Report about Benchmark Test in Power System

Introduction

In past few years, there has been a tremendous increase in the emphasis on power consumption and cooling of computer systems from both the management and design aspect. Managing electric power has significant consequences for system performance and also draws the attention of the computer architecture and system research communities. Benchmarks in power system are used to develop models of system behavior and experimentally assess new ideas. A ‘benchmark system’ consists of a model of the electric power system together with a set of conventional Power System Stabilizers (PSSs) whose parameters get soundly tuned according to one of the several techniques that are broadly applied in practice. Therefore, the benchmark systems offer a basis for evaluating the damping performance of novel damping controls and tuning approaches to the research community. Installing PSSs so as to increase the damping element of the electrical torque of a synchronous generator through the modulation of its excitation voltage, has been a common practice in the industry for several decades now, and aims at improving the small-signal stability of interconnected power systems. There have been proposals of many variants of the phase compensation designs of the 1970s so as to reduce possible adverse dynamic effects of this controller at non-electromechanical frequencies. The developments in robust control theory in the past few years have also resulted in some of the alternative PSSs, all acting through the automatic voltage regulator (AVR) as well as the exciter of the synchronous machines. Controllers with structures apart from the lead-lag phase compensation and applied to FACTS gadgets have been referred to as Power Oscillation Dampers (PODs) (Hanson, et. al., 2007).

The performance of the new controller get verified by digital simulations and compared to that of a conventional PSS using a test system built primarily to pinpoint the benefits of the new controller. In such kind of cases, there is a tendency to over-emphasize the advantages of the new controller as compared to well applied conventional solutions. Hence, a set of benchmark systems is necessary with soundly tuned conventional PSSs so as to give a common basis for fairly assessing the performance of novel damping controllers and PSS tuning techniques in comparison with conventional methodologies.

One of the areas where there has been increased attention in the electric power system includes the focus on power and controlling of computer systems both from design and management. Similarly, there is also an increasing interest in the understanding of performance effects of power management actions. A majority of the power management actions include dynamic voltage and frequency scaling have performance implications and understating the trade-offs between performance and power is significant all the system design levels. Power systems do not always get run at complete capacity, and designers and users require having knowledge of the power consumption and the performance that they can deliver across the whole range of load intensity, from zero to peak capacity. Simultaneously, the benchmarking tests for power and performance give a more complex measurement problem that has been there for performance benchmarking only. There must be a correlation between the power and performance data with each other through time. Simple end-to-end numbers, t transactions consuming j Joules over s seconds do not give adequate information concerning dynamic runtime behavior. 

The Benchmark systems and their selection criteria

Single Machine Infinite Bus (SMIB) test systems have been employed widely in the study of electromechanical oscillations. The SMIB model considers many of the practical components linked to the field commissioning and testing of stabilizers, in which it is not possible to excite interarea modes (Choo, 2015). The simplifications inherent to the SMIB model, however, limit its applicability to the research of system-wide (inter-area) oscillations in massively interconnected power systems. The other critical elements that need a detailed multi-machine power system representation are 1) the coordination of multiple controllers to simultaneously damp different modes, and 2) robust damping of these electromechanical modes for a range of operating conditions.

The requirements considered in the selection of a power system model as a benchmark system are;

1) The power system should have multiple machines and demonstrate a combination of local and inter-area modes. There can also be other kinds of modes including intra-plant modes so as to reflect practical system conditions in a better way.

2) The power system must be provided with at least one soundly executed conventional damping control method whose action leads into a satisfactory damping performance.

3) The system must have got validated through comparison of its eigenvalues and non-linear time-domain responses from at least two different simulation software packages.

Real-time simulation

Since the mid-twentieth century, there has been a widespread usage of simulation tools for the design and improvement of electrical systems. A simulation refers to a representation of the operation or features of a power system through the utilization or operation of another (Mahanta, et. al., 2015). Simulation tools are significant in the successful development of a vast number of applications that include in the layout of transmission lines in large scale power systems and also in the optimization of motor drives in transportation. The rapid evolution of simulation tools in the past few years is attributed to the rapid evolution of computing technologies. As the developments in the computer technologies have led to decreasing in cost and increase in performance, there has been an improvement in the capability of simulation tools in addressing complex challenges in less time. Various digital simulations can be performed in power systems. In discrete time simulation, the time moves forward in steps of equal duration commonly referred to as fixed time-step simulation. In solving mathematical functions and equations at a provided time-step, all the variables or system states are solved successively as a function of variables and states at the end of the previous time-step. The amount of real time needed during a discrete-time simulation in the computation of all equations and functions representing a power system during a given time-step may be shorter or longer as compared to the duration of the simulation time-step. Another kind of simulation is the real-time simulation, in which the accuracy of computations is dependent upon the precise dynamic representation of the system as well as also on the length of time used to generate results. The real-time simulator used for a real –time simulation to be considered valid must accurately produce the internal variables and outputs of the simulation within an equal length of time that its physical counterpart would take. The time required for computation of a solution at given time-step must be shorter when compared to the wall-clock duration of the time-step. It allows for the real-time simulator to carry out all functions necessary to make a real-time simulation relevant, including driving inputs and outputs (I/O) to and from externally connected gadgets.

Description of Benchmark System solved using Mat-lab to do solution

The benchmark system comprises of 39 buses and 10 generators and the damping control issue is the coordination of multiple stabilizers so as to damp electromechanical modes within a control area.

All the electromechanical modes in the system presented above have local or regional nature, except for one that is observed as the oscillation of generators 2 to 10 against generator 1. The last mode has the lowest frequency. The system does not present much of a problem from the small-signal stability stabilization perspective and gets included herein mostly for historical reasons and the sake of verification of the compatibility of outcomes from different software.

The applied solution of this scenario was based on a classical tuning method, which entailed the calculation of the GEP(s) function of all the system generators and the determination of the PSS gains and phase compensation parameters.

In the modeling and validation, the dynamic elements of the benchmark system were done according to the guidelines from IEEE standards. The system model was done on MATLAB and PacDyn. The eigenvalue analyses obtained from the approaches was used for validation. The figure below displays the nine electromechanical modes of the benchmark system.

The 39-bus system was validated as a reliable matching and is obtained for the other eigenvalues of the system as well.

Conclusion

The modern power systems have evolved significantly hence necessitating to a continuous assessment of new constraints. Simulation tools are essential in designing and planning of electrical power systems. The use of MATLAB has been found to be a necessary simulation tool for benchmark systems as it assists in analyzing and designing the systems.

References

Choo, Y. C. (2015). Small signal stability analysis for a turbine-generator unit connected to an HVDC system.

Hanson, H., Rajamani, K., Rubio, J., Ghiasi, S., & Rawson, F. (2007). Benchmarking for power and performance. In 2007 SPEC Workshop.

Mahanta, P. K., Debnath, K., & Rahman, M. H. (2015). Modeling and Simulation of a PV Module Based Power System Using MATLAB/Simulink. Dhaka University Journal of Science, 62(2), 127-132.

Sherry Roberts is the author of this paper. A senior editor at MeldaResearch.Com in write my essay online if you need a similar paper you can place your order from write my essay for me services.