The document discusses distribution network reconfiguration (DNR) using an improved artificial bee colony (IABC) algorithm to reduce power losses. It first introduces the motivation for DNR due to increasing electricity demand. It then summarizes previous related work applying optimization techniques like ABC, PSO, GA to DNR. The methodology section explains the IABC technique, which adds an inertial weight to the ABC algorithm inspired by PSO. Testing on the 33-bus system shows IABC achieves the lowest power losses of 107.1 kW, reducing losses by 47.1 kW compared to ABC. This translates to estimated annual cost savings of RM72,000.
I have done my internship at Institut Kemahiran Belia Negara (IKBN) Bukit Mertajam as teacher/tutor in three subject which is Islamic Education, Entrepreneurship and Leadership (Kepimpinan)
I have done my internship at Institut Kemahiran Belia Negara (IKBN) Bukit Mertajam as teacher/tutor in three subject which is Islamic Education, Entrepreneurship and Leadership (Kepimpinan)
Case study of ms1525 energy efficiency and renewable energy code of practice.Steve Lojuntin
Paper presented at the seminar in Kuala Lumpur on 12 September 2019. "Achieving Sustainable Development Goals Through The Application of MS1525 : Code of Practice – Energy Efficiency & Use of Renewable Energy for Non-residential Buildings".
Tech Vidhya is the premier IT and Telecom training institute of India that is running its quality training courses since last decade and we deliver what we promise. Tech Vidhya is the leading training institute in telecom and IT sector that offers various Telecom, telecommunication, Networking and IT/Software courses in an efficient and friendly manner. We are having the highly qualified and experienced trainers for all the courses. The trainers are updated with the latest technologies and they are working on various live projects on India’s top telecom/IT companies.
Case study of ms1525 energy efficiency and renewable energy code of practice.Steve Lojuntin
Paper presented at the seminar in Kuala Lumpur on 12 September 2019. "Achieving Sustainable Development Goals Through The Application of MS1525 : Code of Practice – Energy Efficiency & Use of Renewable Energy for Non-residential Buildings".
Tech Vidhya is the premier IT and Telecom training institute of India that is running its quality training courses since last decade and we deliver what we promise. Tech Vidhya is the leading training institute in telecom and IT sector that offers various Telecom, telecommunication, Networking and IT/Software courses in an efficient and friendly manner. We are having the highly qualified and experienced trainers for all the courses. The trainers are updated with the latest technologies and they are working on various live projects on India’s top telecom/IT companies.
VTT:n mukaan tuuliennusteiden virheistä aiheutuvat kustannukset voidaan jopa puolittaa, kun tuulivoimaennusteet tehdään useille maantieteellisesti hajautetuille tuulipuistoille yksittäisten tuulipuistojen sijasta. VTT on myös selvittänyt tuotantovaihtelujen tasaantumista Pohjoismaiden alueella. Tuloksia voidaan hyödyntää säätövoimatarpeen suunnittelussa ja tuulivoiman vaihtelun ennustamisessa.
Run time dynamic partial reconfiguration using microblaze soft core processor...eSAT Journals
aydeshmukh@gmail.com
Abstract
DSP Application requires a fast computations & flexibility of the design. Partial Reconfiguration (PR) is an advanced technique,
which improves the flexibility of FPGAs by allowing portions of a design to be reconfigured at runtime by overwriting parts of the
configuration memory. In this paper we are using microblaze soft core processor & ICAP Port to reconfigure the FPGA at runtime.
ICAP is accessed through a light-weight custom IP which requires bit stream length, go, and done signal to interface to a system that
provides partial bit stream data. The partial bit stream is provided by the processor system by reading the partial bit files from the
compact flash card. Our targeted DSP application is matrix multiplication; we are reconfiguring design by changing partial modules
at run time. To change the partial bit stream we interfaces a microblaze Soft processor & using a UART interface.ISE13.1 &
PlanAhead is used for partial reconfiguration of FPGA .EDK is used for microblaze soft processor design & ICAP Interface .The
simulation is done using Chip Scope Logic Analyzer & the complete hardware implementation is done on Xilinx VIRTEX -6 ML605
Platform.
Keywords — PlanAhead, EDK, Dynamic partial reconfiguration, ICAP, Matrix multiplication, Chipscope pro analysis,
DSP application, Microblaze processor
Networks community detection using artificial bee colony swarm optimizationAboul Ella Hassanien
Community structure identification in complex networks has been an important research topic in recent years. Community detection can be viewed as an optimization problem in which an objective quality function that captures the intuition of a community as a group of nodes with better internal connectivity than external connectivity is chosen to be optimized. In this work Artificial bee
colony (ABC) optimization has been used as an effective optimization technique to solve the community detection problem with the advantage that the number of
communities is automatically determined in the process. However, the algorithm performance is influenced directly by the quality function used in the optimization
process. A comparison is conducted between different popular communities’ quality measures when used as an objective function within ABC. Experiments on real life networks show the capability of the ABC to successfully find an optimized community structure based on the quality function used.
