Thematische Bibliographien / MULTIOBJECTIVE ECONOMIC LOAD

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Auswahl der wissenschaftlichen Literatur zum Thema „MULTIOBJECTIVE ECONOMIC LOAD“

Autor: Grafiati

Veröffentlicht am 11. September 2023

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Zeitschriftenartikel zum Thema "MULTIOBJECTIVE ECONOMIC LOAD"

Yasin, Z. M., N. F. A. Aziz, N. A. Salim, N. A. Wahab und N. A. Rahmat. „Optimal Economic Load Dispatch using Multiobjective Cuckoo Search Algorithm“. Indonesian Journal of Electrical Engineering and Computer Science 12, Nr. 1 (01.10.2018): 168. http://dx.doi.org/10.11591/ijeecs.v12.i1.pp168-174.

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In this paper, Multiobjective Cuckoo Search Algorithm (MOCSA) is developed to solve Economic Load Dispatch (ELD) problem. The main goal of the ELD is to meet the load demand at minimum operating cost by determining the output of the committed generating unit while satisfying system equality and inequality constraints. The problem formulation is based on a multiobjective model in which the multiobjective are defined as fuel cost minimization and carbon emission minimization. MOCSA is based on the inspiration from the brooding parasitism of cuckoo species in nature. Three cases are considered to test the effectiveness of the proposed technique which are fuel cost minimization, carbon emission minimization and multiobjective function with fixed weighted sum. The effectiveness of the MOCSA’s performances are illustrated through comparative study with other techniques such as Multiobjective Genetic Algorithm (MOGA) and Multiobjective Particle Swarm Optimization (MOPSO) in terms of fitness functions. The proposed study was conducted on three generating unit system at various loading condition. The result proved that MOCSA provide better solution in minimizing fuel cost and carbon emission usage as compared to other techniques.

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., N. Ramyasri. „FUZZIFIED PSO FOR MULTIOBJECTIVE ECONOMIC LOAD DISPATCH PROBLEM“. International Journal of Research in Engineering and Technology 02, Nr. 08 (25.08.2013): 157–62. http://dx.doi.org/10.15623/ijret.2013.0208026.

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Zhang, Guoping, Weijun Wang, Jie Du und Haoyun Sheng. „Multiobjective Economic Optimal Dispatch for the Island Isolated Microgrid under Uncertainty Based on Interval Optimization“. Mathematical Problems in Engineering 2021 (11.10.2021): 1–14. http://dx.doi.org/10.1155/2021/9983104.

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In order to analyse the impact of renewable generation and load uncertainties on the economic operation optimization of the island microgrid, a multiobjective economic optimal dispatch model under uncertainty based on interval optimization is proposed in this paper. The mathematical model of distributed generation and the prediction model of wind speed and wave generation are established. The uncertainties of renewable generation and load are described by the interval mathematical method. On this basis, the interval multiobjective optimal dispatch model is presented. For the “battery disgusting” users on the island, the battery cost is regarded as a separate optimization objective, and a multiobjective optimization objective function to minimize the economic cost, battery cost, and pollution emission of the island microgrid is discussed. An island microgrid, composed of wind turbine, photovoltaic, wave energy generation, diesel generator, and energy storage system, is chosen as a case study. The NSGA-II algorithm is applied to solve the multiobjective optimal problem. The results for deterministic forecast data and load are analysed, and the optimal operation scheme is obtained by the improved multiobjective grey target decision-making method. The influence of renewable generation fluctuations ±10%, ±20%, and ±30% and the load fluctuations ±10% and ±20% on island microgrid operation optimization is discussed in detail, respectively. The relevant research results can provide a reference for formulating the operating scheme of the island microgrid.

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Singh, Nagendra, und Yogendra Kumar. „Multiobjective Economic Load Dispatch Problem Solved by New PSO“. Advances in Electrical Engineering 2015 (19.02.2015): 1–6. http://dx.doi.org/10.1155/2015/536040.

