Power Supply Constraints Research Articles

Consideration of reliability and economy to Capacity Configuration of energy storage system: Case Study of a large scale wind power plant in the Northwest China

Currently, a serious operation security problem of wind power plant has caused by the massive wind power integration, which has increased the difficulty of the operation in large scale wind power plant. Energy storage system (ESS) is thought the best choice to solve the operation scheduling problem of large-scale wind power plant, therefore, under the premise of ensuring the reliability of power supply and network constraints, it is particularly significant to select the proper capacity with both economy and feasibility, aiming at the problems above, this paper constructs capacity configuration of storage which is of statistical significance by studying the probability distribution characteristics, aiming at the deviation load during the operation of wind power plant, utilized Monte Carlo simulation, through whole lifetime NPV, payback period PBP and operation scheduling deviation OOD to verify the reliability and economy of the capacity. Finally, the actual operation data from a wind power plant installed 99MW in Northwest of China is utilized as a case study, simulation result shows that it could get the best storage capacity under the standard of the characteristics of economic and reliability criteria, which proves the validity and feasibility of the method in this paper.

A model predictive scheduling algorithm in real-time control systems

The ineffective utilization of power resources has attracted much attention in current years. This paper proposes a real-time distributed load scheduling algorithm considering constraints of power supply. Firstly, an objective function is designed based on the constraint, and a base load forecasting model is established when aggregating renewable generation and non-deferrable load into a power system, which aims to transform the problem of deferrable loads scheduling into a distributed optimal control problem. Then, to optimize the objective function, a real-time scheduling algorithm is presented to solve the proposed control problem. At every time step, the purpose is to minimize the variance of differences between power supply and aggregate load, which can thus ensure the effective utilization of power resources. Finally, simulation examples are provided to illustrate the effectiveness of the proposed algorithm.

Joint optimization of high-speed train timetables and speed profiles: A unified modeling approach using space-time-speed grid networks

This paper considers a high-speed rail corridor that requires high fidelity scheduling of train speed for a large number of trains with both tight power supply and temporal capacity constraints. This research aims to systematically integrate problems of macroscopic train timetabling and microscopic train trajectory calculations. We develop a unified modeling framework using three-dimensional space-time-speed grid networks to characterize both second-by-second train trajectory and segment-based timetables at different space and time resolutions. The discretized time lattices can approximately track the train position, speed, and acceleration solution through properly defined spacing and modeling time intervals. Within a Lagrangian relaxation-based solution framework, we propose a dynamic programming solution algorithm to find the speed/acceleration profile solutions with dualized train headway and power supply constraints. The proposed numerically tractable approach can better handle the non-linearity in solving the differential equations of motion, and systematically describe the complex connections between two problems that have been traditionally handled in a sequential way. We further use a real-world case study in the Beijing-Shanghai high-speed rail corridor to demonstrate the effectiveness and computational efficiency of our proposed methods and algorithms.

Wireless Communications With RF-Based Energy Harvesting: From Information Theory to Green Systems

Harvesting energy from ambient environment is a promising technology to free electronic devices from electric wire and lifetime-limited battery, which have found many significant applications in sensor networks and body-area networks. This paper investigates the fundamental limit of information transmission in a wireless communication system with RF-based energy harvesting, where a master node acts both the information source and the energy source for a child node, while only information is transmitted back from the child node to the master node. In the systemic level viewpoint, we jointly investigate the two-way information transmission between the two nodes under the unique external power supply constraint at the master node. In particular, three typical receivers are considered, including the optimum receiver, the orthogonal receiver and the power splitting receiver. We explicitly characterize the achievable capacity-rate region and discuss the effect of signal processing power consumption at the child node. We also derive the boundary of the achievable capacity-rate region, which illustrates the most energy-efficient transmission strategy of the system. Simulation results confirm the substantial gain of employing capacity-rate region achieving transmission strategies and employing optimal receivers. Moreover, we present a typical application of our results, where the required transmit power is minimized to green the system.

Multi‐objective optimal configuration method for a standalone wind–solar–battery hybrid power system

With the development of the energy internet, the standalone wind–solar–battery hybrid power system has gradually become an effective means for the complete utilisation of clean energy for power generation. The allocation of the various types of power sources for ensuring a reliable power supply and for improving the economic efficiency of a system is a crucial issue in the system planning and design stages. The models of the power load and the power sources, containing random components, are first established in this study, based on which the power supply reliability and constraint conditions for the equipment quantities are considered for establishing various evaluation indexes for improving the system performance. Then, according to the combinations of the natural selection particle swarm optimisation algorithm and the weight coefficient transform method, a multi-objective optimisation algorithm is proposed for optimising the configuration of a standalone wind–solar–battery hybrid power system. Finally, it is demonstrated by an example that the optimisation method not only meets the requirements of the multi-objective optimisation system but is also significant in reducing energy wastes and fluctuations, cost saving, and in ensuring the reliability of the power supply.