This is about Comparative Analysis of Artificial Bee Colony and Improve Cuckoo Search algorithm, a thesis work done by us. Finally it is published on February-10-2015 on IJARAI. Here you will find the basic of ABC algorithm, ICS algorithm and the comparison between them.
A brief introduction on the principles of particle swarm optimizaton by Rajorshi Mukherjee. This presentation has been compiled from various sources (not my own work) and proper references have been made in the bibliography section for further reading. This presentation was made as a presentation for submission for our college subject Soft Computing.
Simultaneous network reconfiguration and capacitor allocations using a novel ...IJECEIAES
Power loss and voltage magnitude fluctuations are two major issues in distribution networks that have drawn a lot of attention. Combining two of the numerous strategies for solving these problems and dealing with them simultaneously to get more effective outcomes is essential. Therefore, this study hybridizes the network reconfiguration and capacitor allocation strategies, proposing a novel dingo optimization algorithm (DOA) to solve the optimization problems. The optimization problems for simultaneous network reconfiguration and capacitor allocations were formulated and solved using a novel DOA. To demonstrate its effectiveness, DOA’s results were contrasted with those of the other optimization techniques. The methodology was validated on the IEEE 33-bus network and implemented in the MATLAB program. The results demonstrated that the best network reconfiguration was accomplished with switches 7, 11, 17, 27, and 34 open, and buses 8, 29, and 30 were the best places for capacitors with ideal sizes of 512, 714, and 495 kVAr, respectively. The network voltage profile was significantly improved as the least voltage at bus 18 was increased to 0.9530 p.u. Furthermore, the overall real power loss was significantly mitigated by 48.87%, which, when compared to the results of other methods, was superior.
Improvement of voltage profile for large scale power system using soft comput...TELKOMNIKA JOURNAL
In modern power system operation, control, and planning, reactive power as part of power system component is very important in order to supply electrical load such as an electric motor. However, the reactive current that flows from the generator to load demand can cause voltage drop and active power loss. Hence, it is essential to install a compensating device such as a shunt capacitor close to the load bus to improve the voltage profile and decrease the total power loss of transmission line system. This paper presents the application of a genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC)) to obtain the optimal size of the shunt capacitor where those capacitors are located on the critical bus. The effectiveness of the proposed technique is examined by utilizing Java-Madura-Bali (JAMALI) 500 kV power system grid as the test system. From the simulation results, the PSO and ABC algorithms are providing satisfactory results in obtaining the capacitor size and can reduce the total power loss of around 15.873 MW. Moreover, a different result is showed by the GA approach where the power loss in the JAMALI 500kV power grid can be compressed only up to 15.54 MW or 11.38% from the power system operation without a shunt capacitor. The three soft computing techniques could also maintain the voltage profile within 1.05 p.u and 0.95 p.u.
Coordinated planning in improving power quality considering the use of nonlin...IJECEIAES
Power quality has an important role in the distribution of electrical energy. The use of non-linear load can generate harmonic spread which can reduce the power quality in the radial distribution system. This research is in form of coordinated planning by combining distributed generation placement, capacitor placement and network reconfiguration to simultaneously minimize active power losses, total harmonic distortion (THD), and voltage deviation as an objective function using the particle swarm optimization method. This optimization technique will be tested on two types of networks in the form 33-bus and 69-bus IEEE Standard Test System to show effectiveness of the proposed method. The use of MATLAB programming shows the result of simulation of increasing power quality achieved for all scenario of proposed method.
Determination of location and capacity of distributed generations with recon...IJECEIAES
The use of non-linear loads and the integration of renewable energy in electricity network can cause power quality problems, especially harmonic distortion. It is a challenge in the operation and design of the radial distribution system. This can happen because harmonics that exceed the limit can cause interference to equipment and systems. This study will discuss the determination of the optimal location and capacity of distributed generation (DG) and network reconfiguration in the radial distribution system to improve the quality of electric power, especially the suppression of harmonic distribution. This study combines the optimal location and capacity of DG and network reconfiguration using the particle swarm optimization method. In addition, this research method is implemented in the distribution system of Bandar Lampung City by considering the effect of using nonlinear loads to improve power quality, especially harmonic distortion. The inverter-based DG type used considers the value of harmonic source when placed. The combination of the proposed methods provides an optimal solution. Increased efficiency in reducing power losses up to 81.17% and %total harmonic distortion voltage (THDv) is below the allowable limit.
