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This column surveys selected papers in computational sustainability from the 30th AAAI Conference on Artificial Intelligence. [ABSTRACT FROM PUBLISHER]

In many different applications, it is important to determine the Hilbert transform of a given function. However, it is generally impossible to calculate it in closed form. Therefore Hilbert transform approximations are used. This paper studies the convergence and divergence behavior of general classes of such approximation methods. These classes are characterized by two very natural axioms and they include basically all known traditional numerical algorithms. The convergence of these methods is investigated on a family of signal spaces of continuous functions with finite energy. These spaces are parametrized by a number which measures the energy concentration in the low frequency components of the signal. It is shown that stable methods only exist on signal spaces with a sufficient energy concentration and this paper gives some explicit examples of convergent methods. On all other spaces in the family of signal spaces, every sampling-based Hilbert transform approximation shows a blowup behavior of its peak value, i.e., on these spaces, every sampling-based Hilbert transform approximation diverges. [ABSTRACT FROM AUTHOR]

The operation of variable-speed ac drives with loss-minimizing flux strategies can produce important energy savings without the need of any investment. This paper proposes algorithms for the evaluation of loss motor components and the flux level that produces the minimum-loss operating condition, covering the whole constant-torque operating region. Both scalar and vector drives are considered, although it is found that the operation of scalar- and vector-controlled drives with optimum flux (or $d$ -axis current) gives very similar results for the same operating points. Evaluation is done using four induction motors of 4, 11, 55, and 110 kW. Results confirm that important savings can be achieved, especially in applications where motors operate with high speed and low to moderate load torque. Results will be used in a follow-up paper to evaluate the expected savings of the use of these strategies in a pulp mill and in a paper mill. [ABSTRACT FROM PUBLISHER]

This paper presents a new photovoltaic (PV) power systems laboratory module that was developed to experimentally reinforce students' understanding of design principles, operation, and control of photovoltaic power conversion systems. The laboratory module is project-based and is designed to support a renewable energy course. By using MATLAB real-time software tools in combination with digital signal processor (DSP) hardware tools, the module enables students to: 1) design and build dc–dc and dc–ac power converters; 2) design and implement control algorithms for maximum power point tracking (MPPT) and voltage and current regulation; and 3) design and fabricate a printed circuit board for voltage and current sensing, isolation, and gate driving. In these hands-on experiments, by designing and building their hardware and software integrated systems themselves, students learn by doing and experience the engineering transformative process of building a product out of an idea. This paper is motivated by the dearth of literature on the application of project-based learning methodology to PV systems. The module description, the pedagogical and evaluation methodologies adopted, and reflections on the implementations are discussed. [ABSTRACT FROM PUBLISHER]

Most businesses are feeling the impact of rising energy costs. As energy costs increase, it is becoming more important for plant owners to find ways to reduce energy consumption at their facilities. In addition, the stricter environmental regulations and ambitious \CO2 emission reduction goals of various countries are driving businesses toward more energy-efficient solutions. This paper discusses the vital role that optimal design and application of Trace Heating Systems plays in reducing their energy consumption. This paper presents a case study where an existing trace heating design is optimized to reduce energy consumption by 91%. Energy conservation strategies implemented include selection of an improved insulation system, a control and monitoring strategy, the appropriate trace heating technology, optimal trace heating designs, and the best power distribution option. The results of this paper are important tools to evaluate opportunities to save energy in both existing and new trace heating installations found at many industrial facilities and to reduce total operating costs. [ABSTRACT FROM AUTHOR]

Transformer-customer relationship identification refers to the determination of the physical connection relationship of electricity end-customers and their corresponding transformers. Such connection relationship is critical for distribution utilities to maintain their end-customer profiles. However, management of transformer-customer relationship becomes one of the most emerging challenges due to large number of end-customers and lack of measurement devices in low-voltage distribution systems. To address the above issue, this paper proposes an end-customer data-driven method to identify transformer-customer relationship in low-voltage distribution grid by utilizing the customer field data obtained from advanced metering infrastructure. Specifically, the incidence convolution identification method is proposed to build up the unique mapping relationship between end-customers and their transformers based on the principle of energy conservation. Then the voltage correlation maximization model based on Markov Random Field is proposed, where the voltage correlation matrix is exacted and combined with the adjacency matrix to establish an optimization model to correct the potential abnormal transformer-customer relationship. Finally, the effectiveness of the proposed method is verified by using practical utility tests. [ABSTRACT FROM AUTHOR]

This paper presents a novel power flow control strategy, combined with an economic analysis, for an energy management system (EMS) involving a hybrid energy storage. The EMS operates a remote microgrid and directs the power flow to either batteries or supercapacitors to increase the life of the batteries. This paper demonstrates how the use of supercapacitors increases the lifetime of the batteries and ultimately how it affects the economics of the system. The proposed EMS controller also compensates for the 120-Hz ripple on the dc bus. Modeling, simulations, and experimental verification are presented together with the procedure to perform the assessment of the battery lifetime, according to the tuning parameters of the controller. [ABSTRACT FROM AUTHOR]