A range estimation system using coded ultrasound

Touchless human–computer interfaces, augmented reality, and mixed reality, need the location of user’s limbs or direction of sight in real time, which can be provided by accurate Real Time Locating Systems (RTLS). RTLS can be realized using wireless accurate positioning sensors and multilateration techniques that compute the location of sensors from distance estimates between them and a set of reference points. The main practical difficulty relies in estimating, within the required accuracy, the distances between the reference points and the remote sensors. In addition, the majority of modern applications require miniaturized sensors with both severe size and power supply constraints, and thus limited computational power. In this work, a distance estimation technique using coded ultrasound and a miniaturized sensor is proposed. A prototype of the distance estimation system has been realized and characterized. It is composed of a beacon that emits a coded ultra-acoustic signal, a central processing unit (CPU), and a wireless distance sensor. The main advantages of the proposed system are the high miniaturization and low power of the remote sensor.

Modeling and Design Optimization of an Autonomous Multisource System Under a Permanent Power-Supply Constraint

In this paper, we aim to optimize the sizing of an autonomous multisource system in order to minimize the cost of the installation and to improve the dynamic behavior of the whole system. The multisource system comprises a solar generator, a wind generator (WG), a diesel generator (DG), and a lead-acid battery bank. The modeling of such a system is done by using the power model to describe the behavior of each subsystem. The cost of the multisource system is estimated by implementing the embodied energy (EE) concept. A dynamic simulator (DS) has been developed. Due to the complexity of the multisource system in terms of input variables and meteorological data, the simulation becomes difficult, requiring high-performance computing and moreover, the determination of the optimal configuration is not assured. Therefore, we propose to simplify the model by introducing the design of experiment (DOE) approach. The obtained model has been validated and used to perform a single-objective optimization. This model allows us to ensure the simulation of the multisource system efficiently and faster. An optimal configuration has been determined.

Implantable biomedical devices: Wireless powering and communication

In recent years, there has been major progress on implantable biomedical systems that support most of the functionalities of wireless implantable devices. Nevertheless, these devices remain mostly restricted to research, in part due to limited miniaturization, power supply constraints, and lack of a reliable interface between implants and external devices. This article provides a tutorial on the design of implantable biomedical devices that addresses these limitations. Specifically, it presents analysis and techniques for wireless power transfer and efficient data transfer from both theoretical and practical standpoints. Their potential implementations are also discussed.

Solenoid-free startup experiments in DIII-D

A series of DIII-D experiments was performed to investigate the potential for initiating plasma current using only poloidal field coils located outside the DIII-D central solenoid, i.e. ‘solenoid-free’. Plasma current to 166 kA was achieved using 2–3 MW of electron cyclotron (EC) heating and was limited by coil and power supply constraints. Flux conversion to plasma current was similar to standard DIII-D startup with some degradation at higher plasma current associated with stray fields and vertical stability issues. In preliminary solenoid-free experiments, neutral beam (NB) current drive (CD) levels were small and attributed to reduced CD efficiency associated with low electron temperature produced by the low current, low confinement plasma. Lack of plasma radial position control also contributed to a reduction of NBCD. Similarly, ECCD was small owing to low plasma temperature and outside EC launch which is required in the solenoid-free scenario. Synergistic experiments were carried out using standard solenoid initiated plasmas in order to study noninductive CD in limited, Lmode plasmas, typical of that generated by solenoid-free startup. While substantial noninductive current can be driven, self-sustaining levels of noninductive current have not yet been achieved with our present six-source co-injection NB system combined with EC and fast wave systems. At low plasma current and high levels of localized EC heating, substantial MHD is generated and this was seen to severely limit plasma performance. Although further optimization is possible in the limited plasma regime, full noninductive, steady-state operation may require diverted plasma with H-mode quality confinement. Discharges obtained during the solenoid-free campaign are compared with results of previous DIII-D campaigns aimed at achieving a steady state, noninductive CD solution.

Performance analysis of a delay tolerant application for herd localization

Target localization feasibility may depend on economical and environmental reasons and not only on technical ones as it is considered frequently. Thus, equipment costs may exceed the target value and system operation/deployment may demand tasks which collide with environmental regulations or simply do not pay off if they are compared to the gained advantage. Different solutions have been deployed for animal localization which may require satellite transmitters or employ solar energy as a workaround for power supply constraints. However, the former can turn out to be expensive and the latter useless in latitudes with limited sunlight. We analyze the performance of a localization system which aims to overcome the aforementioned issues in herding environments. Different kinds of nodes along with flexible duty cycles leverage the system adaptiveness, meeting users’ needs and complying with different environmental policies. Our analyses are based on real tests and combinations of such modeling with simulations. As a consequence of the system flexibility, the analyzed configurations exhibit wide ranges for magnitudes such as localization delay and localization events.

