A COMPRESSED AIR ENERGY STORAGE SYSTEM: DESIGN AND STEADY STATE PERFORMANCE ANALYSIS Hanif SedighNejad, Student Member, IEEE, Tariq Iqbal, and John Quaicoe, Senior Member, IEEE Memorial University of Newfoundland St. John s, NL Emails: hanifs@mun.ca, tariq@mun.ca, jquaicoe@mun.ca ABSTRACT Energy storage systems are playing a vital role in increasing the penetration of renewable energy sources in remote isolated hybrid systems. Energy storage systems are used to meet the peak load demand when the available renewable energy is not sufficient. Compressed Air Energy Storage system (CAES) is one of the possible options which has been selected in this research due to its good characteristics such as high number of operating cycles, short or long term storage ability, high depth of discharge and acceptable discharge time. Both energy storage and extraction procedures are done through a thermodynamic compression and expansion of the ambient air. In this paper, design and steady state modeling of a micro CAES for possible applications in remote hybrid power systems is presented. Using the system steady state characteristics, an optimum operating strategy for the system is determined to achieve maximum energy extraction. Steady state models of the air motor, air storage and the coupled synchronous generator are presented. The designed system is simulated in Matlab/Simulink and its expected steady state characteristics are presented. Index Terms hybrid power systems, compressed air energy storage, renewable energy, system optimization and sizing. 1. INTRODUCTION Conventional fossil fuels are widely used in electricity generation plants due to their comparative low price and high energy density [1]. However, these electrical power generation plants have negative effects on the environment, such as green house gases emissions, air and noise pollution, and contribute to global warming phenomena [2]. Increasing economical and industrial growth will increase the energy demand during the next decades. On the other hand, increase in electrical capacity of an electrical network can be handled using small distributed generation plants which incorporate renewable energy sources (RES). This is economically and technically attractive because the construction of new electrical transmission lines can be postponed []. In recent years, the development and implementation of RES in small distributed generation plants has received increasing attention. However, the RES penetration rate in the total electrical energy production is still very low, due primarily to their inherent time variability. Stochastic characteristics of RES lead to mismatch between energy production and demand in an electrical power distribution grid which uses only RES plants. This is especially true for wind energy systems, which is now the most economically competitive renewable energy conversion system. Therefore, solving the energy stability and the continuous power supply problem of RES is a key point in RES development [5]. It has been shown in the literature that wind penetration can be increased by incorporating costeffective storage systems in wind farms [6]. There are three different applications that require energy storage systems: Power quality application for seconds or less as needed to assure continuity of quality power; switching from one source of energy generation to another; decoupling the timing of generation and consumption of electric energy for energy management purpose. Efficient energy storage could transform intermittent RES into a stable energy source with the capacity to be dispatched according to load and market price. Such regulatory benefits could even allow the massive capacity of fossil fuel fired power stations to be scaled down rather than being sized to provide maximum loads and continuous operation. There are different types of energy storage systems, based on various physical principles, and each of these technologies is well suited for a specific power or energy range as well as their operation time [5]. Flywheel, Hydrogen, Pumped hydro, Compressed air energy storage, Electrochemical double layer capacitor or Supercapacitor, Batteries, Superconducting magnetic energy storage and Virtual energy storage systems are some examples of energy storage systems [1,7]. Among the energy storage technologies, Compressed Air Energy Storage (CAES) system is an attractive storage technique which does not have drawbacks such as limited capacity, high costs, low availability, low number of charge/discharge cycles and geographic constraints. There are different CAES systems available such as conventional [1,, 4, 5], liquid piston [8], dual-mode CAES