Low-power is one of the key driving forces in modern very large scale integration systems. Recent studies show that 3-D integrated circuits (ICs) offer a significant power saving over 2-D ICs. However, these studies are mainly limited to two-tier (2-tier) designs. Thus, in this paper, we extend our target to three-tier (3-tier) 3-D ICs. This paper first shows that the one additional tier available in 3-tier 3-D ICs does offer more power saving compared with their 2-tier 3-D IC counterparts, but more careful floorplanning, through-silicon via management, and block folding considerations are required. Second, we find that the 3-tiers can be bonded in several different ways: 1) face-to-back only; 2) face-to-face and face-to-back combined; and 3) back-to-back and face-to-face combined. This paper shows that these choices pose additional challenges in design optimizations for more power saving. Lastly, we develop effective computer-aided-design solutions that are seamlessly integrated into commercial 2-D IC tools to handle 3-tier 3-D IC power optimization under various bonding style options. With our low-power design methods combined, our 3-tier 3-D ICs provide −14.8% more power reduction over 2-tier 3-D ICs, and −36.0% over 2-D ICs in microprocessor cores under the same performance. In full-chip microprocessors, our 3-tier 3-D ICs provide −27.2% more power reduction over 2-D ICs. [ABSTRACT FROM PUBLISHER]

Overall electric energy conservation and improvement in electrical energy efficiency has been a topic of interest to the electric power industry for long time, since 40% of total primary energy used is in the form of electricity. There are many facets to the energy conservation and/or energy efficiency techniques. Energy conservation by voltage reduction popularly called “CVR” has recently gained some momentum, in particular, to reduce the peak demand. This is also an integral part of the discussion in the future smarter grid technology. This paper addresses the pros and cons of the CVR application including a thorough literature search, practical applications, and a quantifiable measure of its actual amount of energy saving from utilities and the cost associated with it. It is expected that this paper will serve as a foundation to all practicing engineers addressing the issue of CVR. [ABSTRACT FROM AUTHOR]

A mobile charging system (MCS) for electric vehicles (EVs) is presented in this paper. The proposed MCS has a 2-MWh energy storage capacity for charging five EVs simultaneously with 75-kW individual charging rates. The MCS would be rechargeable from the available power substations (three phase, 480 V) with 375-kW charging rate. The appropriate modular power interface is designed and implemented between the MCS, batteries of the EVs, and the power substations. Experimental validation is presented in this paper to demonstrate the system performance and effectiveness under rapid charging requirements. [ABSTRACT FROM AUTHOR]

This paper proposes a broadcasting control system of intelligent air conditioners using the narrow-band power line carrier (PLC) (NPLC) technology. The communication protocol of Smart Energy Profile SEP 1.0 is implemented for the master station to issue commands to air conditioners over the power line. The function of demand response (DR) can also be executed via the proposed system. To verify the communication performance of control signal using the PLC technology, the field tests of NPLC over power lines and across transformers are executed. By integrating the PLC with the existing optical fiber network of the Distribution Automation System in the Taiwan Power Company, the Hybrid Communication System for Smart Grid applications is built and tested to support the control of air conditioners and the DR programs. It is found that the energy conservation by reducing the system peak load can be achieved when the proposed system is applied for the remote thermostat settings of air conditioners in the commercial section. The power consumption of various types of loads can also be collected and reported to the control center using the two-way communication provided by the proposed system. [ABSTRACT FROM PUBLISHER]

DC circuit protection applications provide a unique market opportunity for wide-bandgap (WBG) semiconductors, which are outside the conventional focus on power electronic converters. This paper presents an overview of emerging dc power systems, the needs for dc solid-state circuit breakers (SSCBs), and the benefits and advantages of various WBG SSCB concepts. Furthermore, a new class of self-powered SSCBs based on SiC or GaN normally-ON switching devices is proposed in this paper. One implementation of the SSCB concept based on a 1200 V SiC JFET experimentally demonstrated turn-off of a fault current of 125 A at a dc voltage of 400 V within $1~\mu $ s without requiring any external power supply. The SSCB detects short-circuit faults by sensing its drain–source voltage rise and draws power from the fault condition to turn off the SiC JFET. Various implementations of the SSCB concept for unipolar and bipolar capability using both SiC and GaN are also discussed from both device and circuit perspectives. It is concluded that very low ON-resistance normally-ON WBG switching devices are excellent candidates for the emerging SSCB applications. [ABSTRACT FROM AUTHOR]

An energy saving permanent magnet type magnetizer is proposed, examined, and validated in this paper for the manufacturing of linear pattered magnetic medium for the precision control application. With the ultimate goal placed on providing sufficient magnetic field to overwrite and modify patterns on the magnetic media, parameter studies are conducted through finite element studies with results validated by magnetic flux density distribution measurements from produced incremental and index point patterns. Feasibility of utilizing the patterned medium for positioning control is validated through repeatability measurements, indicating that the proposed magnetizer can produce magnetic patterns rendering adequate magnetic signal strength and repeatability in linear precision control applications. [ABSTRACT FROM AUTHOR]

The speed regulation technology for energy conservation of pump and fan systems occupies an important position in industrial field. The paper focuses on the rapid development and research significance of speed regulation technology for energy conservation based on different permanent magnet adjustable speed drives (PMASDs). The development history and speed regulation scheme for energy conservation are introduced step by step. The features of theoretical model based on magnetic vector potential and equivalent magnetic circuit methods are presented and studied in the paper, which is benefit to select a suitable method for a specific drive. Several optimization methods of design parameters of PMASDs are given in the paper. The structure and operating principle of some new speed regulation scheme are described, and their advantages, disadvantages and feasibility of engineering application are analyzed. Finally, the proposed speed regulation technologies for energy conservation are summarized and classified from the aspects of magnetic circuit structure, permanent magnet rotor structure, conductor rotor structure, and the slip power conversion scheme. In a conclusion, the power-fed PMASD will be the future of energy conservation technology for the high-efficiency and low-cost large pump and fan systems.