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Proposed in this paper is a new particle swarm optimization technique for the solution of economic load dispatch as well as environmental emission of the thermal power plant with power balance and generation limit constraints. Economic load dispatch is an online problem to minimize the total generating cost of the thermal power plant and satisfy the equality and inequality constraints. Thermal power plants use fossil fuels for the generation of power; fossil fuel emits many toxic gases which pollute the environment. This paper not only considers the economic load dispatch problem to reduce the total generation cost of the thermal power plant but also deals with environmental emission minimization. In this paper, fuel cost and the environmental emission functions are considered and formulated as a multiobjective economic load dispatch problem. For obtaining the solution of multiobjective economic load dispatch problem a new PSO called moderate random search PSO was used. MRPSO enhances the ability of particles to explore in the search spaces more effectively and increases their convergence rates. The proposed algorithm is tested for the IEEE 30 bus test systems. The results obtained by MRPSO algorithm show that it is effective and efficient.

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Hou, Hui, Mengya Xue, Yan Xu, Jinrui Tang, Guorong Zhu, Peng Liu und Tao Xu. „Multiobjective Joint Economic Dispatching of a Microgrid with Multiple Distributed Generation“. Energies 11, Nr. 12 (23.11.2018): 3264. http://dx.doi.org/10.3390/en11123264.

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Based on the operation characteristics of each dispatch unit, a multi-objective hierarchical Microgrid (MG) economic dispatch strategy with load level, source-load level, and source-grid-load level is proposed in this paper. The objective functions considered are to minimize each dispatching unit’s comprehensive operating cost (COC), reduce the power fluctuation between the MG and the main grid connect line, and decrease the remaining net load of the MG after dispatch by way of energy storage (ES) and clean energy. Firstly, the load level takes electric vehicles (EVs) as a means of controlling load to regulate the MG’s load fluctuation using its energy storage characteristics under time-of-use (TOU) price. Then, in order to minimize the remaining net load of the MG and the COC of the ES unit through Multiobjective Particle Swarm Optimization (MPSO), the source-load level adopts clean energy and ES units to absorb the optimized load from the load level. Finally, the remaining net load is absorbed by the main grid and diesel engines (DE), and the remaining clean energy is sold to the main grid to gain benefits at the source-grid-load level. Ultimately, the proposed strategy is simulated and analyzed with a specific example and compared with the EVs’ disorderly charging operation and MG isolated grid operation, which verifies the strategy’s scientificity and effectiveness.

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Farag, A., S. Al-Baiyat und T. C. Cheng. „Economic load dispatch multiobjective optimization procedures using linear programming techniques“. IEEE Transactions on Power Systems 10, Nr. 2 (Mai 1995): 731–38. http://dx.doi.org/10.1109/59.387910.

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Swain, Rajkishore, Pallab Sarkar, Krishna Chandra Meher und Chandan Kumar Chanda. „Population variant differential evolution-based multiobjective economic emission load dispatch“. International Transactions on Electrical Energy Systems 27, Nr. 10 (09.08.2017): e2378. http://dx.doi.org/10.1002/etep.2378.

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Jain, N. K., Uma Nangia und Iqbal Singh. „Multiobjective Economic Load Dispatch in 3-D Space by Genetic Algorithm“. Journal of The Institution of Engineers (India): Series B 98, Nr. 5 (05.08.2017): 495–501. http://dx.doi.org/10.1007/s40031-017-0280-x.

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Rajesh, Kummari, und N. Visali. „Hybrid method for achieving Pareto front on economic emission dispatch“. International Journal of Electrical and Computer Engineering (IJECE) 10, Nr. 4 (01.08.2020): 3358. http://dx.doi.org/10.11591/ijece.v10i4.pp3358-3366.

