Power and energy management of grid/PEMFC/battery/supercapacitor hybrid power sources for UPS applications

This paper presents a hybrid power and energy source supplied by a proton exchange membrane fuel cell (PEMFC) as the main power source in an uninterruptible power supply (UPS) system. To prevent the PEMFC from fuel starvation and degradation and realize their seamless linking in the hybrid UPS system, the power and energy are balanced by the battery and/or supercapacitor (SC) as two alternative auxiliary power sources. Based on the modeling and sizing of hybrid power and energy components, the power and energy management strategies and efficiency measurements of four operating modes in UPS system are proposed. To evaluate the proposed strategies, an experimental setup is implemented by a data acquisition system, a PEMFC generating system, and a UPS system including AC/DC rectifier, DC/AC inverter, DC/DC converter, AC/DC recharger and its intelligent control unit. Experimental results with the characteristics of a 300 W self-humidified air-breathing of PEMFC, 3-cell 12 V/5 Ah of batteries, and two 16-cell 120 F/2.7 V of SCs in parallel corroborate the excellent management strategies in the four operating modes of UPS system, which provides the basis for the optimal design of the UPS system with hybrid PEMFC/battery/SC power sources.     

Nonlinear intelligent DC grid stabilization for fuel cell vehicle applications with a supercapacitor storage device

This paper presents an intelligent DC link control using a fuzzy logic controller based on the differential flatness control theory for hybrid vehicle applications supplied by a fuel cell (FC) (main source) and a supercapacitor (auxiliary source). The energy in the system is balanced by dc bus energy stabilization (or indirect voltage regulation). A supercapacitor module functions by supplying energy to regulate the dc bus energy. The FC, as a slow dynamic source in this system, supplies energy to the supercapacitor module to maintain its charge. The FC converter combines four-phase parallel boost converters with interleaving, and the supercapacitor converter employs four-phase parallel bidirectional converters with interleaving. These two converters are called a multi-segment converter for high power applications. Because the model of the power switching converters is nonlinear, it is preferable to apply model-based nonlinear control strategies that directly compensate for the nonlinearity of the system without requiring a linear approximation. Using the intelligent fuzzy control law based on the flatness property, we propose straightforward solutions to hybrid energy management and to the dynamic and regulation problems. To validate the proposed method, a hardware system is developed with analogue circuits, and a numerical calculation is generated with a dSPACE controller DS1104. Experimental results for a small-scale power plant (a polymer electrolyte membrane FC (PEMFC) of 1200 W and 46 A with a supercapacitor module of 100 F, 500 A, and 32 V) in the laboratory corroborate the excellent performance of this control scheme during vehicle motor drive cycles.     

Performance investigation of linear and nonlinear controls for a fuel cell/supercapacitor hybrid power plant

In this paper, linear proportional–integral (PI) and nonlinear flatness-based controllers for dc link stabilization for fuel cell/supercapacitor hybrid power plants are compared. For high power applications, 4-phase parallel boost converters are implemented with a switching interleaving technique for a fuel cell (FC) converter, and 4-phase parallel bidirectional converters are implemented with a switching interleaving technique for a supercapacitor converter in the laboratory. As controls, mathematical models (reduced-order models) of the FC converter and the supercapacitor converter are given. The prototype small-scale power plant studied is composed of a PEMFC system (the Nexa Ballard FC power generator: 1.2 kW, 46 A) and a supercapacitor module (100 F, 32 V, based on Maxwell Technologies Company). Simulation (by Matlab/Simulink) and experimental results demonstrate that the nonlinear differential flatness-based control provides improved dc bus stabilization relative to a classical linear PI control method.     

