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Full model of immigration rate and emigration rate
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This paper presents a biogeography-based optimization (BBO) algorithm to solve the economic load Dispatch (ELD) problem with generator constraints in thermal plants. Applied method can solve the ELD problem with constraints like transmission losses, ramp rate limits, and prohibited operating zones. Biogeography is the science of the geographical di...
Contexts in source publication
Context 1
... immigration of creatures from high HSI habitats to low HSI habitats can enhance the HSI of this habitat because the HSI of habitat is directly proportional to creatures' variety. Fig.1 gives a full model of immigration rate and emigration rate [10]. ...
Context 2
... this condition immigration rate is zero because no creatures can enter to this habitat. With considering emigration diagram of figure 1, we can understand that when there are no creatures in the habitat, there is no living thing to immigrate to another habitat and the emigration rate is zero. When the number of creatures increases and habitat becomes populated, large number of creatures can leave their own habitats and seek a new habitat for live and consequently emigration rate increases. ...
Context 3
... to immigrate to another habitat and the emigration rate is zero. When the number of creatures increases and habitat becomes populated, large number of creatures can leave their own habitats and seek a new habitat for live and consequently emigration rate increases. The maximum emigration rate Occurs when the number of creatures is S max . In the Fig. 1 the immigration and emigration lines are in form of straight lines but these lines might be more complicated lines. Calculation of immigration an emigration values in BBO algorithm is so important. Immigration and emigration rate have a important role in selecting those SIV's that migration process should be apply on them. With regard ...
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Citations
... Convex (Smooth) ELD problems neglect transmission losses & other constraints while non-convex or non-smooth ELD problems deviates from idealities & takes them into consideration. Thus complexity or dimensionality of a non-convex ELD problem increases & so does the computation time [25][26][27][28][29][30][31]. ...
Economic load dispatch is the economic loading of different generating units for variable load conditions of any power system. Emission contributions of conventional thermal power plants plays major role in the overall air pollution. The total emissions need to satisfy the allowable limits of the emission. This paper proposes the load scheduling for combined economic emission and load dispatch (CEELD) problems. In this paper, Biogeography Based Optimization (BBO) technique is employed to estimate the fuel cost and emission of all the generating units. The aim of this paper is to minimize the fuel cost and emission of all the units for a given load. Result obtained by BBO are compared with the results obtained by different other optimization techniques such as genetic algorithm (GA), particle swarm optimization (PSO), evolutionary programming (EP) and differential evolution (DE) with respect to total fuel cost, solution time and convergence criteria. The proposed BBO technique has been applied to obtain the CEELD solution for IEEE 30 bus - 6 generator power system. The BBO algorithm is carried out in MATLAB environment. The solutions obtained by BBO technique are quite encouraging.
... This transferring called emigration and the process called immigration. Therefore, high HSI has a high emigration rate while low HSI has high immigration rate [43]. The BBO algorithm is based on migration and mutation. ...
... The modification of each solution is based on the emigration and immigration rates. The elitism process is governed in the BBO algorithm, and just a number of best solutions are transferred to the next iteration [43]. As each solution has its own probability, the one with low probability has the chance to mutate while the solution with high probability has little chance to mutate. ...
... As each solution has its own probability, the one with low probability has the chance to mutate while the solution with high probability has little chance to mutate. Detailed description of the BBO presented elsewhere [42][43][44], and the flowchart of BBO is shown in Figure 3. ...
Hydrological drought forecasting plays a substantial role in water resources management. Hydrological drought highly affects the water allocation and hydropower generation. In this research, short term hydrological drought forecasted based on the hybridized of novel nature-inspired optimization algorithms and Artificial Neural Networks (ANN). For this purpose, the Standardized Hydrological Drought Index (SHDI) and the Standardized Precipitation Index (SPI) were calculated in one, three, and six aggregated months. Then, three states where proposed for SHDI forecasting, and 36 input-output combinations were extracted based on the cross-correlation analysis. In the next step, newly proposed optimization algorithms, including Grasshopper Optimization Algorithm (GOA), Salp Swarm algorithm (SSA), Biogeography-based optimization (BBO), and Particle Swarm Optimization (PSO) hybridized with the ANN were utilized for SHDI forecasting and the results compared to the conventional ANN. Results indicated that the hybridized model outperformed compared to the conventional ANN. PSO performed better than the other optimization algorithms. The best models forecasted SHDI1 with R2=0.68 and RMSE= 0.58, SHDI3 with R2=0.81 and RMSE= 0.45 and SHDI6 with R2=0.82 and RMSE= 0.40.
