CONTROL OF SMALL HYDRO POWER PLANT

Abstract

Energy is an essential factor for economic development and life quality improvement. The non-renewable energy sources are depleting and may be exhausted by the end of the century. So, there is a need to manage the transition from the conventional sources like coal, oil to renewable energy sources. Renewable energy source include small hydro power, wind, solar, ocean energy and biomass resources which can easily be used in sustainable manner. Hydropower can be considered as the oldest source of energy as largest volume of the sphere represents all water on, in, and above the Earth, that would be about 332,500,000 cubic miles. Hydropower operation is complex and time dependent, so when there is any fluctuation in load will affect the natural operating frequency of the system i.e. not well. Previously governors were used but they have slow response, large manpower cost and wear tear of parts and require continuous observation etc due to which we need some fast response controllers for maintaining frequency constant under such situation. Several researches have been carried out in the field of controllers, emerging technologies such as PT controller, PID algorithm etc were frequently being implemented, but they don't guarantee for optimal stability due to which now day's artificial intelligence technique is becoming popular. Artificial Intelligent Controller has successfully implemented in many fields because of their advantages over conventional PID controllers. This intelligent modeling technique of a system having complex mathematical equations has now become easy. Artificial intelligence technique deals with the uncertainties in human perception and reasoning. Fuzzy logic technique provides the powerful inference mechanism that imposes the human reasoning capability on the knowledge based system. In the literature survey, it is found that hydropower plant model has been used to study dynamic response of the gate opening with different types of hydraulic turbine speed variation. The emerging controller i.e. Artificial Intelligent Controller is compared with conventional PID control for the speed control of hydraulic turbines. The comparison is carried out in terms of rise time, smoothness of settling time and overshoot in wicket gate opening with response to change in turbine speed. In this thesis, several controllers' response has been compared under the load disturbance of 1%, where it is found that Fuzzy-PI controller has the minimum settling time of 30 sec and frequency deviation of zero as compared to other controllers. Minimum settling time and frequency deviation shows that the Fuzzy-PI controller has the fastest response with insignificant steady state error. Here three Fuzzy Controllers are also designed for gate opening, load shedding and discharge supervisions. A SIMULINK model of isolated hydro power plant has been developed for the study of different designed controllers. When 1% of load disturbance is applied to the hydro power system, the frequency begins to drop and in - order to compensate the frequency change the turbine need to increase the generation. For increase in generation, water release should be increased for which gate position needs to be modified. Fuzzy Controller-I is designed to provide the necessary required gate control signal depending upon the frequency error and rate of change of error. Sometimes it happens that the gate opening alone is not sufficient to cope up with the change in frequency, so there should be a provision to shed some load and try to maintain the natural operating frequency. For such situation Fuzzy Controller-I! is designed which depending upon the change in frequency and load disturbance produce a control signal for shedding some particular amount of load to have constant frequency. After simulating a SIMULINK model, additional gate opening of 0.02% with load shed of 26% of installed capacity is obtained under 1% load disturbance. Similarly for 5% and 10%of load disturbance, additional gate opening of 0.01% and 0.035 while load shedding was of 26% and 27% respectively. - Hence, The usage of Fuzzy controller provides better performance and reduced the oscillation of the frequency deviation as compared to the conventional P1 and PID controllers which provides zero steady state frequency deviation with step load increment in power system, but have poor dynamic performance (such as more number of oscillation and more setting time) under load variation. Thus the attempt of designing the controllers shows successful results. From the above simulation results, it is clear that the dynamic response in the proposed method is far better than that of the conventional P1 and PID controller. All the drawbacks of the P1 and PID controller are eliminated by using a Fuzzy logic controller. Hence it is concluded that inclusion of fuzzy logic controller is an effective and efficient method of load frequency control.