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. Hybrid real coded genetic algorithm solution to economic dispatch problem. Reactive power optimization by minimization of real power loss has long been attempted for voltage stability improvement 34. 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. A chaotic modified algorithm for economic dispatch problems. So this paper presents a realcoded quantum evolutionary algorithm rcqea. Quantuminspired evolutionary algorithm for real and reactive. Rcqea uses the variable component of the solving complex functions and qubit to construct a real coded triploid chromosome in order to. Sofge natural computation group navy center for applied research in artificial intelligence naval research laboratory washington, dc, usa donald. Real parameter quantum evolutionary algorithm for economic load dispatch. Qepsdms combines quantum inspired evolutionary algorithms qieas with a p system with a dynamic membrane structure.
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. Hybrid quantum genetic particle swarm optimization algorithm. 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. This multi objective evolutionary algorithm eligible to handle a new strength pareto evolutionary based method used. This is a study of economic dispatch using quantum evolutionary algorithm qe a in electrical power system involving distributed generators. An enhanced quantumbehaved particle swarm algorithm for. Prospective algorithms for quantum evolutionary computation. Orpd is necessary for safe operation of power systems with regard to voltage stability.
Evaluation, hybridization and application of quantum inspired. This paper presents a multiobjective teaching learning algorithm based on decomposition for solving the optimal reactive power dispatch problem orpd. Evolutionary quantum and quantum inspired algorithms. 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. The quantum state population is firstly divided into multiple subpopulations, which complete the evolution processes independently.
Quantum inspired evolutionary algorithm for ordering problems. Leequantum inspired evolutionary algorithm for real and reactive power dispatch. The proposed quantuminspired evolutionary algorithm qea has applications in various combinatorial optimization problems in power systems and elsewhere. This paper focuses on the minimization of active power loss, respectively, and uses qpso and dqpso to determine terminal. In this paper, a survey on physicsbased algorithm is done to show how these inspirations led to the solution of wellknown optimizat. In power systems, the two main conditions for economical operation are active power regulation and reactive power dispatch rpd.
This algorithm used to minimize real power loss and voltage deviations are to be optimized simultaneously. Theoretically, there is a coupling relation between arpds. 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. Generally, the production reactive power cost is less, but it effects the production cost of the active power transmission loss. 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. Reactive power optimization by real power loss minimization increases the power system economics to some extent. Lee, quantuminspired evolutionary algorithm for real and reactive power dispatch, ieee transactions on power systems, 23 2008.
Special issue on quantum inspired swarm and evolutionary. Higherorder quantuminspired genetic algorithms annals of. 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. Natural phenomenon can be used to solve complex optimization problems with its excellent facts, functions, and phenomenon. The proposed quantuminspired evolutionary algorithm qea has continue reading. Realparameter quantum evolutionary algorithm for economic load dispatch. In 21 a quantum inspired evolutionary algorithm is 60 developed for real and reactive power optimization. Single and multiobjective optimal reactive power dispatch.
A quantuminspired evolutionary algorithm is a new evolutionary algorithm for a classical computer rather than for quantum mechanical hardware. Improved artificial bee colony algorithm considering harvest. Use of a multiobjective teachinglearning algorithm for. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. 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. Genetic algorithm based multiobjective bilevel programming. Rcqea uses the variable component of the solving complex functions and qubit to construct a. Adaptive quantuminspired evolutionary algorithm for. Proposed iqa can be viewed as a kind of hybridization. Quantuminspired evolutionary algorithm for real and. So this paper presents a real coded quantum evolutionary algorithm rcqea. In this paper, the nature inspired differential evolutionary based bat algorithm deba is introduced to solve. Joint economic and emission dispatch in energy markets.
Optimal reactive power dispatch orpd is an important optimization operation problem in power system field. Lee, quantum inspired evolutionary algorithm for real and reactive power dispatch, ieee transactions on power systems, 23 2008. Qea can be used for the p lacements, sizing and the. An adaptive adjustment strategy of the quantum rotation which is introduced in this study helps improving the convergence. Qea is characterized by principles of quantum computing including concepts of qubits and superposition of states.
