Peak Power Consumption Research Articles

Application of Fast-Charging Graphite-Anode Lithium-Ion Batteries in Black Start

Industrial and commercial energy storage are widely used. Large industrial users can adjust the peak and valley power consumption during the summer peak power consumption to reduce the burden on transformers and to gain certain benefits from the peak and valley power difference. For users with important loads, the energy storage system is a alternative power supply to ensure the continuity of power supply for important loads. This paper systematically introduced the research progress based on the optimization of electrolyte and charging strategy in the field of improving the rapid charging of graphite anodes in recent years, which provided a reference for promoting the commercial application of rapid charging technology and the high-quality development of domestic energy storage technology. The high-power energy storage battery, in particular, can recover power supply as soon as possible after large-scale power system shutdown accidents or even power outages, reducing economic losses and social impact.

Efficient Dynamic Reconfigurable CNN Accelerator for Edge Intelligence Computing on FPGA

This paper proposes an efficient dynamic reconfigurable CNN accelerator (EDRCA) for FPGAs to tackle the issues of limited hardware resources and low energy efficiency in the deployment of convolutional neural networks on embedded edge computing devices. First, a configuration layer sequence optimization method is proposed to minimize the configuration time overhead and improve performance. Second, accelerator templates for dynamic regions are designed to create a unified high-speed interface and enhance operational performance. The dynamic reconfigurable technology is applied on the Xilinx KV260 FPGA platform to design the EDRCA accelerator, resolving the hardware resource constraints in traditional accelerator design. The YOLOV2-TINY object detection network is used to test the EDRCA accelerator on the Xilinx KV260 platform using floating point data. Results at 250 MHz show a computing performance of 75.1929 GOPS, peak power consumption of 5.25 W, and power efficiency of 13.6219 GOPS/W, indicating the potential of the EDRCA accelerator for edge intelligence computing.

Optimal scheduling of park-level integrated energy system considering ladder-type carbon trading mechanism and flexible load

In an attempt to improve the utilization efficiency of multi-energy coupling in park-level integrated energy system (PIES), promote wind power consumption and reduce carbon emissions, a low-carbon economic operation optimization model of PIES integrating flexible load and carbon trading mechanism is constructed. Firstly, according to the characteristics of load response, the demand response is divided into four types: which can be shifted, transferred, reduced and replaced. Secondly, the PIES basic architecture is given by considering the combined heat and power generation coupling equipment, new energy and flexible load in the park. Finally, introducing the ladder-type carbon trading mechanism into the system and minimize the total operating cost, the low-carbon economic operation optimization model of PIES is established. The YALMIP toolbox and CPLEX solver are used to solve the example, the simulation results show that the participation of electrical and thermal coupled scheduling and flexible electric or thermal loads can significantly reduce the system operating cost, reduce the load peak-to-valley difference and relieve peak power consumption pressure.

Automating the Generation of Programs Maximizing the Sustained Switching Activity in Microprocessor units via Evolutionary Techniques

During device testing, an important parameter to be considered by the test engineers is the switching activity (SWA) of the circuit under test (CUT). It is well known that the SWA must be kept to a minimum in order to avoid catastrophic scenarios on the CUTs, e.g., unacceptable peak power consumption or over-stressing that can lead to an artificial yield loss. However, there are scenarios, where the inverse, namely the switching activity maximization, can be proven beneficial. For example, this happens during Burn-In testing, when we aim at exercising the circuit under extreme operating conditions in terms of temperature and temperature gradients to accelerate aging phenomena in a controlled manner. In some cases, this is achieved by applying to the CUT stimuli in a functional manner, based on the Software-Based Self-Test (SBST) paradigm. Though, the generation of such appropriate programs for this task represents a challenge for the test engineers. In this paper we consider the scenario where the modules to be stressed are the units of a pipelined processor. We present a method, based on an evolutionary approach, that is able to automatically generate maximum stress programs, i.e., sequences of instructions achieving a high switching activity in the target module. With respect to other approaches, the generated sequences are built from the ground-up, are short and repeatable, thus guaranteeing their easy usability to stress a module (and increase its temperature). The processor we used for our experiments is the Open RISC 1200. Results demonstrate that the generated stimuli from the proposed method are effective in achieving a high value of sustained switching activity within the considered processor modules while also achieves a better results when comparing with other methods (e.g., stuck-at oriented test programs).