... Where m(s) is the mutation rate, ݉ ௫ is the maximum mutation rate, Ps is the probability that S species in a habitat, and ܲ ௫ is the maximum probability that S species in a habitat. When a solution is selected for mutation then we replace a randomly chosen SIV in the habitat with a new randomly generated SIV [16]. ...
This paper proposes a new hybrid metaheuristique algorithm based on the hybridization of Biogeography-based optimization with the Differential Evolution for solving the optimal power flow problem with emission control. The biogeography-based optimization (BBO) algorithm is strongly influenced by equilibrium theory of island biogeography, mainly through two steps: Migration and Mutation. Differential Evolution (DE) is one of the best Evolutionary Algorithms for global optimization. The hybridization of these two methods is used to overcome traps of local optimal solutions and problems of time consumption. The objective of this paper is to minimize the total fuel cost of generation, total emission, total real power loss and also maintain an acceptable system performance in terms of limits on generator real power, bus voltages and power flow of transmission lines. In the present work, BBO/DE has been applied to solve the optimal power flow problems on IEEE 30-bus test system and the Algerian electrical network 114 bus. The results obtained from this method show better performances compared with DE, BBO and other well known metaheuristique and evolutionary optimization methods.
... The economic load dispatch of generation is the main problems of optimization for both the generating plants and the systems operator. The major part of the variable cost of generation of electricity is the fuel cost, and directly reflected in the electricity bills [1]. ...
... In Eq. (2) P i , P D , and P L are generation of each generator, total power demand and power loss in transmission which can be expressed in term of B-coefficient matrix [8]. Formula (1) shows the all of generators in addition to provide power demand of consumers are responsible for providing transmission loss of lines [1]. ...
... In Eq. (2) P i , P D , and P L are generation of each generator, total power demand and power loss in transmission which can be expressed in term of B-coefficient matrix [8]. Formula (1) shows the all of generators in addition to provide power demand of consumers are responsible for providing transmission loss of lines [1]. ...
... The best results of GWO together with other published methods [6][7][8][9][10][11][12] are shown in Tables 1 and 2 respectively. The results obtained satisfying the system constraints, such as ramp rate limits and prohibited operating zones of units. ...
This paper presents the application of a new meta-heuristic called Grey Wolf Optimizer (GWO) which inspired by grey wolves (Canis lupus) for solving economic dispatch (ED) problems. The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy. In addition, the three main steps of hunting: searching for prey, encircling prey and attacking prey are implemented. In this paper, GWO was demonstrated and tested on two well-known test systems with practical constraints. A comparison of simulation results is carried out with those published in the recent literatures. The results show that the GWO algorithm is able to provide very competitive results for nonlinear characteristics of the generators such as ramp rate limits, prohibited zone and non-smooth cost functions compared to the other well-known meta-heuristics techniques.
... The economic load dispatch of generation is the most important concerned problems of optimization for both the generating plants and the systems operator. The major part of generating cost of electricity is the fuel cost, and directly reflected in the electricity bills [1]. ...
... In Eq. (2) P i , P D , and P L are generation of each generator, total power demand and power loss in transmission line respectively. Eq. (1) shows all the generators in addition to provide power demand of consumers are responsible for providing transmission loss of lines [1]. ...
... Transferring the species from one habitat to another is known as emigration. And the process of entering the species to a habitat from another habitat is known as immigration [1]. Every solution is modified according to modified probability , which is known as the Emigration Immigration E=I ...
This paper presents a Biogeography Based Optimization (BBO) technique to solve the Economic Load Dispatch problem even as considered the generator and transmission constraints and satisfying it. Biogeography basically is the study of the geographical distribution of the biological organism. Biogeography based optimization is a comparatively new approach. Mathematical models of biogeography explain how an organism arises and how to migrate from one habitat to another habitat, or get died out. In BBO algorithm, solutions are sharing the good features between solutions that are immigration and emigration process. This algorithm looks for the overall optimum solution mostly through two steps — Migration and Mutation. Results are obtained on the different-different population size and different-different number of trials. The Results of the proposed method have been compared with results of IEEE 30-bus, 6 generator system and got the better quality of the obtained solution. This method is one of the important approaches for solving the Economic Load Dispatch problems under practical conditions.