This paper demonstrates the impacts of an electronically triggered fault current limiter (ET-FCL) on typical single-ended and main–tie–main (MTM) medium-voltage switchgear arrangements. The fast acting (less than 1 ms) ET-FCL described in this paper effectively opens the normally closed tie connection between two mains, thereby disconnecting one of the sources to the fault. An ultrafast opening of the tie connection simplifies protection coordination by not having to coordinate the main breaker relay with the tie breaker relay at maximum fault levels. System benefits include the following: significantly lower arc flash energy for downstream faults, faster backup clearing times for a feeder relay/breaker failure, reduction of motor starter dropouts due to fault-produced voltage dips, improved system stability, improvement in utility's CAIDI reliability index, reduced stress on switchgear breakers, and overall lower capital costs on new construction (switchgear, cables, etc.). This paper demonstrates relay setting changes on typical single-ended and MTM arrangement with and without applying the ET-FCL. Impacts on incident energy reduction, backup clearing times, dynamic system stability, and voltage dips will be discussed. [ABSTRACT FROM PUBLISHER]

In this paper, an online foot position compensator (FPC) is proposed for improving the robustness of humanoid walking based on orbital energy conservation and discrete control Lyapunov function (DCLF), with which the asymptotic stability of the humanoid system can be maintained and, thus, the foot placement control is achieved. The online FPC is developed based on linear model predictive control (MPC) by replanning the trajectories of the center of mass (CoM) and properly placing the footsteps to resist external disturbances and recover the walking posture. To further improve the robustness of the humanoid robots to suppress strong external disturbance, a strategy of upper body posture control is proposed. The presented controller stabilizes the humanoid robot by utilizing hip joints to modulate the upper body posture online. Webots simulations and real experiments on a full-body NAO humanoid robot verify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Evaluation of conservation voltage reduction (CVR) factor is critical to peak load reduction, 556 energy conservation, and many CVR-related power system control/optimization strategies. This paper proposes a novel robust CVR factor evaluation method using soft constrained gradient analysis based on time-varying load modeling and real utility field measurements. Firstly, the time-varying ZIP parameter identification is formulated as an over-determinant problem composed of first-order gradient with respect to each coefficient and soft constraints representing temporal correlation of loads in each time step, in order to improve the robustness and smoothness of CVR factor evaluation. Then, problems in time series are coordinated with a sliding window approach. A necessary condition for selecting the smallest window size is proposed and strictly proved to guarantee the existence and uniqueness of the solution of time-varying load modeling problem. Finally, time-varying CVR factors are accurately and robustly calculated with field measurements and the identified load model. Case studies are performed using sufficient field measurements obtained from two real utilities. Unlike existing methods that require a large number of measurements to obtain precise estimation of CVR factor, the proposed method is sufficiently accurate even when the measurements are limited or of low time resolution. Further, the accuracy and robustness of the proposed approach are validated under different types of uncertainties and compared with other existing data processing and CVR factor evaluation methods. [ABSTRACT FROM AUTHOR]

In this paper, we focus on enhancing the energy efficiency in open-access femtocell networks where many femto base stations (BSs) are deployed in a large public area such as airports, shopping malls, etc. In those areas, the femtocells are overlapped and underutilized during most of the operation time because femto BSs are densely deployed to support the peak traffic load. Therefore, if we properly coordinate the user association (UA) with BSs and put the femto BSs having no associated users to sleep, the energy consumption can be saved remarkably. In this paper, we propose a scheme that jointly decides the operation modes (e.g., active or sleep) of femto BSs and the association between users and the active BSs to minimize the energy consumption in the network. Simulation results show that the proposed scheme can significantly reduce the total energy consumption in the open-access femtocell networks. [ABSTRACT FROM AUTHOR]

In this paper, we optimize the use of existing DSL low-power sleeping modes (L2 and L3) in order to improve the energy efficiency of DSL access networks. Given that switching on a DSL line can cause instability by increasing the amount of time-varying crosstalk in the cable bundle, and that it takes energy and time to switch a DSL line on and off, we develop a method to optimally choose the appropriate sleeping state based on the line and traffic characteristics. We further develop and prove the structural properties of the optimal policy for switching to the appropriate sleeping state, allowing transitions between submodes with different power and transmit rate characteristics. We also present techniques that guarantee stable sleep mode operation. Using a realistic DSL simulator, we demonstrate the three-way tradeoff among energy consumption, delay performance, and stability. The increased flexibility of control introduced by our approach improves the energy-delay Pareto optimal tradeoff, and results in a more energy efficient and stable DSL operation compared to existing power saving policies. [ABSTRACT FROM PUBLISHER]

