Issarachai Ngamroo

Robust LFC in a Smart Grid With Wind Power Penetration by Coordinated V2G Control and Frequency Controller

In the smart grid, the large scale wind power penetration tends to expand vastly. Nevertheless, due to the intermittent power generation from wind, this may cause a problem of large frequency fluctuation when the load-frequency control (LFC) capacity is not enough to compensate the unbalance of generation and load demand. Also, in the future transport sector, the plug-in hybrid electric vehicle (PHEV) is widely expected for driving in the customer side. Generally, the power of PHEV is charged by plugging into the home outlets as the dispersed battery energy storages. Therefore, the vehicle-to-grid (V2G) power control can be applied to compensate for the inadequate LFC capacity. This paper focuses on the new coordinated V2G control and conventional frequency controller for robust LFC in the smart grid with large wind farms. The battery state-of-charge (SOC) is controlled by the optimized SOC deviation control. The structure of frequency controller is a proportional integral (PI) with a single input. To enhance the robust performance and robust stability against the system uncertainties, the PI controller parameters and the SOC deviation are optimized simultaneously by the particle swarm optimization based on the fixed structure mixed H2/H∞ control. Simulation results show the superior robustness and control effect of the proposed coordinated controllers over the compared controllers.

Parallel micro genetic algorithm for constrained economic dispatch

This paper proposes a parallel micro genetic algorithm (PMGA) for solving ramp rate constrained economic dispatch (ED) problems for generating units with nonmonotonically and monotonically increasing incremental cost (IC) functions. The developed PMGA algorithm is implemented on the 32-processor Beowulf cluster with Ethernet switches network on the systems with the number of generating units ranging from 10 to 80 over the entire dispatch periods. The PMGA algorithm carefully schedules its processors, computational loads, and synchronization overhead for the best performance. The speedup upper bounds and the synchronization overheads on the Beowulf cluster are shown on different system sizes and different migration frequencies. The proposed PMGA is shown to be viable to the online implementation of the constrained ED due to substantial generator fuel cost savings and high speedup upper bounds.

Stabilization of Tie-Line Power Flow by Robust SMES Controller for Interconnected Power System With Wind Farms

This paper presents the use of superconducting magnetic energy storage (SMES) with robust controllers for stabilization of tie-line power flow in a longitudinally interconnected power system with wind farms. The high penetration of wind power with abrupt changes causes fluctuations of tie-line power flow and significantly affects the effective use of transmission lines. A simultaneous active and reactive power control scheme of SMES including a characteristic of SMES coil current is employed for realizing a permissible range of SMES operation. Moreover, a multiplicative uncertainty model is considered in the parameter optimization of robust SMES controllers by using a heuristic method. Finally, simulation results are carried out to show the effectiveness and robustness under various situations.

PHEVs Bidirectional Charging/Discharging and SoC Control for Microgrid Frequency Stabilization Using Multiple MPC

This paper proposes plug-in hybrid electric vehicles bidirectional charging/discharging and state of charge (SoC) control for a microgrid frequency stabilization using a multiple model predictive control (MMPC). The MMPC is the improved version of a model predictive control (MPC) for working with multiple operating condition of the system. The MPC is an effective model-based prediction which calculates the future control signals by optimization of a quadratic programming based on the plant model, past manipulate, and control signals of the system. By optimization of an electric vehicle power control signal at each time instant, as well as changing the MPC by electric vehicle battery SoC, the proposed MMPC is able to improve the frequency stabilization of the microgrid effectively.

Cooperative Control of SFCL and SMES for Enhancing Fault Ride Through Capability and Smoothing Power Fluctuation of DFIG Wind Farm

This paper deals with a cooperative control of a resistive type superconducting fault current limiter (SFCL) and a superconducting magnetic energy storage (SMES) for enhancing fault ride through (FRT) capability and smoothing power fluctuation of the doubly fed induction generator (DFIG)-based wind farm. When the system faults occur, the SFCL is used to limit the fault current, alleviate the terminal voltage drop, and transient power fluctuation so that the DFIG can ride through the fault. Subsequently, the remaining power fluctuation is suppressed by the SMES. The resistive value of the SFCL as well as the superconducting coil inductance of the SMES are simultaneously optimized so that a sudden increase in the kinetic energy in the DFIG rotor during faults, an initial stored energy in the SMES coil, an energy loss of the SFCL, and an output power fluctuation of the DFIG are minimum. The superior control effect of the cooperative SFCL and SMES over the individual device is confirmed by simulation study.

Improving Low-Voltage Ride-Through Performance and Alleviating Power Fluctuation of DFIG Wind Turbine in DC Microgrid by Optimal SMES With Fault Current Limiting Function

The vital problems of doubly fed induction generator (DFIG) wind turbine are power fluctuation and low-voltage ride-through performance. To tackle both problems, the new circuit configuration and optimization technique of the superconducting magnetic energy storage with fault current limiting function (SMES-FCL) in a DC microgrid are presented. The SMES-FCL circuit mainly consists of two DC choppers with common superconducting coil (SC). During normal operation, the SMES-FCL acts as the SMES unit to suppress the power fluctuation of DFIG. When severe faults occur in the system, the SC is automatically connected to the system and used as the fault current limiter. Consequently, the fault current and the terminal voltage drop of DFIG can be alleviated. The energy function method is used to formulate the optimization problem of SC inductance, initial stored energy, and proportional-integral control parameters of choppers. Simulation study confirms the superior control effect of the SMES-FCL over the conventional SMES.

