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This paper presents an Elman neural network based on Genetic algorithms for the identification of dynamic equivalents of power system. The Elman neural network is one of the dynamic recurrent neural networks. In this paper, a modified Elman network is introduced first. Then we propose its training algorithm using Genetic algorithms. Lastly, the proposed method is demonstrated and compared with the...
Under the control object and the structure of control system built, we set the range of parameters and the objective function and get the best parameters of PID control of the system by genetic algorithm, making use of MATLAB we can do the modeling and simulation of the PID control and fuzzy control. The results of simulation show that the dynamic response of fuzzy control is faster than PID control...
This paper proposes a hybrid evolutionary algorithm to solve the maintenance-scheduling problem for thermal generating units. The proposed approach uses a hybrid Fuzzy-Genetic Algorithm that implements Fuzzy Knowledge Based System to emulate the power plant personnel's experience, and uncertainties in the constraints, while a Genetic Algorithm optimizes the total generating cost and the maintenance...
Improved Genetic Algorithm is used for parameter optimization of turbine DEH governing system. The algorithm can avoid the premature convergence effectively and improve the global and local search ability. The optimization results show that such method has the advantages of fast computation, high precision, and better program generality. It provides a new way for parameter optimization of steam turbine...
The generation control is becoming increasingly important in view of increased load demand & reducing generating resources. The increasing load demands are posing serious threats to reliable operation of power systems. This is because the increasing load demand leads to lowering of turbine speed (Ns) & therefore reduction of frequency (f) of out put voltage of the generator. The healthy operation...
Reactive power optimization in power system is a typical non-linear optimization problem with characteristics of multi-objective, multi-constrained, non-linear combination and discreteness. Conventional mathematical programming techniques are inadequate and insufficient to the optimal operation of power systems due to the inherent complexity. A solution to reactive power optimization of power system...
The main benefits of implementing interruptible load management for power suppliers are from the impacts of the level of demand for electricity on spot prices. In terms of CVaR as the measuring index for market trading risk, a model of load curtailing strategies for power suppliers considering the co-utilization of the interruptible load with low price (ILL) and the interruptible load with high compensation...
Using traditional least squares criterion suitable for big sample data to identify the parameters, the small data quantity, the noise disturbance and the unusual data will bring about some adverse effects. In order to overcome these adverse effects, minimum sum of absolute residual criterion suitable for small sample data is applied to identify model parameters in this article. Genetic algorithm is...
Optimal placement and sizing of Distributed Generation (DG) and capacitor for the loss reduction in distribution networks is of utmost importance. Therefore, in this paper by means of using new method of generalized pattern search and genetic algorithm are elaborated and compared with another. Another fact is the direct link between PSAT with the two previous methods. For the generation of this relationship...
Automotive steering system is used to change the direction and keep vehicles traveling straight. Electric power steering system (EPS) can improve vehicle handling performance and economy, has become one of hot spots on research and development in modern automobile steering system. Worm gears are important components of the electric power steering system; its transmission efficiency shall affect directly...
The Bacterial Foraging (BF) optimization algorithm imitates the foraging behavior of Escherichia coli (E. coli) bacteria that exist in human intestine, whose foraging habit is modeled as a distributed optimization process. This paper applies the BF algorithm to design optimal controllers of a single-machine-infinite-bus (SMIB) system equipped with an interline power flow controller (IPFC). The system...
In this paper it is desired to find TCSC (Thyristor-Controlled Series Compensator) economical installation procedure in order to decrease power system losses. Not only the power losses will be reduced, but also TCSC switching loss is considered and modeled to constitute the whole cost function. The degree of compensation and location of TCSC with and without switching loss will be compared in order...
Recently, operational cost for diesel generator such as fossil cost, transport cost, and storage cost are expensive in isolated island. Consequently, renewable energy generation is advanced in the world. Furthermore, all-electric house and electric vehicle carrying a storage battery is increasing. Controllable load in the grid can be installed using all-electric house and electric vehicle carrying...
This paper presents an application of Bees Algorithm (BA) for solving various types of Economic Dispatch (ED) problem. Complete ED problem formulation prohibited, operating zones, ramp-rate limits, and non-smooth or non-convex cost functions arising from the use of multiple fuels should be taken into consideration. To show its efficiency, the Bee algorithm is applied to solve various types ED problems...
This paper presents genetic algorithm method for unit commitment of thermal power plant. The optimum allocation of generations (for a given plant load) to different units of a plant is called unit commitment (UC). It can be easily shown that the optimal operation of the units at a thermal power station can be achieved when the incremental fuel cost (incremental cost) of all the units are equal. A...
In this paper, an improved adaptive genetic algorithm is applied to the proposed power purchase and distribution planning model. The new genetic algorithm adopts new method to get crossover probability. In the late evolutionary stage, there is only mutation operation, crossover probability is zero. Example analysis shows that the new algorithm has good performance in searching the better distribution...
Economic Load Dispatch (ELD) is one of an important optimization tasks which provides an economic condition for a power systems. In this paper, Particle Swarm Optimization (PSO) as an effective and reliable evolutionary based approach has been proposed to solve the constraint economic load dispatch problem. The proposed method is able to determine, the output power generation for all of the power...
For the vertically integrated monopolistic environment in the past, economic dispatch and Unit Commitment (UC) were defined as finding and scheduling generating units in order to minimize the total production cost of utility and constraints such as power demand and spinning reserve are met. These problems under deregulated environment, on the other hand, are more complex and more competitive than...
This paper presents Craziness Based Particle Swarm Optimization (CRPSO) technique for solving constrained optimal power flow problems in power systems, considering nonlinearities like valve point loading and prohibited operating zones of generators. In this paper, the proposed algorithm has been tested in 26-bus system under various simulated conditions and its solutions are compared to those of simple...
Design of an optimal controller requires optimization of multiple performance measures that are often noncommensurable and competing with each other. Design of such a controller is indeed a multi-objective optimization problem. Being a population based approach; genetic algorithm (GA) is well suited to solve multi-objective optimization problems. This paper investigates the application of GA-based...
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