Energy conservation is essential to wireless networks, particularly for third-generation (3G) and fourth-generation (4G) wireless systems, because high-speed data transmissions would rapidly exhaust the energy of a mobile station. This paper presents the details of energy-saving mechanisms for packet data services in two major standards, namely, the Third-Generation Partnership Project (3GPP) and the Third-Generation Partnership Project 2 (3GPP2). In addition to qualitative comparison, analytic models and quantitative comparison based on the energy-saving models are provided. The proposed analytic models analyze and quantify the energy consumption for bursty and streaming traffic in cdma2000 and wideband code division multiple access (WCDMA). The impacts of an inactivity timer on energy consumption and reconnection cost are demonstrated further by simulation and analysis. The analytic results could be used to suggest proper timer lengths that can balance the energy consumption and the reconnection cost. In addition to providing insights of the energy- conservation mechanisms of 3GPP and 3GPP2, which are often difficult to directly obtain from standards specifications, results shown in this paper are also practical for 3GPP and 3GPP2 operators to determine proper parameters for energy efficiency. [ABSTRACT FROM AUTHOR]

In this paper, we study the performance of base station (BS) coordination in heterogeneous networks (HetNets) with cache-enabled and renewable energy-powered small cell BSs (SBSs). Macrocell base stations (MBSs) provide basic coverage, while the SBSs, powered by harvested energy, conduct content-aware coordinated transmission to provide high data rate and further improve the network coverage. Specifically, a joint transmission strategy is performed based on the knowledge of the energy states and the cached contents of SBSs, along with the awareness of the availability of channel resources and the average received signal strength (RSS) of the corresponding link. Stochastic geometry is applied to characterize the statistics of the cell load at MBSs and SBSs, as well as the aggregated information and interference signal strength. Then, the average user capacity for the joint transmission is obtained. Additionally, the coverage probability is derived with gamma approximation for the aggregated information and interference signal strength. Analytical results reveal that the average user capacity and coverage probability can be maximized with optimal cache size, energy harvesting rate and cooperative RSS threshold. Finally, extensive numerical and simulation results are provided. [ABSTRACT FROM AUTHOR]

Energy and power are key challenges in high-performance computing. System energy efficiency must be significantly improved, and this requires greater efficiency in all subcomponents. An important target of optimization is the interconnect, since network links are always on, consuming power even during idle periods. A large number of HPC machines have a primary interconnect based on Ethernet (about 40 percent of TOP500 machines), which, since 2010, has included support for saving power via Energy Efficient Ethernet (EEE). Nevertheless, it is unlikely that HPC interconnects would use these energy saving modes unless the performance overhead is known and small. This paper presents PerfBound, a self-contained technique to manage on/off-based networks such as EEE, minimizing interconnect link energy consumption subject to a bound on the performance degradation. PerfBound does not require changes to the applications and it uses only local information already available at switches and NICs without introducing additional communication messages, and is also compatible with multi-hop networks. PerfBound is evaluated using traces from a production supercomputer. For twelve out of fourteen applications, PerfBound has high energy savings, up to 70 percent for only 1 percent performance degradation. This paper also presents DynamicFastwake, which extends PerfBound to exploit multiple low-power states. DynamicFastwake achieves an energy–delay product 10 percent lower than the original PerfBound technique. [ABSTRACT FROM AUTHOR]

This paper discusses the design criteria for the electrical systems of roadway tunnels with particular regard to the safety in the daily operation and in the case of fire events. It proposes a fit distribution system and an adaptive criterion for the support lighting system in order to minimize costs and energy impact. Electric systems of roadway tunnels need sophisticated architecture to allow the presence of extensively distributed loads and more stringent installation requirements due to the presence of fire hazard. Mechanical and electrical design criteria must be based on equipment qualification categories (EQCs), which are characterized by thermal inherent resistance and environmental parameters. Design criteria must include variable configurations to simplify installation, allow flexible operation, and optimize the cost–benefit ratio. A special power distribution, herein defined as “brush distribution,” and a temperature zone classification are proposed for road tunnels with a higher risk in the case of a fire event. Therefore, this paper suggests as design parameters the temperature exposure levels characterizing the thermal demand in each zones and the EQCs in order to choose the equipment with adequate thermal resistance. [ABSTRACT FROM PUBLISHER]

One of the key techniques toward energy efficiency and conservation is nonintrusive load monitoring (NILM) which lies in the domain of energy monitoring. Event detection is a core component of event-based NILM systems. This paper proposes two new low-complexity and computationally fast algorithms that detect the variations of load data and return the time occurrences of the corresponding events. The proposed algorithms are based on the phenomenon of a sliding window (SW) that tracks the statistical features of the acquired aggregated load data. The performance of the proposed algorithms is evaluated using real-world data and a comparative analysis has been carried out with one of the recently proposed event detection algorithms. Based on the simulations and sensitivity analysis, it is shown that the proposed algorithm can provide the results of up to 93% and 88% in terms of recall and precision, respectively. [ABSTRACT FROM AUTHOR]

In this paper, we first develop an analytical framework for the total energy consumption of an amplify-and-forward (AF) multihop network employing M-ary quadrature amplitude modulation (MQAM) while satisfying an average bit error rate (BER) requirement at the destination over Rayleigh fading channels. Based on this framework, we then establish the conditions under which a dual-hop relay network is always more energy efficient when compared with a reference single-hop network. Moreover, the impact of the relay's location and the energy resource allocation between the relay and the source on the possible energy savings is also analyzed. Since a realistic power consumption model is considered, it is shown that there exists an optimal number of relays for the linear multihop relay network and that the maximum energy efficiency (EE) is obtained through the joint optimization of the number of relays and the constellation size. Considering this fact, we first formulate the optimization problem, and then, this problem is transformed into a convex form by relaxing constraints to be defined over the real numbers (instead of taking only discrete values). The new closed-form optimal solution that involves only elementary functions is derived for this relaxed problem. It is also demonstrated that the optimized multihop network has the potential not only to reduce the total energy consumption but to satisfy the peak-power constraint simultaneously at the expense of more delay as well. Finally, our analysis shows that significant energy savings are possible through joint optimization not only for delay-tolerant networks but for delay-limited networks as well, and up to about 55% energy savings are achievable over the optimized single-hop system. [ABSTRACT FROM PUBLISHER]