Lee, life fellow, ieee abstractthis paper presents an evolutionary algorithm based on quantum computation for bidbased optimal real and reactive power pq. A novel evolutionary computing algorithm called the quantuminspired evolutionary algorithm qea was proposed and pursued. This study presents a comparative study for four evolutionary computation ec methods to the optimal activereactive power dispatch arpd problem. 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. Research article quantuminspired evolutionary algorithm for. Hybrid quantum genetic particle swarm optimization. Research and applications explores the latest quantum computational intelligence approaches, initiatives, and applications in computing, engineering, science, and business.
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. This technique present optimal reactive power dispatch problem is included. This paper presents an evolutionary algorithm based on quantum computation for bidbased optimal real and reactive power pq dispatch. Y quantuminspired evolutionary algorithm for real and reactive power dispatch. A novel constraint handling approach for the optimal. Qu antum inspired evolutionary algorithm for real and reactive power disp. In a more recent work, 12 proposes a novel multiuniverse parallel immune qea that uses a learning mechanism. 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. Ieee transactions on power systems 232008 16271636. In 21 a quantuminspired evolutionary algorithm is 60 developed for real and reactive power optimization. Qepsdms combines quantuminspired evolutionary algorithms qieas with a p system with a dynamic membrane structure. Finding solutions for optimal reactive power dispatch problem. The proposed algorithm introduces an adaptive adjustment strategy of the rotation angle and a cooperative learning strategy into quantum genetic algorithm called iqga. Kannancomprehensive learning particle swarm optimization for reactive power dispatch.
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. 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. 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. 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. An improved quantuminspired genetic algorithm for image. The proposed model has a more accurate evaluation of transmission losses obtained from the load flow equations. Pdf economic dispatch using quantum evolutionary algorithm. 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. This type of algorithm combines principle of quantum and evolutionary computation. The optimal reactive power dispatch orpd problem represents a noncontinuous, nonlinear, highly constrained optimization problem that has recently attracted wide research investigation. Natural computing algorithm represent a very important field in computational intelligence, soft computing and optimization in a general sense.
A quantuminspired evolutionary algorithm with elite group. 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. A novel firefly programming method for function optimization. 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. 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. Optimal reactive power dispatch under unbalanced conditions. Quantum inspired computational intelligence 1st edition.
Special issue on quantum inspired swarm and evolutionary computing algorithms for optimization problems 1. An improved quantuminspired evolutionary algorithm based on. A multilevel thresholding algorithm for histogrambased image segmentation is presented in this paper. Economic dispatch using quantum evolutionary algorithm in. The proposed method maintains the population diversity along with better convergence speed. Introduction of quantuminspired evolutionary algorithm. 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. A novel evolutionary computing algorithm called the quantum inspired evolutionary algorithm qea was proposed and pursued. 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. A novel constraint handling approach for the optimal reactive. Solution to optimal reactive power dispatch in transmission. Optimal reactive power flow is an important tool in terms of secure and operation of power.
Improve this page add a description, image, and links to the quantuminspiredgeneticalgorithm topic page so that developers can more easily learn about it. Evolutionary quantum and quantuminspired algorithms. The proposed quantum inspired evolutionary algorithm qea has applications in various combinatorial optimization problems in power systems and elsewhere. The effectiveness and performance of the proposed algorithm are compared with respect to a multiobjective evolutionary algorithm based on decomposition moead and the nsgaii. Qea uses a qbit representation instead of binary, numeric or symbolic representations. Prospective algorithms for quantum evolutionary computation donald a.
In this algorithm, the standard binary gravitational search algorithm is modified by applying the concept and principles of quantum behaviour as. Control of voltage profile with optimal control and placement. The book explores this emerging field of research that applies principles of quantum mechanics to develop more efficient and. A quantum inspired evolutionary algorithm is a new evolutionary algorithm for a classical computer rather than for quantum mechanical hardware. A novel quantuminspired binary gravitational search. Adaptive quantum inspired evolutionary algorithm for optimizing power losses 329 system. 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. A quantuminspired evolutionary algorithm with elite group guided. 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.