**5. Project of the Paraconsistent Expert System - PESPAL2v**

The project of PESPAL2v starts with the definition of the methods of acquisition of data through the evidence degree extracting algorithms with the goal of generating the paracon‐ sistent logical signals for the analysis network composed of algorithms based on the PAL2v.

#### **5.1. Acquisition of Measurements**

**1.** Pre-failure – consists in the analysis of the sub-transmission system in operation.

contingency.

46 Advances in Expert Systems

network. They are:

contingency.

analysis.

*4.1.1. Propositions Used in the Paraconsistent analysis*

Pp1: There is overcurrent in the electric power network

Pp2: There is sub-voltage in the electric power network

now related to the annotation of the object proposition:

the topology of the power network:

Po: There is the risk of drop by overload in the electric power network.

Po1: There are restrictions of loads in the electric power network.

Po2: The network topology is ideal for the current situation.

cy.

**2.** Post-failure – consists in the analysis of the sub-transmission system at the instant of the

**3.** Restoring – consists in the analysis of the sub-transmission system after the contingen‐

The paraconsistent analysis in the PESPAL2v is based on the configurations of the PANs where the paraconsistent logical signals are extracted from measured values of voltage and electric current. The PAL2v analysis is performed with applied paraconsistent logical signals with

The two first analyze the tension outage and overcurrent at the measurement points and generate evidence degrees related to the existence of overloading in the sub-transmission

Next, through the PANs algorithms, the paraconsistent analysis with the degrees of subvoltage and overcurrent generated by this initial analysis which result evidence degrees,

For the decision-making about the optimized restoring of the sub-transmission system after a contingency, PESPAL2v still analyzes other two propositions related to the restrictions and

That being so, the sequence of maneuvers which are offered to the operation will be condi‐ tioned directly to the configuration of topologies, technical norms and restrictions which in‐ volve the area of the sub-transmission system of the power network affected by the

The classification performed by the paraconsistent analysis network (PANet) generates a re‐ sulting evidence signal whose value will define the type of operation and sequences of re‐

Figure 10 shows the pre-failure analysis with its partial propositions which generate the evi‐ dence degrees for its object proposition and whose result will be used for the post-failure

storing closest to the ideal, given the conditions of the sub-transmission system.

annotations composed of evidence degrees related to 5 partial propositions.

The first task to be performed by the paraconsistent expert system PESPAL2v is the acquisition of values of measurements performed in the system so that the overload risk levels can be detected. For this purpose, we use the data available in the SCADA (Supervisory Control and Data Acquisition) system which, in this phase, has to receive several types of measure‐ ments from the field.

The SCADA system is responsible for the interface between the measurements of electric quantities and the communication network interconnected to the analysis systems.

#### *5.1.2. Block Diagrams of Primary Signals*

The measurements required by SCADA and stored into database are performed by the re‐ mote stations RTU (Remote Terminal Units) and / or by signal capturing devices IED (Intel‐ ligent Electronic Devices). In the practice due to the unbalancing of loads, errors in measurements performed by SCADA and other factors which influence the electric system, it is verified that the amplitude values of quantities of interest (voltage and current) are dif‐ ferent among the three phases of the transmission line.

This condition shows that the measured values bring contradiction levels among them right from the origin. So, in order to obtain reliable values in the signal treatment of the Paracon‐ sistent Expert System -PESPAL2v, the primary values receive an initial treatment of contradic‐ tion extraction.

two signals become input to a contradiction effect extracting algorithm outputting an evi‐

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49

Figure 12 shows the evidence degree of overload risk extracted from a measure point of the

The operating substation seen on the figure 12 is composed by two buses shown horizontal‐ ly where a total of 16 load control breakers are interconnected. Each breaker controls its cor‐ respondent load and are sources of extraction of evidence degrees for the paraconsistent analysis. In each one of the two buses there are 8 load breakers combined, however when a disconnector or electric key is open, it separates two buses with 4 breakers for each one.

Other breakers which control the feeding of the input transformers of the substation and the capacitor bank are also measurement points from where the evidence degrees of overload

The extracting module of resulting risk evidence degree uses the contradiction effect extract‐ ing algorithm so it can receive *n* evidence degrees from several breakers which are intercon‐ nected to the same bus. That being, the PAL2v analysis can offer a unique representing

**5.3. Extracting Module of Evidence Degrees from the Interconnection Buses**

dence degree of overload risk at the measurement point.

**Figure 12.** Overload Risk degree extraction from the breaker of load 16.

risk at the operating substation.

value of the evidence degree of the bus.

breaker (Load 16) of a typical substation of the sub-transmission system.

Considering this condition, the extracting block of primary signals uses algorithms capable of extracting evidence degrees and of extracting contradiction effects, as shown on Figure 11.

**Figure 11.** Block diagram which extracts primary evidence signals related to the sub-voltage and overcurrent on the measurement point.

The maximum and minimum values of the discourse universe of the evidence degree ex‐ tracting algorithm are particular to each load connected to the corresponding breaker at the substation of the electric power transmission line.

