System Load Changes Research Articles

Design and evaluation of a fuzzy cloud controller

The management of cloud deployments is still largely the responsibility of system administrators. Introducing autonomy in cloud management would entail, amongst other things, the ability for automated cloud manager systems to scale up or down the number of deployed virtual machines, and/or deploy machines of different types to meet performance and other SLAs. However, the workload of cloud deployments can exhibit high variability over short time periods. This creates the necessity of introducing autonomic behaviour in the resource management function of the cloud deployment that makes decisions in real time so to optimise cost and/or performance. In this paper, we employ fuzzy logic to design a cloud controller whose scaling policies emulate the reasoning of human cloud operators, and take into account the current system load and the system load rate of change. The fuzzy controller's performance is compared and evaluated against Amazon's AWS auto-scaling policies. Results indicate the ability of the proposed fuzzy controller to adapt better to changing workloads by provisioning virtual machines appropriately to match the rate of system load change. Additionally, fuzzy rules are more intuitive than auto-scaling policies and thus easier to understand and modify by human users.

Automatic generation control of an unequal four‐area thermal system using biogeography‐based optimised 3DOF‐PID controller

This study presents the automatic generation control of an unequal four-area thermal system with appropriate generation rate constraint and governor dead band (GDB). Performances of several classical controllers, such as single degree-of-freedom proportional–integral–derivative (PID), two degree-of-freedom PID (2DOF-PID) and three degree-of-freedom PID (3DOF-PID) as secondary controllers are evaluated separately in the system. An attempt is made to apply the successful evolutionary optimisation technique named as biogeography-based optimisation technique for simultaneous optimisation of several variables, such as controller gains, setpoint weights and so on. Comparison of dynamic responses corresponding to PID, 2DOF-PID and 3DOF-PID reveals that 3DOF-PID controller outperforms the others. Sensitivity analysis reveals that the optimum gains and other parameters of the optimal controller obtained at nominal conditions are robust and need not be reset for wide changes in system condition like system loading, system parameters such as inertia constant (H), synchronising coefficient (Tij ) and GDB. The performance of 3DOF-PID controller is also studied with different step-load perturbations (SLPs) and random-load perturbations (RLPs). Analysis proves that 3DOF-PID controller performs better than 2DOF-PID at different SLPs and RLPs.

AGC of dish‐Stirling solar thermal integrated thermal system with biogeography based optimised three degree of freedom PID controller

The present study emphasises the application of dish-Stirling solar thermal system (DSTS) in automatic generation control (AGC) of an unequal two area thermal system. The thermal systems are equipped with single reheat turbine, generation rate constraint, and governor dead band. The system dynamics with and without DSTS are tested for integral, proportional integral, proportional integral derivative, and three degree of freedom proportional integral derivative (3DOF-PID) as secondary controllers. The simultaneous optimisation of the controller parameters for each controller is done with biogeography based optimisation (BBO) technique. The 3DOF-PID controllers for the system having DSTS outperform the other controllers in terms of magnitude of oscillation, peak deviation, and settling time in system dynamic responses. The same is validated with random load perturbation. Sensitivity analysis proves that BBO optimised 3DOF-PID controller parameters obtained at nominal conditions are healthy enough. These optimised 3DOF-PID controller parameters are not necessarily needed to optimise for wide changes in system loading, and inertia constant H; step load perturbation (SLP) in all areas and higher SLP in area1. Integration of DSTS for AGC of thermal system is safely attributed.

