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.

scholarly journals Capacity-Based Optimization Using Whale Optimization Technique of a Power Distribution Network

2020 ◽  
Author(s):  
Bawoke Simachew ◽  
baseem khan ◽  
Josep M Guerrero ◽  
Sanjeevikumar *Padmanaban ◽  
Om Prakash Mahela ◽  
...  
Keyword(s):  
Distributed Generation ◽  
Power Distribution ◽  
Optimization Technique ◽  
Distribution Network ◽  
Optimal Size ◽  
Voltage Profile ◽  
Power Distribution Network ◽  
Multi Objective ◽  
Whale Optimization ◽  
Profile Management

In the power distribution network, real power loss and voltage profile management are critical issues. By providing active and reactive power support, both of these issues can be managed. This paper utilized the Meta heuristic-based method for the optimal size and placement of distributed generation (DG) and capacitor (QG) sources for loss reduction by incorporating network current carrying capacity constraint in the optimization problem. The overall problem is optimized using an upgraded method of the fitness assignment and solution chasing based on the aggregate approach called Multi-objective Whale Optimization Algorithm (MWOA). Wind and solar photovoltaic sources are utilized as the distributed generation with their probabilistic outputs. The developed method is tested using two feeders of practical Bahir Dar Distribution Network, Ethiopia. The results of loss minimization and voltage profile management with MWOA are compared with multi-objective particle swam optimization (MPSO) with an equal number of iteration to show the superiority of the developed method.

scholarly journals Optimization of fuzzy controllers for a radial distribution network

2019 ◽  
Vol 13 (1) ◽  
pp. 17-23
Author(s):  
Helbert Eduardo Espitia Cuchango ◽  
Iván Machón González ◽  
Hilario López García ◽  
Domingo Guzmán Díaz González
Keyword(s):  
Energy Distribution ◽  
Distributed Generation ◽  
Radial Distribution ◽  
Distribution Systems ◽  
Distribution Network ◽  
Voltage Profile ◽  
Fuzzy Controllers ◽  
Descent Algorithm ◽  
Distributed Approach

Energy distribution systems present alterations in the voltage profile in their nodes when distributed generation elements are installed. As a consequence, tension can be risen in a level beyond the admissible. This paper presents the optimization to three fuzzy controllers located in a distribution network with radial topology. The optimization of each controller is performed using the maximum descent algorithm, which is separately carried out; thus, having a distributed approach. The interaction between generators is considered to perform this process; the results show that the adjustment of the controllers is achieved

Plant propagation algorithm for integration of distributed generation in power systems

2018 ◽  
Vol 37 (1) ◽  
pp. 401-417
Author(s):  
Shreya Mahajan ◽  
Shelly Vadhera
Keyword(s):  
Power System ◽  
Objective Function ◽  
Distributed Generation ◽  
Weighting Factor ◽  
Voltage Profile ◽  
Plant Propagation ◽  
Content Type ◽  
Multi Objective ◽  
Propagation Algorithm ◽  
Optimisation Techniques

Purpose The purpose of this study/paper is to integrate distributed generation optimally in power system using plant propagation algorithm. Distributed generation is a growing concept in the field of electricity generation. It mainly comprises small generation units installed at calculated points of a power system network. The challenge of optimal allocation and sizing of DG is of utmost importance. Design/methodology/approach Plant propagation algorithm and particle swarm optimisation techniques have been implemented where a weighting factor-based multi-objective function is minimised. The objective is to cut down real losses and to improve the voltage profile of the system. Findings The results obtained using plant propagation algorithm technique for IEEE 33-bus systems are compared to those attained using particle swarm optimisation technique. The paper deals with the optimisation of weighting factor-based objective function, which counterpoises the losses and improves the voltage profile of the system and, therefore, helps to deliver the best outcomes. Originality/value This paper fulfils an identified need to study the multi-objective optimisation techniques for integration of distributed generation in the concerned power system network. The paper proposes a novel plant-propagation-algorithm-based technique in appropriate allocation and sizing of distributed generation unit.

