Biblioteca Universității Politehnica Timișoara
https://dspace.upt.ro/xmlui/handle/123456789/1
2024-10-10T14:23:46ZReactive power cost optimization using improved particle swarm optimization [articol]
https://dspace.upt.ro/xmlui/handle/123456789/6748
Reactive power cost optimization using improved particle swarm optimization [articol]
Manzeera, M.; Srikanth, K.
Reactive power optimization (RPO) has an important role to play in the operation of power system. In this paper, the objective is to minimize the real power losses of the network along with the minimization of the investment cost associated with the reactive power sources. Lately, particle swarm optimization (PSO) is gaining more attention due to its convergence properties and ability to attain global optimal solution. In this paper, to solve the RPO problem an improved particle swarm optimization (IPSO) is used. The proposed approach is tested for RPO problem on standard IEEE 14-bus system and IEEE 30-bus system, proves that the improved PSO algorithm used in this paper for0 reactive power optimization gives better results. The proposed algorithm is simple, have higher convergence and thus suitable for solving reactive power optimization problems in the power system network.
2019-01-01T00:00:00ZAn adaptive intelligent sliding mode control method for BLDC motor using optimized fuzzy PID controller [articol]
https://dspace.upt.ro/xmlui/handle/123456789/6747
An adaptive intelligent sliding mode control method for BLDC motor using optimized fuzzy PID controller [articol]
Maya, R.; Sahaya Shanthi, L. Jessi
Brushless DC motor is one type of permanent synchronous motor, which is applied in various industrial and commercial applications. This is because it has number of advantages like high power density, large torque, lifetime, good speed regulation and reliability. However, the controls of effective speed control and current control of brushless DC motor are still difficult. Further, the uncertainty and non-linear characteristics of the motor system degrades the efficiency of controllers. To address and end this difficulty, a novel control scheme is proposed by using optimized tuned parameters with Fuzzy PID controller for the speed control of BLDC motor. Several nature-inspired optimization algorithms like particle swarm and cuckoo search algorithms are developed for controller design. The proposed Fuzzy PID controller design is carried patterned using cuckoo search algorithm for tuning the optimized parameters. The speed of the motor can be tuned depending upon the sliding mode surface parameters. Similarly, Adaptive Intelligent Sliding Mode Controller is designed by using cuckoo search algorithm which employs an inner loop for current control and outer loop as speed control. Here, two cascaded sliding mode controllers taking into account which improves dynamic control of BLDC motor. It is guaranteed that the developed AISMC strategy deals with uncertainty and non-linear characteristics of unknown external disturbance. The precise experimentation was implemented in MATLAB simulation environment, and system performance is analyzed regarding stator current, torque, back EMF, the line to line voltage and settling time of the motor.
2019-01-01T00:00:00ZOptimal allocation of energy storage system (ESS) and UPQC by PSO for grid connected wind model [articol]
https://dspace.upt.ro/xmlui/handle/123456789/6746
Optimal allocation of energy storage system (ESS) and UPQC by PSO for grid connected wind model [articol]
Prabha, S. Sooriya; Babulal, C.K.
In the ambiance of renewable energy integrated grid of electricity generation, the endeavor of energy storage strategy (ESS) has been an inevitable technique to abduct the energy by means of renewable sources and endow during the obligation of huge electrical energy. Inoculation of the wind power into an electric grid affects the power quality. The arbitrary arrangement of ESS in the grid integration has prompt pessimistic characteristic. Vanquishing this bothersome impact of ESS in this errand, one of the meta-heuristic portrayal particle swarm optimization (PSO) has been resolved since requires less computational stretch and depicts in MATPOWER. The proposed model outfits the ideal area of ESS in the system of electricity generation and idealistic aspect of ESS. In this paper introduces a complete audit on the unified power quality conditioner (UPQC) to improve the electric power quality at appropriation levels and also the execution of PSO over the test system relates with pertinence of optimal power flow (OPF) model with assorted investigations, to prognosis the envisage of PSO to forfeiture the unfortunate costs and real power shortfalls imports to transmission for conservative generation of electric power. In this proposed plot UPQC is associated at a state of regular coupling with a battery energy storage system (BESS) to alleviate the power quality issues. The battery energy storage is coordinated to maintain the real power source under fluctuating wind power. The UPQC control conspire for the grid associated wind energy generation system for power quality renovation is simulated using MATLAB/SIMULINK in power system block set.
2019-01-01T00:00:00ZOptimal location and sizing of renewable energy based distributed generation units in a radial distribution power network using ant lion optimization algorithm [articol]
https://dspace.upt.ro/xmlui/handle/123456789/6745
Optimal location and sizing of renewable energy based distributed generation units in a radial distribution power network using ant lion optimization algorithm [articol]
Rajakumar, P.; Kumar, M. Senthil; Shivakumar, R.
The capability of Photovoltaic (PV) system and Wind turbine (WT) in providing electrical power with clean and environment-friendly makes it ideal for distributed generation (DG) resource in distribution networks to meet power demand with lesser environmental effects. The distribution networks power losses are largely influenced by the location and size of the DG unit. This paper introduces an ant lion optimization algorithm (ALOA) for identifying suitable location and capacity of renewable energy based DG units for different distribution network systems. Loss sensitivity factor (LSF) is used to determine candidate buses for DG placement and voltage sensitivity factor (VSF) is used to select a suitable bus location from candidate buses for DG unit installation. The proposed ALOA is developed to deduce the optimal size of different types of DG units at the selected bus locations. The performance of ALOA is validated for IEEE 33 bus and 69 bus radial distribution systems. To highlight the superiority of the proposed algorithm, the results are compared with other algorithms in terms of power loss reduction and voltage profile. The proposed algorithm has given improved performance over other algorithms in terms of power loss reduction and voltage profile enhancement. Also, the response of ALOA under varying loading condition is presented to outline its effectiveness towards voltage profile enhancement and power loss minimization at different load levels.
2019-01-01T00:00:00Z