[9] and advanced adiabatic CAES [1]. The optimal operation and sizing of CAES is critical to increasing renewable energy penetration. This paper explores this issue for a small scale CAES for possible application in a remote hybrid power system. In this paper the anatomy of a hybrid system is introduced and the performance of a CAES system in harvesting the excess energy of a sample wind turbine and matching the load demand is evaluated. 2. HYBRID POWER SYSTEM DESCRIPTION The focus of this work is to design a reliable and efficient source of electricity which can provide continuous service to customers. When the output energy of a wind turbine is more than the energy demand at the load side, the excess energy is converted into the mechanical form using high pressure compressors and stored in a high pressure reservoir as potential energy. In the case that the wind turbine cannot deliver the required energy at the load side, the stored mechanical energy is converted to the electrical energy through an air motor, synchronous generator and a power processing unit consisting of a rectifier, dc-dc converter and inverter. A typical schematic of the proposed hybrid system is shown in Fig. 1.. ENERGY CONVERSION MODEL FOR CAES COMPONENTS AND OPTIMIZATIONS Optimization is the key element of a hybrid RES power system design with a proper designed storage system. The energy production, demand and available stored energy is monitored and processed continually. Energy dispatch control unit defines the amount of energy transfer and working condition of the different power components. The output power control unit changes the synchronous generator field current and the input pressure of the air motor to achieve the required power. Synchronous generator speed is measured and compared to the dynamic reference speed obtained from maximum efficiency path. In the following, simplified models for the steady state operation of a CAES are developed in order to obtain independent control strategy for different components in a typical CAES system and avoid complexity. Energy can be stored as high pressure air in a high pressure reservoir by applying work to the compressor. The amount of work, in a polytropic process is expressed as [2]: W= (n/n-1).p 1 V 1 [PR (n-1/n) -1] (1) Where n is polytropic exponent (c p /c v ), P 1 and P 2 are the atmospheric and the tank pressure in compression cycle respectively, and PR is the pressure ratio. The required power of the compressor can be calculated by derivation of the work equation with respect to time. All the working parameters of the compressor, except flow rate (Q), can be considered constant (assuming a good heat exchange with the environment). The power of the compressor can be obtained from (1) as [2]: P compressor = (n/n-1).p 1 Q [PR (n-1/n) -1] (2) The size of a tank that provides 1kWh energy for isothermal, and polytropic energy conversion is shown in Fig. 2. 1 9 Polytropic process Isothermal 8 7 Tank Volume (m) 6 5 4 Fig 1: Schematic of the proposed hybrid system. The energy dispatch control unit performs a supervisory role. Based on the wind and demand data, the dispatch control unit defines the active operating power generation. The operating condition of each power component, including the compressor, storage tank pressure, air motor, and synchronous generator is controlled in a way that achieves maximum efficiency of the system. Each component is optimized to ensure optimum performance of the hybrid power system. The control unit for each component defines the optimum operating condition of the device. 2 1 5 1 15 2 25 5 4 45 5 Pressure ratio Fig 2: Tank size for isothermal and polytropic energy-conversion As can be concluded from Fig. 2, the required volume for certain energy value and the energy conversion efficiency are a function of the working pressure, which can improve the energy density of CAES with more complicated and expensive system. Using high pressure compressors can help to improve the energy density and performance of the proposed hybrid system. Low efficiency for single stage compression and expansion is the limiting factor of a very high pressure system. Highly efficient heat exchangers for
after compression cooling and pre heating between expansions stages can be utilized to overcome this limitation. Changes in air temperature with different compression stages are shown in Fig.. where N is the number of stages. Temperature [K] 7 65 6 55 5 45 4 5 25 1 2 4 5 6 7 8 9 1 stage Number Figure : Change in air temperature with different compression stages Changes in efficiency of the compression cycle with higher compression stages are shown in Fig. 4. As the figure illustrates, the efficiency can be increased using more compression stages. This can help the performance of the CAES system in cases that the excess energy is available in short duration. Compression with lower pressure is faster than higher pressure, so using lower pressure at the beginning of storage cycle increases the speed of storage..75.7 Air Temperature during compression push of curves N=1 N=2 N= N=4 N=5 N=6 N=7 N=8 N=9 N=1 moving chamber reaches