Vehicular sensor networks (VSNs) are composed of vehicular sensor nodes that collaboratively sample, communicate, and reconstruct the event signal at the sink node. Samples of event signals are subjected to jitter based on the propagation speed of signal and locations of vehicular sensors. In this paper, a theoretical analysis is presented to understand the effects and how to exploit the jitter in the sensed event signal for energy-efficient and reliable communication in VSNs. Results reveal that sampling jitter can be advantageous and can be exploited in developing adaptive communication techniques, which can provide significant energy conservation while maintaining reliability in VSNs. [ABSTRACT FROM PUBLISHER]

Energy conservation and emission reduction in the ethylene industry is the main way to attain sustainable development, which can be achieved if the energy efficiency of petrochemical industries can be accurately analyzed and predicted. This paper proposes an improved radial basis function neural network based on fuzzy C -means (FCM) algorithm integrated with principal component analysis (PCA) technology (PCA-FRBF). The PCA is used to denoise and reduce dimensions of data to decrease the training time and errors of the modeling process. The FCM is used to separate every fuzzy class in input space and decide the number of neurons in hidden layer to overcome the shortcoming of setting them by experience subjectively. Meanwhile, the robustness and effectiveness of the PCA-FRBF model are validated through the standard data set from the University of California Irvine repository. Moreover, to predict the energy efficiency of ethylene plants, a multi-inputs and single-output model of energy efficiency is established based on the PCA-FRBF for monthly data of ethylene production process. We obtain a rational allocation of crude oil, fuel, steam, water, and electricity, and the greatest benefit of ethylene plants under different technologies. Finally, the empirical results show the effectiveness and practicability of the PCA-FRBF model applied to predict and guide the ethylene production in the petrochemical industry. [ABSTRACT FROM PUBLISHER]

In the process of launching the electromagnetic rail guns (EMRGs), the erosion damage to the rail surface is mainly caused by the joule heat generated by the rail body resistance and armature-rail contact resistance as the current runs through the rail. According to the joule heat and the law of conservation of energy, this paper develops a formula to calculate the temperature rise of rail surface, proposes the method of using temperature rise of rail surface for representing rail erosion damage, and the mathematical formula indicates the relevance between the temperature rise of rail surface and current, linear current density, armature moving speed, rail material, state of armature-rail contact, and skin effect. Dynamic test data required for calculation of rail current, muzzle voltage, armature bore displacement, and velocity are obtained through launching tests, and are used to calculate the surface temperature rise of rails of different materials during the launch of EMRGs. The calculation produces the temperature rise of rails at any positions along the length direction. The results are compared with the photographs of rail surface after the launch, and the analysis verifies the feasibility of representing rail erosion damage with temperature rise of rail surface. [ABSTRACT FROM PUBLISHER]

The thermal characteristics of the interface between armatures and rails of electromagnetic railguns (EMRGs) have an impact on the state of armature-rail contact and the launching performance of its system. In the launching process of EMRGs, the temperature rise of rails is mainly caused by the Joule heat generated by the rail resistance and armature-rail contact resistance and the friction heat generated by high-velocity movement of armatures. According to the theories of electromagnetic field, conservation of energy, Joule’s law, and generation of heat by friction, this paper analyzes the property of the contact resistance of the interface between armatures and rails of railguns and the friction factor of the interface, and develops a formula to calculate the transient temperature of rails resulting from the Joule heat and friction heat. Through a launch experiment, such dynamic data as muzzle voltage, rail current, armature displacement, and velocity during the actual launching process are obtained to calculate relevant parameters such as contact resistance, rail resistance under velocity skin effect, and armature-rail contact pressure. Such parameters are substituted into the temperature calculation formula for calculation of the Joule heat generated by the rail resistance and armature-rail contact resistance and the friction heat generated by high-velocity movement of armatures. The calculation produces a curve of change of rail maximum temperature over time under the joint effect of the three factors, thus allowing for the calculation of the transient temperature of rails during the launching process. [ABSTRACT FROM PUBLISHER]

In this paper, two techniques based on Q -learning and action dependent heuristic dynamic programming (ADHDP) are demonstrated for the demand-side management of domestic electric water heaters (DEWHs). The problem is modeled as a dynamic programming problem, with the state space defined by the temperature of output water, the instantaneous hot water consumption rate, and the estimated grid load. According to simulation, Q -learning and ADHDP reduce the cost of energy consumed by DEWHs by approximately 26% and 21%, respectively. The simulation results also indicate that these techniques will minimize the energy consumed during load peak periods. As a result, the customers saved about $466 and $367 annually by using Q -learning and ADHDP techniques to control their DEWHs (100 gallons tank size) operation, which is better than the cost reduction that resulted from using the state-of-the-art ($246) control technique under the same simulation parameters. To the best of the authors’ knowledge, this is the first work that uses the approximate dynamic programming techniques to solve the DEWH’s load management problem. [ABSTRACT FROM AUTHOR]