Flower Pollination Algorithm Optimized PI-PD Cascade Controller in Automatic Generation Control of a Multi-area Power System

This article presents automatic generation control (AGC) of an interconnected four area thermal system. The control areas are provided with single reheat turbine and generation rate constraints of 3%/min. A maiden attempt has been made to apply a Proportional integral-Proportional derivative (PI-PD) cascade controller in AGC. Controller gains are optimized simultaneously using Flower Pollination Algorithm (FPA), a recent evolutionary computational technique. Performance of classical controllers such as Integral (I), Proportional Integral (PI) and Proportional Integral Derivative (PID) controller are investigated and compared with PI-PD cascade controller. Investigations reveal that in this comparison PI-PD cascade controller provides much better response than others. The performances comparison of several objective functions are evaluated and explored that integral squared error is better than others for the system with the PI-PD cascade controller. Sensitivity analysis reveals that the FPA optimized PI-PD cascade controller parameters obtained at nominal condition of loading, size, position of disturbance and system parameter such as inertia constant, H are robust and need not be reset with wide changes in system loading, size, position of disturbance and system parameters. The system dynamic performances are studied with 1% step load perturbation, random load in Area 1.

Hybrid Fuzzy Controller Based Frequency Regulation in Restructured Power System

This paper discusses the implementation of Load Frequency Control (LFC) in restructured power system using Hybrid Fuzzy controller. The formulation of LFC in open energy market is much more challenging; hence it needs an intelligent controller to adapt the changes imposed by the dynamics of restructured bilateral contracts. Fuzzy Logic Control deals well with uncertainty and indistinctness while Particle Swarm Optimization (PSO) is a well-known optimization tool. Abovementioned techniques are combined and called as Hybrid Fuzzy to improve the dynamic performance of the system. Frequency control of restructured system has been achieved by automatic Membership Function (MF) tuned fuzzy logic controller. The parameters defining membership function has been tuned and updated from time to time using Particle Swarm Optimization (PSO). The robustness of the proposed hybrid fuzzy controller has been compared with conventional fuzzy logic controller using performance measures like overshoot and settling time following a step load perturbation. The motivation for using membership function tuning using PSO is to show the behavior of the controller for a wide range of system parameters and load changes. Error based analysis with parametric uncertainties and load changes is tested on a two-area restructured power system.

Integral Performance Criteria Based Analysis of Load Frequency Control in Bilateral Based Market

Performance index based analysis is made to examine and highlight the effective application of Particle Swarm Optimization (PSO) to optimize the Proportional Integral gains for Load Frequency Control (LFC) in a restructured power system that operates under Bilateral based policy scheme. Various Integral Performance Criteria measures are taken as fitness function in PSO and are compared using overshoot, settling time and frequency and tie-line power deviation following a step load perturbation (SLP). The motivation for using different fitness technique in PSO is to show the behavior of the controller for a wide range of system parameters and load changes. Error based analysis with parametric uncertainties and load changes are tested on a two-area restructured power system. The results of the proposed PSO based controller show the better performance compared to the classical Ziegler-Nichols (Z-N) tuned PI and Fuzzy Rule based PI controller.

Load frequency controller design via BAT algorithm for nonlinear interconnected power system

Abstract BAT algorithm is proposed in this paper for optimal tuning of PI controllers for load frequency controller (LFC) design. The problem of robustly tuning of PI based LFC design is formulated as an optimization problem according to time domain objective function that is solved by BAT algorithm to find the most optimistic results. To demonstrate the effectiveness of the proposed method, a two-area interconnected power system is considered as a tested system. To ensure robustness of the proposed control strategy to stabilize frequency oscillations, the design process takes a wide range of operating conditions and system nonlinearities into account. The simulation results are given to detect the superiority of BAT algorithm over Simulated Annealing (SA) in tuning PI controller parameters through different indices. Results evaluation show that the proposed algorithm achieves good robust performance for wide range of system parameters and load changes compared with SA.

Distinct growth of the nasomaxillary complex in Au. sediba.

