Proper pricing of active power is an important issue
in deregulated power environment. This paper presents a
flexible formulation for determining short run marginal cost
of synchronous generators using genetic algorithm based
different re-dispatching scheduling considering economic load
dispatch as well as optimized loss condition. By integrating
genetic algorithm based solution, problem formulation became
easier. The solution obtained from this methodology is quite
encouraging and useful in the economic point of view and it
has been observed that for calculating short run marginal
cost, generator re-dispatching solution is better than classical
method solution. The proposed approach is efficient in the
real time application and allows for carrying out active power
pricing independently. The paper includes test result of IEEE
30 bus standard test system.
NOVEL PSO STRATEGY FOR TRANSMISSION CONGESTION MANAGEMENTelelijjournal
In post deregulated era of power system load characteristics become more erratic. Unplanned transactions
of electrical power through transmission lines of particular path may occur due to low cost offered by
generating companies. As a consequence those lines driven close to their operating limits and becomes
congested as the lines are originally designed for traditional vertically integrated structure of power
system. This congestion in transmission lines is unpredictable with deterministic load flow strategy.
Rescheduling active and reactive power output of generators is the promising way to manage congestion.
In this paper Particle Swarm Optimization (PSO) with varying inertia weight strategy, with two variants
e1-PSO and e-2 PSO is applied for optimal solution of active and reactive power rescheduling for
managing congestion. The generators sensitivity technique is opted for identifying participating generators
for managing congestion. Proposed algorithm is tested on IEEE 30 bus system. Comparison is made
between results obtained from proposed techniques to that of results reported in previous literature.
Multi-Objective based Optimal Energy and Reactive Power Dispatch in Deregulat...IJECEIAES
This paper presents a day-ahead (DA) multi-objective based joint energy and reactive power dispatch in the deregulated electricity markets. The traditional social welfare in the centralized electricity markets comprises of customers benefit function and the cost function of active power generation. In this paper, the traditional social welfare is modified to incorporate the cost of both active and reactive power generation. Here, the voltage dependent load modeling is used. This paper brings out the unsuitability of traditional single objective functions, e.g., social welfare maximization (SWM), loss minimization (LM) due to the reduction of amount of load served. Therefore, a multi-objective based optimization is required. This paper proposes four objectives, i.e., SWM, load served maximization (LSM), LM and voltage stability enhancement index (VSEI); and these objectives can be combined as per the operating condition. The simulation studies are performed on IEEE 30 bus test system by considering the both traditional constant load modeling and the proposed voltage dependent load modeling.
In this paper a load flow based method using MATLAB Software is used to determine the optimum location and optimum size of DG in a 43-bus distribution system for voltage profile improvement and loss reduction. This paper proposes analytical expressions for finding optimal size of three types of distributed generation (DG) units. DG units are sized to achieve the highest loss reduction in distribution networks. Single DG installation case was studied and compared to a case without DG, and 43-bus distribution system is used to demonstrate the effectiveness of the proposed method. The proposed analytical expressions are based on an improvement to the method that was limited to DG type, which is capable of injecting real power only, DG capable of injecting reactive power only and DG capable of injecting both real and reactive power can also be identified with their optimal size and location using the proposed method. This paper has been analysed with varying DG size and complexity and validated using analytical method for Summer case and Winter case in 43-bus distribution system in Myanmar.
Keywords- analytical method,distributed generation,power loss reduction,voltage profile improvement.
Power Loss Allocation in Deregulated Electricity MarketsIJERD Editor
The restructuring of Electricity Supply Industry (ESI) all over the world thatstartedmainlyinthe 20th
century introduces an open electricity marketfor trading electricity betweengenerators and suppliers in
competitive environments. Market participants utilize thenetwork differently to maximize their profits. This
transformation consists of two aspects that are related with each other; restructuring and privatization.
However, dueto this change, some problems and challenges have risen. One of it is theissue of power losses
allocation. When electrical power is transmitted throughanetwork, it will cause power losses. The generators
must compensate this lossbygenerating more power. Under competitive electricity market environment, no
generators would want to generate more to compensate this loss asit will increase their production cost.
Logically both generators and consumers are supposed topayfor the losses because they both use the network
and thus are responsible for the lossesincurred. If there is no specified method to handle this problem, there is a
probability that the Independent System Operator (ISO) which is a non-profit entity and does not have source of
income will be responsible for this losses. However, if ISO paid forthe losses, itis considered unfair. Thus, this
analysis focuses on some existing allocating transmissionlosses.The selected methods are pro rata, postage
stamp, and Current Adjustment Factor (CAF) and these methods have been tested using simple bus network and
the IEEE standard 14 test bus system.
Reactive Power Planning using Real GA Comparison with Evolutionary ProgrammingIDES Editor
This paper proposes an application of real coded
genetic algorithm (RGA) to reactive power planning (RPP).
Several techniques have been developed to make RGA
practicable to solve a real power system problem and other
practical problems. The proposed approach has been used
in the IEEE 30-bus system. Simulation results, compared
with those obtained by using the evolutionary
programming(EP), are presented to show that the present
method is better for power system planning. In the case of
optimization of non-continuous and non-smooth function,
RGA gives much better results than EP. The comprehensive
simulation results show a great potential for applications of
RGA in power system economical and secure operation,
planning and reliability assessment.
This paper recommends the use of grasshopper optimization algorithm (GOA), a nature-inspired optimization algorithm, for optimizing switching-angle applied to cascaded H-bridge multilevel inverter (CHBMLI). Switching angles are selected based on the minimum value of the objective function formulated using the concept of selective harmonic minimization pulse width modulation (SHMPWM) technique. MATLAB/Simulink-PSIM dynamic co-simulation conducted on a 3-phase 9-level CHBMLI shows that the CHBMLI controlled using GOA derived switching-angle is able to respond to varying modulation index demand and synthesize an AC staircase output voltage waveform with the desired fundamental harmonic and minimized selected low-order harmonics. Compared to Newton Raphson (NR) technique, GOA is able to find optimum switching-angle solutions over a wider modulation index range. Compared to Genetic Algorithm (GA), GOA is able to find global minima with higher probability. The simulation results validate the performance of GOA for switching-angle calculation based on the concept of SHMPWM.
This document reviews applications of particle swarm optimization (PSO) for solving economic load dispatch (ELD) problems in power systems. ELD aims to determine the most cost-effective generation dispatch to meet system load while satisfying operational constraints. PSO is an evolutionary optimization technique inspired by swarm behavior in nature. It has been successfully applied to various power system optimization problems due to its simplicity, fast convergence, and ability to find high-quality solutions. The document discusses PSO algorithms for single-objective and multi-objective ELD formulations considering factors like valve point loading effects and multiple fuel options. It also reviews constraint handling and variants of PSO used to improve performance for complex cost functions with multiple minima. Overall, the review shows that
This document discusses four methods for calculating locational marginal pricing (LMP) for optimal power flow under lossy conditions: 1) using a DC optimal power flow (OPF) model with loss factors and delivery factors, 2) using an AC OPF model, 3) using an iterative DC OPF formulation with fictitious nodal demands, and 4) using a genetic algorithm technique. The methods are applied to the IEEE 30-bus test system and the results are compared.
NOVEL PSO STRATEGY FOR TRANSMISSION CONGESTION MANAGEMENTelelijjournal
In post deregulated era of power system load characteristics become more erratic. Unplanned transactions
of electrical power through transmission lines of particular path may occur due to low cost offered by
generating companies. As a consequence those lines driven close to their operating limits and becomes
congested as the lines are originally designed for traditional vertically integrated structure of power
system. This congestion in transmission lines is unpredictable with deterministic load flow strategy.
Rescheduling active and reactive power output of generators is the promising way to manage congestion.
In this paper Particle Swarm Optimization (PSO) with varying inertia weight strategy, with two variants
e1-PSO and e-2 PSO is applied for optimal solution of active and reactive power rescheduling for
managing congestion. The generators sensitivity technique is opted for identifying participating generators
for managing congestion. Proposed algorithm is tested on IEEE 30 bus system. Comparison is made
between results obtained from proposed techniques to that of results reported in previous literature.
