Control Energy Consumption Research Articles

Altitude Optimization of Airborne Wind Energy Systems via Switched Extremum Seeking—Design, Analysis, and Economic Assessment

This paper applies a Lyapunov-based switched extremum seeking (LSES) control algorithm to the application of altitude optimization of airborne wind energy systems. We perform an economic analysis to evaluate the effectiveness of the control scheme. Finding the altitude with the highest energy yield requires energy to be consumed in the search for this optimal altitude. The simultaneous desires to optimize altitude and minimize control energy consumption are balanced in this paper through a variant of ES control, where the periodic perturbation signal is reduced when convergence upon an optimal altitude is detected. The signal is reinstated when the wind speed begins to deviate from its instantaneous optimal value. Because the wind shear profile (wind speed versus altitude) is subject to continual variations, this application represents a challenging case study in LSES control. Using real wind shear data acquired over a 25-day period, the results presented in this paper show that the LSES controller is successful in significantly increasing the net energy production over fixed-altitude and standard ES strategies. The economic advantage of the approach is illustrated through a comparison of achievable wind energy penetration with and without LSES-based altitude optimization in place, using real load demand data.

Suboptimal Output Consensus for Time‐Delayed Singular Multi‐Agent Systems

AbstractThe current paper investigates guaranteed‐cost output consensus analysis and design problems for high‐order linear time‐invariant singular multi‐agent systems with constant time delays, which can realize suboptimal output consensus control. Firstly, a new output consensus protocol with a suboptimal index and a single delay is proposed to realize the tradeoff design between output consensus regulation performances and control energy consumptions. Then, sufficient conditions for guaranteed‐cost output consensus and consensualization are derived in terms of linear matrix inequalities by a combined tool from the Lyapunov‐Krasovskii approach and the free‐weighting matrix technique, respectively, and the output consensus function is determined on the basis of the First Equivalent Form. Finally, a numerical example is performed to demonstrate the effectiveness and conservativeness of theoretical results.

Learning Suboptimal Broadcasting Intervals in Multi-Agent Systems

In this paper, agents learn how often to exchange information with neighbors in cooperative Multi-Agent Systems (MASs) such that their user-defined cost functions are minimized. The investigated cost functions capture trade-offs between the MAS local control performance and energy consumption of each agent in the presence of exogenous disturbances. Agent energy consumption is critical for prolonging the MAS mission and is comprised of both control (e.g., acceleration, velocity) and communication efforts. The proposed methodology starts off by computing upper bounds on asynchronous broadcasting intervals that provably stabilize the MAS. Subsequently, we utilize these upper bounds as optimization constraints and employ an online learning algorithm based on Least Square Policy Iteration (LSPI) to minimize the cost function for each agent. Consequently, the obtained broadcasting intervals adapt to the most recent information (e.g., delayed and noisy agents’ inputs and/or outputs) received from neighbors and provably stabilize the MAS. Chebyshev polynomials are utilized as the approximator in the LSPI while Kalman Filtering (KF) handles sampled, corrupted and delayed data. The proposed methodology is exemplified in a consensus control problem with general linear agent dynamics.

An Operations Model for Home Energy Management System Considering an Energy Storage System and Consumer Utility in a Smart Grid

In this study, we propose an operations model to automate a home energy management system (HEMS) that utilizes an energy storage system (ESS) in consideration of consumer utility. Most previous studies focused on the system for the profits obtained from trading charged energy using large-scale ESS. By contrast, the present study focuses on constructing a home-level energy management system that considers consumer’s utility over energy consumption. Depending on personal preference, some residential consumers may prefer consuming additional energy to earn increased profits through price arbitrage and vice versa. However, the current system could not yet reflect on this aspect. Thus, we develop an operations model for HEMS that could automatically control energy consumption while considering the level of consumer’s preference and the economic benefits of using an ESS. The results of simulations using a dataset of the Korean market show that an operations policy of charging and discharging can be changed depending on consumer’s utility. The impact of this policy is not ignorable. Moreover, the technical specifications of ESS, such as self-discharge rate and round-trip efficiency, can affect the operations policy and automation of HEMS.

