In this paper small signal stability improvement of two-area, four-machine Kundur power system stabilizer is presented using Cuckoo Search algorithm (CSA), particle swarm optimization algorithm (PSOA) and Genetic Algo...
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ISBN:
(纸本)9781467399685
In this paper small signal stability improvement of two-area, four-machine Kundur power system stabilizer is presented using Cuckoo Search algorithm (CSA), particle swarm optimization algorithm (PSOA) and Genetic algorithm (GA). For this the propose, the problem is formulated using an eigenvalue based multiobjective function that shift unstable or poorly damped modes to specific D-shape region in the left-half of the s-plane by controlling the damping ratio and damping factor. To show the effectiveness and superiority of the proposed CSA based PSS (CSAPSS), the non-linear time domain simulations are compared with GA based PSS (GAPSS), PSO based PSS (PSOAPSS) for different line outages and different scenarios of severe disturbances. The robustness of proposed CSAPSS is evaluated by performances indices for wide range of loading conditions with severe faults. Moreover, the lower value of performances indices for proposed CSAPSS than to GAPSS, PSOAPSS exhibit its relative stability.
A particleswarmoptimization (PSO) algorithm based on adaptive mutation and P systems is proposed to overcome trapping in local optimum solution and low optimization precision in this paper. The algorithm combines th...
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ISBN:
(纸本)9783662464694;9783662464687
A particleswarmoptimization (PSO) algorithm based on adaptive mutation and P systems is proposed to overcome trapping in local optimum solution and low optimization precision in this paper. The algorithm combines the evolutionary rules of PSO, the strategy of adaptive mutation with the hierarchical membrane structure, and communication rules of P systems. At the same time, in order to achieve rapid economic operation and effectiveness of the micro-grid the proposed algorithm is investigated in experiments which are based on the function optimization of micro-grid's economic operation. Furthermore, the feasibility and effectiveness of the proposed algorithm are shown in the experimental results.
Vehicles play an important role in transportation. Using fossil fuels as their source of energy, they are a source of pollution. HEVs are improving and a day will come that they will take over the role of conventional...
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ISBN:
(纸本)9781467399395
Vehicles play an important role in transportation. Using fossil fuels as their source of energy, they are a source of pollution. HEVs are improving and a day will come that they will take over the role of conventional vehicles. In the path of improving HEVs, optimizing components sizes of the vehicle and better strategy controls are vital methods to reach the desired goals. In this path practical tools for optimization are evolutionary algorithms and fuzzy controllers as a strategy control decision maker. In this paper, accompanied with these tools extraordinary improvements are made. On the UDDS cycle using PSO algorithm we reached 57%, 68%, 34% and 8% decrease respectively in fuel consumption, emission, economic and acceleration and we reached 30% increase in maximum speed gained. On the HWFET cycle we reached 74%, 79%, 34% and 8% decrease respectively in fuel consumption, emission, economic and acceleration and we reached 30% increase in maximum speed gained. Acquiring a Pareto Front for two fitness functions we can choose a specific vehicle with special capabilities according to our priorities.
In this paper, an evolutionary computing technique comprising of Fuzzy logic and particleswarmoptimization (PSO) algorithm has been proposed for optimal location and sizing of STATCOM to improve the voltage stabilit...
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ISBN:
(纸本)9781509001286
In this paper, an evolutionary computing technique comprising of Fuzzy logic and particleswarmoptimization (PSO) algorithm has been proposed for optimal location and sizing of STATCOM to improve the voltage stability and to minimize the total voltage deviation in a power system. The proposed Fuzzy-PSO algorithm has been applied using two steps. As the first step, the weakest buses selected for placement of STATCOM using modal analysis. In the second step Fuzzy-PSO algorithm has been applied for selecting optimal location of STATCOM considering these selected weakest buses. The proposed approach has been applied on the standard IEEE 30-bus system considering the most severe single line outage contingencies under normal loading and under stressed condition. The proposed Fuzzy-PSO approach has been found to be quite satisfactory.
In order to further improve the accuracy of the short-term traffic flow prediction, a combination of short-term traffic flow prediction model had been proposed by analyzing the characteristics of grey model, adaptive ...
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ISBN:
(纸本)9781467390262
In order to further improve the accuracy of the short-term traffic flow prediction, a combination of short-term traffic flow prediction model had been proposed by analyzing the characteristics of grey model, adaptive particleswarmoptimization (PSO) algorithm and support vector machine (SVM) model. First, use the grey model to accumulate the original traffic flow data, weaken the randomness of the traffic flow data sequence, then optimize the support vector machine model based on adaptive particle swarm optimization algorithm and realize short-term traffic flow prediction, finally, get the final predicted value table by grey mode. The model was verified based on the traffic flow data of the major road in Changchun and the experimental result showed the proposed model was effective and feasible.
Inspired by the behaviors of plant root growth,an Artificial Root Mass(ARM) optimizationalgorithm based on an artificial root model is *** ARM algorithm simulates the plant's root growth strategies including prol...
