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Whatever sophisticated algorithms of signal processing are further used, the overall performance of the protection relay is also a function of quality of the analog signal pre-processing path including current and voltage transformers, analog antialiasing filters and A/D converters.

Having in mind that protective relays are devices that are supposed to evaluate the state of the protected plant and to react properly in case of abnormal operating conditions, the relay final output is usually the command to trip the protected element or to raise an alarm, whenever it is necessary. Before a tripping signal to the associated circuit breaker or an alarm is issued the decision is to be taken that is based on the locally measured criteria values and additional information from other protective relays and/or control centers. While in preceding chapters the measurement techniques and algorithms were presented, here the possible approaches to the decision making are outlined and the detailed decision procedures are described.

The age of protection began some 105 years ago, when control apparatus were for the first time connected to current and voltage transformers, which reduced the primary currents and voltages to secondary levels. The secondary currents and voltages could be processed to generate TRIP or NO-TRIP decisions.

Synthesis of digital power system protection systems is possible with application of many advanced and complex mathematical tools. Understanding of digital systems, digital signal processing, analysis and synthesis of digital filters require transformations between time and frequency domain as well as transitions between continuous and discrete data and systems. All of them belong to the family of methods being a part of signal and system theory and use Fourier, Laplace and Z transforms as well as Fourier series as the most important mathematical basis.

The protection equipment is applied with the aim of minimizing the effects of faults and other abnormal phenomena on the operation of electrical power systems. An electrical power system is considered as all the plants required to generate, transmit and distribute electrical power, including generators, power transformers, lines and cables, circuit-breakers, etc.

The artificial intelligence methods presented in Chaps. 11–14 require a lot of computational power but, in return, provide flexibility and possibility of handling imprecise or missing data. Despite their differences, they all offer soft-signal processing skills, thus one can say that they all form a family of soft computing that can be defined as follows

Standard control systems are designed and evaluated taking into account dynamics and required accuracy for various input signals. Digital protection systems should also be evaluated in a similar way, however, the fundamental parameter is time needed to take decision concerning the state of protected element of the power system. Sometimes it is as short as a fraction of period of the fundamental frequency component. This decision time, different for various power system elements, is usually fixed to avoid possible extended damage of protected plants. For some criterion values and some decision-making methods the final decision is to be done even during transient states of measurement when one can still expect substantial errors criteria values determination. This is why while designing a protection system one must take dynamic features of measurement algorithms into consideration and perform optimization of its elements and the entire system as a decision-making device.

Digital filters allow to pass assumed spectrum part or particular component of the signal and prevent from passing the other signal components, sometimes called noise. Similarly to analog filters one can distinguish: low pass, high pass, band pass and band rejection digital filters.

The signal processing methods and algorithms described in preceding chapters were expressed in form of explicit equations, transfer functions and/or logic rules, either in crisp or in fuzzy versions. There are, however, specific tasks and power system operation conditions when, especially for the problems that are complex and difficult to express in terms of traditional means, other solutions should be applied. In such situations, both for signal processing and decision making Artificial Neural Networks may constitute a good solution.

As mentioned, in the preceding chapter on decision-making, the protective relay equipped with standard, deterministic signal processing algorithms (measurement with fixed data window, discrimination with fixed thresholds or characteristics) may not perform properly for all conceivable power system operating conditions.

In case of protection devices of pre-digital era that were made in analogue technique the processes of measurement and decision-making were integrated. Magnitude or phase comparators were applied and thus the measurement of criterion values could not be realized directly.

In this chapter the procedures originating from biological evolution are presented that can be applied e.g. for intelligent searches and optimization in power systems. The procedures belong to the so-called “biological programming” family, which is not limited to the genetic algorithms only. In wider sense the neural networks described in Chap. 12, being an analogy of human brain, are also good examples of this family.

Digital finite impulse response (FIR) filters produce output signal realizing weighting sum of actual and preceding input signal samples.