A Supplemental Lighting Control Approach in Controlled Environment Agriculture to Reduce Peak Power Consumption

Global population growth requires efficient food production, especially with food security concerns due to natural resources limitation and climate constraints. Supplemental lighting is an effective means of increasing productivity in greenhouses. However, supplemental lighting electricity cost can be high, and systematic lighting strategies are required to reduce lighting electricity cost. Prior research has focused on minimizing electricity use or cost, while maintaining adequate crop growth. However, in addition to being charged for electricity consumption, US greenhouse growers also pay a demand charge that is based on the peak electricity use during a 15-min period within each billing cycle. This demand charge is in the same order of magnitude as the charge for the used electricity, but has been ignored in prior lighting optimization research. This paper presents a lighting strategy for controlled environments (like greenhouses) equipped with dimmable light-emitting diodes (LEDs) to minimize supplemental lighting electricity cost and peak power consumption of supplemental lighting. Markov-based sunlight prediction is employed to develop a realistic control strategy and improve its efficiency. Moreover, the impact of shifting the time of day during which supplemental lighting is used on peak power consumption is investigated. Compared to a heuristic method, the proposed method illustrates an up to 51% mean peak reduction.

Bi-objective speed-scaling robotic cell scheduling with peak power consumption constraint

This article studies the speed-scaling robotic cell scheduling problem with constrained peak power consumption. The objective is to minimize cycle time and peak power consumption simultaneously. First, we formulate a bi-objective mixed integer programming model for the problem and propose a strategy to preprocess overlapping time windows. Then, we analyze the structural properties of the proposed model and develop an iterative $ \varepsilon $-constraint method to generate its complete Pareto front. Numerical experiments demonstrate that the proposed method effectively solves the robotic cell scheduling problem and that appropriate scheduling of speed-scaling machines can make a trade-off between productivity and power consumption.

Heuristics and metaheuristics to minimize makespan for flowshop with peak power consumption constraints

This paper addresses the permutation flowshop scheduling problem with peak power consumption constraints (PFSPP). The real-time power consumption of the PFSPP cannot exceed a given peak power at any time. First, a mathematical model is established to describe the concerned problem. The sequence of operations is taken as a solution and the characteristics of solutions are analyzed. Based on the problem characteristics, eight heuristics are proposed, including balanced machine-job decoding method, balanced machine-job insert method, balanced job-machine insert method, balanced machine-job group insert method, balanced job-machine group insert method, greedy algorithm, beam search algorithm, and improved beam search algorithm. Similarly, the canonical artificial bee colony algorithm and iterated local search algorithm are modified based on the problem characteristics to solve the PFSPP. A large number of experiments are carried out to evaluate the performance of new proposed heuristics and metaheuristics. The results and discussion show that the proposed heuristics and metaheuristics perform well in solving the PFSPP.

Test and Research on Load Capacity of a 210MW Unit in Heating State

As large-scale photovoltaic and wind power are integrated into the power grid, new energy power generation has strong randomicity, volatility and anti-peak shaving characteristics. Both the power supply side and the load side of the power grid will have random fluctuations, which brings huge challenges to the safe and stable operation of the power grid. The power grid will need more capacity and more flexible peak shaving resources as the basis for ensuring the smooth and orderly power supply. During the heating period, the thermoelectric units are faced with double pressures of power consumption peak and heating peak, and are forced to further increase and reduce output to meet the requirements of heating. Therefore, carrying out load capacity test on heating units is conducive to finding out the real output range of units and providing data support for power grid departments.

The Design and Testing of a PEA Powered Ankle Prosthesis Driven by EHA.

Several studies have shown that actuation concepts such as Serial elastic actuator (SEA) can reduce peak power and energy consumption in ankle prostheses. Proper selection and design of the actuation concepts is important to unlock the power source potential. In this work, the optimization design, mechanical design, control scheme, and bench experiments of a new powered ankle-foot prosthesis is proposed. The actuation concept of this prosthesis is parallel elastic actuator (PEA) composed of electro-hydrostatic actuator (EHA) as the power kernel and a unidirectional parallel spring as the auxiliary energy storage element. After the appropriate motor and transmission ratio was selected, a dynamic model of the PEA prosthesis was built to obtain the appropriate spring parameters driven by biological data. The design of the hydraulic and mechanical system and the controller were provided for the implementation of the designed system. Bench experiments were performed to verify the performance. The results showed that the designed prosthesis meets the biomechanical dynamics requirements. This result emphasizes the feasibility of the EHA as a power source and actuator and provides new ideas for the design of ankle-foot prostheses.

