scholarly journals Optimal Filter Placement and Sizing Using Ant Colony Optimization in Electrical Distribution System

2014 ◽  
Author(s):  
Fawaz Masoud Alhaddad ◽  
Mohamed El-Hawary
Keyword(s):  
Ant Colony Optimization ◽  
Distribution System ◽  
Optimal Filter ◽  
Ant Colony ◽  
Filter Placement ◽  
Electrical Distribution

scholarly journals Ant Colony Optimization Technique in Optimal Capacitor Placement and Sizing Problem in Unbalanced Electrical Distribution System

2015 ◽  
Vol 785 ◽  
pp. 78-82 ◽  
Author(s):  
Mohd Ainor Yahya ◽  
Muhammad Murtadha Othman ◽  
Muhd Azri Abdul Razak ◽  
Zilaila Zakaria ◽  
Ismail Musirin ◽  
...  
Keyword(s):  
Ant Colony Optimization ◽  
Distribution System ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Ant Colony ◽  
Placement Problem ◽  
Electrical Distribution ◽  
Capacitor Placement ◽  
Optimal Capacitor Placement ◽  
Line Loss

The optimal capacitor placement problem involves determination on the type, number, location and size of capacitors to be placed in a distribution system for the attainment of energy efficiency. The main objectives of the capacitors placement and sizing are to reduce total line loss and energy consumption while satisfying the operational constraints. This paper presents the optimal capacitor placement and sizing problems solved by using the Ant Colony Optimization (ACO) technique with the integrated of circuitry unbalanced electrical distribution modeled in SIMULINK®MATLAB®software. The proposed technique was tested on a modified IEEE 13-bus unbalanced radial distribution system and the results revealed that the proposed technique has the merit in achieving optimal solution for addressing the problems.

Power Flow Calculation for Distribution System Including PV Type Distributed Generation

2014 ◽  
Vol 694 ◽  
pp. 159-162
Author(s):  
Fei Han ◽  
Ning Zhou ◽  
Jian Wei Ma ◽  
Xian Ling Yu
Keyword(s):  
Ant Colony Optimization ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Flow ◽  
Reactive Power ◽  
Simulation Software ◽  
Ant Colony ◽  
Power Correction ◽  
Calculation Algorithm ◽  
Flow Solution

After distribution network with PV type distributed generation, it emerged PV nodes. Advanced forward and backward substitution method is proposed based on ant colony optimization method to improve power flow solution, which is a method based on ant colony optimization calculation algorithm of reactive power correction, improved the model of PV type distributed generation in the power flow calculation.Use PSSSINCAL power system simulation software to set up the model of distribution System including PV type distributed generation. Through the results of simulation calculation show that the algorithm can cope with power flow solution for distribution system including PV type distributed generation effectively, and the convergence property is very good.

scholarly journals Optimization in Determining Routes of Goods Distribution Vehicle Using the Ant Colony Optimization Algorithm Method at PT XYZ

2020 ◽  
Vol 2 (1) ◽  
pp. 202-215
Author(s):  
Ranti Dwi Djayanti ◽  
Yani Iriani
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Distribution System ◽  
Transportation Cost ◽  
Transportation Costs ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Total Distance ◽  
Ant Behavior ◽  
Total Transportation Cost

PT XYZ is one of freight forwarding companies in Indonesia, which is located in the city of Bandung. This company has managerial functions related to Collecting, Processing, Transporting, Delivery, and Reporting. However, the fact is in the process of Transporting this company still uses a zoning system which is a shipping system that still divides tertiary areas and each of these areas uses one vehicle. One problem that arises is that companies want effective and efficient performance in the distribution system of goods with the minimum total transportation costs. However, the company does not know yet whether the company's shipping routes have been effective and efficient or not. The company has tertiary network distribution route that are 2 routes with a total distance of 143.4 Km and a total transportation cost of  Rp 5,681,484 /month. This research aims to determine the optimal goods distribution route using the Ant Colony Optimization Algorithm method, which is the method of finding the shortest path following ant behavior in taking food to its nest. Based on the results of the research, it is obtained a total distance of 109.2 Km because it becomes 1 route and total transportation costs Rp 3,337,992 /month, then it is obtained optimal results with a difference in distance is 34.2 Km and a total transportation cost of  Rp 2,343,492 /month using one vehicle. Keywords: Optimization, Distribution, Ant Colony Optimization Algorithm    

scholarly journals Continuous domain ant colony optimization for distributed generation placement and losses minimization

