Muhammad Abdillah

Type 2 fuzzy adaptive binary particle swarm optimization for optimal placement and sizing of distributed generation

This paper proposes a new method for optimizing the placement and size of distributed generation (DG) using type-2 fuzzy adaptive binary particle swarm optimization with single mutation operator, called T2FABPSOM. The objective function of the proposed method to minimize active power losses in transmission line with the bus voltage system constraints is allowed. Type-2 fuzzy logic system (type-2 FLS) is used for tuning the inertia weight w, the learning factors c1 and c2 parameters of particle swarm optimization to control the particle velocity. Single mutation also used in the proposed method as a combination to improve and strengthen the ability of particle to search for candidate solutions globally and avoid convergence to local optima. To evaluate the performance of the proposed method, the method is applied on IEEE 30 bus system. The proposed method compared with the binary PSO (BPSO) and fuzzy adaptive binary PSO (FABPSO). The simulation results indicated that the proposed method can determine the size and location of the optimal DG with a total active power losses are minimum compared to other methods.

Optimal placement and sizing of Distributed Generation using Quantum Genetic Algorithm for reducing losses and improving voltage profile

In this paper Quantum Genetic Algorithm (QGA) is combined with The Newton Raphson power flow (NR power flow) to optimize the placement and sizing of Distributed Generations (DGs) in electrical power systems. QGA is used to find the optimal placement and generate real power of DG in accordance with mathematical calculations and NR Power Flow is used to calculate the loss on the network and determine the voltage at bus. The goal is to minimize the losses, while at the same time still maintain the acceptable voltage profiles. DGs may be placed at any load bus. Which load buses to have the DGs and of what size they are respectively are determined using this proposed method. Observations are based on standard IEEE 14 buses input and results are compared to the results of network without DG and network with DG by other methods.

A novel design of WACS based multi-output support vector machine (M-SVM) for oscillation damping on power system

This paper proposes a novel design of wide area control system (WACS). WACS is utilized to damp the oscillation on power system. WACS consists of wide area monitor (WAM) and wide area control (WAC). WAM is used to monitor the dynamic behavior of power system, while WAC is used as the additional controller on power system. The proposed method is called WACS based multi-output support vector machine (M-SVM). M-SVM used in this paper is M-SVM for regression. The input signal which used by WAM is the input signal to the AVR ΔVwi, the mechanical power ΔPmi and the electrical power ΔPei of each generator. The output of WAM is utilized to predict the speed deviation of the generator. WAC is using the input signal of mechanical power ΔPmi and electrical power ΔPei from generator, while the output of WAC is the signal control which injected to the AVR ΔVwi. A two-area-four-generator is utilized as a tested system to evaluate the performance of the proposed method. From the simulation results that has been conducted, the proposed method can reduce the overshoot and compress the settling time better than other methods that presented in this paper.

Optimal Design of TCPST Using Gravitational Search Algorithm

This paper presents the GSA method is used to determine the optimal locations and ratings of TCPST. TCPST is the equipment used to regulate and improve the power flow on the power system. TCPST is implemented on the Java-Bali 500kV power system. The objective function of this study is to minimize the active power losses on transmission line of Java-Bali 500kV power system. The active power losses on transmission line of the Java-Bali 500kV power system before optimization using Newton Raphson method is 297.607MW. While the active power losses results after optimization using the GSA method with 4-TCPST is 234.885MW.

Voltage Control on 500kV Java-Bali Electrical Power System for Power Losses Minimization Using Gravitational Search Algorithm

This paper presents a gravitational search algorithm (GSA) method for voltage control, which reduces transmission losses by adjusting the reactive power variables, such as generator voltages and other sources of reactive power, such as capacitor banks, and provides better system voltage profile. The objective function of the proposed method is to minimize active power losses in transmission line. GSA method uses new meta-heuristics optimizations which are motivated by Newtons law of gravity and motion. This method is implemented in 500 kV Java-Bali electrical power system. The load flow results showed that after the optimization using GSA method, the active power losses was 244.390 MW, while other optimization methods gave 267.559 MW (GA method) and 245.003 MW (PSO method). Comparing the losses obtained by the three optimization methods, GSA method is better for minimizing the active power losses in transmission line.

Neural network based transient stability model to analyze the security of Java-Bali 500 kV power system

A transient stability model based on back propagation neural network is used to analyse transient stability of Java-Bali electricity system, especially in calculating the critical clearing time. Inputs used for the neural network is the real and the active variable load power, whereas the target of the neural network is the critical clearing time (CCT). Data of target CCT used for the training was calculated using the concept of One Machine Infinite Bus (OMIB), which is the reduction of multi-machine system in combination with the method of equal area criterion (EAC) through the Trapezoid method and the 4th Order Runge-Kutta method. The position and type of disturbance is assumed not changed. This model was tested on 500 kv Java-Bali system with type of disturbance is 3 phase ground fault. The results indicate that the approximate value of the CCT calculated by the proposed method has a minimum error of 0% and maximum error of 0.0008% compared with CCT by OMIB.