Load Control Strategy Research Articles

Theoretical and experimental investigation on influence of load control strategy of LY12 duralumin alloy bar fine cropping process

In present work, both the theoretical solutions and the corresponding cropping experiments are carried out to investigate the influence of the load control strategy on bar fine cropping process. The working principle of the new proposed cropping method is detailed introduced. Five different types of the loading cycles are designed basing on it. A new proposed load control strategy with a suitable assumed constant stress intensity factor range is obtained theoretically and verified by the corresponding cropping experiments. According to a new proposed cross-section quality evaluation method, the comparative results show that the section quality and the cropping time are greatly influenced by the cropping load. The best quality is obtained by the loading cycle (iii).

Improving the partial-load fuel economy of 4-cylinder SI engines by combining variable valve timing and cylinder-deactivation through double intake manifolds

The SI engines in passenger cars run in the partial-load conditions in the most time especially in the urban driving cycles; thus it is particularly important to improve the partial-load fuel economy. Cylinder deactivation (CDA) and variable valve timing (VVT) could be applied to improve the fuel economy in the middle to low load region. Current CDA technologies are realized by deactivating all intake and exhaust valves (CDAV) of the inactive cylinders with special mechanisms increasing system cost and complexity. An innovative CDA method is proposed for 4-cylinder SI engines through double intake manifolds (CDAM). A novel load control strategy combining the CDAM and VVT along with late intake valve closure (LIVC) has been investigated. The results show that the pumping loss decreases by 58.9–65.6% and 24.5–35.3%; and the fuel economy improves by 5.5–17.6% and 3.1–9.2% in the CDA mode at 2000 rpm and 4000 rpm, respectively. The fuel economy in the full-cylinder mode also improves by 0.68–2.95% because of the application of the double intake manifolds. The strategy is more effective in the low speed range and more suitable for the urban driving cycles. Although a less fuel economy improvement than the CDAV method, the CDAM method can be realized with less cost and complexity.

Control Strategy for Vehicle Inductive Wireless Charging Based on Load Adaptive and Frequency Adjustment

Wireless charging system for electric vehicles is a hot research issue in the world today. Since the existing research on wireless charging is mostly forward-looking aimed at low-power appliances like household appliances, while electric vehicles need a high-power, high-efficiency, and strong coupling wireless charging system. In this paper, we have specifically designed a 6.6 KW wireless charging system for electric vehicles and have proposed a control strategy suitable for electric vehicles according to its power charging characteristics and existing common wired charging protocol. Firstly, the influence of the equivalent load and frequency bifurcation on a wireless charging system is analyzed in this paper. Secondly, an adaptive load control strategy matching the characteristics of the battery, and the charging pile is put forward to meet the constant current and constant voltage charging requirements to improve the system efficiency. In addition, the frequency adjustment control strategy is designed to realize the real-time dynamic optimization of the entire system. It utilizes the improved methods of rapid judgment, variable step length matching and frequency splitting recognition, which are not adopted in early related researches. Finally, the results of 6.6 kW test show that the control strategy works perfectly since system response time can be reduced to less than 1 s, and the overall efficiency of the wireless charging system and the grid power supply module can reach up to 91%.

BODYWEIGHT HIGH-INTENSITY INTERVAL TRAINING: A SYSTEMATIC REVIEW

ABSTRACT The objective of this study consisted of describing, through a systematic review, the load control strategies and the different adaptations promoted by bodyweight high-intensity interval training. After selecting articles in the Medline/PubMed, ScienceDirect, SPORTDiscus and Scielo databases, 288 studies were found. However, after applying the inclusion and exclusion criteria only two articles were considered eligible for the systematic review. Of these, the sample of the selected studies was made up of 48 individuals, 31 female and 17 male, ranging in age from 20.3 to 20.5 years. The stimulus time of the exercise protocols used was 20 and 30 seconds, and the recovery time was 10 seconds (passive) and 4 minutes (active), while the total session time ranged from 4 to 18 minutes. Intensity in both studies was “all out”, and the weekly frequency was 4 and 3 days, totaling 16 and 12 training sessions in each study. Only one study evaluated changes in body mass and no significant changes were found. In addition, discrepancies between parameters in aerobic fitness and muscle endurance were found between studies. Bodyweight HIIT (High-Intensity Interval Training) protocols use different external load parameters, but the stimulus and recovery times are common variables for the organization of training sessions, with different duration and weekly frequency between sessions, which may have influenced the different adaptations to the parameters of physical fitness between the studies. Level of Evidence I; Prognostic studies - Investigating the effect of patient characteristics on disease outcome.