Network Reconfiguration in Distribution Systems Using Harmony Search AlgorithmIOSRJEEE
This manuscript explores feeder reconfiguration in distribution networks and presents an efficient method to optimize the radial distribution system by means of simultaneous reconfiguration. Network Reconfiguration of radial distribution system is a significant way of altering the power flow through the lines. This assessment presents a modern method to solve the network reconfiguration problem with an objective of minimizing real power loss and improving the voltage profile in radial distribution system (RDS). A precise and load flow algorithm is applied and the objective function is formulated to solve the problem which includes power loss minimization. HSA Algorithm is utilized to restructure and identify the optimal strap switches for minimization of real power loss in a distribution network.. The strategy has been tested on IEEE 33-bus and 69- bus systems to show the accomplishment and the adequacy of the proposed technique. The results demonstrate that a significant reduction in real power losses and improvement of voltage profiles.
Performance comparison of distributed generation installation arrangement in ...journalBEEI
Placing Distributed Generation (DG) into a power network should be planned wisely. In this paper, the comparison of having different installation arrangement of real-power DGs in transmission system for loss control is presented. Immune-brainstorm-evolutionary programme (IBSEP) was chosen as the optimization technique. It is found that optimizing fixed-size DGs locations gives the highest loss reduction percentage. Apart from that, scattered small-sized DGs throughout a network minimizes transmission loss more than allocating one biger-sized DG at a location.
Network loss reduction and voltage improvement by optimal placement and sizin...nooriasukmaningtyas
Minimization of real power loss and improvement of voltage authenticity of
the network are amongst the key issues confronting power systems owing to
the heavy demand development problem, contingency of transmission and
distribution lines and the financial costs. The distributed generators (DG) has
become one of the strongest mitigating strategies for the network power loss
and to optimize voltage reliability over integration of capacitor banks and
network reconfiguration. This paper introduces an approach for the
optimizing the placement and sizes of different types of DGs in radial
distribution systems using a fine-tuned particle swarm optimization (PSO).
The suggested approach is evaluated on IEEE 33, IEEE 69 and a real
network in Malaysian context. Simulation results demonstrate the
productiveness of active and reactive power injection into the electric power
system and the comparison depicts that the suggested fine-tuned PSO
methodology could accomplish a significant reduction in network power loss
than the other research works.
Optimal electric distribution network configuration using adaptive sunflower ...journalBEEI
Network reconfiguration (NR) is a powerful approach for power loss reduction in the distribution system. This paper presents a method of network reconfiguration using adaptive sunflower optimization (ASFO) to minimize power loss of the distribution system. ASFO is developed based on the original sunflower optimization (SFO) that is inspired from moving of sunflower to the sun. In ASFO, the mechanisms including pollination, survival and mortality mechanisms have been adjusted compared to the original SFO to fit with the network reconfiguration problem. The numerical results on the 14-node and 33-node systems have shown that ASFO outperforms to SFO for finding the optimal network configuration with greater success rate and better obtained solution quality. The comparison results with other previous approaches also indicate that ASFO has better performance than other methods in term of optimal network configuration. Thus, ASFO is a powerful method for the NR.
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...IAEME Publication
Distribution system is a critical link between the electric power distributor and the consumers. Most of the distribution networks commonly used by the electric utility is the radial distribution network. However in this type of network, it has technical issues such as enormous power losses which affect the quality of the supply. Nowadays, the introduction of Distributed Generation (DG) units in the system help improve and support the voltage profile of the network as well as the performance of the system components through power loss mitigation. In this study network reconfiguration was done using two meta-heuristic algorithms Particle Swarm Optimization and Gravitational Search Algorithm (PSO-GSA) to enhance power quality and voltage profile in the system when simultaneously applied with the DG units. Backward/Forward Sweep Method was used in the load flow analysis and simulated using the MATLAB program. Five cases were considered in the Reconfiguration based on the contribution of DG units. The proposed method was tested using IEEE 33 bus system. Based on the results, there was a voltage profile improvement in the system from 0.9038 p.u. to 0.9594 p.u.. The integration of DG in the network also reduced power losses from 210.98 kW to 69.3963 kW. Simulated results are drawn to show the performance of each case.
