Analysis on Load Model for Cost Optimization Using Embedded Meta EP-Firefly Algorithm for DG Installation

2015 ◽  
Vol 793 ◽  
pp. 478-482
Author(s):  
S.R.A. Rahim ◽  
Ismail Musirin ◽  
Muhammad Murtadha Othman ◽  
Muhamad Hatta Hussain
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Firefly Algorithm ◽  
Cost Optimization ◽  
Load Model ◽  
Load Models ◽  
Generation Planning ◽  
Voltage Dependent ◽  
The Cost

This paper presents the analysis on load models for cost optimization for distributed generation planning. The Embedded Meta EP – Firefly Algorithm technique is performed in order to identify the optimal distributed generation sizing. The result obtained show that the proposed technique has an acceptable performance to simulate the data and voltage dependent load models have a significant effect on total losses of a distribution system consequently will affect the cost of the system.

scholarly journals Effect of Load Model Using Ranking Identification Technique for Multi Type DG Incorporating Embedded Meta EP-Firefly Algorithm

2018 ◽  
Vol 150 ◽  
pp. 01014
Author(s):  
Siti Rafidah Abdul Rahim ◽  
Ismail Musirin ◽  
Muhammad Murtadha Othman ◽  
Muhamad Hatta Hussain
Keyword(s):  
Power System ◽  
Distributed Generation ◽  
Distribution System ◽  
Firefly Algorithm ◽  
Optimal Allocation ◽  
Load Factor ◽  
Load Model ◽  
Load Models ◽  
Voltage Dependent ◽  
Identification Technique

This paper presents the effect of load model prior to the distributed generation (DG) planning in distribution system. In achieving optimal allocation and placement of DG, a ranking identification technique was proposed in order to study the DG planning using pre-developed Embedded Meta Evolutionary Programming–Firefly Algorithm. The aim of this study is to analyze the effect of different type of DG in order to reduce the total losses considering load factor. To realize the effectiveness of the proposed technique, the IEEE 33 bus test systems was utilized as the test specimen. In this study, the proposed techniques were used to determine the DG sizing and the suitable location for DG planning. The results produced are utilized for the optimization process of DG for the benefit of power system operators and planners in the utility. The power system planner can choose the suitable size and location from the result obtained in this study with the appropriate company’s budget. The modeling of voltage dependent loads has been presented and the results show the voltage dependent load models have a significant effect on total losses of a distribution system for different DG type.

Clustering Technique for DG Planning Considering Load Models

2015 ◽  
Vol 793 ◽  
pp. 457-461 ◽  
Author(s):  
S.R.A. Rahim ◽  
Ismail Musirin ◽  
Muhammad Murtadha Othman ◽  
Muhamad Hatta Hussain
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Loss Minimization ◽  
Load Model ◽  
Clustering Technique ◽  
Load Models ◽  
Generation Planning ◽  
Single Objective ◽  
Minimization Scheme

This paper presents the clustering technique for distributed generation planning considering load models. The study concerns on the effect of different load model prior to the DG installation for single objective implementation in loss minimization scheme. The clustering technique is performed in order to identify the DG placement for DG planning. Results from the study could be beneficial for the energy commission and utility to perform the DG installation as a compensating technique. The proposed technique was tested on 69-Bus Distribution System.

scholarly journals Economic Dispatch of BESS and Renewable Generators in DC Microgrids Using Voltage-Dependent Load Models

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4494 ◽  
Author(s):  
Oscar Danilo Montoya ◽  
Walter Gil-González ◽  
Luis Grisales-Noreña ◽  
César Orozco-Henao ◽  
Federico Serra
Keyword(s):  
Operating Conditions ◽  
Load Model ◽  
Optimal Dispatch ◽  
Load Models ◽  
General Algebraic Modeling System ◽  
Voltage Dependent ◽  
Battery Energy Storage Systems ◽  
Short Term Prediction ◽  
Battery Energy ◽  
The Cost

This paper addresses the optimal dispatch problem for battery energy storage systems (BESSs) in direct current (DC) mode for an operational period of 24 h. The problem is represented by a nonlinear programming (NLP) model that was formulated using an exponential voltage-dependent load model, which is the main contribution of this paper. An artificial neural network was employed for the short-term prediction of available renewable energy from wind and photovoltaic sources. The NLP model was solved by using the general algebraic modeling system (GAMS) to implement a 30-node test feeder composed of four renewable generators and three batteries. Simulation results demonstrate that the cost reduction for a daily operation is drastically affected by the operating conditions of the BESS, as well as the type of load model used.

