optimization of bacteria foraging algorithm (BFA) has been widely implemented in power engineering. This algorithm is emulated from escherichia coli bacteria's ability in finding nutrients in the human body. This ...
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ISBN:
(纸本)9781479935611
optimization of bacteria foraging algorithm (BFA) has been widely implemented in power engineering. This algorithm is emulated from escherichia coli bacteria's ability in finding nutrients in the human body. This research focuses on the implementation of BFA to calculate reliability indices of power system such as Loss of Load Probability (LOLP), Loss of Load Expectation (LOLE) and Expected Energy Not Supplied (EENS). The positions of each bacterium describe the status of the generation system and the resulting fitness value is its probability. The generation system states were visited included a failure state (state which causes load curtailment or loss of load), furthermore some generation systems are configured by block of units which are identically. It is opportunity in this research to improve BFA calculation methodology by considering probability of a system state with identical combinations. New approach of reliability calculation of composite system will be proposed. When the high probability failure states are obtained, the reliability indices can be calculated accurately. To simulate the methodology, case study of BFA and Genetic algorithms (GA) calculation of Muarakarang-Gandul 1 Composite System (islanding system which part of Jawa-Bali-Madura grid in Indonesia) will be applied.
In this paper, a bio inspired hybrid algorithm namely bacterial foraging differential evolution (BFDE) is proposed for design of robust power system stabilizer (PSS) over wide range of operating and system conditions....
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ISBN:
(纸本)9781509041688
In this paper, a bio inspired hybrid algorithm namely bacterial foraging differential evolution (BFDE) is proposed for design of robust power system stabilizer (PSS) over wide range of operating and system conditions. The benefits of two optimization techniques are integrated in this hybrid algorithm. A multi objective optimization problem with eigenvalue based objective functions is solved for optimal tuning of PSS. The convergence with proposed BFDE algorithm is evaluated for investigation of robustness and effectiveness over the wide range of system conditions. Eigenvalue analysis and time domain responses against different type of disturbances for single machine infinite bus (SMIB) system are demonstrated.
Return voltage method can assess water content in transformer pressboard by dominant time constant. However, the data of return voltage method (RVM) takes for a long measuring time. The parameters of dielectric respon...
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ISBN:
(纸本)9781467381079
Return voltage method can assess water content in transformer pressboard by dominant time constant. However, the data of return voltage method (RVM) takes for a long measuring time. The parameters of dielectric response based on extended Debye circuit model can reflect oil-paper insulation state. To shortcut measuring time, therefore, it is necessary to estimate equivalent circuit parameter and calculate return voltage characteristic quantity. This paper established improved mathematical model using return voltage peak, peak time and initial slope characteristics to solve dielectric response equivalent circuit parameters. And then improved bacteria foraging algorithm is used for solving the problem. The improved mathematical model can decrease sampling data of return voltage. The result shows that the dominant time constant calculated and measured return voltage curve have good consistency, which can accurately diagnose the transformer oil-paper insulation status. It illustrates that the improved method proposed in this paper is feasible and effective.
This paper deals with the design and analysis of a fractional-order robust lead-lag compensator based damping controller to enhance the dynamic stability of power system having disturbance uncertainty. First, the frac...
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ISBN:
(纸本)9781665432726
This paper deals with the design and analysis of a fractional-order robust lead-lag compensator based damping controller to enhance the dynamic stability of power system having disturbance uncertainty. First, the fractional order lead-lag controller is optimized as the Power System Stabilizer (PSS) by transforming the design problem to an optimization problem in which, the objective function is the Integral of the Time-Weighted Absolute Error (ITAE), and the constraints are the parameter limits. The parameter optimization is done by using a hybrid met heuristic algorithm. Furthermore, the stability of the closed loop fractional-order power system is discussed, and a sufficient condition for stability analysis is proved. The robustness and stability performance of the proposed controller have been ensured through extensive simulations and evaluating some performance indices on the test system under various disturbance scenario, operating points and system parameter variations.
