Optimization of location and size of distributed generations for maximizing their capacity and minimizing power loss of distribution system based on cuckoo search algorithm

Nguyen, Thuan Thanh; Ngoc, Trieu Ton; Nguyen, Thang Trung; Nguyen, Thanh-Phuc; Nguyen, Ngoc Au

doi:10.11591/eei.v10i4.2278

Cited by 7 publications

(5 citation statements)

References 27 publications

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“…There are several methods to improve the performance of distribution network in terms of reducing voltage drop and losses [10]. One of these methods is optimal reconfiguration of network to balance the feeder loading to reach the best network configuration, which reduces voltage drop losses.…”

Section: Methodsmentioning

confidence: 99%

Comparison of different methods to face the huge increase in future load in power distribution network

Abood

Abdul-Wahhab²

2022

Bulletin EEI

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The main challenge of present distribution networks is the huge increase in demand for electricity especially in city center where the demand is increasing vertically for the same geographical area. This work presents the analyses of 5-Mail distribution network in Basra City/Iraq with conventional system 33/11/0.416 kV, at future load by estimating the increase in load 10 years later. The network is analyzed in terms of voltage drop, power losses, and the feeder loading. To improve the network the 33/11/0.416 kV system is re-analyzed at the expected future load using the optimal reconfiguration of the network or adding capacitor placement to reduce losses and voltage drop. The results of these methods are compared with the results of the network re-analyzed using the proposed 33/0.416 kV system at future load. The results show that the proposed method of upgrading the voltage level of distribution network is the best solution. The GIS software is used to locate the distribution transformers and lying of the underground cables. CYME software is used to simulate the electric distribution system and conduct the load flow and other analyses.The GIS software is used to locate the distribution transformers and lying of the underground cables. CYME software is used to simulate the electric distribution system and conduct the load flow and other analyses.

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Section: Methodsmentioning

confidence: 99%

Comparison of different methods to face the huge increase in future load in power distribution network

Abood

Abdul-Wahhab²

2022

Bulletin EEI

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“…is has been indicated by Malik et al in [3] and Nguyen et al in [4]. In this context, several methodologies and future techniques to optimize energy consumption with minimum consumer interaction have been proposed by many researchers [5][6][7].…”

Section: Introductionmentioning

confidence: 95%

Improvement of Energy Performance Index for Domestic Prosumers Based on Newly Proposed Dynamic Tariff and Rule-Based Strategy

Goswami

Sil

2022

International Transactions on Electrical Energy Systems

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A smart and intelligent energy management system (SIEMS) can make the existing system more reliable, robust, and cost-effective to deal with the present power scenario. This also initiates the necessity to develop a new dynamic tariff system and integrate renewable energy sources (RES) along with the conventional grid which in turn reduces carbon emission. Many countries have adopted different strategies for energy conservation based on energy conservation code, the main aim of which is to enforce design and development of household appliances for efficient power consumption. From data provided by utility sectors, it has been found that even in few countries 25% to 28% of the total energy is consumed by domestic sector and 45% of other residential loads also contribute a major part of the total domestic load consumed in any country. As a whole, residences, which consist of light electrical loads and home appliances constitute prosumers. The total energy consumed by prosumers is also intended by Bureau of energy efficiency, to make them fall under these codes (Energy Conservation Building Code) so that they can be treated on a scale of 1 star to 5 stars. This in turn will help in improving the energy performance index (EPI). In this paper, the optimal scheduling model of household appliances and energy storage system (ESS) has been designed based on the availability of renewable energy sources and newly proposed dynamic tariff system. To validate the efficiency of the model, we have comparatively evaluated the performance of the model with different feature selection methods and optimization techniques. A case study has been done and it has been found that the weighted K nearest neighbor method for feature selection and hybrid greedy particle swarm optimization (HGPSO) technique for optimization are performing better than other existing methods. The proposed model reflects the cost-effectiveness and improvement in EPI for prosumers.

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“…Binary model and multi linear functions are the two models used mainly for logistic regression. It can easily solve the classification problems to a predictive analysis based on the concept of probability [34]. The cost function can be analysed using sigmoid function.…”

Section: Logistic Regressionmentioning

confidence: 99%

Performance analysis of demand forecasting in energy consumption based on ensemble model

Dhanalakshmi

Ayyanathan

2022

Bulletin EEI

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Over the previous decade, energy usage has increased exponentially all over the world. The machine learning algorithms are used to classify the demand and requirement of off and evening peak load of southern regional load dispatch centre (SRLDC) data. In this paper, data are classified based on demand and requirement of both evening and off peak of day wise southern regional grid of Andhra Pradesh, Karnataka, Kerala, Tamilnadu, and Pondicherry of different states are proposed. The machine learning algorithms like k-nearest neighbors (KNN), random forest, and logistic regression have been adopted to classify the model. To improve this model efficiency, an ensemble learning method is used to increase the accuracy. The performance measure of state-wise outcome is determined by classifying its demand and requirement needs over its state energy consumption and with different classification algorithms and it is improved by using a combined method of ensemble model with accuracy of 86%.

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Optimization of location and size of distributed generations for maximizing their capacity and minimizing power loss of distribution system based on cuckoo search algorithm

Cited by 7 publications

References 27 publications

Comparison of different methods to face the huge increase in future load in power distribution network

Comparison of different methods to face the huge increase in future load in power distribution network

Improvement of Energy Performance Index for Domestic Prosumers Based on Newly Proposed Dynamic Tariff and Rule-Based Strategy

Performance analysis of demand forecasting in energy consumption based on ensemble model

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