower layer takes no account of power flow constrains, convert the model into a mixed-integer programming problem through linearization techniques. The lower layer gets the generation schedule, and then passes the data to the upper layer. The upper layer takes the power flow constrains into account, optimize the unit output based on genetic algorithm. The simulation result shows that the proposed algorithm achieves a better complementary of the two kinds of optimization algorithm. At the same time, the optimization result also shows the effectiveness of the algorithm.

scholarly journals Effect of renewable energy sources integration on the optimal coordination of directional over-current relays in distribution system

2020 ◽  
Vol 9 (3) ◽  
pp. 250
Author(s):  
Lazhar Bougouffa ◽  
Abdelaziz Chaghi
Keyword(s):  
Renewable Energy ◽  
Optimization Algorithm ◽  
Power Distribution ◽  
Distribution System ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Software Environment ◽  
Optimal Coordination ◽  
Res Integration ◽  
New Generation

<div data-canvas-width="397.21009877040933">The demand for power electricity is growing fast and one of the main tasks for power engineers is to generate electricity from renewable energy sources (RES).</div><div data-canvas-width="277.2073926627698">Nevertheless, problems arise when the new generation is integrated in the power distribution network. Under this condition, the main purpose in this paper, an investigation of the effect of RES integration on the optimal coordination of directional over-current relays in distribution system, a dual simplex optimization algorithm has been presented to determine the coordination of directional over-current relays (DOCRs). The system used to check the efficiency of the optimization algorithm which is IEEE 33-bus models. The analysis is performed in MATLAB software environment.</div>

Sustainable Cooling with Hybrid Concentrated Photovoltaic Thermal (CPVT) System and Hydrogen Energy Storage

2018 ◽  
Vol 1 (2) ◽  
pp. 40-51 ◽  
Author(s):  
Muhammad Burhan ◽  
Muhammad Wakil Shahzad ◽  
Kim Choon Ng
Keyword(s):  
Energy Storage ◽  
Solar Energy ◽  
Optimization Algorithm ◽  
Concentration Ratio ◽  
Cooling System ◽  
Renewable Energy Sources ◽  
Hot Water ◽  
Hydrogen Energy ◽  
Adsorption Chiller ◽  
Back Plate

Standalone power systems have vital importance as energy source for remote area. On the other hand, a significant portion of such power production is used for cooling purposes. In this scenario, renewable energy sources provide sustainable solution, especially solar energy due to its global availability. Concentrated photovoltaic (CPV) system provides highest efficiency photovoltaic technology, which can operate at x1000 concentration ratio. However, such high concentration ratio requires heat dissipation from the cell area to maintain optimum temperature. This paper discusses the size optimization algorithm of sustainable cooling system using CPVT. Based upon the CPV which is operating at x1000 concentration with back plate liquid cooling, the CPVT system size is optimized to drive a hybrid mechanical vapor compression (MVC) chiller and adsorption chiller, by utilizing both electricity and heat obtained from the solar system. The electrolysis based hydrogen is used as primary energy storage system along with the hot water storage tanks. The micro genetic algorithm (micro-GA) based optimization algorithm is developed to find the optimum size of each component of CPVT-Cooling system with uninterrupted power supply and minimum cost, according to the developed operational strategy. The hybrid system is operated with solar energy system efficiency of 71%.

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