Network-based energy supply optimal system in the condition where both heating and cooling are required simultaneously in a swing season

ABSTRACTRecent building control models have adopted advanced algorithms to replace conventional controllers to improve the performance of plant or system levels. However, most models used to optimize fuel use or fan speed have several disadvantages to respond to, accurately and promptly, zone-scaled level. This paper proposes network-based controllers utilizing Artificial Neural Network (ANN) in space cooling and heating through the simultaneous control of the amount of supply air and its temperature. Two controllers are developed to evaluate the optimum of supply air conditions for a swing season that requires both moderate heating and cooling and they are compared to conventional thermostat on/off model by using the total control errors and energy consumption for operating damper and resistance coil. The result describes the advantage of the ANN simultaneous control that control errors reduce by 61.5% and energy consumption decreases by 3.5% in comparison with on/off controller. The ANN controller effectively optimizes the supply air conditions to reduce control errors and energy consumption, as they relate to human comfort and energy savings in a swing season.

Relay Selection for Heterogeneous Transmission Powers in VANETs

The main challenge in the vehicular ad hoc network vehicle-to-vehicle (V2V) multi-hop dissemination is to control the number of vehicles, that relay the broadcast message. Proper selection of relay nodes governs high delivery ratio, acceptable overall end-to-end delay, and efficient bandwidth usage. To date, several protocols have been proposed to identify appropriate relay vehicles. However, such approaches neglect the fact that vehicle transmission ranges are typically heterogeneous due to different transmission power values or dynamic adjustment of power to alleviate congestion and/or control energy consumption. In this paper, we introduce area-based dissemination protocols that work in heterogeneous transmission powers. The transmissions between relay vehicles are ordered in way that ensures that the node with high potential new coverage area transmits first. This eliminates useless transmission and retransmission that could be contained by other transmission. The new potential coverage area is computed as a function of the common overlap areas. In addition, we propose more reliable approaches by relaying duplicate received message. Thus, we introduce a geometric taxonomy for all possible overlap patterns in wireless environment, which is an apparently hitherto unsolved geometrical problem. Accordingly, we deduce the criteria used to define each pattern and relevant algebraic expression to compute the potential additional coverage area.

OBESITY AND METABOLIC SYNDROME: PATHOPHYSIOLOGICAL ROLE OF GUT MICROBIOTA AND POTENTIAL OF THE ALTERNATIVE THERAPY

The review presents data describing the current state of knowledge about the link between gut microbiota, obesity and metabolic syndrome. Pathophysiological role of gut microbiota in the development of obesity and metabolic syndrome is discussed. Potential of alternative therapy in controlling energy consumption and reducing the prevalence of obesity and metabolic syndrome is considered.

大規模施設園芸における温熱環境の応答予測

Since it is difficult to preserve horticultural crops such as vegetables for a long time, they are increasingly cultivated in a greenhouse and a plant factory for stable supply over a year. Especially in cases of the greenhouse, which size has been increasing for increased-yield and high-efficiency cultivation. Generally, in the greenhouse horticultural, it is necessary to keep the thermal environment inside the greenhouse to be different from the outside environment, therefore energy consumption for thermal environment control has been significant issues. In terms of energy conservation, energy consumption is being reduced by introducing a gas heat pump, operation control of air-conditioning equipment such as circulation fans, and ventilating by opening and closing a skylight. On the other hand, in terms of stable growth of the crops, it is important to homogenize the thermal environment such as temperature and CO2 concentration. In this study, an energy management technology that contributes to balancing the homogenized thermal environment and energy conservation is focused. In this report, the validity and effectiveness of spatiotemporal prediction method of the thermal environment has been presented by comparing multi-point measurements and numerical simulation of a large-scale greenhouse.

