Design Modeling and Simulation of Supervisor Control for Hybrid Power System

Transcription

1 2013 First International Conference on Artificial Intelligence, Modelling & Simulation Design Modeling and Simulation of Supervisor Control for Hybrid Power System Vivek Venkobarao Bangalore Karnataka Chellamuthu Chinnagouder RMK College of Engineering Chennai, India Abstract The main objective of the Hybrid Power System is to satisfy the requirements of the electrical loads at the same time as maximizing the utilization of renewable energy sources while optimizing the operation of the battery bank and the conventional generators. The supervisor control determines the operation mode of each generation subsystem for optimised operation. Fundamentally, these operation modes are determined by the energy balance between the total demand (load and battery bank) and the total generation (wind, solar, and grid). To design the supervisory controller, we select the wind subsystem as the main generator role; the complementary roles are in charge of solar subsystem and the grid respectively. Diesel generator is not taken into account as the source because of the nature of the fuel. Keywords Hybrid Power system (HPS), Supervisor control, State of Charge (SOC) I. INTRODUCTION Under the current global trend toward market liberalization, an overall approach for operation and control of power units is of paramount importance for the survival of any electric utility [7]. When properly applied, plant-wide instrumentation and control systems can increase plant operating efficiency, operability and maneuverability, robustness and reliability, as well as plant availability, thus contributing to keep down fuel, operation, and maintenance costs, which account for most of the expenses in a power plant [9]. Therefore, there is urgency to develop effective plant-wide automation systems, and consequently the associated overall unit control systems and strategies, to keep them running profitably. Also, it should be noted that the intensive use of computer based instrumentation and control systems, with everyday more reliable and powerful general purpose information processing digital devices, allows system designers to focus more on the implementation of software applications to respond to the above mentioned challenges. Since software complexity, and the costs of its development and maintenance, could easily surpass those of the hardware in which it runs, great effort and care should be paid in the design and development of general and comprehensive software systems to ease the incorporation of advanced operation (i.e., protection, control, and automation strategies) applications to enhance the performance of the power units [10]. and locally available, pollution-free wind energy. With the hybrid power system, annual diesel fuel consumption can be reduced and pollution can be minimized at the same time. [1] [3]To take full advantage of the wind energy when it is available and to minimize diesel fuel consumption, a proper control strategy must be developed. The control system is subject to the specific constraints of a particular application [1] [6]. It has to maintain power quality, measured by the quality of electrical performance, meaning that both the voltage and the frequency must be controlled. Because of this, a simulation study of each new system is needed to confirm that a control strategy results in desired system performance. The simulation study can help in the development of control strategies to balance the system power flows under different generation/load conditions. Using the typical modules provided, it is easy to set up a particular system configuration. II. SYSTEM STUDY A. Supervisor control system for a Wind Turbine The complete diagram of HPS including the interaction with the supervisory controller is presented in Figure 1. The supervisor inputs are measure variables as the currents and voltages outputs of the subsystems in the HPS and the SOC of the battery bank. The supervisor outputs are the signals to activate or deactivate each subsystem. The general scheme for inputs and outputs is shown in 2. Figure 1 Diagram with HPS and its interaction with supervisory control The advantage of hybrid power systems is the combination of the continuously available diesel power /13 $ IEEE DOI /AIMS

2 Figure 2 General Scheme for Inputs and Outputs B. Supervisor control- Modes Mode 1: Mode one occurs when the wind generation is enough to satisfy the total demand. The solar subsystem and the grid are inactive even as the battery bank is in recharge mode at maximum charging current if it is discharged or at zero current if it is fully charged, and the wind subsystem is set to power regulation. This mode is running until the maximum available wind power is exceed by the total power demand [1] Mode 4: In this case, the load demand is higher than the power available from renewable sources, and the battery bank current is equal or higher than maximum discharging current. The supervisor control turns on the grid to provide the extra current [2]. On this mode, the battery current is always the maximum discharging current. On this mode, the On Off control for the load may be activated if the total current demand is highest than the total current generated by the renewable energy and the grid. Mode 2: On this mode, the wind generation is not enough to satisfy the total demand, and it is set by the supervisor control to operate at the point of maximum energy conversion. The solar subsystem is set to follow a power reference required to complement the wind subsystem and together satisfy the total power demand. The battery bank is part of the total power demand, because is in recharge cycle, and its current is always the battery reference current [1]. Mode 5 On this mode, the total demand is more than the power available from wind and solar subsystems, and the battery bank is discharged. The supervisor control allows the grid to starts taking the load gradually from the battery to supply the power demand [2]. On this mode, the battery current is always zero. The On Off control for the load may be activated if the total current demand is highest than the total current generated by the system. C. Operation Strategy of the controller The operation strategy for the supervisor control of the HPS is shown in Figure 3 as a state transition diagram for each mode of the supervisory controller. Mode 3: On this mode, the wind and the solar subsystems are set to operate at their maximum energy conversion points, and the battery bank is set to supply power to the load instead to receive energy. This mode is maintained as long as the state of charge of the battery is greater than a minimum required [1] or the battery current is higher than the maximum discharging current [2]. Figure 3 State transition diagrams for the supervisory controller