the outlet, the air is released. The torque output of the air motor has been approximated from the manufacturer data sheet using the following linear equation: T=T (1-N/N f ) (4) where T is the initial torque at zero speed, N is the air motor speed, and N f is the free rotational speed of the air motor. The mechanical power of this air motor can be calculated from the following equation: P m =π. N.T/ (5) The output torque and power of the air motor is a function of the working pressure. To have a general equation to represent the variable pressure performance of the air motor some modification coefficients can be applied to the output torque and power equation. CF torque =CF t1 p+cf t2 (6) CF speed =CF s1 p 2 +CF s2 p+cf s (7) Where CF coefficients are interpolation constants obtained using CFTOOL toolbox in MATLAB software. Applying the correction factors to the approximated output torque and power will result in modified equation for variable pressure operation. The output power of the air motor with different working pressure is shown in Fig. 6. T=CF torque. T (1-N/CF speed. N f ) (8) P m =π. CF torque. CF speed. N.T/ (9).65 Efficiency.6.55 a) b).5.45 1 2 4 5 6 7 8 9 1 Stage number Figure 4: Change in efficiency with different compression stages. The available wind power output on the rotor of a wind turbine can be approximated as [2, 6]. P wind Turbine =.5 C p ρ A V w () where C p is the wind power coefficient, A is the cross section area swept by rotor and V w is the wind speed. The air density ρ can be taken as 1.225kg/m. In this study, the Bergey Excel-S 1kW wind turbine is considered. Its power output is approximated using () with C P =.245. The stored energy can be converted back to electrical energy using an expansion device coupled to a synchronous generator shaft. In this study, a 6AM-FRV-5A GAST vane type air motor has been used. Fig 5a shows the vane-type air motor with four vanes. When the drive shaft starts to rotate, the vanes slide outward due to centrifugal force and are limited by the shape of the rotor housing. This motor can rotate in either clockwise or counter clockwise directions, based on the flow direction. The air expands to a lower pressure in a higher volume between the vane and the next vane. Torque acting on the rotor shaft is created from the air pressure difference, resulting in rotation toward higher chamber volume. When the air motor shaft rotates and the Power [W] 25 2 15 1 5 Figure 5: a) Gast air motor; b): Output torque for different working pressure GAST Air motor Output Power curves for different working pressures 1 2 4 5 Speed [rpm] Maximum power tracking 7 bar Figure 6: Output power of Air motor for different working pressure The curves have different maximum output power for different working pressure as shown in Fig. 6 and in D representation in Fig. 7. The characteristics can be used as a speed control strategy to achieve maximum efficiency 5.6 bar 4.2 bar 2.8 bar 1.4 bar
extraction from the air motor, based on pressure measurement in the reservoir. The maximum efficiency path can be obtained by mapping the maximum points of Fig. 7 in speed-pressure plane. This trajectory can be approximated with a quadratic equation and applied in optimum speed control of the air motor. Power [W] 5 25 2 15 1 5 1 8 6 Speed [rpm] GAST Air motor characteristic curves for different working pressures 4 2 1.5 Figure 7: Output power of the air motor with different pressure and speed. The equation to represent the dynamic behavior of synchronous generator in dq coordinate in rotor reference frame can be written as: V qs =-R s i qs +ω r λ ds +L qs d(i qs )/dt (1) V ds =-R s i ds -ω r L qs i qs +d(λ ds )/dt (11) V s =-R s i s +L ls d(i s )/dt (12) λ ds =-L ds i ds +L md i fd (1) L A =((N s ) 2.π.μ.r.l)/4 (14) L B =((N s ) 2.π.μ.r.l)/8 (15) L q =L mq +L ls (16) L d =L md +L ls (17) L mq =(L A -L B )/2 (18) L md =(L A +L B )/2 (19) E f =R f.i fd +d(l fd.i fd -L md.i ds )/dt (2) Where L qs and L ds are the inductances, i ds and i qs are the currents, and V qs and V ds are the voltage on q and d axes respectively. R s and R f are the stator and excitation resistance respectively, and E f is the excitation voltage and ω r is the angular velocity of rotor. N s is the number stator 2 2.5.5 4 4.5 Pressure [bar] 5 5.5 6 6.5 winding's turn. r is rotor diameter and l is the rotor length. L B for round rotor will be zero. The drive train of the rotor shaft and electromagnetic torque can be written as: d(ω r )/dt=(t mech -T em -Dω r )/J (21) T em =.pole (λ ds i qs -λ qs i ds )/4 (22) where J is the electrical generator inertia and D is the friction coefficient. Figure 8 shows the CAES system model in MATLAB/SIMULINK software. 4. SYSTEM PERFORMANCE ASSESSMENT USING A CASE STUDY To investigate the effectiveness and overall performance of the proposed hybrid system a case study is considered. In this case study the wind speed at a wind farm in Ramea, Newfoundland during a day is applied to the modeled Bergey Excel-S 1 kw wind turbine and the load profile of a single user is considered in modeling the variable load demand. The available wind power and demand power curve for this case study in minute time scale is shown in Fig. 8.The CAES system schematic model based on the mathematical models presented in the previous section is built in MATLAB/SIMULINK and is shown in Fig. 9 power [W] 11 1 9 8 7 6 5 4 2 1 Wind Power Load demand 2 4 6 8 1 12 14 minute Fig 8: The available wind power and demand power curve for the proposed case study in minute time scale Figure 9: The CAES system model in MATLAB/SIMULINK software