Numerical analysis of passive strategies for energy retrofit of existing buildings in Mediterranean climate: thermal mass and natural ventilation combination

The study investigates the potential of coupling natural ventilation and thermal storage systems to improve hygrothermal comfort and reduce energy consumption during summer season in an existing building in the Mediterranean. It aims at bridging the knowledge gap between designers, researchers and building scientists, fostering a multidisciplinary approach and promoting numerical simulation of the energy performance of buildings within architectural professional practice. The study analyses the interaction between six natural ventilation systems (single sided ventilation through facade openings; cross ventilation through facade openings, inlet wind tower, thermal chimney, evaporative cool tower, earth pipes) and with two thermal storage typology (heavy and medium-light) within four strategic Italian location (Rome, Naples, Messina and Catania). For each interaction we perform a numerical dynamic simulation of indoor comfort, indoor air quality and energy consumption during the summer period, on a reference building model corresponding to the most common Italian typology. Results show that the use of the chosen systems ensures significant reductions of discomfort hours and energy consumption in all configurations. The study also highlights the high efficiency of non invasive systems (single-sided and cross ventilation with automatic control present discomfort hours reduction and energy consumption reduction above 68% for all combinations) and the significant influence of the daily thermal range value on the performance of systems without air pre-treatment.

Optimizing Task, Memory and Energy of Wireless Sensor Grids using Grid Cluster based Multilevel Priority Scheduling

With rapid growth of advancements in the field of Internet of Things (IoT), wireless sensor networks are integrated as collaborative constituent for developing insidious smart technologies. Researches based on incorporating grid computing with the wireless sensor network to establish wireless sensor grid are flourishing in this decade to meet the real time requirements. Scheduling is a very vital task in the sensor grid to effectively reduce end to end delay and to control the overhead. In this research work, Multi Level Priority Scheduling (MLPS) scheme is implemented in the sensor grid environment. In order to reduce the energy consumption in the grid, the sensor nodes are grouped as clusters and data communication within the same cluster, across different clusters and from cluster to base station is established based on a novel clustering algorithm called as Grid Cluster. Grid Cluster algorithm combined with Multi Level Priority Scheduling (GCMLPS) is implemented in the sensor grid to optimize the resources including memory awareness, task awareness and energy awareness. Simulation results show the proposed scheme outperforms the existing scheduling mechanisms like First Come First Served Algorithm and the traditional Multi Level Priority scheme in terms of Packet Delivery Rate, Control Message Overhead, Efficiency, Energy Consumption and Routing Tree Cost

基于四元数方法的绳系机器人姿态控制

For better understanding of tethered space robot systems to be used in the future onorbit service, the attitude control problem of targets captured by tethered space robots was investigated. Firstly, based on the quaternion theory, the governing equations for the combined body of the target and the tethered space robot were constructed. Secondly, a projected RungeKutta method was developed for the issue of constraint systems, and this method is explicit and can preserve the norm of quaternions. Finally, a numerical example was given to validate the proposed model and the numerical method, where 3 kinds of control strategies were compared in terms of control effectiveness and energy consumption.

A novel utilisation-aware energy consumption model for content distribution networks

Rapid increase in internet worldwide users is leading a trend towards grand geographical distributed systems. Content distribution networks (CDNs) are one of the popular large-scale distributed systems managing around 40% of internet traffic. In order to reduce services cost and to minimise internet contribution in we footprint, it is very important to manage resources efficiently and to control energy consumption in CDNs. Although different studies propose solutions to reduce energy consumption, there is less concentration on analysing energy consumption and resource utilisation. In this paper, we have evaluated resource utilisation and ultimately energy consumption under different scenarios. We have proposed utilisation-aware energy consumption model. We have considered one of the most popular request redirection policy, that is, load balance. Quality of experience (QoE) metrics such as overall delay in client requests completion and dropped requests are also evaluated. Extensive simulation is performed by varying CDN infrastructure size, client requests traffic volume and intensity of end-user requests.