Studies of facial ontogeny in immature hominins have contributed significantly to understanding the evolution of human growth and development. The recently discovered hominin species Autralopithecus sediba is represented by a well-preserved and nearly complete facial skeleton of a juvenile (MH1) which shows a derived facial anatomy. We examined MH1 using high radiation synchrotron to interpret features of the oronasal complex pertinent to facial growth. We also analyzed bone surface microanatomy to identify and map fields of bone deposition and bone resorption, which affect the development of the facial skeleton. The oronasal anatomy (premaxilla-palate-vomer architecture) is similar to other Australopithecus species. However surface growth remodeling of the midface (nasomaxillary complex) differs markedly from Australopithecus, Paranthropus, early Homo and from KNM-WT 15000 (H. erectus/ergaster) showing a distinct distribution of vertically disposed alternating depository and resorptive fields in relation to anterior dental roots and the subnasal region. The ontogeny of the MH1 midface superficially resembles some H. sapiens in the distribution of remodeling fields. The facial growth of MH1 appears unique among early hominins representing an evolutionary modification in facial ontogeny at 1.9 my, or to changes in masticatory system loading associated with diet.

Application of Multivariable Regression Model for SOFC Stack Temperature Estimation in System Environment

AbstractThe applicability of multivariable linear regression (MLR) models to estimate the maximum temperature inside a SOFC stack is investigated experimentally. The experiments were carried out with a complete 10 kW SOFC system. The behavior of the maximum temperature measured inside a SOFC stack with respect to four independent input variables (stack current, air flow, air inlet temperature and fuel flow) is examined following the design of experiments methodology, and MLR models are created based on the retrieved data. The practical feasibility of the MLR estimate is investigated experimentally with the 10 kW system by evaluating the accuracy of the estimate in two test cases: (i) a system load change where the stack temperature is regulated by a closed‐loop controller using the MLR estimate and (ii) during operator‐imposed disturbances in the fuel system (a variation in the methane conversion in the fuel pre‐reformer). Finally, the performance of the MLR estimate is evaluated with another, 64‐cell stack operated at higher current density.

Evaluating the Underwater Compressed Air Energy Storage Potential in the Gulf of Maine

The United States has recognized the need to offset current and future electrical demand with clean, renewable generation. However, plans for integration of high penetration levels of often variable and uncertain renewable energy, like offshore wind, pose significant challenges to utility gird operators and system planners. The intermittent nature of renewables can result in dramatic changes in system load, indicating a need for large-scale energy storage technologies that would allow renewables to be dispatched when needed. Among different storage technologies, pumped hydro storage, batteries and fuel cells have some inherent advantages over others but only compressed air energy storage (CAES) has the capacity of pumped hydro and potentially lowest overall capital and capacity costs. Advances in system compression designs and utilization of thermal energy storage has made CAES increasingly attractive, especially as new innovations in air storage technologies are now allowing CAES to break away from site specific geological formations like salt domes by allowing the air to be stored underwater in pressure vessels. In this paper, a thermodynamic evaluation of an idealized underwater pressure-balanced CAES system is conducted and compared to other large-scale underwater storage methods. Using the Gulf of Maine as a case study area, the thermodynamic relations are integrated in ArcGIS, a geospatial analysis program, to determine the energy storage resource potential for the New England area.

Hybrid Active Filter With Variable Conductance for Harmonic Resonance Suppression in Industrial Power Systems

Unintentional series and/or parallel resonances, due to the tuned passive filter and the line inductance, may result in severe harmonic distortion in the industrial power system. This paper presents a hybrid active filter to suppress harmonic resonance and to reduce harmonic distortion. The proposed hybrid filter is operated as variable harmonic conductance according to the voltage total harmonic distortion; therefore, harmonic distortion can be reduced to an acceptable level in response to load change or parameter variation of the power system. Since the hybrid filter is composed of a seventh-tuned passive filter and an active filter in series connection, both dc voltage and kVA rating of the active filter are dramatically decreased compared with the pure shunt active filter. In real application, this feature is very attractive since the active power filter with fully power electronics is very expensive. A reasonable tradeoff between filtering performances and cost is to use the hybrid active filter. Design consideration are presented, and experimental results are provided to validate effectiveness of the proposed method. Furthermore, this paper discusses filtering performances on line impedance, line resistance, voltage unbalance, and capacitive filters.

