A mathematical model has been developed for an enzymatic process with kinetically controlled synthesis. Model reduction and detailed system analysis have been undertaken to examine the main properties of this enzyme r...
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A mathematical model has been developed for an enzymatic process with kinetically controlled synthesis. Model reduction and detailed system analysis have been undertaken to examine the main properties of this enzyme reaction system. Optimal experimental design (OED) is developed to obtain the experimental conditions that will generate the most informative measurement data for parameter estimation. Both single-input and multiple-inputs optimisation strategies have been investigated to determine the best intensity levels of control inputs. The results demonstrate that parameter estimation quality can be improved through proper model-based experimental design.
With the consideration of time sequence characteristics of load and distributed generation (DG), a novel method is presented for optimal sitting and sizing of DG in distribution system. multiple-objective functions ha...
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ISBN:
(纸本)9781479964161
With the consideration of time sequence characteristics of load and distributed generation (DG), a novel method is presented for optimal sitting and sizing of DG in distribution system. multiple-objective functions have been formed with the consideration of minimum investment and operational cost of DG, minimum voltage deviation and maximal voltage stability margin. To solve the multiple-objective optimization problem, an Improved Non-dominated Sorting Genetic Algorithm II (INSGA-II) has been proposed. Several experiments have been made on the modified PG&E 69-bus and actual 292-bus test systems. The result and comparisons indicate the proposed method for optimal placement and sizing of DG units is feasible and effective.
An improved particle swarm optimization (PSO) algorithm has been presented in optimal sizing of multiple DG units in this paper. Firstly, multiple-objective functions have been formed with the consideration of minimum...
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ISBN:
(纸本)9781629936017
An improved particle swarm optimization (PSO) algorithm has been presented in optimal sizing of multiple DG units in this paper. Firstly, multiple-objective functions have been formed with the consideration of minimum line loss, minimum voltage deviation and maximal voltage stability margin. Through fuzzy set theory, the multiple-objective optimization problem has been transformed to single objective comprehensive optimization with membership degree. The global particle swarm optimization algorithm dominates the search direction and works out the result; in the meanwhile, the inertia weight w, the cognitive and social parameters are updated in adaptive mode. And multi-initialization method is utilized to refresh the particle populations and increase its diversity. Several experiments have been made based on the IEEE 33-bus, actual 292-588 and 1180-bus test cases with the consideration of multiple DG units. The computational result and comparison indicate the proposed algorithm for optimal sizing of DG in distribution system is feasible and effective.
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