Optimal design of a robust discrete parallel FP + FI + FD controller for the Automatic Voltage Regulator system

The purpose of this paper is to design a good tracking controller for the generator Automatic Voltage Regulator (AVR) system. A fuzzy logic-based controller that is called Fuzzy P + Fuzzy I + Fuzzy D (FP + FI + FD) controller has been designed optimally and applied to AVR system. In the proposed method, optimal tuning of controller parameters is very important to achieve the desired level of robust performance. Thus, a hybrid of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) (HGAPSO) technique has been used to find a better fuzzy system control. The motivation for using this hybrid method is to increase disturbance rejection effort, reduce fuzzy system efforts and take large parametric uncertainties into account. The developed FP + FI + FD control strategy leads to a flexible controller with simple structure that is easy to implement. The simulation results have been compared with the conventional Proportional–Integral–Derivative (PID) and fuzzy PID controllers. Three cases of simulation have been performed, case 1: comparing the tracking capability of the controllers, case 2: comparing the disturbance rejection capability of the controller and case 3: evaluating the performance of the controllers assuming that amplifier and exciter system parameters have 50% uncertainty. The simulation results shows that the proposed parallel FP + FI + FD controller has good performance from the perspective of overshoot/undershoot, settling time, and rise time in comparison with both conventional and fuzzy PID controllers.     

Direct power control of a multilevel inverter based active power filter

A cascaded H-bridge multilevel inverter based active power filter with a novel direct power control is proposed in this paper. It can be directly connected to medium/high voltage power line without using the bulky transformer or passive filter. Due to the limited switching frequency (typically below 1 kHz) of high-power solid-state devices (GTO/IGCT), multiple synchronous/stationary reference frame current controllers are reviewed and derived. Based on this, a novel current controller is proposed for harmonic current elimination and system power factor compensation. Furthermore, a synchronous/stationary hybrid structure can be derived with fundamental de-coupling control. The instantaneous reactive power theory and synchronous reference frame based control are compared based on mathematical models. A direct power control concept is then derived and proposed. It is equivalent as the hybrid synchronous/stationary frame current controller, but has a simpler implementation. It has clear physical meaning and can be considered as a simplified version of the hybrid frame current controller. Simulations on a 4160 V/1.2 MVA system and experimental results on a 208 V/6 kVA laboratory prototype are presented to validate the proposed active power filter design.     

Congestion management solution under secure bilateral transactions in hybrid electricity market for hydro-thermal combination

The deregulation of power system has created an environment of competitiveness among different market players and the transmission lines are forced to operate near to their thermal or stability limits. It is a challenge with System Operators (SO) to ensure a secure and reliable transmission of power under these conditions. This paper proposes a rescheduling based congestion management strategy in hybrid (pool + bilateral) electricity market structure for a combination of hydro and thermal units. The proposed congestion management problem has been formulated as mixed integer nonlinear programming (MINLP) problem with an objective to minimize the congestion management cost by suitably rescheduling the hydro and thermal units based on their up and down generation cost bids. The hydro units having lowest operational cost and fast startup time have been used to alleviate the congestion by considering non-concave piecewise linear performance curves for them. The secure bilateral transactions have been ensured while rescheduling of the generators for alleviating the congestion. The performance of the proposed model has been demonstrated by solving the congestion management problem on modified IEEE-24 bus system.     

Control of cyclic fluctuations in an independent microgrid by an SOFC triple combined cycle inertia system

Technology was investigated to control cyclic fluctuations in an independent microgrid powered with unstable renewable energy by use of a solid oxide fuel cell (SOFC, 1 MW) in a triple combined cycle (SOFC-TCC) that included a gas turbine (G/T, 0.8 MW) and a steam turbine (S/T, 0.2 MW). A large-scale solar power system (0.8 MW) and a wind farm (0.8 MW) were interconnected with the electrical power network through an inverter. The cyclic fluctuations ingredient of the network was controlled by a suitably designed inertia system and by governor-free control of the G/T and S/T. The SOFC-TCC’s control block diagram was submitted to MATLAB/Simulink R 2013a, and the deviation of electrical power and frequency in the independent microgrid caused by the SOFC-TCC and renewable energy interconnection was clarified. As a result, a range of suitable inertial constants for G/T and S/T and the electrical output characteristics were determined. Selecting a small inertial constant for the simulation resulted in a large frequency deviation of G/T and S/T, with frequency stabilized for a short time. On the other hand, selecting a large inertial constant resulted in a controlled frequency deviation, although the unstable frequency of the power grid continued for a long time.     