The evidence degree extracting system receives the three values of voltage (or current) cor‐ responding to the three phases of the line (RST) which are transformed in evidence degrees by a normalization defined by the interest interval or discourse universe. After this first process, the three resulting values pass through a contradiction effect extracting algorithm which outputs a unique resulting evidence degree.

#### *5.2.3. Evidence Degree Extraction at an Operating Substation*

PESPAL2v's project was carried out in order to perform analysis of overload risks through the applications of the algorithms of the PAL2v on monitoring essential points available at the operating substations of the sub-transmission electric system.

The buses that interconnect the several equipments installed at a substation such as trans‐ formers, electric keys and breakers of the sub-transmission system are points where voltage and current can be measured for each one of the loads interconnected by the breakers. In an operating substation a sub-voltage evidence degree and an overcurrent evidence degree are extracted from each breaker which activate loads at an operating substation.

Based on these values, the modules composed by the algorithms of the PAL2v verify the state of that point with respect to tension decreasing and excess of current intensity which together contributes to the increase of the overload risk at the point measured. After the ex‐ traction of the evidence degrees of sub-voltage and overcurrent from the load breaker, these two signals become input to a contradiction effect extracting algorithm outputting an evi‐ dence degree of overload risk at the measurement point.

Figure 12 shows the evidence degree of overload risk extracted from a measure point of the breaker (Load 16) of a typical substation of the sub-transmission system.

**Figure 12.** Overload Risk degree extraction from the breaker of load 16.

sistent Expert System -PESPAL2v, the primary values receive an initial treatment of contradic‐

Considering this condition, the extracting block of primary signals uses algorithms capable of extracting evidence degrees and of extracting contradiction effects, as shown on Figure 11.

**Figure 11.** Block diagram which extracts primary evidence signals related to the sub-voltage and overcurrent on the

The maximum and minimum values of the discourse universe of the evidence degree ex‐ tracting algorithm are particular to each load connected to the corresponding breaker at the

The evidence degree extracting system receives the three values of voltage (or current) cor‐ responding to the three phases of the line (RST) which are transformed in evidence degrees by a normalization defined by the interest interval or discourse universe. After this first process, the three resulting values pass through a contradiction effect extracting algorithm

PESPAL2v's project was carried out in order to perform analysis of overload risks through the applications of the algorithms of the PAL2v on monitoring essential points available at the

The buses that interconnect the several equipments installed at a substation such as trans‐ formers, electric keys and breakers of the sub-transmission system are points where voltage and current can be measured for each one of the loads interconnected by the breakers. In an operating substation a sub-voltage evidence degree and an overcurrent evidence degree are

Based on these values, the modules composed by the algorithms of the PAL2v verify the state of that point with respect to tension decreasing and excess of current intensity which together contributes to the increase of the overload risk at the point measured. After the ex‐ traction of the evidence degrees of sub-voltage and overcurrent from the load breaker, these

extracted from each breaker which activate loads at an operating substation.

tion extraction.

48 Advances in Expert Systems

measurement point.

substation of the electric power transmission line.

which outputs a unique resulting evidence degree.

*5.2.3. Evidence Degree Extraction at an Operating Substation*

operating substations of the sub-transmission electric system.

The operating substation seen on the figure 12 is composed by two buses shown horizontal‐ ly where a total of 16 load control breakers are interconnected. Each breaker controls its cor‐ respondent load and are sources of extraction of evidence degrees for the paraconsistent analysis. In each one of the two buses there are 8 load breakers combined, however when a disconnector or electric key is open, it separates two buses with 4 breakers for each one.

Other breakers which control the feeding of the input transformers of the substation and the capacitor bank are also measurement points from where the evidence degrees of overload risk at the operating substation.

#### **5.3. Extracting Module of Evidence Degrees from the Interconnection Buses**

The extracting module of resulting risk evidence degree uses the contradiction effect extract‐ ing algorithm so it can receive *n* evidence degrees from several breakers which are intercon‐ nected to the same bus. That being, the PAL2v analysis can offer a unique representing value of the evidence degree of the bus.

Figure 13 shows a general diagram of capture of the resulting evidence degree of a bus at a typical operating substation shown in the previous picture which is composed by four breakers.

**5.5. Computing the total resulting evidence degree of overload risk of the substation**

dures for the transmission of electric power after a contingency.

eration, where the load is attended and the operating limits are observed.

important items which must be in the knowledge base of the model are:

disconnection with the best precision possible.

will make the restoring process easier.

of the following situations:

*5.5.1. Restoring control actions*

ure.

studies.

**5.6. Restoring Plans**

After obtaining the evidence degree of overload risks the model for restoring control was developed. This model has as its goal to analyze and present optimized restoring proce‐

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51

The restoring of an electric power system is a very complex procedure because it involves several activities which include: steps for previous study until steps of decision-making un‐ der intense emotional stress by the operators. The goal of the restoring control is to carry out the prompt restoration of the electric power system taking it to the condition of normal op‐

In the practice the reconnection procedure must be carried out by taking several precautions in order to suit all restrictions which take the new system state to a better level than that one which caused the disconnection. In order to start the actions of the restoring control, it is necessary to have full knowledge of the current situation of the electric system. The most

**b.** Knowledge about the parts of the electric power system which were affected by the fail‐

**c.** Knowledge of the source and cause of the disconnections, detecting what caused the

**d.** Knowledge of the existence of real conditions for the reconnection with the verification

If the source of the failure is a permanent failure that prevents from reconnecting.