Automatic generation control of multi area thermal system using Bat algorithm optimized PD–PID cascade controller

Abstract This article presents automatic generation control (AGC) of an interconnected multi area thermal system. The control areas are provided with single reheat turbine and generation rate constraints of 3%/min. A maiden attempt has been made to apply a Proportional derivative–Proportional integral derivative (PD–PID) cascade controller in AGC. Controller gains are optimized simultaneously using more recent and powerful evolutionary computational technique Bat algorithm (BA). Performance of classical controllers such as Proportional Integral (PI) and Proportional Integral Derivative (PID) controller are investigated and compared with PD–PID cascade controller. Investigations reveal that PI, and PID provide more or less same response where as PD–PID cascade controller provides much better response than the later. Dynamic analysis has also been carried out for the controllers in presence of random load pattern, which reveals the superior performance of the PD–PID cascade controller. Sensitivity analysis reveals that the BA optimized PD–PID Cascade controller parameters obtained at nominal condition of loading, size and position of disturbance and system parameter (Inertia constant, H) are robust and need not be reset with wide changes in system loading, size, position of disturbance and system parameters. The system dynamic performances are studied with 1% step load perturbation in Area1.

Comparative performance analysis of teaching learning based optimization for automatic load frequency control of multi-source power systems

• Application of teaching learning based optimization to AGC problems. • PID controller gains have been optimized by teaching learning based optimization. • Dynamic performance is analyzed for single area system and multi area with HVDC link. • Dynamic performances of TLBO based PID controller are better than DE-PID controller. • Sensitivity analysis is done to load changes and different cost functions. This paper presents a new population based parameter free optimization algorithm as teaching learning based optimization (TLBO) and its application to automatic load frequency control (ALFC) of multi-source power system having thermal, hydro and gas power plants. The proposed method is based on the effect of the influence of teacher on the output of learners and the learners can enhance their knowledge by interactions among themselves in a class. In this extensive study, the algorithm is applied in multi area and multi-source realistic power system without and with DC link between two areas in order to tune the PID controller which is used for automatic generation control (AGC). The potential and effectiveness of the proposed algorithm is compared with that of differential evolution algorithm (DE) and optimal output feedback controller tuning performance for the same power systems. The dynamic performance of proposed controller is investigated by different cost functions like integral of absolute error (IAE), integral of squared error (ISE), integral of time weighted squared error (ITSE) and integral of time multiplied absolute error (ITAE) and the robustness of the optimized controller is verified by its response toward changing in load and system parameters. It is found that the dynamic performance of the proposed controller is better than that of recently published DE optimized controller and optimal output feedback controller and also the proposed system is more robust and stable to wide changes in system loading, parameters, size and locations of step load perturbation and different cost functions.

Comparison of performances of several FACTS devices using Cuckoo search algorithm optimized 2DOF controllers in multi-area AGC