Multi-objective distributed generation integration in radial distribution sy...IJECEIAES
This paper introduces a new approach based on a chaotic strategy and a neural network algorithm (NNA), called chaotic-based NNA (CNNA), to solve the optimal distributed generation allocation (ODGA), in the radial distribution system (RDS). This consists of determining the optimal locations and sizes of one or several distributed generations (DGs) to be inserted into the RDS to minimize one or multiple objectives while meeting a set of security limits. The robustness of the proposed method is demonstrated by applying it to two different typical RDSs, namely IEEE 33bus and 69-bus. In this regard, simulations are performed for three DGs in the cases of unity power factor (UPF) and optimal power factor (OPF), considering single and multi-objective optimization, by minimizing the total active losses and improving the voltage profile, voltage deviation (VD) and voltage stability index (VSI). Compared to its original version and recently reported methods, the CNNA solutions are more competitive without increasing the complexity of the optimization algorithm, especially when the RDS size and problem dimension are extended.
Power Quality Improvement in 3-Φ Power System with Shunt Active filter using ...AI Publications
Research paper focuses on enhancement of the power quality, Harmonic reduction and Reactive power compensation . Power quality problems became the foremost important concern now a days. Active filters with synchronous detection methodologies are vividly employed in distribution system to be sure that the harmonics generated by non-linear loads is reduced and leads to less voltage distortion and leads to lesser power superiority problems. The three physical characteristics that mostly underline the power quality and a power quality issues are Voltage, Current and Frequency. Harmonics is defined as a disturbance demonstrated in current or voltage or frequency waveforms which result in devastation, or failure of final equipment ..This paper examines the control of Shunt Active Power Filter with Synchronous Detection Method . Simulation results using MATLAB SIMULINK demonstrates the application of these methods to the control of Active Power Filter . Moreover, this work shows that how the power quality improvement in 3 phase is done with Synchronous Detection Method .
Evolutionary algorithm solution for economic dispatch problemsIJECEIAES
A modified firefly algorithm (FA) was presented in this paper for finding a solution to the economic dispatch (ED) problem. ED is considered a difficult topic in the field of power systems due to the complexity of calculating the optimal generation schedule that will satisfy the demand for electric power at the lowest fuel costs while satisfying all the other constraints. Furthermore, the ED problems are associated with objective functions that have both quality and inequality constraints, these include the practical operation constraints of the generators (such as the forbidden working areas, nonlinear limits, and generation limits) that makes the calculation of the global optimal solutions of ED a difficult task. The proposed approach in this study was evaluated in the IEEE 30-Bus test-bed, the evaluation showed that the proposed FA-based approach performed optimally in comparison with the performance of the other existing optimizers, such as the traditional FA and particle swarm optimization. The results show the high performance of the modified firefly algorithm compared to the other methods.
Review on Optimal Allocation of Capacitor in Radial Distribution System
slide FYP 2
1. Zuhusna Adilla Binti Ibrahim
B011110121
Supervisor : Encik Mohamad Fani bin Sulaima
Distribution Network Reconfiguration (DNR) Using
Improved Artificial Bee Colony (IABC) For Energy Saving
1
2. Motivation
In Malaysia, the growing industrialization and increasing standard of living has
considerably increased the usage of energy.
The increasing demand of the electrical energy is quietly related to the power
demand.
In order to cope the demand of the electricity, the distribution system has
become more complex and causing power loss always occurred while distributing
the electric.
To reduce the power loss, the network distribution system needs to be
reconfigured.
2
3. • The demand for the electricity is rising due to the
increasing population group.
• The distribution system has become more complex.
• The current drawn increasing during the distribution of
electricity which lead to the instability.
• As the system unstable, the power losses will occur.
Problem Statements
3
8. Previous Work
Author Project Title Method Used Description Comment
R.J Safri, M.M.A
Salama, A.Y
Chikhani
Distribution
System
Reconfiguration
for Loss
Reduction : A
New Algorithm
based on a set
of Quantified
Heuristic Rules
Quantified
Heuristic Rules
Aim to reduce
power losses
The method
serves as pre-
processor by
removing the
undesirable
switching
Does not
perform the
complex
analysis load
flow.
This
proposed
method does
not perform
the load flow
analysis
A new
artificial
intelligence
technique is
proposed
8
9. Author Project Title Method
Used
Description Comment
S. Ganesh Network
Reconfiguration of
Distribution
System Using
Artificial Bee
Colony Algorithm
ABC
algorithm
technique
Aim to minimize
power losses
The ABC is tested
on the 33-bus
system
Compared with
Refined Generic
Algorithm (RGA)
and Tabu Search
Algorithm (TSA)
ABC has the best
performance in
minimizing power
losses.