scholarly journals Optimal capacitor placement in a distribution system using ETAP software

2019 ◽  
Vol 15 (2) ◽  
pp. 650
Author(s):  
M. J. Tahir ◽  
Badri. A. Bakar ◽  
M. Alam ◽  
M. S. Mazlihum
Keyword(s):  
Power System ◽  
Objective Function ◽  
Power Factor ◽  
Distribution System ◽  
Voltage Drop ◽  
Optimization Technique ◽  
Voltage Profile ◽  
Power Losses ◽  
Capacitor Placement ◽  
Optimal Capacitor Placement

<p>Mostly loads are inductive in nature in content of distribution side for any power system. Due to which system faces high power losses, voltage drop and reduction in system power factor. Capacitor placement is a common method to improve these factors. To maximize the reduction of inductive load impact, optimal capacitor placement (OCP) is necessary with the objective function of system cost minimization for voltage profile enhancement, power factor improvement and power losses minimization. As OCP is a non-linear problem with equality and inequality limitations, so the stated objective depends upon he placement and sizes of the capacitor banks. Electrical transient analyzer program (ETAP) software is used for the evaluation and modelling the power systems and genetic algorithm (GA) is used as an optimization technique for the minimization of the objective function. In this paper, to show the effectiveness of the technique IEEE 4bus,33bus system and NTDC 220KV real time grid system is modelled and evaluated in terms of objective minimization i-e maximum cost saving of the power system</p>

scholarly journals Optimal planning of RDGs in electrical distribution networks using hybrid SAPSO algorithm

2020 ◽  
Vol 10 (6) ◽  
pp. 6153
Author(s):  
Mohammed Hamouda Ali ◽  
Mohammed Mehanna ◽  
Elsaied Othman
Keyword(s):  
Renewable Energy ◽  
Radial Distribution ◽  
Distribution Network ◽  
Distribution Networks ◽  
Sensitivity Factor ◽  
Sensitivity Index ◽  
Voltage Profile ◽  
Power Losses ◽  
Electrical Distribution ◽  
The Impact

The impact of the renewable distributed generations (RDGs), such as photovoltaic (PV) and wind turbine (WT) systems can be positive or negative on the system, based on the location and size of the DG. So, the correct location and size of DG in the distribution network remain an obstacle to achieving their full possible benefits. Therefore, the future distribution networks with the high penetration of DG power must be planned and operated to improve their efficiency. Thus, this paper presents a new methodology for integrated of renewable energy-based DG units with electrical distribution network. Since the main objective of the proposed methodology is to reduce the power losses and improve the voltage profile of the radial distribution system (RDS). In this regard, the optimization problem was formulated using loss sensitivity factor (LSF), simulated annealing (SA), particle swarm optimization (PSO) and a combination of loss sensitivity index (LSI) with SA & PSO (LSISA, LSIPSO) respectively. This paper contributes a new methodology SAPSO, which prevents the defects of SA & PSO. Optimal placement and sizing of renewable energy-based DG tested on 33-bus system. The results demonstrate the reliability and robustness of the proposed SAPSO algorithm to find the near-optimal position and size of the DG units to mitigate the power losses and improve the radial distribution system's voltage profile.

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 Annual Cost and Loss Minimization in a Radial Distribution Network by Capacitor Allocation Using PSO

2021 ◽  
Vol 11 (24) ◽  
pp. 11840
Author(s):  
Muhammad Bilal ◽  
Mohsin Shahzad ◽  
Muhammad Arif ◽  
Barkat Ullah ◽  
Suhaila Badarol Hisham ◽  
...  
Keyword(s):  
Objective Function ◽  
Radial Distribution ◽  
Annual Cost ◽  
Reactive Power ◽  
Optimal Solution ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Use Case ◽  
Voltage Profile ◽  
Sensitivity Indices

