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.     

Stochastic mid-term generation scheduling incorporated with wind power

A challenge now facing system operator is how to schedule optimally the generation units in a wind integrated power system over a one year time horizon considering the effects of wind forecasting and variability; also, regarding the effects of load uncertainty. By the same token, this paper first develops a new formulation for Stochastic Mid-term Generation Scheduling (SMGS). In the formulation, 2m + 1 point estimate method is developed to accurately estimate the output variables of Mid-term Generation Scheduling (MGS) problem. Then, the formulation is combined with adaptive modified gravitational search algorithm and a novel self-adaptive wavelet mutation strategy for the establishment of new robust algorithm for the present problem. It is noteworthy to say that the classical methods considered certain wind information in the deterministic solution of the MGS problem which is not the realistic approach. However, this study improves modeling of wind–thermal system in the MGS problem by considering possible uncertainties when scheduling the generators of power system. The proposed model is capable of taking uncertainty of load and wind into account. The proposed method is applied on two test cases and the numerical results confirmed the efficiency and stability of the proposed algorithm.     

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 control scheme for improving the efficiency of DFIG at low wind speeds with fractional rated converters

This study proposes a scheme for extending the low speed range of operation of a Doubly Fed Induction Generator (DFIG) without down grading the efficiency. Also, only fractional rated converters are employed. The technique involves two operational modes for the generator. When the rotor speed is between 70% and 130% of the synchronous speed, the machine is operated in the normal Doubly Fed Induction Generator (DFIG) mode and when the rotor speed falls below 70%, it is operated in Stator Short Circuited (SSC) mode. The switch-over from the DFIG mode to the SSC mode is carried out at a threshold speed to maintain the efficiency of generator with the same fractional rated converters. The computer simulations on a typical DFIG (250 kW) in Matlab/Simulink environment illustrate that the range of efficiency improvement is from zero to 15%. Further, the experimental results on a 2.3 kW DFIG set up are also illustrated to demonstrate the efficacy of the scheme.     

The effect of converter configurations of HVDC links on sub- and super-synchronous disturbances to turbine units

In this paper, the rotor torque disturbances to turbine–generator units arising from harmonic interactions between converters of a HVDC system are studied. It is shown that a distinct-pulse converter configuration will be a better choice for avoiding sub- or super-synchronous resonance. For an asynchronous HVDC link, the risk of electromechanical resonance could be completely got rid of on either side of the link, no matter what directions the powers flow, if an 18-pulse converter were used on the 60 Hz side and a 12-pulse converter on the 50 Hz side. Such a configuration could still perform well even under the large frequency deviations. Furthermore, it shows that power system type plays a significant role on the possible excitation of resonance and on the probably damaging sections of a turbine–generator unit. Good match of the converter configuration and power system type is significant for a HVDC link to exempt from sub- and super-synchronous resonance.     

Distributed generation planning using differential evolution accounting voltage stability consideration

This paper describes a technique for selection of buses in a sub transmission system for location of distributed generation (DG) and determination of their optimum capacities by minimizing transmission losses. The buses have been selected based on incremental voltage (dV/dP) sensitivities. Line flow constraints have been accounted. Type-3 DG i.e. wind turbine along with induction generator has been considered for the study. Differential evolution (DE) has been used to evaluate the optimum DG capacity and results have been compared with those obtained using bare bones particle swarm optimization (BBPSO) and multi-membered non-recombinative (μ + λ) evolution strategy (MMNRES). The developed algorithms have been implemented on standard 6-bus and 30-bus test systems.     

Model of distribution system total supply capability considering feeder and substation transformer contingencies

This paper proposes a model for calculating the total supply capability (TSC) for distribution system considering both feeder and substation transformer contingencies. Existing models and methods for TSC only consider substation transformer contingencies and ignore feeder contingencies. However, the feeder contingencies occur much more frequently than substation transformer contingencies in practice. Moreover, some operation state fail the feeder contingencies N − 1 verification even they pass the transformer contingencies N − 1 verification. In this paper, a TSC model is firstly proposed in which feeder and transformer N − 1 contingencies are fully considered. This model is designed in feeder level, which means the topology of interconnection among feeders is accurately modeled. Secondly, a supplementary model for load balancing is set up for a better load distribution solution on feeders and transformers at TSC loading. Finally, the method is tested in a test distribution system and a real partial distribution network and the results are verified by the traditional N − 1 simulation.     

