Tap changer optimisation using embedded differential evolutionary programming technique for loss control in power system

Over-compensation and under-compensation phenomena are two undesirable results in power system compensation. This will be not a good option in power system planning and operation. The non-optimal values of the compensating parameters subjected to a power system have contributed to these phenomena. Thus, a reliable optimization technique is mandatory to alleviate this issue. This paper presents a stochastic optimization technique used to fix the power loss control in a high demand power system due to the load increase, which causes the voltage decay problems leading to current increase and system loss increment. A new optimization technique termed as embedded differential evolutionary programming (EDEP) is proposed, which integrates the traditional differential evolution (DE) and evolutionary programming (EP). Consequently, EDEP was for solving optimizations problem in power system through the tap changer optimizations scheme. Results obtained from this study are significantly superior compared to the traditional EP with implementation on the IEEE 30-bus reliability test system (RTS) for the loss minimization scheme.

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Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system

Bulletin of Electrical Engineering and Informatics ◽

10.11591/eei.v8i3.1631 ◽

2019 ◽

Vol 8 (3) ◽

pp. 978-984

Author(s):

Nur Ainna Shakinah Abas ◽

Ismail Musirin ◽

Shahrizal Jelani ◽

Mohd Helmi Mansor ◽

Naeem M. S. Honnoon ◽

...

Keyword(s):

Monte Carlo ◽

Distributed Generation ◽

Distribution System ◽

Optimization Technique ◽

Evolutionary Programming ◽

Test System ◽

Voltage Profile ◽

Power Losses ◽

Programming Technique ◽

Distributed Generations

This paper presents the optimal multiple distributed generations (MDGs) installation for improving the voltage profile and minimizing power losses of distribution system using the integrated monte-carlo evolutionary programming (EP). EP was used as the optimization technique while monte carlo simulation is used to find the random number of locations of MDGs. This involved the testing of the proposed technique on IEEE 69-bus distribution test system. It is found that the proposed approach successfully solved the MDGs installation problem by reducing the power losses and improving the minimum voltage of the distribution system.

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Optimization of Automatic Transformer Tap Changer Using Cascaded-Evolutionary Programming Technique

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.785.429 ◽

2015 ◽

Vol 785 ◽

pp. 429-434

Author(s):

Mohamad Ariff Nur Hakim Mohamad Zahir ◽

Nur Ain binti Abd Manap ◽

Harizan Che Mat Haris ◽

Ismail Musirin ◽

Mohamad Fadhil Mohd Kamal

Keyword(s):

Evolutionary Programming ◽

Test System ◽

Load Flow ◽

Fine Tuning ◽

Computational Time ◽

Voltage Profile ◽

Instability Condition ◽

Programming Technique ◽

Acceptable Range ◽

Tap Changer

In power system, load variation can cause instability condition. Transformer Tap Changer (TTC) adjustment can be used to alleviate this condition. This paper proposes an algorithm to optimize the adjustment of TTC termed as Cascaded-Evolutionary Programming (EP). This is to allow fine-tuning process on the results if the optimized results are beyond the acceptable range. The Tests were conducted on IEEE 14-Bus Reliable Test System (RTS) to determine minimum Voltage Profile (VP),Vmin at selected load bus, using ordinary Load Flow thus maintaining the voltage at 0.9 p.u. to 1.5 p.u. The result demonstrates the pre-optimization and post-optimization of the minimum VP, Vmin in the system and proves that the proposed algorithm technique identifies the optimum value of TTC whilst reducing computational time.

