Control Design For Micro Hydro Power Generation Computer Science Essay

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In this paper presented fuzzy logic control system for Micro Hydro Power Generating to identify small signal effect cause of load variation. A control method base on fuzzy logic with arrange if-then rules, defazzification and fuzzification with 2 input crisp that is actual tension error delta and error and 1 output crisp change of tension for the input of generator excitation synchronize have been applied. The system consists of hardware using microcontroller ATMEGA 8535 and a software. The software assisting appearance of process control in computer using Delphi 7 programming, fuzzy logic control use C programming and couple with CodevisionAVR software, and then the program is downloaded to ATMEGA 8535 microcontroller use ponyprog2000. The efficiency of logic fuzzy controller system prototype tested using 5 kW three-phase synchronize machine connected to a variety of fluorescent lamp load. The result showed that lowest error is -7 Volt and highest error is 6 Volt. To set error to match its set point required 8 ms up to 23 ms time.

1. Introduction

Conventional control system applied to micro hydro power generation to achieve nominal voltage and frequency as well as stabil operation used Electronic Load Controller ELC or Induction Generator Controller IGC. This system control both of real load and dummy load by using thyristor to maintain final availability of both load constant. The method has adopted step by step control, manual control and directional control method.

The introduction of fuzzy logic control for micro hydro power generation gives a different alternative. Fuzzy logic uses simple mathematic concepts easy to understand, because fuzzy logic controller work based on rules that extract from operator or expert human thinking and knowledge. Further, the fuzzy logic able to model complex nonlinear functions of the system.

The implementation of fuzzy logic technique to control excitation voltage of synchronous machine for every small signal variation of the system is presented in this paper. The fuzzy inference process comprise of 3 part i.e fuzzification, evaluation rule and defuzzyfication.. The fuzzy logic controller technique applied to micro hydro power electric generation using microcontroller ATMega 8535 and its support software. The software based on C programming write in personal computer can interact with control system pass trough parallel port DT-HiQ AVR. The download system using PonyProg2000 software and result process of fuzzy logic small signal processing will display using Delpi 7 programming. This technique has been implemented to control 5 kW three-phase synchronous machine.

2. Fuzzy Logic Concept

2.1. Membership Function of Fuzzy Set

Parameterization function of one dimension with single input membership of fuzzy set have formulated as state below:

1. Triangular Membership Function

Parameter (a,b,c) (with a<b<c) specified by x coordinate that determine angle of membership function as shown in figure below:

Figure 1. Triangular membership function

2. Trapezoid Membership Function

Parameter (a,b,c,d) (with a<b<c<d) specified by x coordinate that determine angle of membership function, for a=1 b=5 c=7 d=8 as shown below:

Figure 2. Trapezoid Membership Function

2.2. IF-THEN Fuzzy Rules

IF-THEN Fuzzy rules (Fuzzy rule, Fuzzy implication, pernyataan Fuzzy terkondisi). In general fuzzy rule follow the form,

IF x is A, THEN y is B or . A is linguistic value as definition as fuzzy membership in space set X, also for B related to Y. R adalah relasi dalam ruang perkalian X x Y.

x term is operator T-Norm and state that A pair with B (“A couple B”). Threre are four fuzzy relation that using operator T-Norm, ones uaing Fuzzy relation developed by Mamdani, as the result using operator min for konjugation,


Figure 3. Structure of FLC

3. Design Fuzzy Logic Control System

Fuzzy logic controls system have been developed have two crisp error input and delta voltage error. Error and delta defined as below:

Error = Actual Voltage â€" Desire Voltage

Derror = Error(n) - Error(n-1)

Actual voltage is the voltage at load. However desire voltage is setpoint voltage.

Design membership fuction for input and output with 3 label i.e Triangular and trapezoid as shown in the figure 4 to 6.

Figure 4. Error Membership Function

Figure 5. DError Membership Function

Figure 6. Output Membership Function

Design fuzzy if-then rules for input Error and DError obtained evaluation output rule for 3 level as shown below:

Tabel 1. If-Then Rule 3 Level Form


















4. Design Fuzzy Logic Control

The software used for fuzzy logic control programming in microcontroller ATMega 8535 series from AVR of Atmel product is Code Vision AVR C Compiler In-System Programmer. The program compiled using C compiler. Then download to microcontroller ATMega 8535 using ponyprog 2000.

Design algorithm of Fuzzy Logic Control system consist of both algorith for data acuisition and data processing. Fuzzy logic control program stating by determine input setting point and read actual voltage system. Voltage signal convert to DC in side of voltage sensor circuit and then convert to digital by ADC in microcontroller ATMega 8535. Actual voltage compare with setting point voltage to get error value and derror for fuzzification process, rule evaluation and defuzzification in digital part. The result of fuzzy logic control process is a high gain or a low gain voltage signal to exciter of synchronous generator as same value with voltage change at load terminal after signal pass through DAC. The flow chart of fuzzy logic control program shown in figure 7.

5. Result

The testing used to evaluate the respond of fuzzy logic control concerning with load increasing that effect to actual voltage variation dan compare to setpoint voltage in relation with time. The generator speed kept constant as shown below:

Load connected


Figure 8. Generator Voltage vs Time with 300 W load connected

Load disconnected

Figure 9. Generator Voltage vs Time with 300 W Load disconnected

Load connected

Figure 10. Generator Voltage vs Time with 1200 W load connected

Figure 11 Fuzzy Logic Control Test Circuit

Load disconnected

Figure 12. Generator Voltage vs Time with 1200 W Load disconnected

6. Conclution

The result of this fuzzy logic control system research to control actual load voltage can be summerized as below:

According to testing result of open loop and close loop fuzzy logic control system , the equipment error still inside of tolerance , control respond work properly for every load increasion. This condition shown by nominal actual voltage, even generator speed decreased.

Fuzzy logic control System easy to implement, cause of its work based on extracted rules so that have ability, reliability and fast respond in controlling operation of syncronous machine 5 kW in order to keep stabil operation for every load variation as shown in Figure 9-10,12.

Development result of fuzzy logic control system by implement microcontroller ATMega 8535 programed module have succesed in iteraction between hardware and dinamic system to respond every low signal changed in millisecond time constrain.