Multi-Objective based Optimal Energy and Reactive Power Dispatch in Deregulat...IJECEIAES
This paper presents a day-ahead (DA) multi-objective based joint energy and reactive power dispatch in the deregulated electricity markets. The traditional social welfare in the centralized electricity markets comprises of customers benefit function and the cost function of active power generation. In this paper, the traditional social welfare is modified to incorporate the cost of both active and reactive power generation. Here, the voltage dependent load modeling is used. This paper brings out the unsuitability of traditional single objective functions, e.g., social welfare maximization (SWM), loss minimization (LM) due to the reduction of amount of load served. Therefore, a multi-objective based optimization is required. This paper proposes four objectives, i.e., SWM, load served maximization (LSM), LM and voltage stability enhancement index (VSEI); and these objectives can be combined as per the operating condition. The simulation studies are performed on IEEE 30 bus test system by considering the both traditional constant load modeling and the proposed voltage dependent load modeling.
In this paper a load flow based method using MATLAB Software is used to determine the optimum location and optimum size of DG in a 43-bus distribution system for voltage profile improvement and loss reduction. This paper proposes analytical expressions for finding optimal size of three types of distributed generation (DG) units. DG units are sized to achieve the highest loss reduction in distribution networks. Single DG installation case was studied and compared to a case without DG, and 43-bus distribution system is used to demonstrate the effectiveness of the proposed method. The proposed analytical expressions are based on an improvement to the method that was limited to DG type, which is capable of injecting real power only, DG capable of injecting reactive power only and DG capable of injecting both real and reactive power can also be identified with their optimal size and location using the proposed method. This paper has been analysed with varying DG size and complexity and validated using analytical method for Summer case and Winter case in 43-bus distribution system in Myanmar.
Keywords- analytical method,distributed generation,power loss reduction,voltage profile improvement.
Power Loss Allocation in Deregulated Electricity MarketsIJERD Editor
The restructuring of Electricity Supply Industry (ESI) all over the world thatstartedmainlyinthe 20th
century introduces an open electricity marketfor trading electricity betweengenerators and suppliers in
competitive environments. Market participants utilize thenetwork differently to maximize their profits. This
transformation consists of two aspects that are related with each other; restructuring and privatization.
However, dueto this change, some problems and challenges have risen. One of it is theissue of power losses
allocation. When electrical power is transmitted throughanetwork, it will cause power losses. The generators
must compensate this lossbygenerating more power. Under competitive electricity market environment, no
generators would want to generate more to compensate this loss asit will increase their production cost.
Logically both generators and consumers are supposed topayfor the losses because they both use the network
and thus are responsible for the lossesincurred. If there is no specified method to handle this problem, there is a
probability that the Independent System Operator (ISO) which is a non-profit entity and does not have source of
income will be responsible for this losses. However, if ISO paid forthe losses, itis considered unfair. Thus, this
analysis focuses on some existing allocating transmissionlosses.The selected methods are pro rata, postage
stamp, and Current Adjustment Factor (CAF) and these methods have been tested using simple bus network and
the IEEE standard 14 test bus system.
Reactive Power Planning using Real GA Comparison with Evolutionary ProgrammingIDES Editor
This paper proposes an application of real coded
genetic algorithm (RGA) to reactive power planning (RPP).
Several techniques have been developed to make RGA
practicable to solve a real power system problem and other
practical problems. The proposed approach has been used
in the IEEE 30-bus system. Simulation results, compared
with those obtained by using the evolutionary
programming(EP), are presented to show that the present
method is better for power system planning. In the case of
optimization of non-continuous and non-smooth function,
RGA gives much better results than EP. The comprehensive
simulation results show a great potential for applications of
RGA in power system economical and secure operation,
planning and reliability assessment.
This paper recommends the use of grasshopper optimization algorithm (GOA), a nature-inspired optimization algorithm, for optimizing switching-angle applied to cascaded H-bridge multilevel inverter (CHBMLI). Switching angles are selected based on the minimum value of the objective function formulated using the concept of selective harmonic minimization pulse width modulation (SHMPWM) technique. MATLAB/Simulink-PSIM dynamic co-simulation conducted on a 3-phase 9-level CHBMLI shows that the CHBMLI controlled using GOA derived switching-angle is able to respond to varying modulation index demand and synthesize an AC staircase output voltage waveform with the desired fundamental harmonic and minimized selected low-order harmonics. Compared to Newton Raphson (NR) technique, GOA is able to find optimum switching-angle solutions over a wider modulation index range. Compared to Genetic Algorithm (GA), GOA is able to find global minima with higher probability. The simulation results validate the performance of GOA for switching-angle calculation based on the concept of SHMPWM.
This document reviews applications of particle swarm optimization (PSO) for solving economic load dispatch (ELD) problems in power systems. ELD aims to determine the most cost-effective generation dispatch to meet system load while satisfying operational constraints. PSO is an evolutionary optimization technique inspired by swarm behavior in nature. It has been successfully applied to various power system optimization problems due to its simplicity, fast convergence, and ability to find high-quality solutions. The document discusses PSO algorithms for single-objective and multi-objective ELD formulations considering factors like valve point loading effects and multiple fuel options. It also reviews constraint handling and variants of PSO used to improve performance for complex cost functions with multiple minima. Overall, the review shows that
This document discusses four methods for calculating locational marginal pricing (LMP) for optimal power flow under lossy conditions: 1) using a DC optimal power flow (OPF) model with loss factors and delivery factors, 2) using an AC OPF model, 3) using an iterative DC OPF formulation with fictitious nodal demands, and 4) using a genetic algorithm technique. The methods are applied to the IEEE 30-bus test system and the results are compared.
Multi Area Economic Dispatch Using Secant Method and Tie Line MatrixIJAPEJOURNAL
In this paper, Secant method and tie line matrix are proposed to solve multi area economic dispatch (MAED) problem with tie line loss. Generator limits of all generators in each area are calculated at given area power demands plus export (or import) using secant method and the generator limits of all generators are modified as modified generator limits. Central economic dispatch (CED) problem is used to determine the output powers of all generators and finally power flows in all tie lines are determined from tie line matrix. Here, Secant method is applied to solve the CED problem. A modified tie line matrix is used to find power flow in each tie line and then tie line loss is calculated from the power flow in each tie line. The proposed approach has been tested on two-area (two generators in each area) system and four-area (four generators in each area) system. It is observed from various cases that the proposed approach provides optimally best solution in terms of cost with tie line loss with less computational burden.
Optimal Power Flow with Reactive Power Compensation for Cost And Loss Minimiz...ijeei-iaes
One of the concerns of power system planners is the problem of optimum cost of generation as well as loss minimization on the grid system. This issue can be addressed in a number of ways; one of such ways is the use of reactive power support (shunt capacitor compensation). This paper used the method of shunt capacitor placement for cost and transmission loss minimization on Nigerian power grid system which is a 24-bus, 330kV network interconnecting four thermal generating stations (Sapele, Delta, Afam and Egbin) and three hydro stations to various load points. Simulation in MATLAB was performed on the Nigerian 330kV transmission grid system. The technique employed was based on the optimal power flow formulations using Newton-Raphson iterative method for the load flow analysis of the grid system. The results show that when shunt capacitor was employed as the inequality constraints on the power system, there is a reduction in the total cost of generation accompanied with reduction in the total system losses with a significant improvement in the system voltage profile
Optimum reactive power compensation for distribution system using dolphin alg...IJECEIAES
The distribution system represents the connection between the consumers and entire power network. The radial structure is preferred for distribution system due to its simple design and low cost. It suffers from problems of rising power losses higher than the transmission system and voltage drop. One of the important solutions to evolve the system voltage profile and to lower system losses is the reactive power compensation which is based on the optimum choice of position and capacitor size in the network. Different models of loads such as constant power (P), constant current (I), constant impedance (Z), and composite (ZIP) are implemented with comparisons among them in order to identify the most effective load type that produces the optimal settlement for minimization loss reduction, voltage profile enhancement and cost savings. Dolphin Optimization Algorithm (DOA) is applied for selecting the sizes and locations of capacitors. Two case studies (IEEE 16-bus and 33-bus) are employed to evaluate the different load models with optimal reactive power compensation. The results show that ZIP model is the best to produce the optimal solution for capacitors position and sizes. Comparison of results with literature works shows that DOA is the most robust among the other algorithms.
This document proposes a generalized quadratic model for optimal power flow problems. It formulates the optimal power flow problem in a quadratic form and develops the necessary conditions for feasibility and optimality. It also describes a generalized algorithm that uses sensitivity analysis and optimal adjustments to constraints to find a global optimal solution. The algorithm can accommodate multiple objective functions like losses, costs, voltages and flows. It was tested on actual power systems and found to reach optimal solutions in few iterations, showing potential for online applications.