A performance comparison of a nonlinear and a linear control for grid connected PMSG wind energy conversion system

With the increased penetration of wind energy on modern power systems all over the world, the Wind Farm Systems (WFS) are today required to participate actively in electric network operation by an appropriate generation control strategy. This paper presents a comparative study of two control strategies for wind farm based on Permanent Magnet Synchronous Generator (PMSG) and interconnected to the distribution network. The 4 MW wind farm consists of 2 PMSGs based on 2 MW generators connected to a common DC-bus system. Each PMSG of the WFS is connected to the DC-bus through a rectifier, but the DC-bus is connected to the grid through only one inverter system. The proposed control laws are based on a sliding mode algorithm and classical Proportional Integral (PI) controllers to regulate both generator and grid-side converters. The control strategy combines a pitch control scheme and Maximum Power Point Tracking (MPPT) to maximize the total generated power of WFS. Furthermore, the aim of the control strategy is to maximize the extracted power with the lowest possible impact in the power network voltage and frequency for fault conditions as well as for normal working conditions. Finally, simulation results with Matlab/Simulink environment confirm that the proposed strategy has excellent performance.     

Multi-objective optimization operation with corrective control actions for meshed AC/DC grids including multi-terminal VSC-HVDC

This paper presents a multi-objective optimal operation of meshed AC/DC power grids including multi-terminal voltage-source-converter-based high-voltage direct current (VSC-MTDC) systems. The proposed approach is modeled as a corrective security-constrained optimal power flow (CSC-OPF) problem, with the minimization of both the operation cost and power loss as the objectives. Moreover, it provides a cost-effective solution to assist in decision-making, and improves the system security during operation. The N − 1 contingency security criterion is enforced for both AC and DC transmission networks, and corrective control is used to eliminate or alleviate post-contingency security violations. The corrective control actions used in this paper include not only secure operation control actions, but also economical post-contingency corrective control of the multi-terminal VSC-HVDC. To increase the computation speed, a contingency screening technique is applied to CSC-OPF by efficiently selecting the most severe case of the N − 1 contingency, as obtained using a voltage security index (VSI). The proposed approach uses the non-dominated sorting genetic algorithm (NSGA-II) to find multi-objective OPF solutions by checking the post-contingency state feasibility while taking into account post-contingency corrective actions. Simulation results confirm the validity and effectiveness of this approach.     

Online energy management strategy of a hybrid fuel cell/battery/ultracapacitor vehicular power system

A hybrid power system based on a fuel cell (FC) and an energy storage system appears to be very promising for satisfying the high energy and high power requirements of automotive applications in which the power demand is impulsive rather than constant. This paper deals with the use of a hybrid energy storage system with the battery (BAT)/ultracapacitor (UC) as ancillary power source in FC electric vehicles. The energy management strategy (EMS) is one of the most important issues for the efficiency and performance of such systems. The designed EMS uses a splitting method, allowing a natural frequency decomposition of the power demands. It takes into account the slow dynamics of FC and the state of charge of the UC and BAT. A simulation is conducted using MATLAB/SIMULINK software in order to verify the effectiveness of the proposed control strategy. It confirms the performance of the control method and also demonstrates the robustness and stability of the control strategy with good tracking response (transient performance), low overshoot, zero steady‐state error, and control flexibility during a power demand cycle. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Automatic generation control of a multi-area system using ant lion optimizer algorithm based PID plus second order derivative controller

This article presents the automatic generation control of an unequal three area thermal system. Single stage reheat turbines and generation rate constraints of 3%/min are considered in each control area. Controllers such as Integral (I), Proportional – Integral (PI), Proportional – Integral – Derivative (PID), and Proportional – Integral – Derivative Plus Second Order Derivative (PID + DD) are treated as secondary controllers separately. A nature inspired optimization technique called Ant Lion Optimizer (ALO) algorithm is used for simultaneous optimization of the controller gains. Comparison of dynamic responses of frequencies and tie line powers corresponding to ALO optimized I, PI, PID and PID + DD controller reveal the better performance of PID + DD controller in terms of lesser settling time, peak overshoots as well as reduced oscillations. Robustness of the optimum gains of best controller obtained at nominal conditions is evaluated using sensitivity analysis. Analysis exposed that the optimum PID + DD controller gains obtained at nominal are robust and not necessary to reset again for changes in loading, parameter like inertia constant (H), size and position of disturbance. Furthermore, the performance of PID + DD controller is found better as compared to PID controller against random loading pattern condition.     