Zero fluctuation: Electric-fluctuation-elimination heat pump system with water storage tank based on time-of-use tax

Due to the difference of heating load between day and night, the power load of heat pump heating system varies greatly day and night. Furthermore, the rapid growth of heat pump heating systems for meeting the requirement of low carbon heating will result in more and more serious electricity fluctuation, which will threaten the stability of the power grid. In order to reduce this power fluctuation, a single-heat-pump heating system with water tank thermal storage (SHPHSTS) is constructed. Based on the thermodynamic calculation of the heat pump refrigeration cycle, using step search optimization method, the operation parameters of the constructed heating system are optimized with the goal of constant power consumption from power grid within a day. Then, the corresponding electricity consumption and power fluctuation, after adopting the proposed operation optimization strategy in heating season are analyzed. At last, function of power fluctuation (FL) and degree of fluctuation (DF and DF’) are proposed to quantitatively evaluate the effect of the power fluctuation reduction in heating season, and the correlation between the electricity consumption of the heating system and power grid load is analyzed. The results show that due to the thermal storage of HWST and the optimizing operation strategy, constant power consumption of heating system could be realized within a day. On the typical heating day, the power consumption in traditional peak time reduces by 60.8%, and the electric bill is 22% lower compared with that of the traditional heat pump heating system. Furthermore, the power consumption fluctuation during the whole heating season reduces substantially, the power fluctuation function reduces from 460% to 150% by adopting the proposed operation optimization strategy. The correlation analysis indicates that the busy degree of power grid in peak time could be relieved by thermal storage and the optimizing operation strategy. Consequently, the peak of power consumption of heat pump heating system could be decoupled from the peak of power grid.

Energy Management for an Air Conditioning System Using a Storage Device to Reduce the On-Peak Power Consumption

To reduce the on-peak electrical power consumption, storage devices are widely performed with the help of an energy management system. According to IEA, residential air conditioning consumes 70% of the electricity, increasing by 4% every year. To minimize peak power consumption, thermal energy storage (TES) can be used to store cooled water for the air conditioning system. An efficient chilled water tank was designed and computationally investigated. Three-dimensional cylindrical tanks were simulated with seven different heights to diameter (H:D) ratios. At first, the temperature changes in a chilled water tank during discharging and charging periods were studied. An 11-h charging period was carried out during the off-peak time at night, while the discharging period was 13 h during the daytime. Under time constraints regarding peak and off-peak periods, a tank with an H:D = 2.0 can only be used for 13-h discharging. Then the chilled water was simulated with a set temperature of 4 °C during the charging. This resulted in the system being usable for six days, after which it had to be stopped for longer charging. A storage tank with an H:D ratio of 2.0 was found to be suitable for an air conditioning system. If six days of operations (one day off) were used, it could save 15.38% of electrical energy consumption and 51.65% of electricity cost. This saving leads to a 5.55-year payback period.

Carbon-free energy optimization in intelligent communities considering demand response

With the gradual improvement in people’s quality of life, intelligent communities are received widespread attention and research. However, the massive use of various smart appliances causes a rapid increase in energy demand and carbon emissions. Therefore, in this paper, the novel carbon-free energy optimization method under the designed energy structure suitable for an intelligent community is proposed to deal with energy depletion and environmental pollution. First, the energy supply side makes full use of clean energy generation technologies to provide users with adequate energy, which is composed of photovoltaic (PV), wind turbine (WT) and hydrogen steam turbines. Second, considering the demand response (DR) of the load side, household appliances are modeled according to the working characteristics. Then, the energy treatment mode of renewable energy sources (RESs) grid-connected reverse transmission is changed. The power to hydrogen (P2H) technology is introduced into the energy structure of intelligent residential quarters to increase the proportion of hydrogen energy in the region. Moreover, the energy storage device and electrification technology are combined to realize the production and application of regional hydrogen and achieve the goal of non-carbonization of regional energy structure. Finally, in simulation part, the optimal solution in the scheduling cycle is obtained by YALMIP solver, and time-of-use (TOU) electricity prices are used to calculate the final electricity cost. It is displayed that carbon emissions and energy consumption cost can be reduced, and the pressure of peak power consumption relieved based on the designed non-carbonization energy structure and energy optimization method.