Optimal Reactive Power Dispatch using Crow Search Algorithm IJECEIAES
The optimal reactive power dispatch is a kind of optimization problem that plays a very important role in the operation and control of the power system. This work presents a meta-heuristic based approach to solve the optimal reactive power dispatch problem. The proposed approach employs Crow Search algorithm to find the values for optimal setting of optimal reactive power dispatch control variables. The proposed way of approach is scrutinized and further being tested on the standard IEEE 30-bus, 57-bus and 118-bus test system with different objectives which includes the minimization of real power losses, total voltage deviation and also the enhancement of voltage stability. The simulation results procured thus indicates the supremacy of the proposed approach over the other approaches cited in the literature.
Enhancements of Extended Locational Marginal Pricing – Advancing Practical Im...Power System Operation
Price formation is critical to efficient wholesale electricity markets that support reliable operation and efficient investment. The Midcontinent Independent System Operator (MISO) developed the Extended Locational Marginal Pricing (ELMP) with the goal of more completely reflecting resource costs and generally improving price formation to better incent market participation. MISO developed ELMP based on the mathematical concept of convex hull. However, considering the computational challenges and the existing market structure, MISO implemented an approximate version of ELMP. This paper presents enhancements to ELMP to bring the practical implementation of ELMP closer to the theoretical ideal and to achieve greater benefits of ELMP in production. The Special Ordered Set of Type Two (SOS2) piece-wise linear cost function formulation is used to tighten the approximation of, and under certain conditions exactly match, the convex hull of the cost function. Regulation commitment logic is also enhanced to maintain optimality under degeneracy conditions while providing flexibility for real-time regulation scheduling and pricing. Simulation results on the MISO system illustrate expected benefits. With the increasing interests in inter-temporal constraints, the on-going work on ELMP ramp modelling is also discussed.
International Journal of Engineering Research and DevelopmentIJERD Editor
The document discusses optimizing the location and size of distributed generations (DGs) in a power distribution system to reduce power losses and improve voltage profiles. It proposes using the Kalman filter algorithm to determine optimal DG sizes after their locations have been selected. The locations are chosen by considering total power loss in the system. Power losses are calculated using distribution factor equations that model power flows from generators to loads and vice versa. The approach will be tested on the IEEE 30-bus system model.
Small Signal Stability Improvement and Congestion Management Using PSO Based ...IDES Editor
In this paper an attempt has been made to study the
application of Thyristor Controlled Series Capacitor (TCSC)
to mitigate small signal stability problem in addition to
congestion management of a heavily loaded line in a
multimachine power system. The Flexible AC Transmission
System (FACTS) devices such as TCSC can be used to control
the power flows in the network and can help in improvement
of small signal stability aspect. It can also provide relief to
congestion in the heavily loaded line. However, the
performance of any FACTS device highly depends upon its
parameters and placement at suitable locations in the power
network. In this paper, Particle Swarm Optimization (PSO)
method has been used for determining the optimal locations
and parameters of the TCSC controller in order to damp small
signal oscillations. Transmission Line Flow (TLF) Sensitivity
method has been used for curtailment of non-firm load to
limit power flow congestion. The results of simulation reveals
that TCSC controllers, placed optimally, not only mitigate
small signal oscillations but they can also alleviate line flow
congestion effectively.
Energy Audit And Management Of Induction Motor Using Field Test And Genetic A...IDES Editor
This paper proposes an economical method that
can be used by industries/plants to make a right decision in
replacing the inefficient induction motors with efficient
ones. proposed method focuses on the field efficiency of
motors without the needs for removing motors and
measuring the output power. The use of a few sets of
measured data from field test coupled with the genetic
algorithms using one operating point for evaluating motor
equivalent circuit parameters instead of using the no load
and blocked-rotor tests is proposed. Test results indicate
that this method has a high accuracy, then it is suitable for
conducting onsite energy audit of motors in order to project
cost savings and payback and to support a confidence
decision regarding the investment in higher efficiency
motors.
This document summarizes two methods for allocating transmission line costs: the Generation Shift Distribution Factor (GSDF) method and the Bialek Tracing method. The GSDF method uses linear power flow approximations to calculate distribution factors that measure the incremental use of transmission lines by generators and loads. These factors can then be used to allocate total fixed transmission costs. The Bialek Tracing method is based on the proportional sharing principle and uses a topological approach to determine the contribution of individual generators or loads to every line flow. Both methods aim to generate appropriate economic signals to recover fixed transmission costs from market participants.
IRJET- A New Approach to Economic Load Dispatch by using Improved QEMA ba...IRJET Journal
This document proposes an improved Quantum behaved electro-magnetism algorithm particle swarm optimization (QEMAPSO) approach to solve the economic load dispatch (ELD) problem. The objective is to minimize the total generation cost while considering constraints like generator limits, transmission losses, and valve point effects. It formulates the ELD problem and describes the QEMA-PSO algorithm which uses QEMA to determine an initial solution that is then optimized using PSO. Results on a 6-generator IEEE 30-bus test system show that the proposed QEMA-PSO approach improves upon other methods like genetic algorithm and dance bee colony optimization in minimizing costs and emissions.
Speed Conrol of Separately Excited dc Motor using Fuzzy TechniqueIDES Editor
This paper presents the speed control of a separately
excited DC motor using Fuzzy Logic Control (FLC). The Fuzzy
Logic Controller designed in this study applies the required
control voltage based on motor speed error (e) and its change
(ce). The performance of the driver system was evaluated
through digital simulations using Simulink. The simulation
results show that the control with FLC outperforms PI control
in terms of overshoot, steady state error and rise time.
Asymmetric quasi impedance source buck-boost converterIJECEIAES
An impedance source buck-boost converter (BBC) prototype for renewable energy (RE) application in the transportation industry is proposed. Its functions include stabilizing the variable output voltage of the RE sources such as fuel cells and photovoltaic cells. The converter utilized a topology of DC-DC quasi-impedance source converters (q-ZSCs) to achieve the gain curve of the BBC. With BBC gain curve, the converter earned advantages over the two other classes of non-isolated DCDC q-ZSCs. These advantages include efficient buck-boost capability at the efficient duty ratio range of 0:35 0:65 and continuous and non-zero gain at the efficient duty ratio range. The converter’s q-ZSC topology implies using two capacitors and two inductors. These two capacitors and inductors formed two separate LC filters that provides second order filtering compared to the first order filtering in BBC. Its other advantages over the traditional BBC include elimination of dead and overlap-time, simple contol and permitting higher switching frequency operation. The converter is capable of utilizing high switching frequency and asymmetric components to achieve BBC gain by using smaller components to reduce cost, weight and size. Its simulation response and that of a corresponding BBC for some given specifications were compared, presented and analyzed. An experimental scaled-down prototype was also developed to confirm its operation. Analysis of the converters responses confirmed the prototype’s second order filtering as against the first order filtering in traditional BBC.
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.
Biogeography Based Optimization Approach for Optimal Power Flow Problem Consi...IDES Editor
This paper presents a novel Biogeography Based
Optimization (BBO) algorithm for solving multi-objective
constrained optimal power flow problems in power system. In
this paper, the feasibility of the proposed algorithm is
demonstrated for IEEE 30-bus system with three different
objective functions and it is compared to other well
established population based optimization techniques. A
comparison of simulation results reveals better solution
quality and computation efficiency of the proposed algorithm
over particle swarm optimization (PSO), Real Coded Genetic
algorithm (RGA) for the global optimization of multiobjective
constrained OPF problems.
Hybrid bypass technique to mitigate leakage current in the grid-tied inverterIJECEIAES
The extensive use of fossil fuel is destroying the balance of nature that could lead to many problems in the forthcoming era. Renewable energy resources are a ray of hope to avoid possible destruction. Smart grid and distributed power generation systems are now mainly built with the help of renewable energy resources. The integration of renewable energy production system with the smart grid and distributed power generation is facing many challenges that include addressing the issue of isolation and power quality. This paper presents a new approach to address the aforementioned issues by proposing a hybrid bypass technique concept to improve the overall performance of the grid-tied inverter in solar power generation. The topology with the proposed technique is presented using traditional H5, oH5 and H6 inverter. Comparison of topologies with literature is carried out to check the feasibility of the method proposed. It is found that the leakage current of all the proposed inverters is 9 mA and total harmonic distortion is almost about 2%. The proposed topology has good efficiency, common mode and differential mode characteristics.