2020 ◽  
Vol 9 (2) ◽  
pp. 261
Author(s):  
Zulkiffli Abdul Hamid ◽  
Ismail Musirin ◽  
Ammar Yasier Azman ◽  
Muhammad Murtadha Othman
Keyword(s):  
Ant Colony Optimization ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Test System ◽  
Ant Colony ◽  
Optimal Size ◽  
Voltage Profile ◽  
Radial Distribution System ◽  
Continuous Domain

This paper proposes a method for distributed generation (DG) placement in distribution system for losses minimization and voltage profile improvement. An IEEE 33-bus radial distribution system is used as the test system for the placement of DG. To facilitate the sizing of DG capacity, a meta-heuristic algorithm known as Continuous Domain Ant Colony Optimization (ACO<sub>R</sub>) is implemented. The ACO<sub>R</sub> is a modified version of the traditional ACO which was developed specially for solving continuous domain optimization problem like sizing a set of variables. The objective of this paper is to determine the optimal size and location of DG for power loss minimization and voltage profile mitigation. Three case studies were conducted for the purpose of verification. It was observed that the proposed technique is able to give satisfactory results of real power loss and voltage profile at post-optimization condition. Experiment under various loadings of the test system further justifies the objective of the study.

scholarly journals Enhancement of the power system distribution reliability using ant colony optimization and simulated annealing methods

2020 ◽  
Vol 17 (2) ◽  
pp. 877 ◽  
Author(s):  
Hadi Suyono ◽  
Rini Nur Hasanah ◽  
Panca Mudjirahardjo ◽  
M Fauzan Edy Purnomo ◽  
Septi Uliyani ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Power System ◽  
Ant Colony Optimization ◽  
Power Distribution ◽  
Distribution System ◽  
Ant Colony ◽  
Service Reliability ◽  
Power Distribution System ◽  
Reliability Indices ◽  
Base Reference

<span>The increasing demand of electricity and number of distributed generations connected to power system greatly influence the level of power service reliability. This paper aims at improving the reliability in an electric power distribution system by optimizing the number and location of sectionalizers using the Ant Colony Optimization (ACO) and Simulated Annealing (SA) methods. Comparison of these two methods has been based on the reliability indices commonly used in distribution system: SAIFI, SAIDI, and CAIDI. A case study has been taken and simulated at a feeder of Pujon, a place in East Java province of Indonesia, to which some distributed generators were connected. Using the existing reliability indices condition as base reference, the addition of two distributed plants, which were micro hydro and wind turbine plants, has proven to lower the indices as much as 0.78% for SAIFI, 0.79% for SAIDI, and 2.32% for CAIDI. The optimal relocation of the existing 16 sectionalizers in the network proved to decrease further the reliability indices as much as 43.96% for SAIFI, 45.52% for SAIDI, and 2.8% for CAIDI, which means bringing to much better reliability condition. The implementation of the SA method on the considered data in general resulted in better reliability indices than using the ACO method.</span>

Implementasi Ant Colony Optimization (ACO) pada Sistem Irigasi Lahan Tadah Hujan

Kilat ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 336-348
Author(s):  
Abdul Haris ◽  
Trisma Juwita ◽  
Rosida Nur Aziza ◽  
Hengki Sikumbang ◽  
Riki Ruli A. Siregar
Keyword(s):  
Ant Colony Optimization ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Irrigation System ◽  
Ant Colony ◽  
Irrigation Systems ◽  
Distribution Process ◽  
Soil Dryness ◽  
The Impact

The purpose of this research is to produce an optimal water distribution system for irrigation of rainfed land. The problem with conventional irrigation systems is that the water distribution process cannot be controlled and monitored automatically and in real time. The impact on water distribution becomes ineffective. The implementation of Ant Colony Optimization (ACO) is used in research as a method to determine the location or node based on the pheromone pattern of the soil dryness level at the sprinkler nodes to be distributed by the water flow, taking into account the criteria level on the soil as a trend of probability values ​​and determining the nodes according to the needs in the flow water. The results obtained from this study indicate that the data displayed is the level of dryness of each node, the volume of water in the reservoir, and the flow of water flowing. The ACO test shows the sequence of nodes that will be passed after the optimization process of water distribution in a rainfed irrigation system using the ACO method gets an error value calculated by the MAPE method of 43% so that it gets an accuracy value of 57%.

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