Orpd is necessary for safe operation of power systems with regard to voltage stability. To improve the performance of quantuminspired evolutionary algorithms qieas, a new kind of qieaselite group guided qiea eqiea are proposed through introducing an elite group guidance updating approach to solve knapsack problems. So this paper presents a real coded quantum evolutionary algorithm rcqea. Adaptive quantuminspired evolutionary algorithm for. Optimal reactive power dispatch orpd is an important optimization operation problem in power system field. Orpd can enable power systems to work stably and economically by setting the most appropriate parameters for electric components such as tap changer value of transformers, reactive power generation of capacitors and voltage magnitude of generators.
Hybrid quantum genetic particle swarm optimization. Evolutionary quantum and quantum inspired algorithms. Qepsdms combines quantuminspired evolutionary algorithms qieas with a p system with a dynamic membrane structure. Optimal reactive power dispatch under unbalanced conditions. Lee, life fellow, ieee abstractthis paper presents an evolutionary algorithm based on quantum computation for bidbased optimal real and reactive power pq. Higherorder quantuminspired genetic algorithms annals of. The quantum state population is firstly divided into multiple subpopulations, which complete the evolution processes independently. Qea uses a qbit representation instead of binary, numeric or symbolic representations. Proposed iqa can be viewed as a kind of hybridization. A novel quantuminspired binary gravitational search. Hybrid quantum genetic particle swarm optimization algorithm.
Qu antum inspired evolutionary algorithm for real and reactive power disp. This chapter presents how multiobjective bilevel programming moblp in a hierarchical structure can be efficiently used for modeling and solving optimal power generation and dispatch problems via genetic algorithm ga based fuzzy goal programming fgp method in a power system operation and planning horizon. Qepsdms combines quantum inspired evolutionary algorithms qieas with a p system with a dynamic membrane structure. Lee, quantuminspired evolutionary algorithm for real and reactive power dispatch, ieee transactions on power systems, 23 2008. Quantum inspired evolutionary algorithms, one of the three main research areas related to the complex interaction between quantum computing and evolutionary algorithms, are receiving renewed attention. A novel evolutionary computing algorithm called the quantuminspired evolutionary algorithm qea was proposed and pursued. Pdf economic dispatch using quantum evolutionary algorithm. In this paper, the nature inspired differential evolutionary based bat algorithm deba is introduced to solve. Real parameter quantum evolutionary algorithm for economic load dispatch. Finding solutions for optimal reactive power dispatch problem. Leequantum inspired evolutionary algorithm for real and reactive power dispatch.
Single and multiobjective optimal reactive power dispatch. Use of a multiobjective teachinglearning algorithm for. Natural computing algorithm represent a very important field in computational intelligence, soft computing and optimization in a general sense. In 21 a quantum inspired evolutionary algorithm is 60 developed for real and reactive power optimization. Special issue on quantum inspired swarm and evolutionary computing algorithms for optimization problems 1. An improved quantuminspired evolutionary algorithm based on. The proposed quantuminspired evolutionary algorithm qea has continue reading. A quantuminspired evolutionary algorithm with elite group guided.
Quantuminspired evolutionary algorithm for real and reactive. This paper presents an evolutionary algorithm based on quantum computation for bidbased optimal real and reactive power pq dispatch. This paper puts forward a novel particle swarm optimization algorithm with quantum behavior qpso to solve reactive power optimization in power system with distributed generation. Rcqea uses the variable component of the solving complex functions and qubit to construct a. A quantuminspired evolutionary algorithm with elite group. Evolutionary quantum and quantuminspired algorithms. Quantum inspired evolutionary algorithm for real and reactive power dispatch, in this paper, qea determines the settings of control variables, such as generator outputs, generator voltages. Optimal reactive power dispatch using differential evolution. Natural phenomenon can be used to solve complex optimization problems with its excellent facts, functions, and phenomenon. Theoretically, there is a coupling relation between arpds. Big bangbig crunch bbbc algorithm for reactive power optimization 8 latest development in the field of eas is quantum evolutionary algorithms qea 45, 46, which synergistically combines the principles of quantum computing and eas. This paper presents a multiobjective teaching learning algorithm based on decomposition for solving the optimal reactive power dispatch problem orpd.