Optimal power flow based congestion management using enhanced genetic algorithmsIJECEIAES
Congestion management (CM) in the deregulated power systems is germane and of central importance to the power industry. In this paper, an optimal power flow (OPF) based CM approach is proposed whose objective is to minimize the absolute MW of rescheduling. The proposed optimization problem is solved with the objectives of total generation cost minimization and the total congestion cost minimization. In the centralized market clearing model, the sellers (i.e., the competitive generators) submit their incremental and decremental bid prices in a real-time balancing market. These can then be incorporated in the OPF problem to yield the incremental/ decremental change in the generator outputs. In the bilateral market model, every transaction contract will include a compensation price that the buyer-seller pair is willing to accept for its transaction to be curtailed. The modeling of bilateral transactions are equivalent to the modifying the power injections at seller and buyer buses. The proposed CM approach is solved by using the evolutionary based Enhanced Genetic Algorithms (EGA). IEEE 30 bus system is considered to show the effectiveness of proposed CM approach.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
FAST VOLTAGE STABILTY INDEX BASED OPTIMAL REACTIVE POWER PLANNING USING DIFFE...elelijjournal
This Article presents an application of Fast Voltage Stability Index (FVSI) to Optimal Reactive Power
Planning (RPP) using Differential Evolution(DE). FVSI is used to identify the weak buses for the Reactive
Power Planning problem which involves process of experimental by voltage stability analysis based on the
load variation. The peak at Fast Voltage Stabilty Index secure to 1 indicates the greatest feasible connected
load and the bus with least connected load is identified as the weakest bus at the point of bifurcation. This technique is tested on the IEEE 30-bus system. The outcome confirm significant decrease in system losses and enhancementt of voltage stability with the use of Fast Voltage Stability Index based optimal Reactive Power Planning using Differential Evolution and compared with Evalutionary Programming
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The document discusses voltage stability enhancement in radial distribution systems through optimal placement of distributed generators (DGs) and capacitors. It proposes using the Moth Flame Optimization algorithm to determine the optimal location and sizing of DGs and capacitors to minimize power losses and maximize net savings. The methodology considers constraints like voltage limits and power flow limits. Test systems like IEEE 12 and 33 node systems are used to demonstrate the effectiveness of the proposed approach.
IRJET- Optimal Power Flow Solution of Transmission Line Network of Electric p...IRJET Journal
This document discusses using a genetic algorithm to solve the optimal power flow problem in large power transmission networks. The optimal power flow problem aims to minimize generation costs while meeting operational constraints. A genetic algorithm is proposed to solve this problem globally and efficiently. The controllable variables are divided into dynamic constraints directly impacting cost and static constraints maintained within limits by the load flow. The algorithm is tested on the IEEE 30-bus system and shown to effectively find the optimal solution. Genetic algorithms are well-suited for this problem as they can evaluate multiple solutions in parallel without requiring derivative information like traditional methods.
Multi Area Economic Dispatch Using Secant Method and Tie Line MatrixIJAPEJOURNAL
In this paper, Secant method and tie line matrix are proposed to solve multi area economic dispatch (MAED) problem with tie line loss. Generator limits of all generators in each area are calculated at given area power demands plus export (or import) using secant method and the generator limits of all generators are modified as modified generator limits. Central economic dispatch (CED) problem is used to determine the output powers of all generators and finally power flows in all tie lines are determined from tie line matrix. Here, Secant method is applied to solve the CED problem. A modified tie line matrix is used to find power flow in each tie line and then tie line loss is calculated from the power flow in each tie line. The proposed approach has been tested on two-area (two generators in each area) system and four-area (four generators in each area) system. It is observed from various cases that the proposed approach provides optimally best solution in terms of cost with tie line loss with less computational burden.
Optimal Power Flow with Reactive Power Compensation for Cost And Loss Minimiz...ijeei-iaes
One of the concerns of power system planners is the problem of optimum cost of generation as well as loss minimization on the grid system. This issue can be addressed in a number of ways; one of such ways is the use of reactive power support (shunt capacitor compensation). This paper used the method of shunt capacitor placement for cost and transmission loss minimization on Nigerian power grid system which is a 24-bus, 330kV network interconnecting four thermal generating stations (Sapele, Delta, Afam and Egbin) and three hydro stations to various load points. Simulation in MATLAB was performed on the Nigerian 330kV transmission grid system. The technique employed was based on the optimal power flow formulations using Newton-Raphson iterative method for the load flow analysis of the grid system. The results show that when shunt capacitor was employed as the inequality constraints on the power system, there is a reduction in the total cost of generation accompanied with reduction in the total system losses with a significant improvement in the system voltage profile
Optimum reactive power compensation for distribution system using dolphin alg...IJECEIAES
The distribution system represents the connection between the consumers and entire power network. The radial structure is preferred for distribution system due to its simple design and low cost. It suffers from problems of rising power losses higher than the transmission system and voltage drop. One of the important solutions to evolve the system voltage profile and to lower system losses is the reactive power compensation which is based on the optimum choice of position and capacitor size in the network. Different models of loads such as constant power (P), constant current (I), constant impedance (Z), and composite (ZIP) are implemented with comparisons among them in order to identify the most effective load type that produces the optimal settlement for minimization loss reduction, voltage profile enhancement and cost savings. Dolphin Optimization Algorithm (DOA) is applied for selecting the sizes and locations of capacitors. Two case studies (IEEE 16-bus and 33-bus) are employed to evaluate the different load models with optimal reactive power compensation. The results show that ZIP model is the best to produce the optimal solution for capacitors position and sizes. Comparison of results with literature works shows that DOA is the most robust among the other algorithms.
This document proposes a generalized quadratic model for optimal power flow problems. It formulates the optimal power flow problem in a quadratic form and develops the necessary conditions for feasibility and optimality. It also describes a generalized algorithm that uses sensitivity analysis and optimal adjustments to constraints to find a global optimal solution. The algorithm can accommodate multiple objective functions like losses, costs, voltages and flows. It was tested on actual power systems and found to reach optimal solutions in few iterations, showing potential for online applications.
Optimal Reactive Power Dispatch using Crow Search Algorithm IJECEIAES
The optimal reactive power dispatch is a kind of optimization problem that plays a very important role in the operation and control of the power system. This work presents a meta-heuristic based approach to solve the optimal reactive power dispatch problem. The proposed approach employs Crow Search algorithm to find the values for optimal setting of optimal reactive power dispatch control variables. The proposed way of approach is scrutinized and further being tested on the standard IEEE 30-bus, 57-bus and 118-bus test system with different objectives which includes the minimization of real power losses, total voltage deviation and also the enhancement of voltage stability. The simulation results procured thus indicates the supremacy of the proposed approach over the other approaches cited in the literature.
Enhancements of Extended Locational Marginal Pricing – Advancing Practical Im...Power System Operation
Price formation is critical to efficient wholesale electricity markets that support reliable operation and efficient investment. The Midcontinent Independent System Operator (MISO) developed the Extended Locational Marginal Pricing (ELMP) with the goal of more completely reflecting resource costs and generally improving price formation to better incent market participation. MISO developed ELMP based on the mathematical concept of convex hull. However, considering the computational challenges and the existing market structure, MISO implemented an approximate version of ELMP. This paper presents enhancements to ELMP to bring the practical implementation of ELMP closer to the theoretical ideal and to achieve greater benefits of ELMP in production. The Special Ordered Set of Type Two (SOS2) piece-wise linear cost function formulation is used to tighten the approximation of, and under certain conditions exactly match, the convex hull of the cost function. Regulation commitment logic is also enhanced to maintain optimality under degeneracy conditions while providing flexibility for real-time regulation scheduling and pricing. Simulation results on the MISO system illustrate expected benefits. With the increasing interests in inter-temporal constraints, the on-going work on ELMP ramp modelling is also discussed.
International Journal of Engineering Research and DevelopmentIJERD Editor
The document discusses optimizing the location and size of distributed generations (DGs) in a power distribution system to reduce power losses and improve voltage profiles. It proposes using the Kalman filter algorithm to determine optimal DG sizes after their locations have been selected. The locations are chosen by considering total power loss in the system. Power losses are calculated using distribution factor equations that model power flows from generators to loads and vice versa. The approach will be tested on the IEEE 30-bus system model.
Small Signal Stability Improvement and Congestion Management Using PSO Based ...IDES Editor
In this paper an attempt has been made to study the
application of Thyristor Controlled Series Capacitor (TCSC)
to mitigate small signal stability problem in addition to
congestion management of a heavily loaded line in a
multimachine power system. The Flexible AC Transmission
System (FACTS) devices such as TCSC can be used to control
the power flows in the network and can help in improvement
of small signal stability aspect. It can also provide relief to
congestion in the heavily loaded line. However, the
performance of any FACTS device highly depends upon its
parameters and placement at suitable locations in the power
network. In this paper, Particle Swarm Optimization (PSO)
method has been used for determining the optimal locations
and parameters of the TCSC controller in order to damp small
signal oscillations. Transmission Line Flow (TLF) Sensitivity
method has been used for curtailment of non-firm load to
limit power flow congestion. The results of simulation reveals
that TCSC controllers, placed optimally, not only mitigate
small signal oscillations but they can also alleviate line flow
congestion effectively.
