- 标题
- 摘要
- 关键词
- 实验方案
- 产品
过滤筛选
- 2019
- 2018
- 2016
- rural electrification
- optimised renewable energy utilisation
- power sharing
- micro grid
- community development
- grid interconnection
- Battery energy storage systems
- techno-economic modeling
- photovoltaics
- net-metering
- Electrical Engineering and Automation
- New Energy Science and Engineering
- Optoelectronic Information Science and Engineering
- Amrita School of Engineering
- State Grid Sichuan Electric Power Research Institute
- Aristotle University of Thessaloniki
- The University of Texas at Austin
- Northern (Arctic) Federal University named after M.V. Lomonosov
- Univ. Grenoble Alpes, Grenoble INP
- Dracula Technologies
- Majmaah University
- Ritsumeikan University
- KNIT
-
Energy Harvesting Wireless Communications || Energy Harvesting in Next-Generation Cellular Networks
摘要： To handle the explosive growth of mobile traffic, next-generation cellular network will deploy more and more small-cell BSs (SBSs) in addition to the macro base stations (MBSs). The resultant network, namely, the heterogeneous network (HetNet), provides capacity boost on one hand but brings more energy consumption with the densely deployed SBSs on the other hand. In fact, due to the dynamics of wireless traffic load, many BSs are lightly loaded but almost work at their peak power, due to the elements like power amplifiers and supporting circuits. Unfortunately, these BSs can hardly be turned off for the coverage guarantee. To solve this problem, a new separation architecture called hyper-cellular network (HCN) is proposed, and the main idea is to decouple the function of control signaling from the function of data transmission, such that the data coverage can match the traffic dynamics in a more elastic way. Under HCN, SBSs are only utilized for high data rate transmission, whereas MBSs guarantee the network coverage and provide low data rate service. Therefore, SBSs can be turned off to save energy without worrying about the user coverage. To this end, its nature is to further power SBSs with renewable energy to save more grid power consumption. However, due to the randomness of renewable energy arrivals, it is challenging to manage wireless resource and the on-off states of energy harvesting (EH) BSs. It can be more challenging in HCN. First, diverse types of SBSs may be equipped with different kinds of energy sources, making the energy arrival statistically nonuniform over the space. In addition, the traffic load is nonevenly distributed across different base station (BS) tiers and also not in accordance with the energy arrivals over the spatial and temporal domains. To this end, on top of the techniques introduced in Chapter 4, in HCN the key to match the random energy arrival with the traffic load variation over time and space is to jointly optimize the working states of SBSs and the user traffic offloading. Although traffic offloading has been extensively studied in grid-powered cellular networks, the conventional offloading methods cannot be directly applied as they do not consider the energy states of BSs. Accordingly, energy-aware traffic offloading schemes are needed, and some energy-aware traffic offloading schemes have been proposed for single-tier homogeneous networks and two-tier HCN with one renewable energy-powered SBS, respectively. In the first part of the chapter, we will illustrate how to coordinate the on-off switching of SBSs with inter-tier traffic offloading, under the scenario with different types of SBSs, powered by various energy sources. The goal is to minimize the on-grid power consumption of the whole HCN system while satisfying the quality of service (QoS) requirements of users. Another emerging technology of next-generation cellular networks is to exploit edge caching with proactive services, like push. While the initial motivation of proactive caching and push is to reduce the duplicated content transmissions, and thus reduce the core network traffic load as well as the content delivery delay, it is also beneficial to address the mismatch between the energy and traffic in renewable energy-powered SBSs. Specifically, the contents can be cached at the storage of SBSs and then pushed to users earlier than the actual demands when there is sufficient harvested energy. The users can successfully get the contents when they actually require it even if at that time the SBS does not have enough energy for transmission. Consequently, the energy waste due to the battery overflow can be avoided as the harvested energy can be used effectively and timely. It can be viewed as transferring the harvested energy along with the timeline to the future to match the random energy arrival with the traffic needs. In the second part of this chapter, we will demonstrate the concept of integrating proactive service provisioning with EH HCN and provide a detailed study on the optimal policy design for content push from an EH-based SBS.
关键词： push,cellular networks,renewable energy,proactive caching,traffic offloading,quality of service,small-cell base stations,Markov decision process,Energy harvesting,hyper-cellular network
更新于2025-09-23 15:22:29
-
[IEEE 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2) - Beijing, China (2018.10.20-2018.10.22)] 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2) - Concentrating Solar Power Station Optimal Operation Model
摘要： With the improvement of energy structure, large scale grid connection of renewable energy, as a new technology for absorbing solar energy, concentrating solar power generation uses a thermal storage system to make it a schedulable resource without increasing the uncertainty of the system. This paper considers the energy transfer process and the thermal energy conversion efficiency among the concentrating solar modules, and constructs their basic operation models respectively. Through the design of different operating modes, the examples are simulated. The values of key parameters are taken into account to optimize the operation results. The impact of the analysis shows that concentrating solar power plants have certain advantages in dealing with solar energy uncertainty, prolonging production cycles, improving the utilization efficiency of heat storage tanks, and economic efficiency.