基于数值天气预报的风能预测系统

随着世界范围内风电事业的飞速发展,大量大容量风电机组直接接入高压输电网络,是对电网安全运营、电能质量保证的重大挑战,迫切需要使用风能预测系统来对风电机组的发电功率进行预测。提出一种基于数值天气预报以及人工神经网络的混合型风能预测系统。该系统以基于数值天气预报的风速和风向预测数据作为输入数据,以自组织神经网络作为预处理模型,以径向基函数网络模型作为预测模型,并依据特定风电机组或风场的发电量的历史数据对输出数据进行修正。用该预测系统对河北某风电场进行了实例计算,得到可接受的预测结果,表明系统可行。     

A new approach for low voltage ride through capability in DFIG based wind farm

Protection against voltage dips is very important for transient stability in a Doubly Fed Induction Generator (DFIG). Conventional crowbar circuits have been used for protection of DFIGs; however, they may be insufficient in some transient situations. Therefore, the Low Voltage Ride Through (LVRT) capability was enhanced by a Demagnetization Current Controller (DCC) for the purpose of transient analysis. In addition, both stator and rotor circuit electromotive forces were modeled in a DFIG. The performances of the DFIG models with and without the DCC were compared. Modeling was carried out in a MATLAB/SIMULINK environment. A comparison of system behaviors was made between three-phase faults with and without a stator–rotor dynamic. Parameters for the DFIG including output voltage, speed, electrical torque variations and d–q axis rotor–stator current variations in addition to a 34.5 kV bus voltage were examined. It was found that in the DFIG model the system became stable in a short time when using the DCC.     

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.     

Particle swarm optimization algorithm for capacitor allocation problem in distribution systems with wind turbine generators

This paper aims at adopting the Particle Swarm Optimization (PSO) technique to find the near-optimal solutions for the capacitor allocation problem in distribution systems for the modified IEEE 16-bus distribution system connected to wind energy generation based on a cost function. The proper allocation and the optimized number of capacitors have led to adequate power losses reduction and voltage profile enhancement. Because of the wind power generation variations due to the nature of wind speed intermittency and the lack of reactive power compensation, the problem under study have been presented involving a nonlinear fitness function. In order to solve it, the corresponding mathematical tools have to be used. The formulated fitness cost function has consisted of four terms: cost of real power loss, capacitor installation cost, voltage constraint penalty, and capacitor constraint penalty. PSO technique has been used to obtain the near-optimum solution to the proposed problem. Simulation results demonstrate the efficiency of the proposed fitness cost function when applied to the system under study. Furthermore, the application of PSO to the modified IEEE 16-bus system has shown better results in terms of power losses cost and voltage profile enhancement compared to Genetic Algorithm (GA). In order to verify the successful adaptation of PSO toward attaining adequate near-optimal capacitor allocations in distribution systems, this metaheuristic technique has been employed to the large-scale IEEE 30-bus system. The proposed PSO technique has provided adequate results while modifying the objective function and constraints to include the power factor and transmission line capacities for normal and contingency (N-1) operating conditions.     

小型风力发电机偏航控制系统实验研究

为提高风力发电机发电效率,提出一种基于PLC控制的小型风力发电机偏航控制系统方案,搭建以PLC为控制器,风速风向传感器为检测装置,步进电机为偏航驱动装置的实验平台,重点介绍了基于modbus总线通信的风速风向数据采集、基于PLS指令编程的偏航电机控制和基于MCGS组态软件的上位机监控。经系统测试与实验验证表明,数据采集系统能够实时显示现场风速风向数据,偏航电机能够根据风向的变化而自动迎风,满足了控制要求,取得了良好的控制效果,具有成本低、稳定性好的优点。系统的应用为提高风能利用率提供了保障,为小型风力发电机偏航电机控制提供了参考     

Maclaurin–Newton algorithms in 132 kV subtransmission security simulations

This paper examines how applicable approximate Jacobian inversions are when implemented in the security analysis simulations of 132 kV power subtransmission. The complete Scottish 400/275/132 kV power transmission network was simulated, including the 132 kV subtransmission network with its high r/x ratios. Both the coupled and decoupled Maclaurin–Newton load flow algorithms were tested. It was proved that high r/x ratios found in the 132 kV level, five times higher than in 400/275 kV, have an important influence on convergence and accuracy of the inversion Jacobian load flow algorithms. It was found that the decoupled inversion load flow was applicable for 132 kV, it converged regularly, but had worse convergence and accuracy characteristics, compared to 400/275 kV applications, while the coupled inversion load flow was not applicable at all for 132 kV, it always diverged.     

Improving power quality of wind energy conversion system with unconventional power electronic interface

The increasing interest to utilize wind energy as a power source prompted more researches to be dedicated to the unconventional integration of this power source into the current grid. In this paper, one avenue to achieve this efficient utilization, through the use of integrated wind energy conversion system (WECS) using doubly fed induction generator (DFIG) is presented. Wind grid integration brings the problems of voltage fluctuation and harmonic distortion. This paper presents an Unconventional Power Electronic Interface (UPEI) to reduce the total harmonic distortion (THD) and enhance power quality during disturbances. The models used in the paper includes a pitch-angled controlled wind turbine model, a DFIG model, power system model and an UPEI having controlled converters. A phase to phase fault is simulated on 132 kV bus and the measured results obtained from grid connection of the wind generation system are presented. The results have demonstrated the ability of UPEI to regulate pitch angle, VAR and to reduce THD. The proposed system increases the effectiveness of the utilization of wind energy.     