The portion of clock power in system is rapidly increasing with the continuous increasing of clock frequency and clock resources. Last two decades, a great research attention has been paid to minimizing the clock power. Recently, it is shown that the structure of resonant clock networks is very effective in saving power since it can store electric energy to the inserted inductors rather than dissipate. On the other side, it has been known that dynamic voltage-frequency scaling (DVFS) is one of the most effectively and widely used power reduction techniques. However, so far no works have addressed the design methodology problem of synthesizing resonant clock networks that are able to operate under the designs with DVFS capability even though the problem is potentially very important to maximize the synergy effect on saving power. In this context, this paper proposes a comprehensive solution to the problem. Precisely, we propose a two-phase synthesis algorithm: 1) formulating the problem of inductor allocation, placement, and adjustable-sizing to support DVFS into a weighted set cover problem with the objective of minimizing total area of inductors and 2) followed by performing the task of resizing of adjustable driving buffers to support the switch of driving strength according to the clock frequencies by DVFS. Through experiments with benchmark circuits, it is shown that for designs with DVFS using 1 and 3 GHz, our algorithm synthesizes resonant clock networks with 25.9% less power on the execution of the clock frequency, which is not supported by resonant clocking in the previous no-DVFS aware resonant clock synthesis algorithm. [ABSTRACT FROM PUBLISHER]

This is the second paper in a series of two that describe our research in intelligent energy management in a hybrid electric vehicle (HEV). In the first paper, we presented the machine-learning framework ML_EMO_HEV, which was developed for learning the knowledge about energy optimization in an HEV. The framework consists of machine-learning algorithms for predicting driving environments and generating the optimal power split of the HEV system for a given driving environment. In this paper, we present the following three online intelligent energy controllers: 1) IEC_HEV_SISE; 2) IEC_HEV_MISE ; and 3) IEC_HEV_MIME. All three online intelligent energy controllers were trained within the machine-learning framework ML_EMO_HEV to generate the best combination of engine power and battery power in real time such that the total fuel consumption over the whole driving cycle is minimized while still meeting the driver's demand and the system constraints, including engine, motor, battery, and generator operation limits. The three online controllers were integrated into the Ford Escape hybrid vehicle model for online performance evaluation. Based on their performances on ten test drive cycles provided by the Powertrain Systems Analysis Toolkit library, we can conclude that the roadway type and traffic congestion level specific machine learning of optimal energy management is effective for in-vehicle energy control. The best controller, IEC_HEV_MISE, trained with the optimal power split generated by the DP optimization algorithm with multiple initial SOC points and single ending point, can provide fuel savings ranging from 5% to 19%. Together, these two papers cover the innovative technologies for modeling power flow, mathematical background of optimization in energy management, and machine-learning algorithms for generating intelligent energy controllers for quasioptimal energy flow in a power-split HEV. [ABSTRACT FROM PUBLISHER]

In this paper, the application of optimal state estimation and optimal state feedback algorithms for real-time active magnetic bearing control is treated. A linear quadratic Gaussian controller, consisting of an extended Kalman filter and an optimal state feedback regulator, is implemented. It is shown that this controller yields improved rotor positioning accuracy, better system dynamics, higher bearing stiffness, and reduced control energy effort compared to the conventionally used proportional–integral–differential control approaches. In addition, a method for compensating unbalance-caused forces and vibrations of the magnetically levitated rotor is presented which is based on the estimation of unknown disturbance forces. All results achieved in this paper are verified by means of measurements. [ABSTRACT FROM PUBLISHER]

Obtaining an accurate mechanical model of a soft deformable robot compatible with the computation time imposed by robotic applications is often considered an unattainable goal. This paper should invert this idea. The proposed methodology offers the possibility to dramatically reduce the size and the online computation time of a finite element model (FEM) of a soft robot. After a set of expensive offline simulations based on the whole model, we apply snapshot-proper orthogonal decomposition to sharply reduce the number of state variables of the soft-robot model. To keep the computational efficiency, hyperreduction is used to perform the integration on a reduced domain. The method allows to tune the error during the two main steps of complexity reduction. The method handles external loads (contact, friction, gravity, etc.) with precision as long as they are tested during the offline simulations. The method is validated on two very different examples of FEMs of soft robots and on one real soft robot. It enables acceleration factors of more than 100, while saving accuracy, in particular compared to coarsely meshed FEMs and provides a generic way to control soft robots. [ABSTRACT FROM AUTHOR]

Energy management of heating, ventilation, and cooling (HVAC) has become a primary concern for residential and commercial buildings. In order to save energy without compromising the comfort of occupants, various techniques have been explored to sense the real-time occupancy/vacancy of HVAC zones. Among all these approaches, wireless-camera-based sensing stands out for its potential application in surveillance and security in addition to energy management. However, limited lifetime and detection accuracy have prevented pervasiveness of wireless-camera-based occupancy detection. This paper presents a novel wireless device platform and prototype development that incorporates an infrared (IR) camera with an optical (OP) camera to provide collaborative intelligence at low power and enhanced accuracy. Compared to the single-sensor baseline design, the proposed fusion-based OP/IR design demonstrates $5\times$ miss rate improvement, $5\times$ reduction in false positive rate, and $3\times$ lifetime extension for battery usage with respect to a single-sensor-based design. Compared to a programmed thermostat and schedule-based HVAC control, the design saves a maximum of $26\%$ of HVAC energy. [ABSTRACT FROM AUTHOR]