Investigation on the energy conversion and load control of supercritical circulating fluidized bed boiler units

Load control is the core of the operation control system on power plant units. The energy conversion process is complicated in the supercritical circulating fluidized bed (SCFB) boiler due to the special fluidized combustion type, which also results in the large thermal inertia. So the control performances of conventional load control scheme without the consideration of carbon storage are poor in SCFB units. To reveal and monitor the energy storage in the boiler, the control model of burning carbon is established. Through the analysis on energy conversion process, the signal of advanced dynamic heat is structured to characterize the variation trend of energy. Based on the combination of the burning carbon control model and the dynamic heat signal, the boiler main control and feed-water control schemes are designed to optimal the control performance. Finally, the verification and application on the 600 MW SCFB unit prove the effectiveness of advanced dynamic heat signal and feasibility of the proposed control scheme.

Variable load control strategy for room-temperature magnetocaloric cooling applications

Room temperature magnetocaloric cooling is more environmental friendly but not yet more energy efficient than the state-of-the-art vapor compression technology. In this paper, we provide one more argument to support magnetic cooling technology, which is the superior energy saving potential under part load conditions. Therefore, magnetic cooling system may not compete with vapor compression under full load nominal condition, but its seasonal or annual overall efficiency could be better when part load characteristics are taken into account. To show the operation feasibility under part load condition, a feedback control strategy is proposed and incorporated into a magnetic cooling system model in Simulink first. The robust control quality is then revealed by numerical simulation studies for five different variable part load profiles. Furthermore, the transient accumulated energy performances are compared with those estimated based on the quasi-steady state condition to simplify the calculation on the overall energy efficiency benefit. Finally, a case study is carried out for unitary air-conditioning application, revealing that the overall energy efficiency is almost twice of the energy efficiency evaluated under full load condition.

Optimal demand charge reduction for commercial buildings through a combination of efficiency and flexibility measures

A substantial part of electricity bills in commercial buildings can consist of demand charges. Lowering the peak power and/or reducing the hours that a power threshold is exceeded can drastically reduce demand charges. The ability to do so by dynamic, operational adjustments reflects the “energy flexibility” of the building. This paper targets the optimal combination of design and operational measures in a retrofit or new design project that delivers the most effective way of reducing demand charges by increasing energy flexibility and efficiency of commercial buildings. This goal is achieved through an analysis of all feasible energy consumption and peak reduction measures in different building types and in different use contexts. A search algorithm that compares all possible interventions will deliver the optimum. This leads to a stochastic optimization approach with recognition of the effects of all possible sources of uncertainty. This paper evaluates the measures that are commonly adopted to decrease energy consumption and increase energy flexibility, including (1) upgrading building components and installing energy efficient equipment; (2) applying dynamic building load control strategies; (3) installing a rooftop photovoltaic panel array. Operational interventions include the manipulation of thermostat settings and the voltage reduction of lighting and appliances (in some cases including HVAC components) in the building, which may cause some level of thermal and visual discomfort during certain periods. In order to support retrofit and design improvement decisions, an approach is developed to find the optimal mix of measures that maximize the net present value of the investment in all measures over twenty years for the owner. This paper analyzes the optimal solutions for three commercial building types, office, hospital, and retail. The paper suggests a modeling and optimization framework that can be used by building designers and operators to make optimal investment decisions to reduce demand charges. The paper shows a novel support of the decision making by building operators when faced with the opportunity to reduce demand charges.