If the disconnection happened from previously established emergency control actions. In this case the electric power system is known to have programmed "islands" which

If there are previously established control actions. This is a situation which happened when the emergency control takes the energy system to a condition known by previous

The restoring plans have detailed actions by means of operation instructions which must be carried out by the operator in order to reconnect the electric power system. The strategy of these plans is based on the division of the procedures in steps in order to obtain a larger de‐ centralization of the recomposition actions. In the development of the Paraconsistent Expert System - PESPAL2v, the model of restoring control was designed to present actions based on

**a.** Knowledge about the part of the electric power system which was disconnected.

Through amplitude signals of the quantities received by the extraction modules of primary signals, and the signal which represents the state of the breaker key, each breaker has its evi‐ dence degree of risk which will be treated by the final module, resulting in a unique value of evidence degree of overload risk on the buses.

#### **5.4. Paraconsistent Logical Model of Operating Substation**

Using contradiction effect extracting blocks a paraconsistent logical model of operating sub‐ station can be created encompassing the evidence degree of overload risk of all possible points to be monitored.

In the typical operating substation the goal is to obtain the degree of overload risk generated by the four buses. So, from the models of the main devices installed in a typical substation, a paraconsistent modeling for the whole substation was designed.

First the overload risks at a typical substation were classified in four types:


The resulting evidence degree of overload risk of the substation is then obtained by the par‐ aconsistent analysis performed among these four values extracted from the model.

**Figure 13.** Diagram of capture of evidence degree of risks from a typical bus of a substation.

#### **5.5. Computing the total resulting evidence degree of overload risk of the substation**

After obtaining the evidence degree of overload risks the model for restoring control was developed. This model has as its goal to analyze and present optimized restoring proce‐ dures for the transmission of electric power after a contingency.

#### *5.5.1. Restoring control actions*

Figure 13 shows a general diagram of capture of the resulting evidence degree of a bus at a typical operating substation shown in the previous picture which is composed by four

Through amplitude signals of the quantities received by the extraction modules of primary signals, and the signal which represents the state of the breaker key, each breaker has its evi‐ dence degree of risk which will be treated by the final module, resulting in a unique value of

Using contradiction effect extracting blocks a paraconsistent logical model of operating sub‐ station can be created encompassing the evidence degree of overload risk of all possible

In the typical operating substation the goal is to obtain the degree of overload risk generated by the four buses. So, from the models of the main devices installed in a typical substation, a

The resulting evidence degree of overload risk of the substation is then obtained by the par‐

aconsistent analysis performed among these four values extracted from the model.

**Figure 13.** Diagram of capture of evidence degree of risks from a typical bus of a substation.

breakers.

50 Advances in Expert Systems

points to be monitored.

evidence degree of overload risk on the buses.

**1.** Risks of overload on the buses (µEbus).

**2.** Risks of load transfer (µETRANS).

**5.4. Paraconsistent Logical Model of Operating Substation**

paraconsistent modeling for the whole substation was designed.

**3.** Risks of overload on the secondary windings (µESeC).

**4.** Risks of overload on the primary windings (µEPRIM).

First the overload risks at a typical substation were classified in four types:

The restoring of an electric power system is a very complex procedure because it involves several activities which include: steps for previous study until steps of decision-making un‐ der intense emotional stress by the operators. The goal of the restoring control is to carry out the prompt restoration of the electric power system taking it to the condition of normal op‐ eration, where the load is attended and the operating limits are observed.

In the practice the reconnection procedure must be carried out by taking several precautions in order to suit all restrictions which take the new system state to a better level than that one which caused the disconnection. In order to start the actions of the restoring control, it is necessary to have full knowledge of the current situation of the electric system. The most important items which must be in the knowledge base of the model are:


If the source of the failure is a permanent failure that prevents from reconnecting.

If the disconnection happened from previously established emergency control actions. In this case the electric power system is known to have programmed "islands" which will make the restoring process easier.

If there are previously established control actions. This is a situation which happened when the emergency control takes the energy system to a condition known by previous studies.

#### **5.6. Restoring Plans**

The restoring plans have detailed actions by means of operation instructions which must be carried out by the operator in order to reconnect the electric power system. The strategy of these plans is based on the division of the procedures in steps in order to obtain a larger de‐ centralization of the recomposition actions. In the development of the Paraconsistent Expert System - PESPAL2v, the model of restoring control was designed to present actions based on the evidence degrees of overload risks obtained by the paraconsistent analysis on several points of the electric power system.

The reconnecting maps were done based on operational norms and restrictions of each sub‐ station and sequences of optimized restoring were established taking into consideration the values of risk degrees of overload before and after the contingency.