Power capping: a prelude to power shifting

We present a technique that controls the peak power consumption of a high-density server by implementing a feedback controller that uses precise, system-level power measurement to periodically select the highest performance state while keeping the system within a fixed power constraint. A control theoretic methodology is applied to systematically design this control loop with analytic assurances of system stability and controller performance, despite unpredictable workloads and running environments. In a real server we are able to control power over a 1 second period to within 1 W and over an 8 second period to within 0.1 W. Conventional servers respond to power supply constraint situations by using simple open-loop policies to set a safe performance level in order to limit peak power consumption. We show that closed-loop control can provide higher performance under these conditions and implement this technique on an IBM BladeCenter HS20 server. Experimental results demonstrate that closed-loop control provides up to 82% higher application performance compared to open-loop control and up to 17% higher performance compared to a widely used ad-hoc technique.

Scheduling and Admission Control in Power-Constrained OFDM Wireless Mesh Routers: Analysis and Optimization

We investigate the packet-level and the connection-level performances in a power-constrained (e.g., solar-powered) wireless mesh router with packet scheduling and admission control. The system model under consideration is compatible with the IEEE 802.16a standard with orthogonal frequency division multiple access (OFDMA) air interface. In the medium access control (MAC) layer, transmission frames are grouped into super-frames and the allocation of subchannel and number of frames to each connection (i.e., scheduling) is performed to satisfy the traffic requirement of each connection and also the power supply constraint at a mesh router/802.16a base station (BS). A queueing analytical model based on discrete-time Markov chain (DTMC) is used to analyze the packet-level performances. Based on this scheduling, router capacity in terms of the maximum number of ongoing connections is obtained. Subsequently, a threshold-based admission control method is proposed for both relay and local connections in a router so that connection-level performances are satisfied. To this end, we optimize the admission control over multiple time periods in which the amount of supplied power and the traffic load at a mesh router are time-dependent.

Real-time multimedia processing in video sensor networks

Video sensor networks (VSNs) has become the recent research focus due to the rich information it provides to address various data-hungry applications. However, VSN implementations face stringent constraints of limited communication bandwidth, processing capability, and power supply. In-network processing has been proposed as efficient means to address these problems. The key component of in-network processing, task mapping and scheduling problem, is investigated in this paper. Although task mapping and scheduling in wired networks of processors has been extensively studied, their application to VSNs remains largely unexplored. Existing algorithms cannot be directly implemented in VSNs due to limited resource availability and shared wireless communication medium. In this work, an application-independent task mapping and scheduling solution in multi-hop VSNs is presented that provides real-time guarantees to process video feeds. The processed data is smaller in volume which further releases the burden on the end-to-end communication. Using a novel multi-hop channel model and a communication scheduling algorithm, computation tasks and associated communication events are scheduled simultaneously with a dynamic critical-path scheduling algorithm. Dynamic voltage scaling (DVS) mechanism is implemented to further optimize energy consumption. According to the simulation results, the proposed solution outperforms existing mechanisms in terms of guaranteeing application deadlines with minimum energy consumption.

Software implementation strategies for power-conscious systems

A variety of systems with possibly embedded computing power, such as small portable robots, hand-held computers, and automated vehicles, have power supply constraints. Their batteries generally las...

Quench protection studies of LHC interaction region quadrupoles at Fermilab

High gradient quadrupoles are being developed by the US-LHC Accelerator Project for the LHC interaction region inner triplets. Protection strip heaters are the primary means of protecting these magnets against excessively high coil temperatures and coil voltage to ground as a result of a spontaneous quench. The main objective of the quench protection R&D program is to optimize the heater performance within the constraints of the LHC heater power supply and quench detection system. The results of these studies on several two meter long model magnets are presented.

Desirability Of Electro-Optic Materials For Guided-Wave Optics

An illustrative, device-systems-level desirability optimization analysis is performed for a number of important electro-optic materials that are candidates for use in high-speed guided-wave optical devices. Ferroelectric materials with high and low transition temperatures, cubic crystals, organic crystals, and alloy semiconductors are considered. The simple bulk (lumped-type) guided-wave phase modulator is taken as the initial screening device. Performance measures such as electrical power supply constraints and the device's maximum operating speed are analyzed as a function of system variables that include material properties and electrode architectures. A desirability analysis is presented as a composite mathematical function that describes two or more indepen-dent performance measures in terms of all relevant system variables. This function is displayed graphically to identify those sets of system variables that jointly optimize the performance measures of greatest interest. The initial screening analysis ignores propagation loss and less-than-ideal overlap between electrical and optical fields. Potassium niobate, barium titanate, and lithium niobate are found to be among the more desirable electro-optic materials. The use of dielectric buffer layers, several thousand angstroms thick, is found necessary to isolate the modulator electrodes from materials of high dielectric constant, high electro-optic strength such as potassium niobate. Buffer layers, however, are generally unnecessary when the lower permittivity and lower electro-optic strength materials such as lithium niobate are used.

Power supply constraints in megabit DRAMs of the future

La densite des memoires DRAM a ete multipliee par quatre tous les trois ans. Le developpement des memoires a 1Mb est d'ores et deja tres avance. L'evolution de l'alimentation est donc d'importance capitale etant donne les reductions des dimensions qui sont intervenues