A PID controller has been used to regulate the speed error signal with respect to the reference speed calculated from the maximum efficiency trajectory determined from pressure measurement. The simulation result based on required power and maximum efficiency working path is shown in Fig.1. In this study the performance of the system to provide the required power (7W) is investigated. Based on the load demand the reference values of the direct and quadratic current are defined and the produced power is injected to the load. The simulation result shows that the system can reach the new steady state in 2s with reasonable overshoot. This result shows the effectiveness of the proposed compressed air energy storage system to supply the required power. performance of the proposed hybrid system has been discussed. A CAES system has been simulated and controlled based on maximum efficiency control strategy. The simulation results show that the proposed control strategy can be applied to the system to achieve desired CAES system performance. This hybrid power system with cost effective energy storage as a stable energy source can be implemented to solve the mismatch problem between energy production and demand due to fluctuation of the load and the stochastic characteristics of RES. 6. REFERENCES [1] H.Ibrahim, A.Ilinca, J.Perron., Energy storage systems characteristics and comparisons. Renew Sustain Energy Rev 28; 12: 1221 5. [2] Varin Vongmanee, "The Renewable Energy Applications for Uninterruptible Power Supply Based on Compressed Air Energy Storage System", 29 IEEE Symposium on Industrial Electronics and Applications (ISIEA 29), October 4-6, 29, Kuala Lumpur, Malaysia. Figure 1: The simulation results based on required power and maximum efficiency trajectory. The stored energy and rejected energy for the proposed case study is calculated and shown in Fig. 11, considering the working pressure of 1 Bars for the system. Rejected power is the amount of power that a storage system cannot harvest from a RES because of its limited capacity. The shortage energy is the amount of energy which cannot be supplied using only the wind turbine and the CAES. This energy has to be provided using diesel generator to prevent shortage in load demand. [] H. Ibrahim, R. Younès, A. Ilinca, M. Dimitrova, J. Perron, Study and design of a hybrid wind diesel-compressed air energy storage system for remote areas, Applied Energy 87, Elsevier (21) 1749 1762. [4] Sonal Patel, "The return of compressed air energy storage", Power Magazine (Available online), 1 October 28, Volume 152, Number 1. [5] Giuseppe Grazzini, Adriano Milazzo. Thermodynamic analysis of CAES/TES systems for renewable energy plants, Renewable Energy, Elsevier (28) 1998 26 [6] J.K. Kaldellis, The wind potential impact on the maximum wind energy penetration in autonomous electrical grids, Renewable Energy, Elsevier (28) 1665 1677 [7] Schoenung SM. "Characteristics and technologies for long- vs. short term energy storage". Sandia National Laboratories report (Available online), No SAND21-765, 21. Figure 11: The stored, rejected and shortage energy for the proposed case study (considering the working pressure of 1 bar) 5. CONCLUSION Thermodynamic modeling and simulation of compression and expansion energy conversion cycles has been investigated in this paper to obtain the characteristic and performance of a small scale CAES system. Different working pressure and system design effects on the overall [8] Sylvain Lemofouet and Alfred Rufer, A Hybrid Energy Storage System Based on Compressed Air and Supercapacitors with Maximum Efficiency Point Tracking (MEPT), IEEE Trans. on Industrial Electronics, VOL. 5, NO. 4, August 26 P 115-1115 [9] D. Zafirakis, J.K. Kaldellis, Autonomous dual-mode CAES systems for maximum wind energy contribution in remote island networks, Energy Conversion and Management 51, Elsevier (21) 215 2161 [1] Stefan Zunft, Christoph Jakiel, Martin Koller and Chris Bullough, "Adiabatic Compressed Air Energy Storage for the Grid Integration of Wind Power ", Sixth International Workshop on Large-scale Integration of wind power and transmission networks for offshore Wind farms, 26-28 October, Delft, The Netherland.