Energy Audit And Management Of Induction Motor Using Field Test And Genetic A...IDES Editor
This paper proposes an economical method that
can be used by industries/plants to make a right decision in
replacing the inefficient induction motors with efficient
ones. proposed method focuses on the field efficiency of
motors without the needs for removing motors and
measuring the output power. The use of a few sets of
measured data from field test coupled with the genetic
algorithms using one operating point for evaluating motor
equivalent circuit parameters instead of using the no load
and blocked-rotor tests is proposed. Test results indicate
that this method has a high accuracy, then it is suitable for
conducting onsite energy audit of motors in order to project
cost savings and payback and to support a confidence
decision regarding the investment in higher efficiency
motors.
This document summarizes two methods for allocating transmission line costs: the Generation Shift Distribution Factor (GSDF) method and the Bialek Tracing method. The GSDF method uses linear power flow approximations to calculate distribution factors that measure the incremental use of transmission lines by generators and loads. These factors can then be used to allocate total fixed transmission costs. The Bialek Tracing method is based on the proportional sharing principle and uses a topological approach to determine the contribution of individual generators or loads to every line flow. Both methods aim to generate appropriate economic signals to recover fixed transmission costs from market participants.
IRJET- A New Approach to Economic Load Dispatch by using Improved QEMA ba...IRJET Journal
This document proposes an improved Quantum behaved electro-magnetism algorithm particle swarm optimization (QEMAPSO) approach to solve the economic load dispatch (ELD) problem. The objective is to minimize the total generation cost while considering constraints like generator limits, transmission losses, and valve point effects. It formulates the ELD problem and describes the QEMA-PSO algorithm which uses QEMA to determine an initial solution that is then optimized using PSO. Results on a 6-generator IEEE 30-bus test system show that the proposed QEMA-PSO approach improves upon other methods like genetic algorithm and dance bee colony optimization in minimizing costs and emissions.
Speed Conrol of Separately Excited dc Motor using Fuzzy TechniqueIDES Editor
This paper presents the speed control of a separately
excited DC motor using Fuzzy Logic Control (FLC). The Fuzzy
Logic Controller designed in this study applies the required
control voltage based on motor speed error (e) and its change
(ce). The performance of the driver system was evaluated
through digital simulations using Simulink. The simulation
results show that the control with FLC outperforms PI control
in terms of overshoot, steady state error and rise time.
Asymmetric quasi impedance source buck-boost converterIJECEIAES
An impedance source buck-boost converter (BBC) prototype for renewable energy (RE) application in the transportation industry is proposed. Its functions include stabilizing the variable output voltage of the RE sources such as fuel cells and photovoltaic cells. The converter utilized a topology of DC-DC quasi-impedance source converters (q-ZSCs) to achieve the gain curve of the BBC. With BBC gain curve, the converter earned advantages over the two other classes of non-isolated DCDC q-ZSCs. These advantages include efficient buck-boost capability at the efficient duty ratio range of 0:35 0:65 and continuous and non-zero gain at the efficient duty ratio range. The converter’s q-ZSC topology implies using two capacitors and two inductors. These two capacitors and inductors formed two separate LC filters that provides second order filtering compared to the first order filtering in BBC. Its other advantages over the traditional BBC include elimination of dead and overlap-time, simple contol and permitting higher switching frequency operation. The converter is capable of utilizing high switching frequency and asymmetric components to achieve BBC gain by using smaller components to reduce cost, weight and size. Its simulation response and that of a corresponding BBC for some given specifications were compared, presented and analyzed. An experimental scaled-down prototype was also developed to confirm its operation. Analysis of the converters responses confirmed the prototype’s second order filtering as against the first order filtering in traditional BBC.
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.
Biogeography Based Optimization Approach for Optimal Power Flow Problem Consi...IDES Editor
This paper presents a novel Biogeography Based
Optimization (BBO) algorithm for solving multi-objective
constrained optimal power flow problems in power system. In
this paper, the feasibility of the proposed algorithm is
demonstrated for IEEE 30-bus system with three different
objective functions and it is compared to other well
established population based optimization techniques. A
comparison of simulation results reveals better solution
quality and computation efficiency of the proposed algorithm
over particle swarm optimization (PSO), Real Coded Genetic
algorithm (RGA) for the global optimization of multiobjective
constrained OPF problems.
Hybrid bypass technique to mitigate leakage current in the grid-tied inverterIJECEIAES
The extensive use of fossil fuel is destroying the balance of nature that could lead to many problems in the forthcoming era. Renewable energy resources are a ray of hope to avoid possible destruction. Smart grid and distributed power generation systems are now mainly built with the help of renewable energy resources. The integration of renewable energy production system with the smart grid and distributed power generation is facing many challenges that include addressing the issue of isolation and power quality. This paper presents a new approach to address the aforementioned issues by proposing a hybrid bypass technique concept to improve the overall performance of the grid-tied inverter in solar power generation. The topology with the proposed technique is presented using traditional H5, oH5 and H6 inverter. Comparison of topologies with literature is carried out to check the feasibility of the method proposed. It is found that the leakage current of all the proposed inverters is 9 mA and total harmonic distortion is almost about 2%. The proposed topology has good efficiency, common mode and differential mode characteristics.
Optimal power flow based congestion management using enhanced genetic algorithmsIJECEIAES
Congestion management (CM) in the deregulated power systems is germane and of central importance to the power industry. In this paper, an optimal power flow (OPF) based CM approach is proposed whose objective is to minimize the absolute MW of rescheduling. The proposed optimization problem is solved with the objectives of total generation cost minimization and the total congestion cost minimization. In the centralized market clearing model, the sellers (i.e., the competitive generators) submit their incremental and decremental bid prices in a real-time balancing market. These can then be incorporated in the OPF problem to yield the incremental/ decremental change in the generator outputs. In the bilateral market model, every transaction contract will include a compensation price that the buyer-seller pair is willing to accept for its transaction to be curtailed. The modeling of bilateral transactions are equivalent to the modifying the power injections at seller and buyer buses. The proposed CM approach is solved by using the evolutionary based Enhanced Genetic Algorithms (EGA). IEEE 30 bus system is considered to show the effectiveness of proposed CM approach.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
FAST VOLTAGE STABILTY INDEX BASED OPTIMAL REACTIVE POWER PLANNING USING DIFFE...elelijjournal
This Article presents an application of Fast Voltage Stability Index (FVSI) to Optimal Reactive Power
Planning (RPP) using Differential Evolution(DE). FVSI is used to identify the weak buses for the Reactive
Power Planning problem which involves process of experimental by voltage stability analysis based on the
load variation. The peak at Fast Voltage Stabilty Index secure to 1 indicates the greatest feasible connected
load and the bus with least connected load is identified as the weakest bus at the point of bifurcation. This technique is tested on the IEEE 30-bus system. The outcome confirm significant decrease in system losses and enhancementt of voltage stability with the use of Fast Voltage Stability Index based optimal Reactive Power Planning using Differential Evolution and compared with Evalutionary Programming
FAST VOLTAGE STABILTY INDEX BASED OPTIMAL REACTIVE POWER PLANNING USING DIFFE...
Similar to Genetic algorithm based Different Re-dispatching Scheduling of Generator Units for Calculating Short Run Marginal Cost in Deregulated Environment
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The document discusses voltage stability enhancement in radial distribution systems through optimal placement of distributed generators (DGs) and capacitors. It proposes using the Moth Flame Optimization algorithm to determine the optimal location and sizing of DGs and capacitors to minimize power losses and maximize net savings. The methodology considers constraints like voltage limits and power flow limits. Test systems like IEEE 12 and 33 node systems are used to demonstrate the effectiveness of the proposed approach.
IRJET- Optimal Power Flow Solution of Transmission Line Network of Electric p...IRJET Journal
This document discusses using a genetic algorithm to solve the optimal power flow problem in large power transmission networks. The optimal power flow problem aims to minimize generation costs while meeting operational constraints. A genetic algorithm is proposed to solve this problem globally and efficiently. The controllable variables are divided into dynamic constraints directly impacting cost and static constraints maintained within limits by the load flow. The algorithm is tested on the IEEE 30-bus system and shown to effectively find the optimal solution. Genetic algorithms are well-suited for this problem as they can evaluate multiple solutions in parallel without requiring derivative information like traditional methods.