The Optimization dispatching of Micro Grid Considering Load Control

This paper proposes an optimization control of micro-grid system economy operation model. It coordinates the new energy and storage operation with diesel generator output, so as to achieve the economic operation purpose of micro-grid. In this paper, the micro-grid network economic operation model is transformed into mixed integer programming problem, which is solved by the mature commercial software, and the new model is proved to be economical, and the load control strategy can reduce the charge and discharge times of energy storage devices, and extend the service life of the energy storage device to a certain extent.

Neural Network Based Central Heating System Load Prediction and Constrained Control

A neural network (NN) based heating system load prediction and control scheme are proposed. Different from traditional physical principle based load calculation method, a multilayer NN is incorporated with selected input features and trained to predict the heating load as well as the desired supply water temperature in heating supply loop. In this manner, a complicated load calculation model can be replaced by simple but efficient data-driven scheme and the response time to outdoor temperature variation can be enhanced. Moreover, in order to handle the input and output constraints in valve opening degree control task to achieve desired supply water temperature, Barrier Lyapunov candidate function and axillary system technique are involved. An additional NN is employed to approximate the system transfer function with reliable accuracy. The stability of the system is guaranteed through rigorous mathematical analysis. The excellent performance of the novelly proposed control over traditional PID is demonstrated via extensive simulation study. A quantitative case study is also conducted to verify the flexibility and validity of proposed load prediction strategy.

Design, Development, and Evaluation of a Control Framework for an Atkinson Cycle Engine

The efficiency of the spark ignition (SI) engine degrades while working at part loads. It can be optimally dealt with a slightly different thermodynamic cycle termed as an Atkinson cycle. It can be implemented in the conventional SI engines by incorporating advanced mechanisms as variable valve timing (VVT) and variable compression ratio (VCR). In this research, a control framework for the Atkinson cycle engine with flexible intake valve load control strategy is designed and developed. The control framework based on the extended mean value engine model (EMVEM) of the Atkinson cycle engine is evaluated in the view of fuel economy at the medium and higher load operating conditions for the standard new European driving cycle (NEDC), federal urban driving schedule (FUDS), and federal highway driving schedule (FHDS) cycles. In this context, the authors have already proposed a control-oriented EMVEM model of the Atkinson cycle engine with variable intake valve actuation. To demonstrate the potential benefits of the VCR Atkinson cycle VVT engine, for the various driving cycles, in the presence of auxiliary loads and uncertain road loads, its EMVEM model is simulated by using a controller having similar specifications as that of the conventional gasoline engine. The simulation results point toward the significant reduction in engine part load losses and improvement in the thermal efficiency. Consequently, considerable enhancement in the fuel economy of the VCR Atkinson cycle VVT engine is achieved over conventional Otto cycle engine during the NEDC, FUDS, and FHDS cycles.

A direct load control strategy of centralized air-conditioning systems for building fast demand response to urgent requests of smart grids

Abstract When receiving an urgent request from a smart grid, shutting down part of operating chillers directly in the air-conditioning system in a building can achieve immediate power reduction. However, no study has addressed how to determine the number of chillers/pumps to be shut down and how to regulate the load of retained equipment systematically during DR events. This paper presents a new approach to address these issues based on three schemes. A power demand optimization scheme predicts the building cooling demand and the power limiting threshold in response to a received DR request. A system sequence control resetting scheme determines the number of operating chillers/pumps to be retained. An online control/regulation scheme ensures the system power following the expected profile by regulating the total chilled water flow delivered to the building and therefore the chiller load. It also employs a cooling distributor to distribute chilled water to individual zones concerning different sensitivities/sacrifices to temperature increases. Case studies are conducted on a simulated dynamic building air-conditioning system. Results show that, during DR events, the proposed strategy can achieve the expected power reduction (i.e., about 23%) and also maintain acceptable zone temperature even though uncertainties exist in the prediction process.