3 The supervisory controller can shed some loads if the total power demand is higher than what the overall system could supply. This strategy was not included as an operation mode because it depends basically of the load demand and not on the availability of the generation sources. Figure 4 shows the transition criteria to apply shedding load Figure 7 Battery bank voltage and SOC when discharged Figure 4 Transition criteria to apply load shedding D. Controller Operation Two scenarios were evaluated to represent all the possible situations on the system behaviour. First scenario was simulated with the battery bank fully charged and the second scenario with the battery bank totally discharged. Scenario1 When Battery is fully charged (SOC 0.78) Figure 5 shows a) the wind speed, with variations between m/sec, and b) the cell temperature of PV array which varies between ºC. The three zones of the load were selected to force the HPS and the Supervisor Control to operate in all possible modes. Figure 6 and 7 show the battery voltage and SOC for fully charged and discharged battery power source. Figure 5 wind speed, and the cell temperature Figure 6 Battery bank voltage and SOC when charged Figure 8 Scenario1 - Response of the HPS when Battery is fully charged

4 Scenario2 When Battery is fully discharged (SOC = 0.755) Battery Bank Totally Discharged: The initial condition of the battery bank is totally discharged (SOC = 0.755); the limit to allow the grid generation because the battery is considered discharged is 0.755, so the battery reference current for the renewable source to charge the battery bank is the maximum charging current, which is 20A. The Maximum power needed by the load is provided by the renewable energy source namely wind energy, solar power, battery etc. It s also seen that the marginal power from the central grid is taken for supplying to the load. Almost 90% of the load power is supplied by the renewable energy sources. The requested power from the grid is fully utilized there by reducing the losses. The usage of controlled energy sources like wind, solar, battery constitutes about 85% of the total power. There is no load shutdown seen because of excess load. For a fully discharged battery the flowing observations are derived from simulation It s also seen that the marginal power from the central grid is taken for supplying to the load. When the total demand exceeds the generated power mode automatically shifts to load shedding namely Mode 5. Substantial power from the grid is drawn but it s still not sufficient for the system to save from load shedding. IV. CONCLUSION A unified control law has been developed and simulated. The various zones of generation are also discussed. The paper also shows an insight of the various entry and exit conditions of each zone of operation thereby we can efficiently switch between different generating units to meet the demand efficiently. When the generation is not sufficient then there is no option but to have a load shedding which is also a critical state in the emerging markets. The result represents an aid to evaluate the transient behaviour of power flow in the system. Investigation has been devoted to study of dynamic behaviour in the normal and realistic change in load condition. Therefore, oscillation in power and frequency occur with periods which are imposed by the source with the largest time constant. These oscillations may be excessive for the operation of the power system. Oscillation and instabilities can be avoided by using the controller proposed. V. REFERENCES Figure 9 Scenario2 Response of the HPS when Battery is fully discharged III. RESULTS AND DISCUSSION The hybrid power system with supervisory control is very efficient when compared to the conventional control laws. For a fully charged battery the flowing observations are derived from simulation [1] Valenciaga, F and Puleston, P F. "Supervisor control for stand alone hybrid power system using wind and photovoltaic energy". IEEE transaction Energy Conversion. Vol. 20. No2, pp , June [2] Omari, Osama, Ortjohann, Egon and Morton, Danny. "An Online Control Strategy for DC Coupled Hybrid Power Systems". IEEE Power Engineering Society General Meeting. pp. 18, June [3] De Lemos Pereira, Alexandre. "Modular Supervisory Controller for Hybrid Power Systems"

5 [4] Phd. Thesis. Riso National Laboratory, Roskilde. University of Denmark, June [5] Roscia, M and Zaninelli, D. "Sustainability and quality through solar electric energy". 10th International conference on Harmonics and quality of Power. Vol. 2, pp , [6] Ross, M and Turcotte, D. "Bus configuration in Hybrid Systems". Hybrid info Semiannual newsletter on photovoltaic hybrid power systems in Canada. 7, pp. 25, Summer [7] Meinhardt, M and Cramer, G. "Past, Present and Future of grid connected Photovoltaic and Hybrid PowerSystems". IEEE Power Engineering Society Summer Meeting. Vol. 2, pp , July [8] Chang, Liuchen. "Wind Energy conversion Systems". Canadian Review. pp , [9] Ross, M, Turcotte, D and Roussin, S. "Comparison of AC, DC, and AC/DC bus configurations for PV Hybrid Systems". SESCI Conference [10] Wright, Alan D. "Modern Control Design for Flexible Wind Turbines". Technical Report on National Renewable Energy Laboratory (NREL). pp. 1223, July VI. BIOGRAPHY Venkoba Rao Vivek received his B.E. degree in electrical and electronics engineering from Kuvempu University, India, in He received his M.S. degree in electrical engineering from Anna University, India, in he did his Ph.D in Electrical Engineering in His main research interests are AC motor drives and application of neural networks for drives, power quality and deregulation, and modeling and simulation of processes