Assessing thermal comfort and energy efficiency in buildings by statistical quality control for autocorrelated data

In this paper, a case study of performing a reliable statistical procedure to evaluate the quality of HVAC systems in buildings using data retrieved from an ad hoc big data web energy platform is presented. The proposed methodology based on statistical quality control (SQC) is used to analyze the real state of thermal comfort and energy efficiency of the offices of the company FRIDAMA (Spain) in a reliable way. Non-conformities or alarms, and the actual assignable causes of these out of control states are detected. The capability to meet specification requirements is also analyzed. Tools and packages implemented in the open-source R software are employed to apply the different procedures. First, this study proposes to fit ARIMA time series models to CTQ variables. Then, the application of Shewhart and EWMA control charts to the time series residuals is proposed to control and monitor thermal comfort and energy consumption in buildings. Once thermal comfort and consumption variability are estimated, the implementation of capability indexes for autocorrelated variables is proposed to calculate the degree to which standards specifications are met. According with case study results, the proposed methodology has detected real anomalies in HVAC installation, helping to detect assignable causes and to make appropriate decisions. One of the goals is to perform and describe step by step this statistical procedure in order to be replicated by practitioners in a better way.

AMPKα2 Regulates Bladder Cancer Growth through SKP2-Mediated Degradation of p27.

These results highlight the contribution of AMPKα2 as a mechanism for controlling bladder cancer growth by regulating proliferation through mTOR suppression and induction of p27 protein levels, thus indicating how AMPKα2 loss may contribute to tumorigenesis. Mol Cancer Res; 14(12); 1182-94. ©2016 AACR.

Improving environmental management accounting: how to use statistics to better determine energy consumption

The accounting literature voices increased concerns about sustainability issues. Environmental performance as one dimension of sustainability includes among others the management and control of energy. Energy is a key production factor to which the stakeholders of a firm pay increased attention. Since energy has a significant influence on the economic costs and the environmental footprint of firms, management accounting is under growing pressure to better monitor and control energy costs. As a consequence, management accounting needs to develop energy management systems which control energy consumption and aim to reduce energy costs which in turn diminish a firm’s environmental impact and thus improve corporate reputation. One of the most important elements for energy management systems is an effective and cost-efficient measure of the energy consumption. However, firms and their management accounting departments, respectively, are still struggling to develop any cost-efficient approach for measuring energy consumption. That is why we suggest a statistical approach to easily and cost-efficiently measure energy utilization which in turn provides information input to improve environmental management accounting (e.g., cost allocations). We demonstrate our approach for a firm from an energy-intensive industry. The approach allows to distinguish more efficient from less efficient production units. We derive implications from this measurement approach for environmental management accounting and environmental management control systems.

Investigating relationships between functional coupling and the energy efficiency of embedded software

Software coupling involves dependencies among pieces of software called modules. Different types of coupling will dictate the manner whereby software modules interact and will result in different approaches to mutual function calls and return values, which can affect software quality attributes. Undoubtedly, coupling has been one of the most critical factors for supporting software modularity because it affects such important software quality attributes as reusability, readability, and maintainability. It is no surprise that coupling can affect energy efficiency. Recently, energy efficiency has increasingly been recognized as a critical software quality attribute, particularly for embedded software, including smartphone applications. Unfortunately, few studies have been conducted to date concerning coupling in developing energy-efficient and modular software, other than general studies on energy consumption and resource overutilization in the context of modularity. In this study, we aim to investigate the relationship between energy consumption and software coupling. In particular, we aim to determine whether it is possible to control energy consumption by applying different types of software coupling and, if so, how this might be done. We have performed a large number of experiments from which we have gained insight, although that insight might not be applicable to all possible types of coupling that are feasible, to help guide software engineers in developing energy-efficient embedded software. From the experimental results, we observe that overall “data” coupling reduces energy consumption when a large amount of data must be passed from one module to another, whereas “common” coupling is preferred when continuous memory references are needed, although energy consumption can also be somewhat dependent upon the operating environment. We describe such insights into the relationship between energy consumption and software coupling.