Rcqea uses the variable component of the solving complex functions and qubit to construct a real coded triploid chromosome in order to. Joint economic and emission dispatch in energy markets. Special issue on quantum inspired swarm and evolutionary. Research and applications explores the latest quantum computational intelligence approaches, initiatives, and applications in computing, engineering, science, and business. In this algorithm, the standard binary gravitational search algorithm is modified by applying the concept and principles of quantum behaviour as. Read improved artificial bee colony algorithm considering harvest season for computing economic dispatch on power system, ieej transactions on electrical and electronic engineering on deepdyve, the largest online rental service for scholarly research with thousands of academic publications available at your fingertips. Research article quantuminspired evolutionary algorithm for. Optimal reactive power flow is an important tool in terms of secure and operation of power. Generally, the production reactive power cost is less, but it effects the production cost of the active power transmission loss. Hybrid real coded genetic algorithm solution to economic dispatch problem. Control of voltage profile with optimal control and placement.
Prospective algorithms for quantum evolutionary computation. The book explores this emerging field of research that applies principles of quantum mechanics to develop more efficient and. The proposed meed formulation includes emission minimization objective, ac load flow constraints and security constraints of the power system which usually are found simultaneously in realworld power systems. A chaotic modified algorithm for economic dispatch problems. Improve this page add a description, image, and links to the quantuminspiredgeneticalgorithm topic page so that developers can more easily learn about it. Qea can be used for the p lacements, sizing and the. A novel evolutionary computing algorithm called the quantum inspired evolutionary algorithm qea was proposed and pursued.
This study presented a novel quantum inspired binary gravitational search algorithm method for solving the optimal power quality monitor placement problem in power systems for voltage sag assessment. In 20 a multiobjective orpd is solved by means of a 59 nondominated sorting genetic algorithm. Evaluation, hybridization and application of quantum inspired. This is a study of economic dispatch using quantum evolutionary algorithm qe a in electrical power system involving distributed generators. Economic dispatch using quantum evolutionary algorithm in electrical power system involving distributed generators. A novel firefly programming method for function optimization. An improved quantuminspired genetic algorithm for image. This technique present optimal reactive power dispatch problem is included. Quantuminspired evolutionary algorithms, one of the three main research areas related to the complex interaction between quantum computing and evolutionary algorithms, are receiving renewed attention. Research article quantum inspired evolutionary algorithm for continuous space optimization based on multiple chains encoding method of quantum bits ruizhang,zhitengwang,andhongjunzhang pla university of science and technology, nanjing, china correspondence should be addressed to zhiteng wang. Research article quantuminspired evolutionary algorithm for continuous space optimization based on multiple chains encoding method of quantum bits ruizhang,zhitengwang,andhongjunzhang pla university of science and technology, nanjing, china correspondence should be addressed to zhiteng wang.
Deepika joshi, ashish mani, and anjali jain, solving economic load dispatch problem with valve loading effect using adaptive real coded quantuminspired evolutionary algorithm, ieee international conference cipech17, ghaziabad, up, india, 1819 th nov, 2016. A novel constraint handling approach for the optimal reactive. Solution to optimal reactive power dispatch in transmission. In this paper, a survey on physicsbased algorithm is done to show how these inspirations led to the solution of wellknown optimizat. The proposed model has a more accurate evaluation of transmission losses obtained from the load flow equations. The proposed algorithm introduces an adaptive adjustment strategy of the rotation angle and a cooperative learning strategy into quantum genetic algorithm called iqga. Quantuminspired evolutionary algorithm for real and reactive power dispatch, in this paper, qea determines the settings of control variables, such as generator outputs, generator voltages. Reactive power optimization by minimization of real power loss has long been attempted for voltage stability improvement 34. This multi objective evolutionary algorithm eligible to handle a new strength pareto evolutionary based method used. Lee, quantum inspired evolutionary algorithm for real and reactive power dispatch, ieee transactions on power systems, 23 2008. The proposed quantum inspired evolutionary algorithm qea has applications in various combinatorial optimization problems in power systems and elsewhere. The proposed quantuminspired evolutionary algorithm qea has applications in various combinatorial optimization problems in power systems and elsewhere. Quantum inspired computational intelligence 1st edition. Quantuminspired evolutionary algorithm for real and.