Increasing power demand from passive distribution networks has led to deteriorated voltage profiles and increased line flows. This has increased the annual operations and installation costs due to unavoidable reinforcement equipment. This work proposes the reduction in annual costs by optimal placement of capacitors used to alleviate power loss in radial distribution networks (RDNs). The optimization objective function is formulated for the reduction in operation costs by (i) reducing the active and reactive power losses, and (ii) the cost and installation of capacitors, necessary to provide the reactive power support and maintain the voltage profile. Initially, the network buses are ranked according to two loss sensitivity indices (LSIs), i.e., active loss sensitivity with respect to node voltage (LSI1) and reactive power injection (LSI2). The sorted bus list is then fed to the particle swarm optimization (PSO) for solving the objective function. The efficacy of the proposed work is tested on different IEEE standard networks (34 and 85 nodes) for different use cases and load conditions. In use case 1, the values finalized by the algorithm are selected without considering their market availability, whereas in use case 2, market-available capacitor sizes close to the optimal solution are selected. Furthermore, the static and seasonal load profiles are considered. The results are compared with recent methods and have shown significant improvement in terms of annual cost, losses and line flows reduction, and voltage profile.

scholarly journals Optimasi Aliran Daya pada Sistem Kelistrikan Opsi Nuklir Berdasarkan Multi-Objective Function: Fuel Cost dan Flat Voltage Profile

2017 ◽  
Vol 18 (2) ◽  
pp. 75
Author(s):  
Rizki Firmansyah Setya Budi ◽  
Sarjiya Sarjiya ◽  
Sasongko Hadi Pramono
Keyword(s):  
Objective Function ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Voltage Profile ◽  
Fuel Cost ◽  
Multi Objective ◽  
Optimal Power

Tujuan dari pengoperasian sistem tenaga listrik adalah untuk memasok daya dengan kualitas baik dan biaya pembangkitan seminimal mungkin. Kualitas yang baik membutuhkan biaya yang lebih besar, sehingga untuk mencapai tujuan tersebut diperlukan optimasi dengan fungsi obyektif yang bertujuan untuk memaksimalkan kualitas sekaligus meminimalkan biaya. Penelitian ini bertujuanuntuk mendapatkan kondisi aliran daya optimal atau optimal power flow (OPF) dari segi biaya pembangkitan maupun kualitas tenaga listrik di suatu sistem kelistrikan dengan opsi nuklir pada waktu beban puncak dengan menggabungkan fungsi obyektif fuel cost dan flat voltage profile. Fungsi obyektif fuel cost bertujuan untuk meminimalkan biaya pembangkitan sedangkan fungsi obyektif flat voltage profile bertujuan untuk memaksimalkan kualitas dengan meminimalkan perbedaan/variasi tegangan dalam sebuah sistem. Penelitian dilakukan melalui studi literatur, penentuan fungsi obyektif optimasi, penggabungan fungsi objektif, simulasi menggunakan contoh kasus dan analisis sensitivitas. Contoh kasus menggunakan sistem IEEE 9 Bus yang telah ditambahkan fungsi bahan bakar PLTN, PLTU, dan PLTG. Simulasi menggunakan program bantu ETAP 12.6.0. Analisis sensitivitas dilakukan dengan menggunakan nilai pembobotan dari 0-100% untuk tiap fungsi obyektif. Hasil simulasi menunjukkan bahwa OPF dicapai pada faktor pembebanan 60% untuk fuel cost dan 40% untuk flat voltage profile. Biaya pembangkitan padakondisi optimal tersebut sebesar 7266 US$/jam dengan selisih tegangan maksimum minimumnya sebesar 2,85%. Pada sistem ini PLTU membangkitkan daya sebesar 133,2 MW + 22,1 MVar dan PLTG sebesar 80,7 MW + 13,8 MVar. Sedangkan PLTN membangkitkan daya sebesar 89,9 MW + 12,9 Mvar dan akan ekonomis jika membangkitkan daya kurang dari 90 MW.

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