Experimental analysis of a solar PV/diesel hybrid system without storage: Focus on its dynamic behavior

Integration of solar photovoltaic systems with diesel generators for the electrification of remote and rural areas would assist in expanding the electricity access in the sub-Saharan Africa region. In fact, countries of this region are well endowed in solar resource: their mean daily solar radiation exceeds 5.5 kWh/m²/day. They are, therefore, good locations for PV systems. This paper deals with an experimental study of the dynamic behavior of a hybrid system prototype (based on “flexy-energy” concept) set up at Kamboinsé, located at 15 km far from Ouagadougou (12, 22° N and 1, 31° W) in Burkina Faso. The prototype is composed of a 2.85 kWp PV array, a 3.3 kW single phase inverter and a diesel generator rated at 9.2 kW. Two resistive load banks of about 4 kW each are used to simulate the load profiles. Experimental results show that the PV generation leads the distribution feeder to shift toward higher voltages. The voltage rise is exacerbated when the PV generation is at its highest and the demand at its lowest. Care should then be taken to ensure that for a hybrid PV/diesel system, the PV rated power connected to each phase of the diesel generator is as equal as possible. The present study also points out that “well designed” inverters generate very small voltage harmonics and current distortions, even when high PV penetration systems are considered.     

A novel wavelet transform based voltage sag/swell detection algorithm

This paper proposes a novel sag/swell detection algorithm based on wavelet transform (WT) operating even in the presence of flicker and harmonics in source voltage. The developed algorithm is the hybrid of Daubechies wavelets of order 2 (db2) and order 8 (db8) to detect voltage sag/swell with and without positive/negative phase jumps. The hybrid detection algorithm can detect the start and end times of voltage sag/swell with and without phase jumps within 0.5 ms and 1.15 ms, respectively. The performance of the proposed voltage sag/swell detection method is compared with the results of dq-transformation, Fast Fourier Transform (FFT) and Enhanced Phase Locked Loop (EPLL) based voltage sag/swell detection methods. The good robustness and faster processing time to detect balanced and unbalanced voltage sag/swell are provided using proposed method. With the proposed hybrid detection algorithm consisting of db2 and db8 wavelet functions, a robust sag/swell detection is achieved which can give precise and quick response. The performance of proposed hybrid algorithm is validated and confirmed through simulation studies using the PSCAD/EMTDC analysis program.     

Rank-constrained semidefinite program for unit commitment

Unit Commitment (UC) is a combinatorial optimization problem that can be posed as minimizing a quadratic objective function under quadratic constraints. This paper presents a solution to UC based on Semidefinite Programming (SDP). In particular, it shows that an approximate solution can be obtained by using Shor’s semidefinite relaxation scheme together with a rank constraint enforced via convex iteration. The approximate solution has the majority of Boolean variables set by the SDP solver to either 0 or 1; it is modified by a simple heuristic to yield a feasible schedule. The proposed SDP formulation employs 3 × 3 semidefinite matrices and therefore requires computational effort that increases only moderately with problem size. Numerical results on test systems with up to 100 units dispatched over a period of 24 h show that the method is robust and produces schedules that are comparable with those from previous techniques.     

Robust predictive dual-loop control method based on Lyapunov function stability and energy equilibrium though double-core processors for active power filter

In this paper, a robust predictive dual-loop control method based on Lyapunov function stability and energy equilibrium for active power filter (APF) is proposed to improve the anti-interference performance and self-adaptive capability of system. The proposed control method mainly includes robust predictive current control based on Lyapunov function stability (RPCC-LFS) in the inner current loop and energy equilibrium proportional-integrator (PI) control in the outer dc-link voltage loop. The RPCC-LFS is proposed to enhance self-adaptive capability when the output filter inductors vary, speed up the dynamic response, and improve the tracking accuracy when the loads fluctuate. The energy equilibrium PI controller is proposed to maintain the dc-link voltage stable and suppress the transient impulse. The stability and dynamic response of the proposed control system are analyzed in detail, and the proper control parameters are selected. A specific hardware and software design program based on double-core processors DSP + FPGA is thoroughly given out. Finally, the comparative simulations and experiments verified the validity of the proposed method.     