Investigation of Distributed Cooperative Control for DC Microgrids in Different Communication Medium

This paper is based on a detailed study of cooperative secondary control strategy for accurate load sharing in DC microgrids in different communication medium. Since accuracy in DC voltage regulation and load sharing can’t be achieved simultaneously in a non-negligible impedance network, an adaptive droop has been proposed to address this issue to a significant extent via a secondary controller. A fixed primary droop controller along with a conventional secondary controller generally introduces a loading mismatch between converters while accomplishing voltage regulation at load bus. To combat this issue, an adaptive droop is proposed to improve power sharing along with a tertiary update used for fine-tuning. Since a distributed controller collect information from its neighbors, its performance is highly influenced by the communication medium and its characteristics, such as latency, failure rate, etc. Hence, the efficacy of the proposed distributed communication architecture is tested in OPNET environment to conclude communication factors. These results are used to validate the performance of the proposed control strategy in MATLAB/SIMULINK environment for various communication as well as converter adversities.

Aerodynamic load control strategy of wind turbine in microgrid

A control strategy is proposed in the paper to optimize the aerodynamic load of the wind turbine in micro-grid. In grid-connection mode, the wind turbine adopts a new individual variable pitch control strategy. The pitch angle of the blade is rapidly given by the controller, and the pitch angle of each blade is fine tuned by the weight coefficient distributor. In islanding mode, according to the requirements of energy storage system, a given power tracking control method based on fuzzy PID control is proposed. Simulation result shows that this control strategy can effectively improve the axial aerodynamic load of the blade under rated wind speed in grid-connection mode, and ensure the smooth operation of the micro-grid in islanding mode.

Hierarchical control strategy for residential demand response considering time-varying aggregated capacity

Load control strategy has become a focus of researches, as demand-side resources are technically and economically desirable to relieve system power imbalance. In this paper, a hierarchical control strategy via load aggregator (LA) is proposed, considering both the evaluation of potential response capacity of large-scale residential loads and optimal allocation of response demand to each individual load. First, an aggregate model is established to exploit the time-varying potential response capacity of a population of residential loads. In the upper strategy, an equivalent response potential (ERP) index is created to quantitatively calculate the aggregate capacity and utilized to guide the allocation of total response demand to each LA. In the lower strategy, an optimal allocation model is built to determine the response status of each residential load per minute, ensuring end-user satisfaction and demand response requirements. The aggregate model and control strategy are verified valid through case studies. Furthermore, model accuracy and strategy implementation are discussed as well.

Adaptive Load Control Scheme for Emergency Biometric Data

Remote caring at home is becoming imperative with the rapid increase in ageing population. Wireless Health which enables remote health monitoring (RHM), has emerged as a promising field as a result of recent advances in wireless sensors and communication technologies. Many RHM devices are proposed through the use of advanced technologies of a Wireless Body Area Network in which sensors continuously record vital signs and pass them on to the personal server. Reliable procedures for the transmission of biometric data are of great significance for RHM devices. In this paper, we propose a policy based adaptive scheme for a previously proposed load control scheme. The proposed adaptive load control scheme will adjust the threshold according to the load of the data packets (i.e., emergency data packets and normal data packets), making the performance of the load control scheme even better in emergency cases.

Gust Load Alleviation: Identification, Control, and Wind Tunnel Testing of a 2-D Aeroelastic Airfoil

One important element in the progression of aircraft environmental impact reduction is to reduce their overall weight (without impacting other consumption-oriented performance index, such as drag). In addition to the numerous work conducted in material and structural engineering, from a control viewpoint, this challenge is strongly connected to the need of the development and assessment of dedicated load control strategies in response to gust disturbances . Indeed, the load factors due to gust are considered as sizing criteria during the aircraft conception steps and require specific verification according to the certification process. To this end, a dedicated experimental research program based on wind tunnel (WT) campaigns has been carried out. More specifically, this paper contributions are twofold: 1) to identify the gust load effect using two different versatile frequency-domain techniques, namely, the Loewner interpolation and a modified subspace approach and 2) to design and implement an active closed-loop control to alleviate the gust main effect. The entire procedure is validated in a WT setup, involving a gust generator device and a 2-D aeroelastic airfoil, for varying configuration traveling from sub to transonic airflow and varying angles of attack, emphasizing the effectiveness and robustness of the overall approach.

