scholarly journals The Improvement of Electric Power Losses Using Bank Capacitor and Tap Changer With Shark Smell Algorithm

Teknik ◽  
2020 ◽  
Vol 41 (3) ◽  
pp. 212-218
Author(s):  
Radiktyo Nindyo Sumarno ◽  
Susatyo Handoko ◽  
Mochammad Facta

One way to optimize the transmission line is to reduce electrical power losses. Tap changers on power transformers and bank capacitors can be used to regulate the system voltage resulting in lower power losses in the transmission line. Determining the value of tap settings and bank capacitors in the planning process is challenging to do with certainty. It is generally carried out through a trial and error mechanism using the power flow method. Since the determination of tap settings and bank capacitors values is difficult to do with certainty, this research was carried out with optimization with the shark smell algorithm. Such optimization aims to get a more appropriate tap changer and capacitor bank change values on the IEEE 30-bus system. In this study, several optimizations were carried out, namely optimization of tap settings, optimization of bank capacitors, and tap setting optimization combined with bank capacitors' optimization. Conducting tap setting optimization, we obtained an active power loss of 0.65% from the condition without optimization. In optimizing bank capacitors, we reduce active power losses of 0.90% compared to conditions without optimization. In optimizing the combination of tap setting and bank capacitors, the active power losses are reduced by 1.23%. Comparing the results of all these optimizations shows that the combination of bank tap setting and capacitor optimization is obtained by reducing the most active power losses. In this study, the reduction of active power losses resulted in 217.2 kW. The results show that the Shark Smell algorithm can provide better optimization results of 1.23% compared to conditions without optimization based on the test value.

Author(s):  
Adedayo A. Yusuff ◽  
Thapelo C. Mosetlhe ◽  
Temitope Raphael Ayodele

Abstract This paper presents a method for allocating active power losses in electric power networks to generators. A technique that uses current distribution factor is used to allocate losses to generator nodes. The core of the allocation scheme is based on graph theory and flows distribution in a network. Losses are only allocated based on the segment of a network that is used for power evacuation. Models of IEEE 14, 39, 57 and 118 test systems in PYPOWER 5.12 were used to test the scheme. It was observed that although the total network losses is minimised when optimal power flow is used for scheduling generation, however that does not translate to minimisation of loss allocation to some generators. The results obtained show that, the scheme can be used to allocate transmission network losses to generation nodes in electric power networks in a fair manner.


2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Neda Hantash ◽  
Tamer Khatib ◽  
Maher Khammash

In this paper, an improved particle swarm optimization method (PSO) is proposed to optimally size and place a DG unit in an electrical power system so as to improve voltage profile and reduce active power losses in the system. An IEEE 34 distribution bus system is used as a case study for this research. A new equation of weight inertia is proposed so as to improve the performance of the PSO conventional algorithm. This development is done by controlling the inertia weight which affects the updating velocity of particles in the algorithm. Matlab codes are developed for the adapted electrical power system and the improved PSO algorithm. Results show that the proposed PSO algorithm successfully finds the optimal size and location of the desired DG unit with a capacity of 1.6722 MW at bus number 10. This makes the voltage magnitude of the selected bus equal to 1.0055 pu and improves the status of the electrical power system in general. The minimum value of fitness losses using the applied algorithm is found to be 0.0.0406 while the average elapsed time is 62.2325 s. In addition to that, the proposed PSO algorithm reduces the active power losses by 31.6%. This means that the average elapsed time is reduced by 21% by using the proposed PSO algorithm as compared to the conventional PSO algorithm that is based on the liner inertia weight equation.


2017 ◽  
Vol 2017 (3) ◽  
pp. 65-70
Author(s):  
A.F. Zharkin ◽  
◽  
V.A. Novskyi ◽  
N.N. Kaplychnyi ◽  
A.V. Kozlov ◽  
...  

2016 ◽  
Vol 2016 (4) ◽  
pp. 23-25
Author(s):  
A.V. Krasnozhon ◽  
◽  
R.O. Buinyi ◽  
I.V. Pentegov ◽  
◽  
...  

Author(s):  
Souhil Mouassa ◽  
Tarek Bouktir

Purpose In the vast majority of published papers, the optimal reactive power dispatch (ORPD) problem is dealt as a single-objective optimization; however, optimization with a single objective is insufficient to achieve better operation performance of power systems. Multi-objective ORPD (MOORPD) aims to minimize simultaneously either the active power losses and voltage stability index, or the active power losses and the voltage deviation. The purpose of this paper is to propose multi-objective ant lion optimization (MOALO) algorithm to solve multi-objective ORPD problem considering large-scale power system in an effort to achieve a good performance with stable and secure operation of electric power systems. Design/methodology/approach A MOALO algorithm is presented and applied to solve the MOORPD problem. Fuzzy set theory was implemented to identify the best compromise solution from the set of the non-dominated solutions. A comparison with enhanced version of multi-objective particle swarm optimization (MOEPSO) algorithm and original (MOPSO) algorithm confirms the solutions. An in-depth analysis on the findings was conducted and the feasibility of solutions were fully verified and discussed. Findings Three test systems – the IEEE 30-bus, IEEE 57-bus and large-scale IEEE 300-bus – were used to examine the efficiency of the proposed algorithm. The findings obtained amply confirmed the superiority of the proposed approach over the multi-objective enhanced PSO and basic version of MOPSO. In addition to that, the algorithm is benefitted from good distributions of the non-dominated solutions and also guarantees the feasibility of solutions. Originality/value The proposed algorithm is applied to solve three versions of ORPD problem, active power losses, voltage deviation and voltage stability index, considering large -scale power system IEEE 300 bus.


2021 ◽  
Vol 4 (2) ◽  
pp. 38-43
Author(s):  
Linta Khalil ◽  
Mughees Riaz ◽  
M.Arslan Iqbal Awan ◽  
M.Kamran Liaquat Bhatti ◽  
Rabbia Siddique ◽  
...  

Utilization of new technologies and people lifestyle has greatly affected the world’s electricity market. This demands to design innovative renewable energy systems for efficient use of green energy. In terms of greenhouse gas emissions, electricity from traditional energy supplies has become particularly harmful for the world. To decrease the reliance on fossil fuels, it is need of time to enhance the renewable energy integration in the conventional energy systems. Renewable DGs integration in existing energy systems is not a simple task. To overcome challenges caused by enhanced penetration of renewable energy systems in existing networks, adaptation of smart techniques is essential. DGs Optimal size and selection of their suitable location for integration is crucial for cost effective power delivery to the consumers without compromising the quality of power. This paper presents impartial performance management by optimal network reconfiguration in parallel with renewable DGs and selecting suitable size for reducing active power losses, pollutant gas emissions and costs of annual operation. For analysis of active power losses, Fuzzy and SPEA2 based algorithms are used in MATLAB with IEEE BUS14 acting as load bus. While the cost of power generation and pollutant gases emissions are estimated using HOMER Pro software.


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