Statistical Analysis for Active Power Loss Incorporating Distributed Generation in Distribution System

2019 ◽  
Author(s):  
Shrunkhala S. Halve ◽  
A. Koshti ◽  
R. Arya
Keyword(s):  
Statistical Analysis ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Active Power

scholarly journals MINIMIZING POWER LOSS BY PLACING DG OPTIMALLY IN DISTRIBUTION SYSTEM BY PSO TECHNIQUE

2021 ◽  
Vol 6 (4) ◽  
Author(s):  
Prakash D B ◽  
Lakshminarayana C
Keyword(s):  
Particle Swarm Optimization ◽  
Objective Function ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Active Power ◽  
Optimal Placement ◽  
Swarm Optimization ◽  
Intelligence Technique

— This paper presents optimal placement and sizing of Distributed Generation (DG) by using an intelligence technique called Particle Swarm Optimization (PSO). Here the objective function is considered as minimization of active power loss. The proposed methodology is applied and tested for IEEE 33 and IEEE 69 bus radial distribution systems. The result shows that the proposed algorithm is more effective.

scholarly journals Proposal of an Adaptive Neurofuzzy System to Control Flow Power in Distributed Generation Systems

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Helbert Eduardo Espitia ◽  
Iván Machón-González ◽  
Hilario López-García ◽  
Guzmán Díaz
Keyword(s):  
Statistical Analysis ◽  
Distributed Generation ◽  
Distribution System ◽  
Voltage Control ◽  
Control Flow ◽  
The Other ◽  
Charge Variation ◽  
Flow Power ◽  
Dynamics Identification ◽  
Neurofuzzy Systems

Systems of distributed generation have shown to be a remarkable alternative to a rational use of energy. Nevertheless, the proper functioning of them still manifests a range of challenges, including both the adequate energy dispatch depending on the variability of consumption and the interaction between generators. This paper describes the implementation of an adaptive neurofuzzy system for voltage control, regarding the changes observed in the consumption within the distribution system. The proposed design employs two neurofuzzy systems, one for the plant dynamics identification and the other for control purposes. This focus optimizes the controller using the model achieved through the identification of the plant, whose changes are produced by charge variation; consequently, this process is adaptively performed. The results show the performance of the adaptive neurofuzzy system via statistical analysis.

Application of Tabu Search for Optimal Placement and Sizing of Distributed Generation for Loss Reduction

2012 ◽  
Vol 433-440 ◽  
pp. 7190-7194 ◽  
Author(s):  
Nattachote Rugthaicharoencheep ◽  
Thong Lantharthong ◽  
Awiruth Ratreepruk ◽  
Jenwit Ratchatha
Keyword(s):  
Tabu Search ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Power Flow ◽  
Search Algorithm ◽  
Optimal Placement ◽  
Loss Reduction ◽  
Placement Problem ◽  
Bus Voltage

This paper presents the optimal and sizing of distributed generation (DG) placement in a radial distribution system for loss reduction. The main emphasis of this paper is to identify proper locations for installing DGs in a distribution system to reduce active power loss and improve bus voltages. Nevertheless, proper placement and sizing of DG units are not straightforward to be identified as a number of their positions and capacities need to be determined. It is therefore proposed in this paper to solve a DG placement problem based on a Tabu search algorithm. The objective function of the problem is to minimize the system loss subject to power flow constraints, bus voltage limits, pre specified number of DGs, and their allowable total installed capacity, and only one distributed generator for one installation position. The effectiveness of the methodology is demonstrated by a practical sized distribution system consisting of 69 bus and 48 load points. The results show that the optimal DG placement and sizing can be identified to give the minimum power loss while respecting all the constraints.

scholarly journals An Enhanced Quantum-Behaved Particle Swarm Algorithm for Reactive Power Optimization considering Distributed Generation Penetration

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Runhai Jiao ◽  
Bo Li ◽  
Yuancheng Li ◽  
Lingzhi Zhu
Keyword(s):  
Distributed Generation ◽  
Power Loss ◽  
Reactive Power ◽  
Power Optimization ◽  
Particle Swarm ◽  
Active Power ◽  
Particle Swarm Algorithm ◽  
Reactive Power Optimization ◽  
Distributed Generations ◽  
Better Than

This paper puts forward a novel particle swarm optimization algorithm with quantum behavior (QPSO) to solve reactive power optimization in power system with distributed generation. Moreover, differential evolution (DE) operators are applied to enhance the algorithm (DQPSO). This paper focuses on the minimization of active power loss, respectively, and uses QPSO and DQPSO to determine terminal voltage of generators, and ratio of transformers, switching group number of capacitors to achieve optimal reactive power flow. The proposed algorithms are validated through three IEEE standard examples. Comparing the results obtained from QPSO and DQPSO with those obtained from PSO, we find that our algorithms are more likely to get the global optimal solution and have a better convergence. What is more, DQPSO is better than QPSO. Furthermore, with the integration of distributed generation, active power loss has decreased significantly. Specifically, PV distributed generations can suppress voltage fluctuation better than PQ distributed generations.