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Multi-Objective Evolutionary Programming for Static VAR Compensator (SVC) in Power System Considering Contingencies (N-m)

International Journal of Power Electronics and Drive Systems (IJPEDS) ◽

10.11591/ijpeds.v9.i2.pp880-888 ◽

2018 ◽

Vol 9 (2) ◽

pp. 880

Author(s):

Nor Rul Hasma Abdullah ◽

Mahaletchumi A P Morgan ◽

Mahfuzah Mustafa ◽

Rosdiyana Samad ◽

Dwi Pebrianti

Keyword(s):

Power System ◽

Transmission Lines ◽

Power Flow ◽

Evolutionary Programming ◽

Test System ◽

Programming Technique ◽

Multi Objective ◽

Static Var Compensators ◽

Current Transmission ◽

Flexible Alternating Current Transmission

Static VAR Compensators (SVCs) is a Flexible Alternating Current Transmission System (FACTS) device that can control the power flow in transmission lines by injecting capacitive or inductive current components at the midpoint of interconnection line or in load areas. This device is capable of minimizing the overall system losses and concurrently improves the voltage stability. A line index, namely SVSI becomes indicator for the placement of SVC and the parameters of SVCs are tuned by using the multi-objective evolutionary programming technique, effectively able to control the power. The algorithm was tested on IEEE-30 Bus Reliability Test System (RTS). Comparative studies were conducted based on the performance of SVC in terms of their location and sizing for installations in power system.

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Multi-verse optimization based evolutionary programming technique for power scheduling in loss minimization scheme

IAES International Journal of Artificial Intelligence (IJ-AI) ◽

10.11591/ijai.v8.i3.pp292-298 ◽

2019 ◽

Vol 8 (3) ◽

pp. 292

Author(s):

Muhamad Hazim Lokman ◽

Ismail Musirin ◽

Saiful Izwan Suliman ◽

Hadi Suyono ◽

Rini Nur Hasanah ◽

...

Keyword(s):

Power Systems ◽

Power System ◽

Computational Intelligence ◽

Power Transmission ◽

Evolutionary Programming ◽

Test System ◽

Reliability Test ◽

Font Size ◽

Programming Technique ◽

Power Scheduling

The growth of computational intelligence technology has witnessed its application in numerous fields. Power system study is not left behind as far as computational intelligence trend is concerned. In power system community, optimization process is one of the crucial efforts for most remedial action to maintain the power system security. Basically, power scheduling refers to prior to fact action(such as scheduling generators to generate certain powers for next week). Power scheduling process is one of the most important routines in power systems. Scheduling of generators in a power transmission system is an important scheme; especially its offline studies to identify the security status of the system. This determines the cost effectiveness in power system planning. This paper investigates the performance of multi-verse based evolutionary programming(lowest EP) technique in the application of power system scheduling to ensure loss is gained by the system. Losses in the system can be controlled through this implementation which can be realized through the validation on a chosen reliability test system as the main model. Validation on <span style="font-size: 10.0pt; font-family: 'Times New Roman','serif'; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US">IEEE 30-Bus Reliability Test System resulted that both techniques are reliable and robust in addressing this issue.

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Application of UPFC for enhancement of voltage profile and minimization of losses using Fast Voltage Stability Index (FVSI)

Archives of Electrical Engineering ◽

10.2478/v10171-012-0020-4 ◽

2012 ◽

Vol 61 (2) ◽

pp. 239-250 ◽

Cited By ~ 6

Author(s):

M. Kumar ◽

P. Renuga

Keyword(s):

Power System ◽

Voltage Stability ◽

Reactive Power ◽

Optimization Technique ◽

Optimal Solution ◽

Stability Index ◽

Test System ◽

Unified Power Flow Controller ◽

Voltage Profile ◽

Voltage Stability Index

Application of UPFC for enhancement of voltage profile and minimization of losses using Fast Voltage Stability Index (FVSI)Transmission line loss minimization in a power system is an important research issue and it can be achieved by means of reactive power compensation. The unscheduled increment of load in a power system has driven the system to experience stressed conditions. This phenomenon has also led to voltage profile depreciation below the acceptable secure limit. The significance and use of Flexible AC Transmission System (FACTS) devices and capacitor placement is in order to alleviate the voltage profile decay problem. The optimal value of compensating devices requires proper optimization technique, able to search the optimal solution with less computational burden. This paper presents a technique to provide simultaneous or individual controls of basic system parameter like transmission voltage, impedance and phase angle, thereby controlling the transmitted power using Unified Power Flow Controller (UPFC) based on Bacterial Foraging (BF) algorithm. Voltage stability level of the system is defined on the Fast Voltage Stability Index (FVSI) of the lines. The IEEE 14-bus system is used as the test system to demonstrate the applicability and efficiency of the proposed system. The test result showed that the location of UPFC improves the voltage profile and also minimize the real power loss.