scholarly journals Cost of Energy Losses for Distributed Generation Using Hybrid Evolutionary Programming-Firefly Algorithm

2021 ◽  
Vol 2107 (1) ◽  
pp. 012049
Author(s):  
Noor Najwa Husnaini Mohammad Husni ◽  
Siti Rafidah Abdul Rahim ◽  
Mohd Rafi Adzman ◽  
Muhammad Hatta Hussain ◽  
Ismail Musirin
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Distribution Systems ◽  
Firefly Algorithm ◽  
Evolutionary Programming ◽  
Optimization Techniques ◽  
Energy Losses ◽  
Type I ◽  
Cost Of Energy ◽  
The Cost

Abstract The cost of energy losses analysis for distributed generation (DG) is presented in this paper using a Hybrid Evolutionary Programming-Firefly Algorithm (EPFA). The proposed method was created to determine the optimal DG sizing in the distribution system while accounting for the system’s energy losses. This study presents an investigation into hybrid optimization techniques for DG capabilities and optimal operating strategies in distribution systems. The objectives of this study were to reduce the cost of energy losses while increasing the voltage profile and minimize distribution system losses. In this study, the analysis was done by consider DG type I which is DG-PV. The suggested methodology was tested using the IEEE 69-bus test system, and the simulation was written in the MATLAB programming language. Power system planners can use appropriate location and sizing from the results obtained for utility planning in terms of economic considerations. From the simulation, the result shows the proposed method can identify the suitable sizing of DG while reduce cost of energy losses and total losses in the system.

scholarly journals Loadability Investigation of Power System Network Integrated Distributed Generation Including Multi-Sector Consumers

2020 ◽  
Vol 55 (4) ◽  
Author(s):  
Yusran ◽  
Yuli Asmi Rahman ◽  
Prisma Megantoro
Keyword(s):  
Distributed Generation ◽  
Firefly Algorithm ◽  
Initial Conditions ◽  
Hybrid Approach ◽  
Stability Index ◽  
Optimal Placement ◽  
Load Model ◽  
Voltage Curve ◽  
Actual Load ◽  
Curve Method

This article describes the hybrid approach of the Firefly Algorithm and power-voltage curve method in optimal placement of Distributed Generation while considering the actual load model. The actual load model is represented by six models. The six load models are a composite of industrial, residential, and commercial loads with dissimilar percentages. The Institute of Electrical and Electronics Engineers 30 Bus is selected as the testing object for the proposed method. The optimal Distributed Generation placement process was performed using the Firefly Algorithm, while evaluation of optimal Distributed Generation on the loading and stability index is continued using the power-voltage curve method. The results show that commercial loads contribute to high power loss values. The optimal Distributed Generation integration results in an increase the stability index from 53.83% at initial conditions to 90.84% at maximum load level when increasing the maximum loading limit to 95%.

Different responses of load models when facing short-circuits in a distribution system with intermittent distributed generation

2019 ◽  
Author(s):  
Andre Luis da Silva Pessoa ◽  
Pedro Henrique Aquino Barra ◽  
Mario Oleskovicz ◽  
Fernando Ribeiro Arduini ◽  
Paulo Estevao Teixeira Martins
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Load Models ◽  
Short Circuits

Multiple DG Planning Considering Distribution Loss and Penetration Level using EMEFA-ANN Method

2017 ◽  
Vol 7 (1) ◽  
pp. 1 ◽  
Author(s):  
S. R. A. Rahim ◽  
I. Musirin ◽  
M. M. Othman ◽  
M. H. Hussain
Keyword(s):  
Distributed Generation ◽  
Computational Intelligence ◽  
Distribution System ◽  
Mean Squared Error ◽  
Optimization Technique ◽  
Type I ◽  
Load Variations ◽  
Generation Planning ◽  
Computational Intelligence Technique ◽  
Artificial Neural Network Ann

<p>This paper presents the implementation of multiple distributed generation planning in distribution system using computational intelligence technique. A pre-developed computational intelligence optimization technique named as Embedded Meta EP-Firefly Algorithm (EMEFA) was utilized to determine distribution loss and penetration level for the purpose of distributed generation (DG) installation. In this study, the Artificial Neural Network (ANN) was used in order to solve the complexity of the multiple DG concept. EMEFA-ANN was developed to optimize the weight of the ANN to minimize the mean squared error. The proposed method was validated on IEEE 69 Bus distribution system with several load variations scenario. The case study was conducted based on the multiple unit of DG in distribution system by considering the DGs are modeled as type I which is capable of injecting real power. Results obtained from the study could be utilized by the utility and energy commission for loss reduction scheme in distribution system.</p>

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