Structural design and analysis of a servo crank press

Due to precision, flexibility, simplicity in construction, easy control, higher speed and lower energy consumptions, servo presses have recently become popular in metal forming applications. Servo press technology combines the advantages of hydraulic and conventional mechanical presses without their drawbacks. This study presents design, construction and demonstration of a servo crank press system for metal forming operations. The research involves structural design and analysis with dynamic considerations of the servo press. A design and manufacturing guide is offered. The press used in this work has a load capacity of 500kN and stroke capacity of 200mm. Structural CAD model is constructed, and Finite Element Analysis (FEA) of press parts are performed within safety limits. Experimental studies are performed on this machine. Satisfaction at the output is seen.

A study on the key performance indicator of the dynamic positioning system

The dynamic positioning system (DPS) maintains an offshore vessel's position and heading under various environmental conditions by using its own thrust. DPS is regarded as one of the most important systems in offshore vessels. So, efficient operation and maintenance of the DPS are important issues. To monitor the DPS, it is necessary to define an appropriate key performance indicator (KPI) that can express the condition of the DPS from the perspective of operational efficiency and maintenance. In this study, a new KPI for the DPS is proposed considering the efficiency of the machinery and controller, the energy efficiency, and the environmental conditions in which the DPS is operated. The KPI is defined as a function of control deviation, energy consumption, and environmental load. A normalization factor is used to normalize the effect of environmental load on the KPI. The KPI value is calculated from DPS simulation and model test data. The possibility of applying the KPI to monitoring of DPS condition is discussed by comparing the values. The result indicates the feasibility of the new KPI.

Effects of building energy optimisation on the predictive accuracy of external temperature in forecasting models

The practice of using external temperature as a predictor of energy consumption in commercial buildings is well understood and it has been shown that this predictor is the most important when compared to other weather-based factors. In the literature, where a study has shown the external temperature not to be sufficiently accurate in forecasting energy usage by statistical methods, more predictors can be added to derive a more accurate forecasting model. The influence of the operating efficiency of the building on this accuracy has not been properly explained. This may be because of a lack of internal performance data for the building under review.This study has been developed to examine the effects of building operating efficiency on the forecasting accuracy of a statistical model by isolating external temperature as the sole predictor. The mechanism used to demonstrate the effects of the building's operating efficiency on the merit of using solely external temperature as a predictor is linear regression between external temperature and energy usage data.The study was carried out on two buildings of differing scale, occupational use and construction techniques. Using revised operational schemes involving more carefully controlled energy consumption and by monitoring local external temperatures, the relative accuracy of the various regression models is seen to be enhanced significantly following the efficiency programmes. The study has also facilitated an examination of the relative contributions to forecasting model accuracy resulting from energy efficiency actions taken in both buildings compared to the use of various external temperature indices.

Experiments on vibration control of a piezoelectric laminated paraboloidal shell

A paraboloidal shell plays a key role in aerospace and optical structural systems applied to large optical reflector, communications antenna, rocket fairing, missile radome, etc. Due to the complexity of analytical procedures, an experimental study of active vibration control of a piezoelectric laminated paraboloidal shell by positive position feedback is carried out. Sixteen PVDF patches are laminated inside and outside of the shell, in which eight of them are used as sensors and eight as actuators to control the vibration of the first two natural modes. Lower natural frequencies and vibration modes of the paraboloidal shell are obtained via the frequency response function analysis by Modal VIEW software. A mathematical model of the control system is formulated by means of parameter identification. The first shell mode is controlled as well as coupled the first and second modes based on the positive position feedback (PPF) algorithm. To minimize the control energy consumption in orbit, an adaptive modal control method is developed in this study by using the PPF in laboratory experiments. The control system collects vibration signals from the piezoelectric sensors to identify location(s) of the largest vibration amplitudes and then select the best two from eight PVDF actuators to apply control forces so that the modal vibration suppression could be accomplished adaptively and effectively.