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Effect of SVC installation on loss and voltage in power system congestion management

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v14.i1.pp428-435 ◽

2019 ◽

Vol 14 (1) ◽

pp. 428 ◽

Cited By ~ 3

Author(s):

Nur Zahirah Mohd Ali ◽

Ismail Musirin ◽

Hasmaini Mohamad

Keyword(s):

Power System ◽

Voltage Stability ◽

Optimization Technique ◽

Stability Index ◽

Evolutionary Programming ◽

Congestion Management ◽

Optimal Operation ◽

Voltage Profile ◽

Voltage Stability Index ◽

Ac Transmission

In this paper, a new hybrid optimization technique is proposed namely Adaptive Embedded Clonal Evolutionary Programming (AECEP). This idea comes from the combination part of the clone in an Artificial Immune System (AIS) and then combined with Evolutionary Programming (EP). This technique was implemented to determine the optimal sizing of Flexible AC Transmission Systems (FACTS) devices. This study focused on the ability of Static Var Compensator (SVC) is used for the optimal operation of the power system as well as in reducing congestion in power system. In order to determine the location of SVC, the previous study has been done using pre-developed voltage stability index, Fast Voltage Stability Index (FVSI). Congested lines or buses will be identified based on the highest FVSI value for the purpose of SVC placement. The optimizations were conducted for the SVC sizing under single contingency, where SVC was modeled in steady state analysis. The objective function of this study is to minimize the power loss and improve the voltage profile along with the reduction of congestion with the SVC installation in the system. Validation on the IEEE 30 Bus RTS and IEEE 118 Bus RTS revealed that the proposed technique managed to reduce congestion in power system.

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Application of Immune Log-Normal Evolutionary Programming in Distributed Generation Installation

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v6.i3.pp730-736 ◽

2017 ◽

Vol 6 (3) ◽

pp. 730

Author(s):

M. H. Mansor ◽

I. Musirin ◽

M. M. Othman ◽

S. A. Shaaya ◽

S. A. Syed Mustaffa

Keyword(s):

Power System ◽

Distributed Generation ◽

Evolutionary Programming ◽

Test System ◽

Optimal Location ◽

Total System ◽

Transmission Network ◽

Artificial Immune ◽

A New Technique ◽

Log Normal

Nowadays, the location and sizing of distributed generation (DG) units in power system network are crucial to be at optimal as it will affect the power system operation in terms of stability and security. In this paper, a new technique termed as Immune Log-Normal Evolutionary Programming (ILNEP) is applied to find the optimal location and size of distributed generation units in power system network. Voltage stability is considered in solving this problem. The proposed technique has been tested on the IEEE 26 bus Reliability Test System to find the optimal location and size of distributed generation in transmission network. In order to study the performance of ILNEP technique in solving DG Installation problem, the results produced by ILNEP were compared with other meta-heuristic techniques like evolutionary programming (EP) and artificial immune system (AIS). It is found that the proposed technique gives better solution in term of lower total system loss compared to the other two techniques.

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Ranking Index in the Pareto Optimal Front Based Evolutionary Programming Technique for Best Selection of Several Optimal Multi-Objective Capacity Benefit Margins

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.785.506 ◽

2015 ◽

Vol 785 ◽

pp. 506-510

Author(s):

Muhammad Murtadha Othman ◽

Nurulazmi Abd Rahman ◽

Ismail Musirin

Keyword(s):