Electricity peak load reduction of a refrigerator using phase change material

Phase change material (PCM) has become a topic of study in thermal management, as it has a high-energy storage density. Most refrigerators have a fixed-speed compressor, which operates randomly (on/off) during their cycle. This leads to a high-power peak of electricity when the refrigerators start at the same time. Therefore, this study aims to investigate the reduction potential of the power peak and energy consumption of a refrigerator using PCM as a heat absorber. Nine testing conditions were performed by using water as the internal thermal load, at 1, 2, and 3 kg. Besides, each internal thermal load condition was varied with a PCM mass of 500, 1,500, and 2,500 g. The necessary data, such as the internal temperature and power of a refrigerator and the outside ambient temperature, were collected. The results show that the mass of PCM significantly affected the peak power of the refrigerator and energy consumption. Moreover, the results clearly show that the PCM can be used to reduce the peak power and energy consumption of the refrigerator. The correlation of the power, related to the mass of the internal heat load, and the mass of PCM was also reported. The conclusion of this study is that the PCM is suitable for reducing the peak power and energy consumption of a household refrigerator.

Adaptive Control of Energy Storage Systems for Real-Time Power Mediation Based on Energy on Demand System

The concept of i-Energy as a new smart demand-side energy management system is proposed, which can realize the versatile and efficient control of e-power flows between distributed generators, numerous appliances, and energy storage systems in the home domain, factories, offices, and local communities. The Energy on Demand (EoD) system is proposed, which is the automatic power control and management system that supplies power to home appliances based on the power demand requests issued from the home appliances. The EoD system can guarantee the reduction in total power consumption by implementing a ceiling control while keeping the quality of life (QoL) of the home user considering the limitation of power supply. This paper proposes an adaptive battery storage management and control method based on the EoD system, which we call the “storage-supported EoD system”. In particular, the storage-supported EoD system can handle multiple power generators, including storage batteries. The overall goals of this paper are not limited to the extension of multiple power supplies only; rather, it provides additional contributions, which are (i) extend the existing power consumption control of home appliances and peak demand shift control (i.e., EoD system) by adding a second power source, i.e., a storage battery system; (ii) propose adaptive storage system design and management for the EoD system; (iii) realize minimum storage capacity for large peak power consumption; and (iv) minimize the home user’s discomfort level due to the limited power supply of one power source. The simulation results have shown the effectiveness of the proposed algorithm with a couple of experiments using real-life data in the smart apartment room. Additionally, simulation results are presented to compare and evaluate the proposed system performance with the EoD system.

Investigation of chordwise functionally graded flexural rigidity in flapping wings using a two-dimensional pitch–plunge model

Insect wings are heterogeneous structures, with flexural rigidity varying one to two orders of magnitude over the wing surface. This heterogeneity influences the deformation the flapping wing experiences during flight. However, it is not well understood how this flexural rigidity gradient affects wing performance. Here, we develop a simplified 2D model of a flapping wing as a pitching, plunging airfoil using the assumed mode method and unsteady vortex lattice method to model the structural and fluid dynamics, respectively. We conduct parameter studies to explore how variable flexural rigidity affects mean lift production, power consumption and the forces required to flap the wing. We find that there is an optimal flexural rigidity distribution that maximizes lift production; this distribution generally corresponds to a 3:1 ratio between the wing’s flapping and natural frequencies, though the ratio is sensitive to flapping kinematics. For hovering flight, the optimized flexible wing produces 20% more lift and requires 15% less power compared to a rigid wing but needs 20% higher forces to flap. Even when flapping kinematics deviate from those observed during hover, the flexible wing outperforms the rigid wing in terms of aerodynamic force generation and power across a wide range of flexural rigidity gradients. Peak force requirements and power consumption are inversely proportional with respect to flexural rigidity gradient, which may present a trade-off between insect muscle size and energy storage requirements. The model developed in this work can be used to efficiently investigate other spatially variant morphological or material wing features moving forward.

A Smooth Nadir-Pointing Attitude Guidance law for Satellites Constrained by the Deviation of Sun-Pointing

This paper proposes a novel nadir-pointing guidance method for satellites constrained by the deviation of sun-pointing, to ensure the attitude of the satellite steering smoothly. The main idea of establishing the expected attitude contains two steps. Firstly, establishing a temporary attitude according to the nadir direction and the normal direction of the ecliptic. Secondly, in order to reduce the deviation between the expected Sun-pointing axis and the Sun-pointing direction, the temporary attitude will be rotated along one Euler axis, and ensure that the expected nadir-pointing axis fixed in the nadir direction at the same time. The nadir-pointing method provided in this paper overcomes the singular phenomenon that the expected attitude of the satellite flips, without serious loss of Sun-pointing. In this way, the peak expected angular velocity and the peak power consumption will be greatly reduced.

