A dynamic multi-objective optimal dispatch model is established with considering both the economic and environmental costs in this paper, of which the dynamic constraints are power balance, load interruption rate, cha...
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ISBN:
(纸本)9781538622124
A dynamic multi-objective optimal dispatch model is established with considering both the economic and environmental costs in this paper, of which the dynamic constraints are power balance, load interruption rate, charge and discharge of energy storage and power output restriction of the internal micro-sources. Then, A multi-objective improved biogeography-basedoptimization (MOIBBO) algorithm is used to solve the proposed model, where the individual fitness is based on ''distance evaluation", and the ''congestion mechanism" is used to deal with the capacity overflow of the Pareto optimal solution in order to maintain the diversity and uniformity of Pareto optimal frontier (POF) distribution. Moreover, a technique of the initial point guidance is implemented in the algorithm to widen the POF, and the optimal compromise solution is determined by applying the fuzzy theory. Example simulation results verify the model rationality and present that the mentioned MOIBBO algorithm can obtain a POF with good distribution characteristics.
A biogeography-basedoptimization (BBO) algorithm was used for tuning the parameters of a proportional integral derivative (PID) controller-based power system stabilizer (PSS). The proposed method minimizes the low fr...
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A biogeography-basedoptimization (BBO) algorithm was used for tuning the parameters of a proportional integral derivative (PID) controller-based power system stabilizer (PSS). The proposed method minimizes the low frequency electromechanical oscillations (0.1-2.5 Hz) and enhances the stability of the power system by optimally tuning the PID parameters. This was achieved by minimizing the objective function of the integral square error for various disturbances. The performance of the BBO algorithm was tested on a single machine infinite bus system for a different range of operating conditions and the results were compared with particle swam optimization, adaptation law, and conventional PSS. The result analysis concluded that the BBO algorithm damps out the low frequency oscillations in the rotor of the synchronous machine effectively when compared to other methods. The algorithms were simulated with MATLAB/Simulink. The results from the simulation showed that the proposed controller yields a fast convergence rate and better dynamic performance.
biogeography-basedoptimization (BBO) algorithm is an better global optimizationalgorithm. Compared with traditional algorithms, BBO algorithm has advantages of less parameters, simple calculation, fast convergence. ...
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ISBN:
(纸本)9781479986460
biogeography-basedoptimization (BBO) algorithm is an better global optimizationalgorithm. Compared with traditional algorithms, BBO algorithm has advantages of less parameters, simple calculation, fast convergence. The supercritical (ultra-supercritical) unit flue-reheat steam temperature object has characteristics such as large inertia and hysteresis. Traditional PID controller parameter setting method is difficult to obtain good control effect. Aiming at this problem, the article put up a hybrid optimization method based on BBO algorithm. The method has a significant comprehensive optimization result in the test of value disturbance, internal disturbances and external disturbance. The optimized PID controller also has better tracking ability and a better performance to fight inside and outside interference. The simulation results show that it's feasible and effective to control the temperature by using the optimized PID controller on flue reheat steam control system.
The optimization of condenser vacuum is significant to improve efficiency and save energy in the power plant. Taking a 600MW unit as the research object, the condenser vacuum optimization model was established synthet...
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ISBN:
(纸本)9783037859728
The optimization of condenser vacuum is significant to improve efficiency and save energy in the power plant. Taking a 600MW unit as the research object, the condenser vacuum optimization model was established synthetically based on neural network, simulated annealing and biogeographyoptimization hybrid algorithm (SA-BBO). Circulating pumps power, slight increase of turbine power as well as the market value difference between coal and electric were included in the model. The objective function of the model is to maximize the profit of the power plant. The most effective combinations of the condenser vacuum and the circulating water pump were calculated eventually in different operating conditions by using characteristic analysis of variable condenser conditions. In a certain condition, running three circulating pumps for two steam turbines instead of two pumps can make the condenser vacuum reduce 0.49kPa, and increase revenue 110.2 yuan/h.
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