A new Pareto multi-objective sine cosine algorithm for performance enhancement of radial distribution network by optimal allocation of distributed generators

2020 ◽  
Author(s):  
Usharani Raut ◽  
Sivkumar Mishra
Keyword(s):  
Radial Distribution ◽  
Optimal Allocation ◽  
Performance Enhancement ◽  
Distribution Network ◽  
Multi Objective ◽  
Distributed Generators ◽  
Sine Cosine Algorithm

scholarly journals Multi-Objective Grey Wolf Optimization for Optimal Allocation of Distributed Generators in Distribution Networks

2020 ◽  
Vol 9 (3) ◽  
pp. 664-670
Keyword(s):  
Radial Distribution ◽  
Power Loss ◽  
Distribution Network ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Real Power ◽  
Multi Objective ◽  
Distributed Generators

The power loss in the radial distribution network is appreciable as compared to transmission network. To reduce the power loss in distribution network which is radial in nature, the solution methodology adopted in this paper is optimal placement of distributed generators (DG). The optimization incorporated is Multi-objective Grey Wolf Optimization (MOGWO). The optimization is accomplished for three different cases. In each case two objective functions are simultaneously optimized to obtain non-dominated solutions using Multi-objective Grey Wolf Optimization. Case (1): To minimize the real power loss and maximize the savings obtained due to DG installation. Case (2): To minimize real power loss and maximum voltage deviation in the network. Case (3): To minimize real power loss and rating of DG installed. MOGWO method maintains an archive which contains pareto-optimal solutions. The archive mimics the behaviour of grey wolves. MOGWO method is verified on radial distribution networks. The effectiveness of the optimization method is proven by comparing the results with other optimization methods available in the literature.

scholarly journals Investigation of Optimal PV Allocation to Minimize System Losses and Improve Voltage Stability for Distribution and Transmission Networks Using MATLAB and DigSilent

2021 ◽  
Vol 9 ◽  
Author(s):  
Mohamed Abdul Rasheed ◽  
Renuga Verayiah
Keyword(s):  
Objective Function ◽  
Radial Distribution ◽  
Power Factor ◽  
Analytical Method ◽  
Distribution Network ◽  
Computation Time ◽  
Transmission Network ◽  
Voltage Profile ◽  
Multi Objective ◽  
Test Systems

Electricity generation from renewable energy sources such as solar energy is an emerging sustainable solution. In the last decade, this sustainable source was not only being used as a source of power generation but also as distributed generation (DG). Many literatures have been published in this field with the objective to minimize losses by optimizing the DG size and location. System losses and voltage profile go hand-in-hand; as a result, when system losses are minimized, eventually the voltage profile improves. With improvement in inverter technologies, PV-DG units do not have to operate at a unity power factor. The majority of proposed algorithms and methods do not consider power factor optimization as a necessary optimization. This article aims to optimize the size, location, and power factor of PV-DG units. The simulations are performed on the IEEE 33 bus radial distribution network and IEEE 14 bus transmission network. The methodologies developed in this article are divided into two sections. The first section aims to optimize the PV-DG size and location. A multi-objective function is developed by using system losses and a voltage deviation index. Genetic algorithm (GA) is used to optimize the multi-objective function. Next, analytical processes are developed for verification. The second section aims to further enhance PV-DG by optimizing the power factor of PV-DG. The simulation is performed for static load in both systems, which are the IEEE 33 bus radial distribution network and IEEE 14 bus transmission network. A mathematical analytical method was developed, and it was found to be sufficient to optimize the power factor of the PV-DG unit. The results obtained show that voltage stability indices help minimize the computation time by determining the optimal locations for DG placement in both networks. In addition, the GA method attained faster convergence than the analytical method and hence is the best optimal sizing for both test systems with minimum computation time. Additionally, the optimization of the power factor for both test systems has demonstrated further improvement in the voltage profile and loss minimization. In conclusion, the proposed methodology has shown promising results for both transmission and distribution networks.

Optimal Allocation and Operating Point of DG Units in Radial Distribution Network Considering Load Pattern

2017 ◽  
Vol 45 (12) ◽  
pp. 1287-1297 ◽  
Author(s):  
Sajjad Hadavi ◽  
Ali Zoghi ◽  
Behrooz Vahidi ◽  
Gevork B. Gharehpetian ◽  
Seyed Hossein Hosseinian
Keyword(s):  
Radial Distribution ◽  
Optimal Allocation ◽  
Distribution Network ◽  
Operating Point ◽  
Load Pattern
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