Linear-machine-based direct-drive systems are attracting extensive attention for many industrial applications including wave energy conversion and railway traction. By using a linear machine, the complexity of linear motion systems is considerably reduced due to the elimination of the rotary to linear conversion mechanism. In this paper, a novel linear stator spoke-type permanent magnet (PM) vernier (LSSPMV) machine is presented in which the surface-mounted radial magnets used in conventional linear stator-PM vernier machines are replaced by spoke-type magnets that are magnetized parallel to the direction of motion. The proposed machine adopts a non-magnetic space between PMs and stator pole shoes decreasing the leakage flux and leading to higher flux linkage of armature winding. After designing the proposed LSSPMV machine and comparing it with its existing counterpart, the finite-element method results reveal that the thrust force density and the efficiency of the proposed machine are higher than that of the existing one as a result of utilizing spoke-type PMs. [ABSTRACT FROM AUTHOR]

Power electronic converter-interfaced distributed energy resources (DERs) are being increasingly deployed for achieving high energy efficiency, power quality, and flexibility of power system operation and controls. They facilitate access to a wide array of energy sources, including renewables, fuel cells, microturbines, variable speed engine-generator sets, etc. However, recent tests carried out at the Consortium for Electric Reliability Technology Solutions (CERTS) Microgrid have indicated that their deployment in the mixed source microgrid can cause a cascading collapse during extreme events. To investigate the problem, simulation models of two types of DERs are developed in PSCAD/EMTDC software and validated with the experimental test results. Furthermore, the validated models are used to study a cascading collapse problem in a large-scale mixed source microgrid on the benchmark IEEE 33-bus test system. In this paper, three alternative techniques are evaluated to prevent the cascading collapse in the large-scale microgrid caused by fast-acting inverter-based DERs. [ABSTRACT FROM AUTHOR]

In traditional cognitive radio networks (CRNs), the interweave, underlay, overlay, and hybrid spectrum sharing schemes are only spectrum-efficient in specific circumstances. In order to improve the robustness of spectrum sharing schemes in a dynamic traffic environment from the perspective of energy efficiency, adaptive spectrum sharing schemes are proposed in this paper for both half-duplex (HD) and full-duplex (FD) CRNs. The proposed schemes allow the secondary users to adaptively access the licensed spectrum, provided that PUs’ traffic arrives at a low rate and energy efficiency gains exist. Based on the intermittent nature of the arrival and departure processes for PUs’ traffic, closed-form expressions of energy efficiency for the traditional interweave, underlay, overlay, hybrid and the proposed schemes are investigated for both HD and FD modes. By defining energy efficiency loss, the impacts of the spectrum sensing error and channel estimation error are analyzed to evaluate the energy efficiency of the proposed schemes. Theoretical analysis shows that the proposed adaptive spectrum sharing schemes improve the minimum energy efficiency in HD mode and improve the overall energy efficiency in FD mode. The numerical results validate the energy efficiency improvements and the robustness of the proposed schemes. [ABSTRACT FROM AUTHOR]

As power density emerges as the main constraint for many-core systems, controlling power consumption under the thermal design power while maximizing the performance becomes increasingly critical. To dynamically save power, dynamic voltage frequency scaling techniques have proved to be effective and are widely available commercially. Meanwhile, systems have certain performance constraints that the applications should satisfy to ensure quality of service. In this paper, we present an online distributed reinforcement learning (OD-RL)-based DVFS control algorithm for many-core system performance improvement under both power and performance constraints. At the finer grain, a per-core RL method is used to learn the optimal control policy of the voltage/frequency (VF) levels in a model-free manner. At the coarser grain, an efficient global power budget reallocation algorithm is used to maximize the overall performance. The experiments show that compared to the state-of-the-art algorithms: 1) OD-RL produces up to 98% less budget overshoot; 2) up to 23% higher energy efficiency; and 3) two orders of magnitude speedup over state-of-the-art techniques for systems with hundreds of cores. Furthermore, priority-aware OD-RL can better satisfy performance constraints than OD-RL with: 1) $17.8\boldsymbol {\times }$ more epochs satisfying the performance constraints; 2) $5.6\boldsymbol {\times }$ better performance gain; and 3) $20.0\boldsymbol {\times }$ better performance-power tradeoffs under similar efficiency and scalability. [ABSTRACT FROM AUTHOR]

The study of transmission lines forms an integral part of any curriculum in electrical engineering. This paper presents some little-known but interesting facts about transmission lines, which are generally not found in textbooks, along with some new facts, which arose as extensions of these little-known ones. The facts highlighted in this paper are that: 1) the real part of the characteristic impedance is always greater than the magnitude of its imaginary part; 2) the real and imaginary parts of the characteristic impedance and the propagation constant are interrelated by four inequalities; 3) the magnitude of the load reflection coefficient ( \vert \Gamma L \vert ) may exceed unity, even for a passive load; 4) the concepts of incident power and reflected power, as usually employed in dealing with lossless lines, are not, in general, valid in a lossy line; 5) the law of power conservation is not violated because of Fact 3; and that 6) the maximum value of \vert \Gamma L \vert depends on whether the load or the characteristic impedance is variable and whether the load is active or passive. [ABSTRACT FROM PUBLISHER]