Electricity Market ◽

Evolutionary Programming ◽

Test System ◽

Pareto Optimal ◽

Programming Technique ◽

Pareto Optimal Front ◽

Multi Objective ◽

Transfer Capability ◽

Loss Of Load Expectation ◽

Ranking Index

The amount of power transfer between areas is purporting as imperative information required by the utility so that this will assist them towards an effective operation of electricity market performed in a deregulated power system. CBM is defined as the amount of the transfer capability reserved by the load-serving entities which will be used during the case of generation deficiency. This paper presents a new approach used to perform simultaneous determination of capacity benefit margin (CBM) for all areas by using the evolutionary programming (EP) technique. Ranking index in the Pareto optimal front cluster of total loss-of-load expectation (LOLE) and total LOLE difference will be used for selecting several best solutions of multi-objective CBMs. Eventually, performance of the proposed method is investigated thoroughly via a test system of modified IEEE-RTS79. Utilization of the proposed technique is superior in terms of offering flexibility to the utility in selecting several best solutions of multi-objective CBMs.

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FACTS location and size for reactive power system compensation through the multi-objective optimization

Archives of Control Sciences ◽

10.2478/v10170-010-0027-2 ◽

2010 ◽

Vol 20 (4) ◽

pp. 473-489 ◽

Cited By ~ 6

Author(s):

Messaoud Belazzoug ◽

Mohamed Boudour ◽

Karim Sebaa

Keyword(s):

Power System ◽

Reactive Power ◽

Test System ◽

Load Flow ◽

Electrical Network ◽

Multi Objective Optimization ◽

Nsga Ii ◽

Flow Equations ◽

Multi Objective ◽

System Compensation

FACTS location and size for reactive power system compensation through the multi-objective optimizationThe problem of the FACTS (Flexible Alternative Current Transmission System Devices) location and size for reactive power system compensation through the multi-objective optimization is presented in this paper. A new technique is proposed for the optimal setting, dimension and design of two kinds of FACTS namely: Static Volt Ampere reactive (VAR) Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC) handling the minimization of transmission losses in electrical network. Using the proposed scheme, the type, the location and the rating of FACTS devices are optimized simultaneously. The problem to solve is multi criteria under constraints related to the load flow equations, the voltages, the transformer turn ratios, the active and reactive productions and the compensation devices. Its solution requires the the advanced algorithms to be applied. Thus, we propose an approach based on the evolutionary algorithms (EA) to solve multi-criterion problem. It is similar to the NSGA-II method (Ellitist Non Dominated Sorting Genetic Algorithm). The Pareto front is obtained for continuous, discrete and multiple of five MVArs (Mega Volt Ampere reactive) of compensator devices for the IEEE 57-bus test system (IEEE bus test is a standard network).

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Index-based transmission for distributed generation in voltage stability and loss control incorporating optimization technique

IAES International Journal of Artificial Intelligence (IJ-AI) ◽

10.11591/ijai.v9.i2.pp244-251 ◽

2020 ◽

Vol 9 (2) ◽

pp. 244

Author(s):

Fareed Danial Ahmad Kahar ◽

Ismail Musirin ◽

Muhamad Faliq Mohamad Nazer ◽

Shahrizal Jelani ◽

Mohd Helmi Mansor

Keyword(s):

Distributed Generation ◽

Optimization Algorithm ◽

Voltage Stability ◽

Optimization Technique ◽

Stability Index ◽

Test System ◽

Voltage Security ◽

Grasshopper Optimization Algorithm ◽

Grasshopper Optimization ◽

Loss Control

The integration of Distributed Generation (DG) in a distribution network may significantly affect distribution performance. With the penetration of DG, voltage security is no longer an issue in the transmission network. This paper presents a study of Distributed Generation on the IEEE 26-Bus Reliability Test System (RTS) with the use of Fast Voltage Stability Index (FVSI) for determining its location and incorporated with Grasshopper Optimization Algorithm (GOA) to optimize the sizing of the DG. The study emphasizes the power loss of the system in which a comparison between Evolutionary Programming (EP) and Grasshopper Optimization Algorithm is done to determine which optimization technique gives an optimal result for the DG solution. The results show that the proposed algorithm is able to provide a slightly better result compared to EP.

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