Economic Load Dispatch for Multi-Generator Systems with Units Having Nonlinea...IJAPEJOURNAL
This document presents an economic load dispatch problem that uses the Gravity Search Algorithm to minimize total generation costs for multi-generator power systems. It discusses how practical constraints like valve point loading, multi-fuel operation, and forbidden zones result in non-ideal, non-continuous generator cost curves. The Gravity Search Algorithm is applied to find the optimal dispatch schedule that accounts for these realistic cost functions and minimizes the total cost of generation while satisfying demand. The algorithm is tested on sample power systems and able to find solutions within acceptable timeframes that outperform traditional optimization methods for large, complex problems.
Hybrid Particle Swarm Optimization for Multi-objective Reactive Power Optimiz...IDES Editor
This paper proposes a hybrid particle swarm optimization (HPSO) method to solve the multi-objective reactive power dispatch problem of minimizing transmission losses and maximizing voltage stability. The HPSO method expands on PSO and genetic algorithms to handle mixed integer and nonlinear optimization problems with both continuous and discrete control variables. The method is evaluated on the IEEE 30-bus and 57-bus test systems. Results show the HPSO approach improves voltage stability compared to conventional, genetic algorithm, and particle swarm optimization methods.
Network loss reduction and voltage improvement by optimal placement and sizin...nooriasukmaningtyas
This document presents a study on optimizing the placement and sizing of distributed generators (DGs) in radial distribution systems using a fine-tuned particle swarm optimization approach. Simulation results on the IEEE 33 bus, IEEE 69 bus, and a 54 bus Malaysian network show that integrating both active and reactive power injection (type II DGs) achieves greater reductions in network power losses and improvements in voltage profiles compared to only active power injection (type I DGs). The maximum power loss reductions achieved with three type II DGs are 89.54% for IEEE 33 bus, 94.95% for IEEE 69 bus, and 95.23% for the 54 bus Malaysian network.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
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.
A new approach to the solution of economic dispatch using particle Swarm opt...ijcsa
This document presents a new approach to solving the economic dispatch problem using particle swarm optimization combined with simulated annealing (PSO-SA). The economic dispatch problem aims to minimize the total generation cost while satisfying constraints like power demand and generator limits. Previous solutions had limitations. The authors propose using PSO-SA to find high quality solutions more efficiently. PSO is able to find global optima but can get trapped in local optima. SA helps avoid this through probabilistic jumping. The authors combine PSO and SA techniques to leverage their benefits while overcoming individual limitations. They test the PSO-SA method on three generator systems and find it provides better results than traditional and other computational methods.
This document summarizes a research paper that proposes a new approach for solving the economic dispatch problem in power systems using a hybrid particle swarm optimization and simulated annealing algorithm. The paper introduces economic dispatch and describes previous solution methods. It then presents the new hybrid algorithm, which combines the global search capabilities of particle swarm optimization with the probabilistic jumping of simulated annealing to find high-quality solutions faster. The paper applies the method to test cases and finds it performs better than traditional and other computational techniques at determining low-cost generation schedules that satisfy operational constraints.
The document proposes a new approach for solving the economic dispatch problem in power systems using a hybrid particle swarm optimization and simulated annealing algorithm. It begins with introductions to economic dispatch and optimization techniques like particle swarm optimization and simulated annealing. It then describes the economic dispatch problem formulation, including the objective of minimizing generation cost while satisfying constraints. The document proposes a novel hybrid algorithm that combines the salient features of particle swarm optimization and simulated annealing to generate high-quality solutions efficiently. It presents the particle swarm optimization, simulated annealing and hybrid algorithms in detail. The effectiveness of the proposed approach is demonstrated through case studies on different power systems.
IRJET- A Comparative Study of Economic Load Dispatch Optimization MethodsIRJET Journal
This document presents a comparative study of different optimization methods for solving the economic load dispatch (ELD) problem in power systems. The ELD problem involves minimizing generation costs while meeting demand, and is formulated as a non-linear optimization problem with constraints. Various conventional and evolutionary algorithms have been used to solve ELD, but more recently bio-inspired algorithms like flower pollination algorithm and Jaya optimization have shown better performance. The paper evaluates these nature-inspired algorithms and compares their results for the ELD problem to demonstrate their effectiveness.
Optimal Economic Load Dispatch of the Nigerian Thermal Power Stations Using P...theijes
This document summarizes the application of particle swarm optimization (PSO) to solve the economic load dispatch (ELD) problem for Nigeria's thermal power stations. PSO is used to determine the optimal allocation of total power demand among generating units to minimize total fuel costs while satisfying constraints. The PSO algorithm is applied to a 1999 model of Nigeria's power network and results are compared to other heuristic methods. PSO efficiently distributes load to minimize costs and overcomes limitations of traditional optimization techniques for non-linear power system problems.
Comparative study of methods for optimal reactive power dispatchelelijjournal
Reactive power dispatch plays a main role in order to provide good facility secure and economic operation
in the power system. In a power system optimal reactive power dispatch is supported to improve the voltage
profile, to reduce losses, to improve voltage stability, to reduce cost etc. This paper presents a brief literature survey of reactive power dispatch and also discusses a comparative study of conventional and evolutionary computation techniques applied for reactive power dispatch. The paper is useful for researchers for further research and study so that it can apply in the various areas of power system
Optimal Unit Commitment Based on Economic Dispatch Using Improved Particle Sw...paperpublications3
The document presents an improved particle swarm optimization (IPSO) algorithm for solving the optimal unit commitment problem in power systems. The IPSO algorithm extends the standard PSO algorithm by using additional particle information to control mutation and mimic social behaviors. The algorithm was implemented on the IEEE 14 bus test system in MATLAB. Results showed the IPSO approach committed units to meet load demand over 24 hours while satisfying constraints, with bus voltages maintained between 1.0017 and 1.0751 per unit. Total costs including fuel, startup, and shutdown costs were minimized at each hour.
IMPROVED SWARM INTELLIGENCE APPROACH TO MULTI OBJECTIVE ED PROBLEMSSuganthi Thangaraj
Electrical power industry restructuring has created highly vibrant and competitive market that altered many aspects of the power industry. In this changed scenario, scarcity of energy resources, increasing power generation cost, environment concern, ever growing demand for electrical energy necessitate optimal economic dispatch. Practical economic dispatch (ED) problems have nonlinear, non-convex type objective function with intense equality and inequality constraints. The conventional optimization methods are not able to solve such problems as due to local optimum solution convergence. Metaheuristic optimization techniques especially Improved Particle Swarm Optimization (IPSO) has gained an incredible recognition as the solution algorithm for such type of ED problems in last decade. The application of IPSO in ED problem, which is considered as one of the most complex optimization problem has been summarized in present paper. This paper illustrates successful implementation of the Improved Particle Swarm Optimization (IPSO) to Economic Load Dispatch Problem (ELD). Power output of each generating unit and optimum fuel cost obtained using IPSO algorithm has been compared with conventional techniques. The results obtained shows that IPSO algorithm converges to optimal fuel cost with reduced computational time when compared to PSO and GA for the three, six and IEEE 30 bus system.
Firefly Algorithm to Opmimal Distribution of Reactive Power Compensation Units IJECEIAES
The issue of electric power grid mode of optimization is one of the basic directions in power engineering research. Currently, methods other than classical optimization methods based on various bio-heuristic algorithms are applied. The problems of reactive power optimization in a power grid using bio-heuristic algorithms are considered. These algorithms allow obtaining more efficient solutions as well as taking into account several criteria. The Firefly algorithm is adapted to optimize the placement of reactive power sources as well as to select their values. A key feature of the proposed modification of the Firefly algorithm is the solution for the multi-objective optimization problem. Algorithms based on a bio-heuristic process can find a neighborhood of global extreme, so a local gradient descent in the neighborhood is applied for a more accurate solution of the problem. Comparison of gradient descent, Firefly algorithm and Firefly algorithm with gradient descent is carried out.
Dual technique of reconfiguration and capacitor placement for distribution sy...IJECEIAES
Radial Distribution System (RDS) suffer from high real power losses and lower bus voltages. Distribution System Reconfiguration (DSR) and Optimal Capacitor Placement (OCP) techniques are ones of the most economic and efficient approaches for loss reduction and voltage profile improvement while satisfy RDS constraints. The advantages of these two approaches can be concentrated using of both techniques together. In this study two techniques are used in different ways. First, the DSR technique is applied individually. Second, the dual technique has been adopted of DSR followed by OCP in order to identify the technique that provides the most effective performance. Three optimization algorithms have been used to obtain the optimal design in individual and dual technique. Two IEEE case studies (33bus, and 69 bus) used to check the effectiveness of proposed approaches. A Direct Backward Forward Sweep Method (DBFSM) has been used in order to calculate the total losses and voltage of each bus. Results show the capability of the proposed dual technique using Modified Biogeography Based Optimization (MBBO) algorithm to find the optimal solution for significant loss reduction and voltage profile enhancement. In addition, comparisons with literature works done to show the superiority of proposed algorithms in both techniques.