• Comparison of CS algorithm with different versions in 3 area thermal system. • Comparisons of some FACTS devices with best CS optimized 2DOF-IDD controller. • Performance of IPFC with 2DOF-IDD controller reveals the best among all. • Study with placement of IPFC first time in AGC and is best with IPFC in all areas. • Sensitivity analysis reveals robustness of optimum parameters obtained at nominal. This paper presents automatic generation control (AGC) of three unequal area thermal systems with single reheat turbine and appropriate generation rate constraints (GRC) in each area. A two degree of freedom (2DOF) controller called 2DOF-integral plus double derivative (2DOF-IDD) is proposed for the first time in AGC as secondary controller. Secondary controller gains and other parameters are optimized simultaneously using a more recent evolutionary computational technique called Cuckoo Search algorithm (CS). The system dynamic responses for various 2DOF controllers such as 2DOF-PI, 2DOF-PID, and 2DOF-DD are compared. Investigations reveal that responses with 2DOF-IDD are better than others. Performance of several FACTS devices such as Static synchronous series compensator (SSSC), Thyristor controlled series capacitor (TCSC), Thyristor controlled phase shifter (TCPS), and Interline power flow controller (IPFC) in presence of 2DOF-IDD controller are compared and found that the dynamic responses with IPFC are better than others. For the first time in AGC, a case study is performed with placement of IPFC and observed that IPFC present in all three areas of the system performs better. Sensitivity analysis reveals that the CS optimized 2DOF-IDD controller parameters obtained in presence of IPFC in all three areas at nominal condition of loading and size of step load perturbation (SLP) are robust and need not be reset with wide changes in system loading and SLP. Also, the comparison of convergence curve of various algorithms reveals that CS algorithm converges much faster than others.

Machine fault detection by signal denoising—with application to industrial gas turbines

The paper proposes a new methodology of machine fault detection for industrial gas turbine (IGT) systems. The integrated use of empirical mode decomposition (EMD), principal component analysis (PCA) and Savitzky–Golay (S–G) adaptive filtering are applied to extract noise from underlying measurements. Through analysis of the resulting noise, along with the use of a developed power index, it is shown that transient measurements associated with system load or demand changes, for instance, can be effectively discriminated from those that are characteristic of emerging faults – the former being a primary contributor to generating ‘false alerts’ using more traditional techniques that are only robust when used with steady-state measurements. Comparative studies show the benefits of the hybrid technique compared to the more usual use of EMD and PCA alone. Three operational conditions are identifiable from the resulting noise analysis viz. normal behaviour, transient operation, and characteristics of emerging machine faults. The efficacy of the proposed approach is demonstrated using two experimental case studies (bearing wear and burner faults) on sub-15MW IGTs.

Comparison of performances of several Cuckoo search algorithm based 2DOF controllers in AGC of multi-area thermal system

This paper presents the automatic generation control (AGC) of an unequal three area thermal system with single reheat turbine and generation rate constraints of 3%/min in each area. A two degree of freedom (2DOF) controller called 2DOF – integral plus double derivative (2DOF – IDD) is proposed for the first time in AGC as secondary controller. Secondary controller gains and other parameters are simultaneously optimized using a more recent and powerful evolutionary computational technique called Cuckoo search algorithm (CS). The system dynamic responses obtained with 2DOF – IDD controller are compared with that obtained with other 2DOF controllers such as 2DOF – Proportional-Integral (2DOF – PI), 2DOF Proportional – Integral-Derivative (2DOF – PID). Investigations reveals that 2DOF – PI, and 2DOF – PID provide more or less same response where as 2DOF – IDD controller provides much better response than the others. Sensitivity analysis reveals that the CS optimized 2DOF – IDD controller parameters obtained at nominal condition of loading and nominal size of step load perturbation (SLP) are robust and need not be reset with wide changes in system loading and (SLP).

Robust analysis and design of power system load frequency control using the Kharitonov's theorem

This paper presents a robust decentralized proportional-integral (PI) control design as a solution of the load frequency control (LFC) in a multi-area power system. In the proposed methodology, the system robustness margin and transient performance are optimized simultaneously to achieve the optimum PI controller parameters. The Kharitonov’s theorem is used to determine the robustness margin, i.e., the maximal uncertainty bounds under which the stable performance of the power system is guaranteed. The integral time square error (ITSE) is applied to quantify the transient performance of the LFC system. In order to tune the PI gains, the control objective function is optimized using the genetic algorithm (GA). To validate the effectiveness of the proposed approach, some time based simulations are performed on a three-area power system and the results are then compared with an optimal PI controller. The comparisons show that the proposed control strategy provides the satisfactory robust performance for the wide range of system parameters and load changes in the presence of system nonlinearities and is superior to the other methods.