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ISBN:
(纸本)9781509009107
Inspired by the behaviors of plant root growth,an Artificial Root Mass(ARM) optimizationalgorithm based on an artificial root model is *** ARM algorithm simulates the plant's root growth strategies including proliferation and'intelligent' decisions about growth *** well-known benchmark functions are employed to validate its optimization *** is compared with other existingalgorithms,includinggenetic algorithm(GA),particleswarmoptimization(PSO) and differential evolution(DE).The experimental results show that ARM seems much superior to other algorithms on the selected benchmark functions in multidimensional *** algorithm is used for data clustering on several benchmark *** performance of the ARM algorithm is compared with GA,PSO and DE on clustering *** simulation results show that the proposed ARM outperforms the otherthree algorithms in terms of accuracy and robustness onmost of selected *** proposed algorithm ARM provides a new reference for solving data clustering problems.
The paper presents a constrained optimization procedure to design a DC-DC converter with coupled inductors for minimizing the power losses. Two algorithms have been used, Genetic and particleswarmoptimization algori...
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ISBN:
(纸本)9784886860989
The paper presents a constrained optimization procedure to design a DC-DC converter with coupled inductors for minimizing the power losses. Two algorithms have been used, Genetic and particle swarm optimization algorithm, and the results have been compared. In particular, with the proposed technique, the electrical, magnetic and geometrical characteristics of the coupled inductors have been obtained and the values of duty cycle and frequency have been defined in order to obtain the maximum efficiency.
The widespread use of renewable energy in microgrid power systems would cause frequency *** in this work,is the frequency stability of the microgrid consisting of wind power systems,photovoltaic systems,micro-turbines...
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ISBN:
(纸本)9781509009107
The widespread use of renewable energy in microgrid power systems would cause frequency *** in this work,is the frequency stability of the microgrid consisting of wind power systems,photovoltaic systems,micro-turbines,electrolyzers and fuel cells with the variation of load power.A novel robust controller is designed for the microgrid to suppress frequency fluctuation by tuning the output of the micro-turbine,electrolyzer and fuel *** generation-rate constraint of the micro-turbine is *** integrating the switching states of the fuel cell and electrolyzer with the micro-turbine power output in order to prevent too large changing rate of the micro-turbine power and improve the utilization of renewable *** is well known that the key point of design a H∞ mixed sensitivity controller is how to select appropriate weighting ***,there are no effective rules to do *** this reason,the particleswarmoptimization（PSO） algorithm is used to optimize the weighting functions to enable the system to achieve optimal *** results show that the mentioned frequency control strategy can effectively stabilize the frequency fluctuation and improve the utilization of renewable energy,and is still effective for the case of large-scale renewable energy penetration.
Over the past few years, distribution system operators try their best in order to obtain the well-balanced distribution systems to reduce the power loss, decrease the operation cost and improve the reliability indices...
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Over the past few years, distribution system operators try their best in order to obtain the well-balanced distribution systems to reduce the power loss, decrease the operation cost and improve the reliability indices. This paper presents an efficient method to solve the multi-periods distribution feeder reconfiguration (DFR) with respect to the presence of Distributed Generators (DGs). Most studies so far have investigated reconfiguration problem as a single period problem considering a fixed level of load. However, in this study, time-varying characteristics of load profiles and line failure rates are considered. The proposed framework formulates and studies the direct and implied costs of power supply, reliability, energy loss, and switching operations, simultaneously. By considering these conditions to the DFR problem, the number of decision variables is significantly increased and the problem becomes more complicated than before. To this end a new modified particleswarmoptimization (PSO) algorithm, compatible with the multi-periods problems, is presented. In the proposed algorithm, the costs of individual periods and the total cost are considered simultaneously in order to update the particles. To evaluate the performance of the proposed method, the results are compared with the original one. A typical distribution test system is used to demonstrate the performance of the proposed approach.
Nowadays, using model checking techniques is one of the best solutions for software (and hardware) verification. The problem while using model checking techniques is state space explosion in which all the available me...
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Nowadays, using model checking techniques is one of the best solutions for software (and hardware) verification. The problem while using model checking techniques is state space explosion in which all the available memory is consumed by the model checker to generate all the reachable states. Among different approaches to cope with the state space explosion problem, using heuristic and meta-heuristic algorithms seems a proper solution. Although in all of these approaches it is not possible to solve the problem totally, however, it is possible to use them as refutation techniques. In the meta-heuristic techniques it is tried to generate only a portion of the state space with the highest probability to reach a faulty state. In this paper, we propose two new algorithms to deadlock detection in complex software systems specified through graph transformation systems. The first approach is a hybrid algorithm using PSO and BAT (BAPSO) and the second one is a greedy algorithm to find deadlocks. The experimental results show that the hybrid approach (BAPSO) is more accurate than PSO, BAT and other existing approaches like Genetic algorithm (GA). In addition, in most of the case studies, the proposed greedy algorithm can compete with the meta-heuristic algorithms in terms of speed and accuracy.
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