A Decomposition Aggregation Method for Solving Electrical Power Dispatch Prob...raj20072
This document proposes a decomposition/aggregation method to solve large-scale economic dispatch problems with many generators. It decomposes a power system into areas, each containing generators and loads. An evolutionary programming technique optimizes dispatch in each area locally. The area solutions are then aggregated to solve the overall system problem while minimizing total cost. The method is demonstrated on 5-bus and 26-bus test systems decomposed into two areas each. Local area problems are solved as subproblems, while the overall system solution is the "master problem". Results are compared to a centralized approach. The decomposition/aggregation method shows promise in solving economic dispatch with large numbers of generators.
Hybrid Particle Swarm Optimization for Solving Multi-Area Economic Dispatch P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation to the power generators in such a manner that the total fuel cost is minimized while all operating constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration Coefficients (PSO-TVAC) and RCGA.
Similar to Genetic algorithm based Different Re-dispatching Scheduling of Generator Units for Calculating Short Run Marginal Cost in Deregulated Environment (20)
Power System State Estimation - A ReviewIDES Editor
This document provides a review of power system state estimation techniques. It discusses both static and dynamic state estimation algorithms. For static state estimation, it covers weighted least squares, decoupled, and robust estimation methods. Weighted least squares is commonly used but can have numerical instability issues. Decoupled state estimation approximates the gain matrix for faster computation. Robust estimation uses M-estimators and other techniques to handle outliers and bad data. Dynamic state estimation applies Kalman filtering, leapfrog algorithms, and other methods to continuously monitor system states over time.
Artificial Intelligence Technique based Reactive Power Planning Incorporating...IDES Editor
This document summarizes a research paper that proposes using artificial intelligence techniques and FACTS controllers for reactive power planning in real-time power transmission systems. The paper formulates the reactive power planning problem and incorporates flexible AC transmission system (FACTS) devices like static VAR compensators (SVC), thyristor controlled series capacitors (TCSC), and unified power flow controllers (UPFC). Evolutionary algorithms like evolutionary programming (EP) and differential evolution (DE) are applied to find the optimal locations and settings of the FACTS controllers to minimize losses and costs. Simulation results on IEEE 30-bus and 72-bus Indian test systems show that UPFC performs best in reducing losses compared to SVC and TCSC.
Design and Performance Analysis of Genetic based PID-PSS with SVC in a Multi-...IDES Editor
Damping of power system oscillations with the help
of proposed optimal Proportional Integral Derivative Power
System Stabilizer (PID-PSS) and Static Var Compensator
(SVC)-based controllers are thoroughly investigated in this
paper. This study presents robust tuning of PID-PSS and
SVC-based controllers using Genetic Algorithms (GA) in
multi machine power systems by considering detailed model
of the generators (model 1.1). The effectiveness of FACTSbased
controllers in general and SVC-based controller in
particular depends upon their proper location. Modal
controllability and observability are used to locate SVC–based
controller. The performance of the proposed controllers is
compared with conventional lead-lag power system stabilizer
(CPSS) and demonstrated on 10 machines, 39 bus New England
test system. Simulation studies show that the proposed genetic
based PID-PSS with SVC based controller provides better
performance.
Optimal Placement of DG for Loss Reduction and Voltage Sag Mitigation in Radi...IDES Editor
This paper presents the need to operate the power
system economically and with optimum levels of voltages has
further led to an increase in interest in Distributed
Generation. In order to reduce the power losses and to improve
the voltage in the distribution system, distributed generators
(DGs) are connected to load bus. To reduce the total power
losses in the system, the most important process is to identify
the proper location for fixing and sizing of DGs. It presents a
new methodology using a new population based meta heuristic
approach namely Artificial Bee Colony algorithm(ABC) for
the placement of Distributed Generators(DG) in the radial
distribution systems to reduce the real power losses and to
improve the voltage profile, voltage sag mitigation. The power
loss reduction is important factor for utility companies because
it is directly proportional to the company benefits in a
competitive electricity market, while reaching the better power
quality standards is too important as it has vital effect on
customer orientation. In this paper an ABC algorithm is
developed to gain these goals all together. In order to evaluate
sag mitigation capability of the proposed algorithm, voltage
in voltage sensitive buses is investigated. An existing 20KV
network has been chosen as test network and results are
compared with the proposed method in the radial distribution
system.
Line Losses in the 14-Bus Power System Network using UPFCIDES Editor
Controlling power flow in modern power systems
can be made more flexible by the use of recent developments
in power electronic and computing control technology. The
Unified Power Flow Controller (UPFC) is a Flexible AC
transmission system (FACTS) device that can control all the
three system variables namely line reactance, magnitude and
phase angle difference of voltage across the line. The UPFC
provides a promising means to control power flow in modern
power systems. Essentially the performance depends on proper
control setting achievable through a power flow analysis
program. This paper presents a reliable method to meet the
requirements by developing a Newton-Raphson based load
flow calculation through which control settings of UPFC can
be determined for the pre-specified power flow between the
lines. The proposed method keeps Newton-Raphson Load Flow
(NRLF) algorithm intact and needs (little modification in the
Jacobian matrix). A MATLAB program has been developed to
calculate the control settings of UPFC and the power flow
between the lines after the load flow is converged. Case studies
have been performed on IEEE 5-bus system and 14-bus system
to show that the proposed method is effective. These studies
indicate that the method maintains the basic NRLF properties
such as fast computational speed, high degree of accuracy and
good convergence rate.
Study of Structural Behaviour of Gravity Dam with Various Features of Gallery...IDES Editor
The size and shape of opening in dam causes the
stress concentration, it also causes the stress variation in the
rest of the dam cross section. The gravity method of the analysis
does not consider the size of opening and the elastic property
of dam material. Thus the objective of study is comprises of
the Finite Element Method which considers the size of
opening, elastic property of material, and stress distribution
because of geometric discontinuity in cross section of dam.
Stress concentration inside the dam increases with the opening
in dam which results in the failure of dam. Hence it is
necessary to analyses large opening inside the dam. By making
the percentage area of opening constant and varying size and
shape of opening the analysis is carried out. For this purpose
a section of Koyna Dam is considered. Dam is defined as a
plane strain element in FEM, based on geometry and loading
condition. Thus this available information specified our path
of approach to carry out 2D plane strain analysis. The results
obtained are then compared mutually to get most efficient
way of providing large opening in the gravity dam.
Assessing Uncertainty of Pushover Analysis to Geometric ModelingIDES Editor
Pushover Analysis a popular tool for seismic
performance evaluation of existing and new structures and is
nonlinear Static procedure where in monotonically increasing
loads are applied to the structure till the structure is unable
to resist the further load .During the analysis, whatever the
strength of concrete and steel is adopted for analysis of
structure may not be the same when real structure is
constructed and the pushover analysis results are very sensitive
to material model adopted, geometric model adopted, location
of plastic hinges and in general to procedure followed by the
analyzer. In this paper attempt has been made to assess
uncertainty in pushover analysis results by considering user
defined hinges and frame modeled as bare frame and frame
with slab modeled as rigid diaphragm and results compared
with experimental observations. Uncertain parameters
considered includes the strength of concrete, strength of steel
and cover to the reinforcement which are randomly generated
and incorporated into the analysis. The results are then
compared with experimental observations.
Secure Multi-Party Negotiation: An Analysis for Electronic Payments in Mobile...IDES Editor
This document summarizes and analyzes secure multi-party negotiation protocols for electronic payments in mobile computing. It presents a framework for secure multi-party decision protocols using lightweight implementations. The main focus is on synchronizing security features to avoid agreement manipulation and reduce user traffic. The paper describes negotiation between an auctioneer and bidders, showing multiparty security is better than existing systems. It analyzes the performance of encryption algorithms like ECC, XTR, and RSA for use in the multiparty negotiation protocols.