This paper proposes a deep learning-based forecasting system for carbon emissions trading in regional markets. The system utilizes a hybrid convolutional neural network (CNN) deep learning algorithm to predict future ...
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This paper proposes a deep learning-based forecasting system for carbon emissions trading in regional markets. The system utilizes a hybrid convolutional neural network (CNN) deep learning algorithm to predict future carbon emission levels and facilitate the trading of carbon emission allowances. The system is compared to traditional methods of forecasting in order to assess the accuracy and performance of the system. In order to enhance the CNN performance, a new optimization algorithm based on bacteria foraging algorithm (BFA) is proposed which uses a modification to make a global search. By leveraging digital twins in the markets, a comparison is conducted using data from three regional carbon markets: the European Union Emissions Trading System, the Regional Greenhouse Gas Initiative, and the China Carbon Market. Results show that the proposed BFA-CNN based deep learning-based system outperforms traditional forecasting methods in terms of accuracy and provides more reliable estimates of future carbon emissions. The proposed system is a novel approach to carbon emissions trading and has the potential to improve the efficiency of regional carbon markets.
Nowadays, flexible AC transmission system (FACTS) devices are increasingly used in power systems. They have remarkable effects on increasing the damping of the system. In this paper, a bacterial-foraging oriented by p...
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Nowadays, flexible AC transmission system (FACTS) devices are increasingly used in power systems. They have remarkable effects on increasing the damping of the system. In this paper, a bacterial-foraging oriented by particle swarm optimization (BF- PSO) algorithm is employed to design the coordinated parameters of power system stabilizer (PSS) and static VAR compensator (SVC). With regard to nonlinearities of power system, linear methods can’t be used to design coordinated parameters of controllers. In this paper, nonlinear model of power system and SVC is used to design parameters of PSS and SVC. For this purpose, this design problem is firstly converted to an optimization problem and then the BF-PSO algorithm is used to solve it. Simulations are carried out on four machine 11 bus power system in MATLAB software. The results confirm the efficiency of the proposed method for stabilizing the power system oscillations. Comparing BF-PSO algorithm with other intelligent methods, (PSO, BFA) verifies better performance of the BF-PSO method.
In this paper, a bio inspired hybrid algorithm namely bacterial foraging differential evolution (BFDE) is proposed for design of robust power system stabilizer (PSS) over wide range of operating and system conditions....
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ISBN:
(纸本)9781509041695
In this paper, a bio inspired hybrid algorithm namely bacterial foraging differential evolution (BFDE) is proposed for design of robust power system stabilizer (PSS) over wide range of operating and system conditions. The benefits of two optimization techniques are integrated in this hybrid algorithm. A multi objective optimization problem with eigenvalue based objective functions is solved for optimal tuning of PSS. The convergence with proposed BFDE algorithm is evaluated for investigation of robustness and effectiveness over the wide range of system conditions. Eigenvalue analysis and time domain responses against different type of disturbances for single machine infinite bus (SMIB) system are demonstrated.
Return voltage method can assess water content in transformer pressboard by dominant time constant. However, the data of return voltage method (RVM) takes for a long measuring time. The parameters of dielectric respon...
详细信息
ISBN:
(纸本)9781467381086
Return voltage method can assess water content in transformer pressboard by dominant time constant. However, the data of return voltage method (RVM) takes for a long measuring time. The parameters of dielectric response based on extended Debye circuit model can reflect oil-paper insulation state. To shortcut measuring time, therefore, it is necessary to estimate equivalent circuit parameter and calculate return voltage characteristic quantity. This paper established improved mathematical model using return voltage peak, peak time and initial slope characteristics to solve dielectric response equivalent circuit parameters. And then improved bacteria foraging algorithm is used for solving the problem. The improved mathematical model can decrease sampling data of return voltage. The result shows that the dominant time constant calculated and measured return voltage curve have good consistency, which can accurately diagnose the transformer oil-paper insulation status. It illustrates that the improved method proposed in this paper is feasible and effective.
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