Thermal-Aware Standby-Sparing Technique on Heterogeneous Real-Time Embedded Systems

Low power consumption, real-time computing, and high reliability are three key requirements/design objectives of real-time embedded systems. The standby-sparing technique can improve system reliability while it might increase the temperature of the system beyond safe limits. In this paper, we propose a <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</u> hermal- <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</u> ware <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</u> tandby- <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</u> paring (TASS) technique that aims at maximizing the Quality of Service (QoS) of soft real-time tasks, which is defined as a function of the finishing time of running tasks. The proposed technique tolerates permanent and transient faults for multicore real-time embedded systems while meeting the Thermal Safe Power (TSP) as the core-level power constraint, which avoids thermal emergencies in on-chip systems. Executing the main and backup tasks on the cores at any power consumption below TSP guarantees that no thermal violation occurs. Our TASS proposed method provides an opportunity to remove the overlaps of the execution of main and backup tasks to prevent extra power consumption due to applying the fault-tolerant technique. Meanwhile, in order to maximize the QoS, we employ a heterogeneous platform to execute the main tasks as soon as possible on high-performance cores with more power budget. The backup tasks are executed on low power cores after finishing the main tasks. In this case, when the main task finishes successfully, the whole of its corresponding backup task can be dropped, resulting in a significant amount of power and temperature reduction. Therefore, in the fault-free scenarios, the spare cores can be powered down, and only the main tasks are scheduled and executed on the primary cores. Experiments show that our proposed method improves QoS up to 39.78% (on average by 18.40%) and reduces the peak power consumption and temperature by up to 40.21% and 15.47˚C (on average 28.31% and 13.60˚C), respectively, at runtime, while keeping the system reliability at the required level.

Sensor Fusion Based Intelligent Hydroponic Farming and Nursing System

In this paper, a sensor-fusion based smart hydroponic system has been proposed. The system aims to monitor and regulate environmental conditions to boost the yield of plants grown using hydroponics. The system employs multiple sensors synchronized to work and communicate to a common server giving shape to sensor fusion and the Internet of Things. The proposed system reduces human intervention to a minimum, by operating autonomously. The Random Forest algorithm has been used to help the system identify the ambient parameter to be regulated based on priority, thus making the system intelligent. By using the randomized priority-based selection of operations, the algorithm determines the parameter to be altered, based on the input from the sensors, reducing the sensor crowding problem. The ability to regulate nutrient concentration is a salient feature of the proposed system. Sensor fusion along with the Random Forest algorithm has been implemented in a hardware prototype of the proposed system. The system was able to save 20.4% of the peak power consumption while temperature and water level regulation and 82.1 % of peak power while light regulation, thus making the system smarter and more energy-efficient for a hydroponic system.

A reconfigurable test method based on LFSR for 3D stacking integrated circuits

The specificity of the 3D integrated circuit and the changes in the design integration flow bring many new problems to the test process, such as reducing the controllability of the test and increasing the test cost. To address these problems, this paper proposes a low-power hybrid test scheme based on multiple reconfigurable linear feedback shift register(LFSRs) for 3D integrated circuit, which can reuse the test vector generator of the pre-binding test phase in the in-binding and post-binding test phase, reconfiguring a new test vector generator with lower test cost. Compared with the method of using the linear feedback shift register(LFSR) of each layer circuit independently as the test vector generator of the whole circuit in the in-binding test phase, the scheme in this paper can effectively utilize the original LFSR of each layer circuit and reduce the area overhead; the reconfigured 3D-LFSR can obtain better test data compression effect and lower test power consumption, improve test efficiency and reduce test time. Experiments have shown a 5% improvement in average test data compression, 53.1% and 9.6% reduction in average and peak power consumption respectively, 28% reduction in test area and 19.6% reduction in test time.

Design optimization of powered ankle prosthesis to reduce peak power requirement.

The aim of the prosthetic devices is to replicate the able-bodied angle-torque profile of a healthy human during locomotion. A lightweight and energy-efficient ankle joint is able to lower the actuator peak power and/or energy consumption per gait cycle, while adequately fulfilling the profile matching constraints. This study presents the design optimization of the prosthetic ankle joint containing an elastic element and actuator coupled with a rigid triangular part. The dimensions of the ankle joint triangular part were optimized to minimize actuator peak power and maximize spring energy within its elastic limits. As a result of series simulation tests, at 1.1 and 1.6 m/s walking speeds, the simulation of dorsi/plantar flexion shows up to 78.8% and 66.98% reduction in motor peak power compared to a direct drive system, respectively. Low power ankle-prosthetic device that closely matches the angle-torque profile of a healthy human's ankle, is one of the key parameters for the cost-effectiveness of lower limb prostheses.