Updated: Jul 7, 2020
SIGNAL PROCESSING APPLICATION ACROSS THE SMART GRIDS
Signal processing has been used in various fields for the betterment of the respective fields. One such application is use of signal processing in power systems. Signal processing provides the Information about characterization and analysis about the signal which is to be used and of the parameters to be measured. Signal processing techniques also consist of invariable techniques such as notch filters and some distortions. This concept brings about several time varying variable but the linear and time invariant systems will continue to be the tools to analyze small grids. Signal processing helps us to check the parameters and to keep it under control.Furthermore, analytical tools are required for the state estimation of system parameters due to the uncertainty and non-feasibility of monitoring system parameters at various locations.
This makes the estimation and further processing of electrical power system parameters an essential feature of the power system analysis. Power frequency is an important parameter in a power system that is determined using spectrum estimation or spectral analysis. Te applications of spectral analysis in power systems can be found in power quality analysis, protection and control. Previously, spectral analysis was used to estimate the harmonic component of a stationary signal. However, spectrum analysis of non-stationary signals with a time-varying frequency and inter-harmonics is the current focus of researchers .Signals in electrical power system are time and frequency dependent. Frequency domain analysis is used to extract features and information for possible transient conditions. These transient conditions are associated with the presence of high frequency harmonics and other disturbances. As the electric smart grid of the future becomes more complex in terms of the variability of loads and generation, growth in response to market incentives and utilization of power electronics for energy processing is required.
Therefore, electrical signals will require a broader set of tools and methods for signal processing. Te basic bridge between time and frequency domains is the Fourier transform (FT). Te FT is not the best tool to analyze power system signals because power system signals are non-stationary signals but FT assumes that the signals under analysis are
SINGLE-CHIP SOLUTION FOR ALL DIGITAL SIGNAL PROCESSING
Single chip solution is excellent in power consumption and performance, it is impossible for this solution to support multiple standard sand multiple applications. Also, an ASIC-based solution is not suitable for upgrading to better signal processing algorithms that highly determine the performance of digital processing systems.FPGA- or DSP-based solutions offer great flexibilities in supporting multiple standards(or models or applications) and also in supporting different signal processing algorithms. The problem of this FPGA/DSP-based solution is its inefficiency from the power consumption and cost point of view. The third representative computing platform is some combination of these two solutions and can be viewed as an accelerator-based solution, which can offer some advantages in both flexibilities and performance.However, one major problem in this third solution is the difficulty in programming/porting different algorithms into its platform, mainly due to the heterogeneous interfaces among its control units,computational units, data units, and accelerator units. A single chip solution, by having better compromise among the power efficiency, cost reduction, time-to market,flexibility, and programming ability,is highly desirable. In other words,what we need to develop is a single-chip computing platform that is able to perform all signal processing algorithms from RF through base band to applications layers while being
1)as good as ASIC in performance, power, prize, and cost;
2) as flexible as FPGA/DSP in multiple standards,multiple modes, and cross-layers;
3)as easy as C language in the programming model.
Although some are-configurable architecture-based computing platforms, which have homogeneous interfaces but heterogeneous processing elements/cores(many-cores or multi cores), can be considered as good candidates of this desired processing platform, much more efforts from the signal processing community are still needed to achieve the goal.