Alleviation of Power Fluctuation in Interconnected Power Systems With Wind Farm by SMES With Optimal Coil Size

The large penetration of wind power into interconnected power systems causes the severe power fluctuation in tie-lines. To alleviate power fluctuation, the superconducting magnetic energy storage (SMES) can be applied. Nevertheless, the installation of SMES is quite costly. Especially, the superconducting coil size which is the vital part of SMES, must be carefully specified. This paper proposes a new optimization technique of power controller parameters and coil sizes of multiple SMES units for alleviation of tie-line power fluctuation in interconnected power systems with wind farms. The structure of active and reactive power controllers of SMES is the proportional-integral (PI). Based on the minimization of the variance of tie-line power fluctuation and the initial stored energy of a SMES unit, the optimal PI parameters and coil size can be automatically tuned by a particle swarm optimization. Simulation study in the West Japan interconnected systems confirms that the proposed SMES with optimal coil size is able to effectively and robustly suppress power fluctuation against various wind power patterns and heavy power flow levels.

Coordinated Control of Optimized SFCL and SMES for Improvement of Power System Transient Stability

It is well known that the Superconducting Magnetic Energy Storage (SMES) is effective to damp the power swing after the occurrence of faults. Nevertheless, if the SMES is also applied for transient stability improvement, a large power capacity of SMES is required. Additionally, the SMES is not able to absorb enough energy during faults since the bus voltage where the SMES is installed, drops considerably. To enhance the SMES control effect and transient stability, this paper proposes the coordinated control of the optimized resistive type superconducting fault current limiter (SFCL) and SMES. When the fault occurs, the SFCL rapidly suppresses the transient power swing by limiting the fault current. Subsequently, the SMES damps out the remaining power swing. The optimization problem of SFCL resistance and power controller parameters of SMES with optimal coil size is formulated based on an augmentation of transient stability margin and damping performance. Solving the problem by the particle swarm optimization, the optimal parameters of SFCL and SMES can be automatically obtained. Simulation study confirms the superior stabilizing effect of the coordinated SFCL and SMES over the individual device. The SFCL not only solves the voltage drop problem at the SMES bus, but also assists the SMES to stabilize the system. Besides, the MW and MJ capacities of the SMES operated with SFCL are significantly reduced.

Power system stabilizer tuning based on multiobjective design using hierarchical and parallel micro genetic algorithm

In order to achieve the optimal design based on some specific criteria by applying conventional techniques, sequence of design, selected locations of PSSs are critical involved factors. This paper presents a method to simultaneously tune PSSs in multimachine power system using hierarchical genetic algorithm (HGA) and parallel micro genetic algorithm (parallel micro-GA) based on multiobjective function comprising the damping ratio, damping factor and number of PSSs. First, the problem of selecting proper PSS parameters is converted to a simple multiobjective optimization problem. Then, the problem is solved by a parallel micro GA based on HGA. The stabilizers are tuned to simultaneously shift the lightly damped and undamped oscillation modes to a specific stable zone in the s-plane and to self identify the appropriate choice of PSS locations by using eigenvalue-based multiobjective function. Many scenarios with different operating conditions have been included in the process of simultaneous tuning so as to guarantee the robustness and their performance. A 68-bus and 16-generator power system has been employed to validate the effectiveness of the proposed tuning method.

Coordinated Robust Control of DFIG Wind Turbine and PSS for Stabilization of Power Oscillations Considering System Uncertainties

Uncertainties in power systems, such as intermittent wind power, generating and loading conditions may cause the malfunction of power system stabilizing controllers, which are designed without considering such uncertainties. To enhance the robustness of stabilizing controllers against system uncertainties, this paper proposes a new coordinated robust control of doubly fed induction generator (DFIG) wind turbine equipped with power oscillation damper (POD) and synchronous generator installed with power system stabilizer (PSS) for stabilization of power system oscillations. Without the difficulty of mathematical representation, the inverse output multiplicative perturbation is used to model system uncertainties. The structure of POD and PSS is specified as a practical second-order lead/lag compensator with single input. The parameters optimization of POD and PSS is conducted so that the stabilizing performance and robustness of POD and PSS are augmented. The improved firefly algorithm is applied to solve the optimization problem and achieve the POD and PSS parameters automatically. Simulation study in the modified IEEE-39 bus New England system included with DFIG wind turbines ensures that the robustness and stabilizing performance of the proposed coordinated DFIG with POD and PSS are much superior to those of the conventional DFIG with POD and PSS under various severe disturbances and system uncertainties.