scholarly journals Enhanced sunflower optimization for placement distributed generation in distribution system

2021 ◽  
Vol 11 (1) ◽  
pp. 107
Author(s):  
Thuan Thanh Nguyen
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Optimization Problem ◽  
Test System ◽  
Loss Reduction ◽  
Power Loss Reduction ◽  
Distribution Generation

Installation of distribution generation (DG) in the distribution system gains many technical benefits. To obtain more benefits, the location and size of DG must be selected with the appropriate values. This paper presents a method for optimizing location and size of DG in the distribution system based on enhanced sunflower optimization (ESFO) to minimize power loss of the system. In which, based on the operational mechanisms of the original sunflower optimization (SFO), a mutation technique is added for updating the best plant. The calculated results on the 33 nodes test system have shown that ESFO has proficiency for determining the best location and size of DG with higher quality than SFO. The compared results with the previous methods have also shown that ESFO outperforms to other methods in term of power loss reduction. As a result, ESFO is a reliable approach for the DG optimization problem.

scholarly journals Optimal sizing and location of multiple distributed generation for power loss minimization using genetic algorithm

2019 ◽  
Vol 16 (2) ◽  
pp. 956
Author(s):  
Abdulhamid Musa ◽  
Tengku Juhana Tengku Hashim
Keyword(s):  
Genetic Algorithm ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Total Power ◽  
Power Losses ◽  
Loss Minimization ◽  
Power Constraints ◽  
Voltage Deviation ◽  
Power Limits

This paper presents a Genetic Algorithm (GA) for optimal location and sizing of multiple distributed generation (DG) for loss minimization. The study is implemented on a 33-bus radial distribution system to optimally allocate different numbers of DGs through the minimization of total active power losses and voltage deviation at power constraints of 0 – 2 MW and 0 – 3 MW respectively. The study proposed a PQ model of DG and Direct Load Flow (DLF) technique that uses Bus Incidence to Branch current (BIBC) and Branch Current to Bus Voltage (BCBV) matrices. The result obtained a minimum base case voltage level of 0.9898 p.u at bus 18 with variations of voltage improvements at other buses after single and multiple DG allocations in the system. Besides, the total power loss before DG allocation is observed as 0.2243 MW, and total power loss after DG allocation was determined based on the power constraints. Various optimal locations were seen depending on the power limits of different DG sizes. The results have shown that the impact of optimal allocation and sizing of three DG is more advantageous concerning voltage improvement, reduction of the voltage deviation and also total power loss in the distribution system. The results obtained in the 0 – 2 MW power limit is consistent to the 0 – 3 MW power limits regarding the influence of allocating DG to the network and minimization of total power losses.

scholarly journals DG integration to distribution system with active power injection control

2020 ◽  
Vol 11 (2) ◽  
pp. 692
Author(s):  
P. V. V Satyanarayana ◽  
P. V. Ramana Rao
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Electrical Power ◽  
Active Power ◽  
Control Technique ◽  
Integration Scheme ◽  
Electrical Power System ◽  
Grid Simulation ◽  
Power Injection ◽  
Injection Control

Conventional methodology for electrical power generation is vulnerable due to environmental limitations and the availability of fuel. Distributed generation, offering virtuous benefits to the market partakers, is trending in electrical power system in modern era. This paper presents the distributed generation integration to grid with active power injection control. Distributed generation source delivers DC power which is processed through square wave inverter. Inverter circuit is controlled using a simple control technique to match grid code. Fixing the current reference and varying the same, analysis is carried out for grid integration scheme of distributed generation injecting active power to grid. Simulation work is carried out and results are shown using MATLAB/SIMULINK software.

scholarly journals Recloser-Fuse settings in distribution systems with optimizing multiple distributed generation considering technical aspects

2020 ◽  
Vol 17 (3) ◽  
pp. 1135
Author(s):  
Ahmed Mohamed Abdelbaset ◽  
AboulFotouh A. Mohamed ◽  
Essam Abou El-Zahab ◽  
M. A. Moustafa Hassan
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Test System ◽  
Optimal Size ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Power Loss Reduction ◽  
System Power

<p><span>With the widespread of using distributed generation, the connection of DGs in the distribution system causes miscoordination between protective devices. This paper introduces the problems associated with recloser fuse miscoordination (RFM) in the presence of single and multiple DG in a radial distribution system. Two Multi objective optimization problems are presented. The first is based on technical impacts to determine the optimal size and location of DG considering system power loss reduction and enhancement the voltage profile with a certain constraints and the second is used for minimizing the operating time of all fuses and recloser with obtaining the optimum settings of fuse recloser coordination characteristics. Whale Optimizer algorithm (WOA) emulated RFM as an optimization problem. The performance of the proposed methodology is applied to the standard IEEE 33 node test system. The results show the robustness of the proposed algorithm for solving the RFM problem with achieving system power loss reduction and voltage profile enhancement.</span></p>

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