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In this paper hybrid method, Modified Nondominated Sorted Genetic Algorithm (MNSGA-II) and Modified Population Variant Differential Evolution(MPVDE) have been placed in effect in achieving the best optimal solution of Multiobjective economic emission load dispatch optimization problem. In this technique latter, one is used to enforce the assigned percent of the population and the remaining with the former one. To overcome the premature convergence in an optimization problem diversity preserving operator is employed, from the tradeoff curve the best optimal solution is predicted using fuzzy set theory. This methodology validated on IEEE 30 bus test system with six generators, IEEE 118 bus test system with fourteen generators and with a forty generators test system. The solutions are dissimilitude with the existing metaheuristic methods like Strength Pareto Evolutionary Algorithm-II, Multiobjective differential evolution, Multi-objective Particle Swarm optimization, Fuzzy clustering particle swarm optimization, Nondominated sorting genetic algorithm-II.

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Singh, Nagendra, Tulika Chakrabarti, Prasun Chakrabarti, Martin Margala, Amit Gupta, Sivaneasan Bala Krishnan und Bhuvan Unhelkar. „A New PSO Technique Used for the Optimization of Multiobjective Economic Emission Dispatch“. Electronics 12, Nr. 13 (05.07.2023): 2960. http://dx.doi.org/10.3390/electronics12132960.

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Most power is generated using fossil fuels like coal, natural gas, and diesel. The contribution of coal to power generation is very high compared to other sources. Almost all thermal power plants use coal as a fuel for power generation. Such sources of fossil fuels are limited and thus the cost of power generation increases. At the same time, the induced toxic gases due to these fossil fuels pollute the environment. The objective of this work is to solve the economic emission dispatch problem. Economic emission dispatch helps to find out how to operate power plants at the minimum cost and induce the minimum emissions at a thermal power plant. Economic emission dispatch with constraints is a nonlinear optimization problem. For the solution of such nonlinear economic emission load dispatch problems, this work considers a new particle swarm optimization technique. The proposed new PSO gives the best solution for economic emission load dispatch and handles the constraints. For the testing of the proposed new PSO algorithm, this work considered a case study of a system of six generating units, and it was tested for load demands of 700 MW, 800 MW, and 1000 MW. The results of the new PSO for the three load demands considered give the minimum generation cost, minimum emission, and minimum total cost compared to other optimization algorithms. The proposed techniques are effective, and they can help obtain the minimum generation cost and minimize emissions.

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Dissertationen zum Thema "MULTIOBJECTIVE ECONOMIC LOAD"

CHOUHAN, CHETAN. „MULTIOBJECTIVE ECONOMIC LOAD DISPATCH USING WEIGHTING METHOD“. Thesis, 2012. http://dspace.dtu.ac.in:8080/jspui/handle/repository/13939.

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M.TECH
In general, a large scale power system possesses multiple objectives to be achieved. The ideal power system operation is achieved when various objectives like cost of generation, system transmission loss, environmental pollution, security etc. are simultaneously attained with minimum values. Since these objectives are conflicting in nature, it is impossible to achieve the ideal power system operation. In this thesis work, three objectives of Multiobjective Economic Load Dispatch (MOELD) problem-cost of generation, system transmission loss and environmental pollution- are considered. The MOELD problem is formulated as a multiobjective optimization problem using weighting method and a number of noninferior solutions are generated in 3D space. The optimal power system operation is attained by Ideal Distance Minimization method. This method employs the concept of an ‘Ideal Point’ (IP) to scalarize the problems having multiple objectives and it minimizes the Euclidean distance between IP and the set of noninferior solutions. This method has been applied to IEEE 30 bus system.

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Konferenzberichte zum Thema "MULTIOBJECTIVE ECONOMIC LOAD"

Jain, N. K., Uma Nangia und Jyoti Jain. „GA based multiobjective economic load dispatch by Maximization Of Minimum Relative Attainments“. In 2012 IEEE 5th India International Conference on Power Electronics (IICPE). IEEE, 2012. http://dx.doi.org/10.1109/iicpe.2012.6450460.

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Rizk-Allah, Rizk M., und Ragab A. El-Sehiemy. „A novel sine cosine approach for single and multiobjective emission/economic load dispatch problem“. In 2018 International Conference on Innovative Trends in Computer Engineering (ITCE). IEEE, 2018. http://dx.doi.org/10.1109/itce.2018.8316637.

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