Genetic algorithm based multiobjective bilevel programming. The optimal reactive power dispatch orpd problem represents a noncontinuous, nonlinear, highly constrained optimization problem that has recently attracted wide research investigation. Improve this page add a description, image, and links to the quantum inspired genetic algorithm topic page so that developers can more easily learn about it. In a more recent work, 12 proposes a novel multiuniverse parallel immune qea that uses a learning mechanism.
Introduction of quantuminspired evolutionary algorithm. Economic dispatch using quantum evolutionary algorithm in. Quantum inspired evolutionary algorithm for ordering problems. Prospective algorithms for quantum evolutionary computation donald a. So this paper presents a realcoded quantum evolutionary algorithm rcqea. Jun 29, 2010 quantum inspired evolutionary algorithms, one of the three main research areas related to the complex interaction between quantum computing and evolutionary algorithms, are receiving renewed attention. The proposed method maintains the population diversity along with better convergence speed.
Kannancomprehensive learning particle swarm optimization for reactive power dispatch. Adaptive quantum inspired evolutionary algorithm for optimizing power losses 329 system. Introduction of quantuminspired evolutionary algorithm kukhyun han and jonghwan kim department of electrical engineering and computer science, korea advanced institute of science and technology kaist, 3731, guseongdong, yuseonggu, daejeon, 305701, republic of korea. Ieee transactions on power systems 232008 16271636. Roy 19, 20 used two different metaheuristic algorithms for optimal location and capacity of dg with an objective to reduce the power losses and improve the voltage profile.
In 21 a quantuminspired evolutionary algorithm is 60 developed for real and reactive power optimization. Improved artificial bee colony algorithm considering harvest. Realparameter quantum evolutionary algorithm for economic load dispatch. Y quantuminspired evolutionary algorithm for real and reactive power dispatch. May 01, 2014 read improved artificial bee colony algorithm considering harvest season for computing economic dispatch on power system, ieej transactions on electrical and electronic engineering on deepdyve, the largest online rental service for scholarly research with thousands of academic publications available at your fingertips. This type of algorithm combines principle of quantum and evolutionary computation. Economic dispatch using quantum evolutionary algorithm in electrical power system involving distributed generators ni ketut aryani1, adi soeprijanto2, i made yulistya negara3, mat syaiin4 department of electrical engineering, institut teknologi sepuluh nopember its, surabaya, indonesia article info abstract article history. To improve the performance of quantuminspired evolutionary algorithm based on p systems qeps, this paper presents an improved qeps with a dynamic membrane structure qepsdms to solve knapsack problems.
This paper presents a new hybridization technique for solving the orpd problem based on the integration of particle swarm optimization pso with artificial physics optimization apo. A novel constraint handling approach for the optimal. An enhanced quantumbehaved particle swarm algorithm for. Sofge natural computation group navy center for applied research in artificial intelligence naval research laboratory washington, dc, usa donald. Qea is characterized by principles of quantum computing including concepts of qubits and superposition of states. To improve the performance of quantum inspired evolutionary algorithm based on p systems qeps, this paper presents an improved qeps with a dynamic membrane structure qepsdms to solve knapsack problems. A quantum inspired evolutionary algorithm is a new evolutionary algorithm for a classical computer rather than for quantum mechanical hardware. A multilevel thresholding algorithm for histogrambased image segmentation is presented in this paper. This paper proposes a refined bacterial foraging algorithm rbfa for solving the multiobjective based optimal power dispatch with optimal placement of distributed generation dg to minimize the total real power loss, generation cost, the environmental emission and considering various controls and limits.
Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. In power systems, the two main conditions for economical operation are active power regulation and reactive power dispatch rpd. A quantuminspired evolutionary algorithm is a new evolutionary algorithm for a classical computer rather than for quantum mechanical hardware. This paper focuses on the minimization of active power loss, respectively, and uses qpso and dqpso to determine terminal. Reactive power optimization by real power loss minimization increases the power system economics to some extent. This study presented a novel quantuminspired binary gravitational search algorithm method for solving the optimal power quality monitor placement problem in power systems for voltage sag assessment. An adaptive adjustment strategy of the quantum rotation which is introduced in this study helps improving the convergence. This study presents a comparative study for four evolutionary computation ec methods to the optimal activereactive power dispatch arpd problem.
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