Recently, battery-powered wireless sensor network (WSN) technology has been applied on various environment detections. The capacity of the battery, however, limits the working time of the sensor. The conventional censoring scheme, in which either the entire log-likelihood ratio (LLR) value is transmitted or only a single-bit indicating signal, namely "1," is sent to the fusion center (FC) if the LLR falls within the "send" region, has been introduced for reduced communication rate in a parallel fusion network where decisions made at local nodes need to be communicated to an FC. In this paper, a new sensor-censoring scheme is proposed to further exploit its energy-efficiency capability. As opposed to conventional censoring schemes, the proposed scheme allows each sensor to transmit a binary decision, i.e., either "1" or "-1," to the FC only when the reliability of its observation on the environment is beyond a given level. The binary hypothesis on the phenomenon of the environment in WSNs has been assumed, and the error performance of the binary code applied for data transmission to the FC under the considered censoring strategy has been analyzed. Under the proposed censoring scheme, the main problem of this paper is to minimize the fusion errors via obtaining the optimum energy saving rate. The result obtained from the conducted examples confirms that the goal of energy saving by the proposed scheme is archived. [ABSTRACT FROM AUTHOR]

This paper describes energy management architecture for multimedia applications in battery powered devices to dynamically control the energy consumption of the device with an effort to increase the battery life. The architecture is divided into two parts, a not notification manager and a controller. The notification manager is a generic block and is implemented as part of the system software. It consists of a module that continuously monitors the battery state and sends out notifications. The controller is application specific. The notification manager issues notifications to the multimedia applications to operate under different energy modes based on an energy management algorithm proposed in the paper. The paper describes the implementation of the architecture for multimedia applications as they are the most energy consuming components in a handheld device. Experimental results provided at the end of the paper show the effectiveness of the described architecture. The notification manager also incorporates prediction and sensory modules to utilize the real world scenarios and achieve maximum energy saving. [ABSTRACT FROM AUTHOR]

Location-based services (LBSs), considered as a killer application in the wireless data market, provide information based on locations specified in the queries. In this paper, we examine the indexing issue for querying location-dependent data in wireless LBSs; in particular, we focus on an important class of queries, planar point queries. To address the issues of responsiveness, energy consumption, and bandwidth contention in wireless communications, an index has to minimize the search time and maintain a small storage overhead. It is shown that the traditional point-location algorithms and spatial index structures fail to achieve either objective or both. This paper proposes a new index structure, called D-tree, which indexes spatial regions based on the divisions that form the boundaries of the regions. We describe how to construct a binary D-tree index, how to process queries based on the D-tree, and how to page the binary D-tree. Moreover, two parameterized methods for partitioning the original space, called fixed grid assignment (FGA) and adaptive grid assignment (AGA), are proposed to enhance the D-tree. The performance of the D-tree is evaluated using both synthetic and real data sets. Experimental results show that the proposed D-tree outperforms the well-known indexes such as the R*-tree, and that both the FGA and AGA approaches can achieve different performance trade-offs between the index search time and storage overhead by fine-tuning their algorithmic parameters. [ABSTRACT FROM AUTHOR]

In this paper, we propose a complete active-power-management scheme for the control of battery energy-storage systems (BESSs) for two main applications: 1) photovoltaic (PV) capacity firming and 2) energy time shift (ETS). In the proposed approach, first two control algorithms are designed to provide active-power set points to BESS for the above applications. Then, an optimization routine for integrating these controllers is designed. The proposed approach uses an energy-conservation method to integrate these two applications of energy-storage system. The designed algorithm was tested on a transient simulation platform and then implemented on a 720-node actual power distribution feeder. The main advantage of the proposed method is that the algorithm can be used to optimize multiple functions and perform simultaneous control of BESS. [ABSTRACT FROM AUTHOR]

With the advancement of wireless energy harvesting and transfer technologies, e.g., radio frequency (RF) energy, mobile nodes are fully untethered as energy supply is more ubiquitous. The mobile nodes can receive energy from wireless chargers, which can be static or mobile. In this paper, we introduce the use of a mobile energy gateway that can receive energy from a fixed charging facility, as well as move and transfer energy to other users. The mobile energy gateway aims to maximize the utility by optimally taking energy charging/transferring actions. We formulate the optimal energy charging/transferring problem as a Markov decision process (MDP). The MDP model is then solved to obtain the optimal energy management policy for the mobile energy gateway. Furthermore, the optimal energy management policy obtained from the MDP model is proven to have a threshold structure. We conduct an extensive performance evaluation of the MDP-based energy management scheme. The proposed MDP-based scheme outperforms several conventional baseline schemes in terms of expected overall utility. [ABSTRACT FROM AUTHOR]

Today, an ever-increasing number of devices has networking capability. The main implication of this fact is that such devices are often left fully powered yet idle just to maintain their network presence, hence leading to large energy waste. This ultimately results in higher electricity cost for consumers. This paper tackles an effective mechanism to reduce energy waste of consumer electronics, by boosting the usage of lowpower states available in most devices. The main concept is to delegate background networking routines to home gateways, which are today available in most homes and offices. The paper describes the functionality and the software architecture to be implemented by home gateways and consumer electronics, reports performance evaluation on a working prototype, and provides estimation of potential benefits for consumers. [ABSTRACT FROM AUTHOR]