Study on FRT compliance of VSC-HVDC connected offshore wind plants during AC faults including requirements for the negative sequence current control

In this paper three new control modules are introduced for offshore wind power plants with VSC-HVDC transmission. The goal is to enhance the Fault Ride Thought (FRT) capability of the HVDC system and the connected offshore wind power plant during balanced and unbalanced AC faults. Firstly, a positive-sequence-voltage-dependent (PSVD) active current reduction control loop is introduced to the offshore wind turbines. The method enhances the performance of the offshore AC voltage drop FRT compliance strategy. Secondly, an adaptive current limiting control strategy which operates simultaneously on the positive and the negative sequence current is discussed. It enables negative sequence current injection, while at the same time respecting the maximum fault current capacity of the HVDC converter station. Finally, a state machine is proposed for the VSC-HVDC system and for the offshore wind turbines respectively. It coordinates the fault and the post-fault response during balanced as well as unbalanced faults, ensuring a smooth shift from the normal operating point towards the fault and the post-fault period. The test system consists of a two level VSC-HVDC link, rated at ±250 kV, connecting an offshore wind power plant with 700 MW generation capacity. Simulation results with a detailed EMT type model in PSCAD/EMTDC environment are presented.     

纯电动汽车蓄电池-超级电容复合能源系统研究

为弥补现有纯电动汽车单一能源的不足,采用蓄电池为主超级电容为辅的复合能源系统,通过对车辆动力性、续驶里程、制动能量回收等约束的分析,对复合能源进行参数匹配;考虑超级电容电压与其容量和效率的关系,将超级电容电压、蓄电池SOC和车辆需求功率作为输入量制定模糊控制策略;为避免一次行驶路况结论的片面性,在UDDS路况进行多次循环仿真直至蓄电池放电结束。结果表明,所采用的蓄电池——超级电容复合能源系统参数匹配方法和模糊控制策略能够很好的满足纯电动汽车在完整放电行驶中对能源系统能量和功率的需求,能够有效回收利用再生制动能量,提高能源系统效率,提高车辆动力性能和经济性能,起到延长蓄电池使用寿命的作用。     

Pole-zero assignment adaptive stabiliser

This paper presents a new adaptive power system stabiliser able to provide acceptable damping over a wide range of operating points. The control strategy is based on a new adaptive technique named Pole-Zero Assignment Controller (PZAC) in which a particular power system transfer function (G_d(s) = Δδ/ΔP_m) is modified to a standard form based on an explicit system identification. Controller design is mainly based on continuous-time system because of using the delta operator rather than the more usual shift operator. Simulation studies performed on a multimachine model are presented. Results clearly show the benefits of the proposed adaptive controller for stability enhancement of a power system, especially where there are large changes in operating point.     

Plug-In并联式混合动力汽车实时优化能量管理策略

能量管理策略是混合动力汽车的核心技术之一,其品质直接影响车辆的动力性、经济性和排放性能。首先制定了基于确定性规则的Plug-In并联式混合动力汽车能量管理策略;然后,为了提高车辆的燃油经济性,设计了电池能量观测单元,并对等效燃油消耗最小策略进行改进,提出了适用于Plug-In混合动力汽车的实时优化能量管理策略。研究结果表明,该能量管理策略显著提高了Plug-In并联式混合动力汽车的燃油经济性。     

Optimization models based on GM (1, 1) and seasonal fluctuation for electricity demand forecasting

In this paper, a novel combined approach which combines the first-order one-variable gray differential equation (GM (1, 1)) model derived from gray system theory and seasonal fluctuation from time series method (SFGM (1, 1)) is proposed. This combined model not only takes advantage of the high predictable power of GM (1, 1) model but also the prediction power of time series method. To improve the forecasting accuracy, an adaptive parameter learning mechanism is applied to SFGM (1, 1) model to develop a new model named APL-SFGM (1, 1). As an example, the statistical electricity demand data from 2002 to 2011 sampled from South Australia of Australia are used to validate the effectiveness of the two proposed models. Simulation and graphic results indicated that both of two proposed models achieve better performance than the original GM (1, 1) model. In addition, the APL-SFGM (1, 1) model, which is actually an adaptive adjustment model, obtains a higher forecasting accuracy as compared to the SFGM (1, 1) model.