Does not
apply the
improved
ABC
algorithm
Does not
improve the
voltage
profile
9
10. Author Project Title Method
Used
Description Comment
M.
Assadian,
M.M
Farsangi,
Hossein
GCPSO in
cooperation with
graph theory to
distribution
network
reconfiguration
for energy
saving
Guaranteed
Convergence
Particle
Swarm
Optimization
(GCPSO)
and Particle
Swarm
Optimization
(PSO)
Objectives are to
reduce power loss
and enhancement
of voltage profile
Compared with
applied GA +
GCPSO
Results show that
the GA and
GCPSO are better
than conventional
PSO in term of
energy saving.
The paper
does not
show the cost
saving
The
proposed
method does
not show the
value of
energy
saved.
10
13. Improved Artificial Bee Colony (IABC) Technique
• Inspired by the improved strategies of Particle Swarm Optimization (PSO)
• An inertial weight w inspired by PSO evolution equation and its improving
strategies are added.
• The benefits of using this technique are:
Maximize the exploitation capacity
Balanced the exploitation and exploration phase
13
14. Start
Initialization Phase
Employed Bee Phase
(Weight is added here)
Onlooker Bee Phase
Scout Bee Phase
Memorize the best solution
Exceed
maximum
cycle?
Stop
No
Yes
Flowchart of IABC
14
18. • In this system, the 33-bus initial
configuration are consists of:
• 1 feeder, 32 normally closed tie
line and 5 normally open tie
lines.
• The normally open tie lines are
represented by 33, 34, 35, 36
and 37 branches.
Sectionalizing Switch
Tie Switch
Figure 1: IEEE 33-bus radial original network configuration
Test System Analysis
18
19. • The IABC algorithm is tested on 33-bus
network system for 30 times.
• From the 30 run times, only 12 of them
are radial.
• The best combination of switches that
has been chosen is at 20 because
value of power loss at this 20th
running
times is the lowest which is 107.1 kW
and has the fastest computational time
(1222.6623s).
• The best combination switches are
opened at S31, S6, S21, S13 and, S37
Test System Analysis
19
20. Figure 4.2: The Power Loss after IABC Network Reconfiguration
20
27. Company SAIDI (Minute)
2008 2009 2010 2011 2012 2013
TNB 68.31 56.72 88.1 63.25 49.30 56.20
Data from SAIDI (TNB)
Table 4.3: The Average SAIDI data in Peninsular Malaysia [22]
Region Electricity Average Selling Price
(sen/kWh)
Peninsular Malaysia 33.88
Table 4.4: The Electricity Average Selling Price (sen/kWh) [22]
27
28. Energy Saving
Network
Reconfiguration
Initial Network ABC IABC
Total Power Loss
(kW)
202.71 134.26 107.10
Energy (kWh) 4 833.82 3201.56 2553.90
Total loss Cost for
one day (RM)
1 637.70 1084.69 865.26
Table 5.2: The total energy and total cost loss in one day
28
31. Conclusion
• IABC algorithm technique has shown a good performance in minimizing the
power loss when it is compared to the ABC and other optimization method
• Succeeded in reducing the energy losses in the distribution network system
• The objectives of this study have been achieved successfully
31
32. Recommendation
• Tested on 14-kV and 69-kV IEEE test bus system in
order to get better outcomes and analysis.
• To consider the Distribution Generators (DGs) in the
future.
• To consider the power quality.
32
33. References
[1] R.J Safri, M.M.A Salama and A.Y Chickani, “Distribution system reconfiguration for
loss reduction: a new algorithm based on a set of quantified heuristic rules”, Proceedings
of Electrical and Computer Engineering, Vol. 1, Canada , pp. 125-130,1994.
[2] S. Ganesh, “Network Reconfiguration of Distribution System Using Artificial Bee
Colony Algorithm”, International Journal of Electrical, Robotics, Electronics and
Communication Engineering, Vol.8, No. 2, pp. 403-409, 2014.
[3] M. Assadian, M. M. Farsangi, Hossein Nezamabadi, “GCPSO in cooperation with
graph theory to distribution network reconfiguration for energy saving”, Energy
Conversion and Management vol. 51,pp. 418-417, 2010.
[22] Suruhanjaya Tenaga, Performance and Statistical Information on Electricity Supply
Industry in Malaysia, pp. 22-24, 2013.
[14] M. Rohani, H. Tabatabaee & A. Rohani, “Reconfiguration Optimization for Loss
reduction in Distribution Networks using Hybrid PSO Algorithm and Fuzzy Logic”,
MAGNT Research Report, Vol. 2(5), pp. 903-911, 2011
33