Effect of varying concentration and temperature on steady and dynamic parameters of low concentration photovoltaic energy system

Low-concentration photovoltaic (LCPV) system has huge potential for further cost reduction of solar photovoltaic (PV) power as compared to flat panel PV. The dependence of steady state and dynamic parameters on concentration and temperature is crucial to extract maximum power from solar photovoltaic system. This article aims to present the effect of varying concentration and temperature on steady state and dynamic parameters of LCPV system under actual test conditions (ATC). The rate of change in I_SC with solar irradiation i.e., dI_SC/dG is found as 0.25 A/W assuming ≈±1 °C change in module temperature. The effect of temperature on inherent material properties responsible for photo-conversion efficiency is studied using impedance spectroscopy technique. A linear response of series resistance of LCPV module is observed with respect to change in module temperature, i.e. dR_S/dT from 297 to 333 K is in the range of 1.15–1.20 Ω with a rate of 1 mΩ/K. From real-time analysis of LCPV system open-circuit voltage found decreasing from 21 to 20.6 V with temperature coefficient of voltage ≈−0.061 V/K. The dynamic resistance has a positive coefficient of module temperature i.e., dr_d/dT given by 0.49 Ω/K.     

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.     

基于微处理器的风力发电机综合优化控制策略

由于风能能量密度低、随机性和不稳定性的特点,给风力发电带来发电效率低、电能不稳定等问题。提出使用微处理器控制,集偏航系统和变桨距控制系统为一体,共同实现风机的优化控制。将风向标测得的风向和风速信息输入给CPU,通过对风能及风机性能的综合分析和决策,由微控制器发出各项操作指令。当风速小于额定风速时,启动偏航控制系统,始终保证风机获得最大风能;当风速大于额定风速时,同时启动偏航系统和变桨距控制系统,根据风速大小调节桨距角,保证风机的输出功率不变;当风速过大时,采用紧急停机策略,调节桨距角使风叶与风向方向平行,以保护风机。研究结果表明,不仅实现了风能的最大利用,还提高了输出电能的稳定性,保证了分布式电源并网的电能质量,控制过程简单、过渡平缓,具有良好的应用前景。     

Methods used for evaluation of actual power generating thermal cycles and comparing them

In this study, thermodynamic optimization criteria used for assessing thermal engines are investigated and compared. The Purpose of this is to determine the most advantageous criteria. An irreversible Carnot cycle is analyzed by using five different methods and results are compared. According to calculations, the ecological function criterion (ECF) is defined as the most convenient optimization method. Although, its work output is less than the maximum work criteria and maximum available work (MAW), it has advantageous in terms of entropy generation and first law efficiency. In addition, ecological coefficient of performance (ECOP) and exergetic performance criteria (EPC) values provide minimum entropy generation and maximum efficiency at their maximum, however, their work output is very small. ECF obtains its maximum values at x = 0.488 (377.175 kW) for endoreversible cycle and at x = 0.477 (329.812 kW) for irreversible cycle. For these reasons, ECF is suggested as the best optimization criteria.     

Assessing the relevance of load profiling information in electrical load forecasting based on neural network models

The article is focused on evaluating the relevance of load profiling information in electrical load forecasting, using neural networks as the forecasting methodology. Different models, with and without load profiling information, were tested and compared, and, the importance of the different inputs was investigated, using the concept of partial derivatives to understand the relevance of including this type of data in the input space. The paper presents a model for the day ahead load profile prediction for an area with many consumers. The results were analyzed with a simulated load diagram (to illustrate a distribution feeder) and also with a specific output of a 60/15 kV real distribution substation that feeds a small town. The adopted methodology was successfully implemented and resulted in reducing the mean absolute percentage error between 0.5% and 16%, depending on the nature of the concurrent methodology used and the forecasted day, with a major benefit regarding the treatment of special days (holidays). The results illustrate an interesting potential for the use of the load profiling information in forecasting.     

New pole tip shapes mitigating torque ripple in short pitched and fully pitched switched reluctance motors

High torque ripple is one of the major disadvantages of switched reluctance motor (SRM). Although there are several publications in the literature addressing the full or partial solution to the problem for conventional SRM, no publication exists for the torque ripple reduction of recently emerging fully pitched SRM. This paper deals with finding best dimension set for a particular stator and rotor pole tip shape aiming to reduce torque ripple in both short pitched and fully pitched SRMs. Five new stator and rotor pole tip structures have been investigated and compared with conventional pole tip. Analyses have been performed with the finite element (FE) models of 6/43-phase short pitched and fully pitched SRM with unipolar excitation. With the proposed pole tips, torque ripple is reduced by 24.1% in short pitched SRM for 10 A phase current and by 22.6% in fully pitched SRM for 5.59 A phase current.