Selfish Node Isolation & Incentivation using Progressive ThresholdsIDES Editor
The problems associated with selfish nodes in
MANET are addressed by a collaborative watchdog approach
which reduces the detection time for selfish nodes thereby
improves the performance and accuracy of watchdogs[1]. In
the related works they make use of credit based systems, reputation
based mechanisms, pathrater and watchdog mechanism
to detect such selfish nodes. In this paper we follow an approach
of collaborative watchdog which reduces the detection
time for selfish nodes and also involves the removal of such
selfish nodes based on some progressively assessed thresholds.
The threshold gives the nodes a chance to stop misbehaving
before it is permanently deleted from the network.
The node passes through several isolation processes before it
is permanently removed. Another version of AODV protocol
is used here which allows the simulation of selfish nodes in
NS2 by adding or modifying log files in the protocol.
Various OSI Layer Attacks and Countermeasure to Enhance the Performance of WS...IDES Editor
Wireless sensor networks are networks having non
wired infrastructure and dynamic topology. In OSI model each
layer is prone to various attacks, which halts the performance
of a network .In this paper several attacks on four layers of
OSI model are discussed and security mechanism is described
to prevent attack in network layer i.e wormhole attack. In
Wormhole attack two or more malicious nodes makes a covert
channel which attracts the traffic towards itself by depicting a
low latency link and then start dropping and replaying packets
in the multi-path route. This paper proposes promiscuous mode
method to detect and isolate the malicious node during
wormhole attack by using Ad-hoc on demand distance vector
routing protocol (AODV) with omnidirectional antenna. The
methodology implemented notifies that the nodes which are
not participating in multi-path routing generates an alarm
message during delay and then detects and isolate the
malicious node from network. We also notice that not only
the same kind of attacks but also the same kind of
countermeasures can appear in multiple layer. For example,
misbehavior detection techniques can be applied to almost all
the layers we discussed.
Responsive Parameter based an AntiWorm Approach to Prevent Wormhole Attack in...IDES Editor
The recent advancements in the wireless technology
and their wide-spread deployment have made remarkable
enhancements in efficiency in the corporate and industrial
and Military sectors The increasing popularity and usage of
wireless technology is creating a need for more secure wireless
Ad hoc networks. This paper aims researched and developed
a new protocol that prevents wormhole attacks on a ad hoc
network. A few existing protocols detect wormhole attacks but
they require highly specialized equipment not found on most
wireless devices. This paper aims to develop a defense against
wormhole attacks as an Anti-worm protocol which is based on
responsive parameters, that does not require as a significant
amount of specialized equipment, trick clock synchronization,
no GPS dependencies.
Cloud Security and Data Integrity with Client Accountability FrameworkIDES Editor
This document summarizes a proposed cloud security and data integrity framework that provides client accountability. The framework aims to address issues like lack of user control over cloud data, need for data transparency and tracking, and ensuring data integrity. It proposes using JAR (Java Archive) files for data sharing due to benefits like portability. The framework incorporates client-side verification using MD5 hashing, digital signature-based authentication of JAR files, and use of HMAC to ensure data integrity. It also uses password-based encryption of log files to keep them tamper-proof. The framework is intended to provide both accountability and security for data sharing in cloud environments.
Genetic Algorithm based Layered Detection and Defense of HTTP BotnetIDES Editor
A System state in HTTP botnet uses HTTP protocol
for the creation of chain of Botnets thereby compromising
other systems. By using HTTP protocol and port number 80,
attacks can not only be hidden but also pass through the
firewall without being detected. The DPR based detection
leads to better analysis of botnet attacks [3]. However, it
provides only probabilistic detection of the attacker and also
time consuming and error prone. This paper proposes a Genetic
algorithm based layered approach for detecting as well as
preventing botnet attacks. The paper reviews p2p firewall
implementation which forms the basis of filtering.
Performance evaluation is done based on precision, F-value
and probability. Layered approach reduces the computation
and overall time requirement [7]. Genetic algorithm promises
a low false positive rate.
Enhancing Data Storage Security in Cloud Computing Through SteganographyIDES Editor
This document summarizes a research paper that proposes a method for enhancing data security in cloud computing through steganography. The method hides user data in digital images stored on cloud servers. When data needs to be accessed, it is extracted from the images. The document outlines the cloud architecture and security issues addressed. It then describes the proposed system architecture, security model, and data storage and retrieval process. Data is partitioned and hidden in multiple images to improve security. The goal is to prevent unauthorized access to user data stored on cloud servers.
The main tasks of a Wireless Sensor Network
(WSN) are data collection from its nodes and communication
of this data to the base station (BS). The protocols used for
communication among the WSN nodes and between the WSN
and the BS, must consider the resource constraints of nodes,
battery energy, computational capabilities and memory. The
WSN applications involve unattended operation of the network
over an extended period of time. In order to extend the lifetime
of a WSN, efficient routing protocols need to be adopted. The
proposed low power routing protocol based on tree-based
network structure reliably forwards the measured data towards
the BS using TDMA. An energy consumption analysis of the
WSN making use of this protocol is also carried out. It is
found that the network is energy efficient with an average
duty cycle of 0:7% for the WSN nodes. The OmNET++
simulation platform along with MiXiM framework is made
use of.
Permutation of Pixels within the Shares of Visual Cryptography using KBRP for...IDES Editor
The security of authentication of internet based
co-banking services should not be susceptible to high risks.
The passwords are highly vulnerable to virus attacks due to
the lack of high end embedding of security methods. In order
for the passwords to be more secure, people are generally
compelled to select jumbled up character based passwords
which are not only less memorable but are also equally prone
to insecurity. Multiple use of distributed shares has been
studied to solve the problem of authentication by algorithms
based on thresholding of pixels in image processing and visual
cryptography concepts where the subset of shares is considered
for the recovery of the original image for authentication using
correlation function[1][2].The main disadvantage in the above
study is the plain storage of shares and also one of the shares
is being supplied to the customer, which will lead to the
possibility of misuse by a third party. This paper proposes a
technique for scrambling of pixels by key based random
permutation (KBRP) within the shares before the
authentication has been attempted. Total number of shares to
be created is dependent on the multiplicity of ownership of
the account. By this method the problem of uncertainty among
the customers with regard to security, storage, retrieval of
holding of half of the shares is minimized.
This paper presents a trifocal Rotman Lens Design
approach. The effects of focal ratio and element spacing on
the performance of Rotman Lens are described. A three beam
prototype feeding 4 element antenna array working in L-band
has been simulated using RLD v1.7 software. Simulated
results show that the simulated lens has a return loss of –
12.4dB at 1.8GHz. Beam to array port phase error variation
with change in the focal ratio and element spacing has also
been investigated.
Band Clustering for the Lossless Compression of AVIRIS Hyperspectral ImagesIDES Editor
Hyperspectral images can be efficiently compressed
through a linear predictive model, as for example the one
used in the SLSQ algorithm. In this paper we exploit this
predictive model on the AVIRIS images by individuating,
through an off-line approach, a common subset of bands, which
are not spectrally related with any other bands. These bands
are not useful as prediction reference for the SLSQ 3-D
predictive model and we need to encode them via other
prediction strategies which consider only spatial correlation.
We have obtained this subset by clustering the AVIRIS bands
via the clustering by compression approach. The main result
of this paper is the list of the bands, not related with the
others, for AVIRIS images. The clustering trees obtained for
AVIRIS and the relationship among bands they depict is also
an interesting starting point for future research.
Microelectronic Circuit Analogous to Hydrogen Bonding Network in Active Site ...IDES Editor
A microelectronic circuit of block-elements
functionally analogous to two hydrogen bonding networks is
investigated. The hydrogen bonding networks are extracted
from â-lactamase protein and are formed in its active site.
Each hydrogen bond of the network is described in equivalent
electrical circuit by three or four-terminal block-element.
Each block-element is coded in Matlab. Static and dynamic
analyses are performed. The resultant microelectronic circuit
analogous to the hydrogen bonding network operates as
current mirror, sine pulse source, triangular pulse source as
well as signal modulator.
Texture Unit based Monocular Real-world Scene Classification using SOM and KN...IDES Editor
In this paper a method is proposed to discriminate
real world scenes in to natural and manmade scenes of similar
depth. Global-roughness of a scene image varies as a function
of image-depth. Increase in image depth leads to increase in
roughness in manmade scenes; on the contrary natural scenes
exhibit smooth behavior at higher image depth. This particular
arrangement of pixels in scene structure can be well explained
by local texture information in a pixel and its neighborhood.
Our proposed method analyses local texture information of a
scene image using texture unit matrix. For final classification
we have used both supervised and unsupervised learning using
K-Nearest Neighbor classifier (KNN) and Self Organizing
Map (SOM) respectively. This technique is useful for online
classification due to very less computational complexity.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.