차량용 PEMFC 동적 모델을 이용한 시스템 부하 응답 특성

The stringent emission regulation and future shortage of fossil fuel motivate the research of alternative powertrain. In this study, a system of proton exchange membrane fuel cell has been modeled to analyze the performance of the fuel cell system for automotive application. The model is composed of the fuel cell stack, air compressor, humidifier, and intercooler, and hydrogen supply which are implemented by using the Matlab/Simulink(R). Fuel cell stack model is empirical model but the water transport model is included so that the system performance can be predicted over various humidity conditions. On the other hand, the model of air compressor is composed of motor, static air compressor, and some manifolds so that the motor dynamics and manifold dynamics can be investigated. Since the model is concentrated on the strategic operation of compressor to reduce the power consumption, other balance of components (BOP) are modeled to be static components. Since the air compressor model is empirical model which is based on curve fitting of experiments, the stack model is validated with the commercial software and the experiments. The dynamics of air compressor is investigated over unit change of system load. The results shows that the power consumption of air compressor is about 12% to 25% of stack gross power and dynamic response should be reduced to optimize the system operation.

DYNAMIC AND STEADY-STATE ANALYSIS OF SPLIT SPOOL FLOW DIVIDER VALVE

ABSTRACTFlow divider valve is a critical hydraulic component for which it used to synchronizeactuators motion in a predetermined ratio. The flow divider valve types divided into agear type flow divider and a spool type flow divider valve in which the spool has a rigidconnection between the two ports. As a special construction, here, a split type spoolflow divider has been studied to investigate the effects of special features on the staticand dynamic characteristics of the flow divider valve.The construction of a special type flow divider valve, split spool type, has acompensating spool/orifice mechanism to maintain equal pressure drops across thevalve metering orifice regardless of the change in system load. This split spool flowdivider valve thought to have a low inertia effect and enhanced valve response.In the present work, the static and dynamic characteristics of this special type flowdivider valve, split spool valve, have been studied at different load pressures.Experimental test rig has been established to investigate the effect of system pressureon the static characteristic of the special flow divider valve. A mathematical model hasbeen carried out to study static and dynamic characteristics of the flow divider valve; themodel has been verified by direct comparisons with the experimental results.For the dynamic response of the split spool flow divider; with the increase of the supplyflow rates at the same load pressure, split spool flow divider valve spools displacementswill increase equally in both spools at the same given response time. The supply flowrate is equally divided between the two outlets ports of the split spool flow divider valvewill reach the half of the supply flow rate at rate increased with the increase of the supplyflow rate.The comparison between experimental and mathematical model has a good agreementfor the studied system pressures up to 50 bars. It has been found that this special typeflow divider, split spool type, has a low inertia effect and enhanced valve response at thestudied load pressure regimes.

Fuzzy based Power Flow control of Two Area Power System

This paper deals with the novel approach of fuzzy based power flow control of two area power system. Interconnected operation enables utilities to share the generation from one area to other areas. In each area, all the generators are synchronized at same frequency. The change in system load within the area causes frequency deviation in the generating buses and tie line error in the tie lines connecting neighboring areas. The control of interconnected power system is achieved by Automatic Generation Control (AGC), which maintains the balance between generation and load. In this paper, the components of AGC, frequency deviation (DF), tie line error (DP tie ) and the output change in generations (DP gi ) are calculated by steady state power flow analysis using decoupled Newton Raphson method. The control action is performed by conventional method using participation factor and Fuzzy Logic Controller (FLC). The DF and DP tie are the inputs to the conventional controller and Fuzzy Logic Controller (FLC). The proposed method is tested with modified IEEE 30 bus system and the results are compared. Analysis reveals that FLC is quite capable of suppressing the frequency deviation and tie line error effectively as compared to that obtained with conventional controller. DOI: http://dx.doi.org/10.11591/ijece.v2i1.219