Switched Control Strategies of Aggregated Commercial HVAC Systems for Demand Response in Smart Grids

This work proposes three switched control strategies for aggregated heating, ventilation, and air conditioning (HVAC) systems in commercial buildings to track the automatic generation control (AGC) signal in smart grid. The existing control strategies include the direct load control strategy and the setpoint regulation strategy. The direct load control strategy cannot track the AGC signal when the state of charge (SOC) of the aggregated thermostatically controlled loads (TCLs) exceeds their regulation capacity, while the setpoint regulation strategy provides flexible regulation capacity, but causes larger tracking errors. To improve the tracking performance, we took the advantages of the two control modes and developed three switched control strategies. The control strategies switch between the direct load control mode and the setpoint regulation mode according to different switching indices. Specifically, we design a discrete-time controller and optimize the controller parameter for the setpoint regulation strategy using the Fibonacci optimization algorithm, enabling us to propose two switched control strategies across multiple time steps. Furthermore, we extend the switched control strategies by introducing a two-stage regulation in a single time step. Simulation results demonstrate that the proposed switched control strategies can reduce the tracking errors for frequency regulation.

Demand-Side Contribution to Power System Frequency Regulation : -A Critical Review on Decentralized Strategies

Abstract Nowadays the contribution of smart load technologies to power system frequency regulation is spurred due to the increasing penetration of renewable energy resources. This paper presents a comprehensive and up-to-date critical review on different decentralized load control strategies. This includes a joint literature- as well as simulation-based investigation in order to scrutinize different decentralized frequency-based load modulation strategies through organizing a taxonomy table and performing different simulation scenarios. Furthermore, the effectiveness of different gain tuning procedures in each control action are scrutinized and compared in terms of frequency nadir and steady state error. The detailed simulation is performed using SimPowerSystem (SPS) toolbox, in phasor mode, on IEEE 39-bus New England test system.

Multi-load Groups Coordinated Load Control Strategy Considering Power Network Constraints

Loads with energy storage property can actively participate in power balance for power systems, this paper takes air conditioner as a controllable load example, proposing a multi-load groups coordinated load control strategy considering power network constraints. Firstly, two load control modes considering recovery of load diversity are designed, blocking power oscillation of aggregated air conditioners. As the same time, air conditioner temperature setpoint recovery control strategy is presented to avoid power recovery peak. Considering inherent characteristics of two load control modes, an coordinated load control mode is designed by combining the both. Basing on this, a multi-load groups coordinated load control strategy is proposed. During the implementing of load control, power network constraints should be satisfied. An indice which can reflect the security of power system operating is defined. By minimizing its value through optimization, the change of air conditioning loads’ aggregated power on each load bus can be calculated. Simulations are conducted on an air conditioners group and New England 10-generator 39-bus system, verifying the effectiveness of the proposed multi-load groups coordinated load control strategy considering power network constraints.

Adaptive Load Control Scheme for Emergency Biometric Data

Remote caring at home is becoming imperative with the rapid increase in ageing population. Wireless Health which enables remote health monitoring (RHM), has emerged as a promising field as a result of recent advances in wireless sensors and communication technologies. Many RHM devices are proposed through the use of advanced technologies of a Wireless Body Area Network in which sensors continuously record vital signs and pass them on to the personal server. Reliable procedures for the transmission of biometric data are of great significance for RHM devices. In this paper, we propose a policy based adaptive scheme for a previously proposed load control scheme. The proposed adaptive load control scheme will adjust the threshold according to the load of the data packets (i.e., emergency data packets and normal data packets), making the performance of the load control scheme even better in emergency cases.