关键词： Concentrating solar power,renewable energy,thermal energy storage,optimal operation
更新于2025-09-23 15:22:29
-
[IEEE 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP) - Hangzhou, China (2018.10.18-2018.10.20)] 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP) - Energy Depositing for Energy Harvesting Wireless Communications
摘要： Energy borrowing (EB) technique has been proposed recently to improve the performance of wireless communications, which also decreases the burden of the smart grid (SG). To further reduce the burden of SG, we propose an energy depositing (ED) strategy. Specifically, the energy harvesting (EH) device can deposit its unused energy in the SG for decreasing the burden of SG, and it also can extract the deposited energy with additional amount of energy as incentive. An EB-and-ED structure is also proposed to promote a more energy-efficient wireless system. This paper focuses on the ED process, a joint optimization of both ED policy and power scheduling for maximizing the system throughput has been formulated. The simulation results using real solar irradiance data confirm the effectiveness of the proposed ED strategy.
关键词： energy depositing,energy harvesting,throughput
更新于2025-09-23 15:22:29
-
[IEEE 2018 International Flexible Electronics Technology Conference (IFETC) - Ottawa, ON, Canada (2018.8.7-2018.8.9)] 2018 International Flexible Electronics Technology Conference (IFETC) - Screen Printed Vias for a Flexible Energy Harvesting and Storage Module
摘要： This case study evaluates a highly flexible screen printed through-hole-via using silver microparticle inks for applications in energy harvesting and storage modules. The printed vias fabrication and reliability are evaluated by means of a double sided screen-printing method and repetitive (cyclic) bending tests. Vias, in 125 μm thick PET, were laser cut (50, 100, 150, and 200 μm nominal diameter) then filled, and simultaneously connected to adjacent vias, by screen printing. To investigate the use of the printed via in a monolithic energy module, the vias were used for the fabrication of a flexible printed supercapacitor (aqueous electrolyte and carbon electrode). The results indicate that the lower viscosity silver ink (DuPont 5064H) does not fill the via as effectively as the higher viscosity ink (Asahi LS411AW), and only the sidewall of the via Conversely, the Asahi silver paste fills the via more thoroughly and exhibited a 100 % yield (1010 vias; 100 μm nominal via diameter) with the 2-step direct screen-printing method. The bending test showed no signs of via specific breakdown after 30 000 cycles. The results indicate that this via filling process is likely compatible with roll-to-roll screen printing to enable multi-layered printed electronics devices.
关键词： flexible and printed electronics,screen printing,printed vias,bending reliability,energy module
更新于2025-09-23 15:22:29
-
[IEEE 2018 IEEE International Multidisciplinary Conference on Engineering Technology (IMCET) - Beirut, Lebanon (2018.11.14-2018.11.16)] 2018 IEEE International Multidisciplinary Conference on Engineering Technology (IMCET) - Design of Low Cost and High Efficiency Smart PV Solar System for Sustainable Residential Home
摘要： Renewable energy is becoming an essential element when it comes to climate change. The cost of energy storage is one of the main setbacks for sustainable homes. The paper includes important information on designing the PV solar system with energy storage for residential properties. It introduces the priority concept to reduce the battery storage size. The concept reduces the investment cost to make it attractive to homeowners. A case study is included.
关键词： Smart System,Maximum Demand,Solar Energy,Sustainable House
更新于2025-09-23 15:22:29
-
Learning-based Computation Offloading for IoT Devices with Energy Harvesting
摘要： Internet of Things (IoT) devices can apply mobile edge computing (MEC) and energy harvesting (EH) to provide high level experiences for computational intensive applications and concurrently to prolong the lifetime of the battery. In this paper, we propose a reinforcement learning (RL) based offloading scheme for an IoT device with EH to select the edge device and the offloading rate according to the current battery level, the previous radio transmission rate to each edge device and the predicted amount of the harvested energy. This scheme enables the IoT device to optimize the offloading policy without knowledge of the MEC model, the energy consumption model and the computation latency model. Further, we present a deep RL based offloading scheme to further accelerate the learning speed. Their performance bounds in terms of the energy consumption, computation latency and utility are provided for three typical offloading scenarios and verified via simulations for an IoT device that uses wireless power transfer for energy harvesting. Simulation results show that the proposed RL based offloading scheme reduces the energy consumption, computation latency and task drop rate and thus increases the utility of the IoT device in the dynamic MEC in comparison with the benchmark offloading schemes.
关键词： Mobile edge computing,energy harvesting,reinforcement learning,computation offloading,Internet of Things
更新于2025-09-23 15:22:29
-
[IEEE 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) - Aalborg, Denmark (2018.10.29-2018.10.31)] 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) - Distributed Cooperative Energy Management in Smart Microgrids with Solar Energy Prediction
摘要： Smart Microgrid (SMG), integrated with renewable energy, energy storage system and advanced bidirectional communication network, has been envisioned to improve efficiency and reliability of power delivery. However, the stochastic nature of renewable energy and privacy concerns due to intensive bidirectional data exchange make the traditional energy management system (EMS) perform poorly. In order to improve operational efficiency and customers’ satisfaction, we propose a distributed cooperative energy management system (DCEMS). We adopt recurrent neural network with long short-term memory to predict the solar energy generation with high accuracy. We then solve the underlying economic dispatch problem with distributed scalable Alternating Direction Method of Multipliers (ADMM) algorithm to avoid single point of failure problem and preserve customers’ privacy. In the first stage, each SMG optimizes its operation decision vector in a centralized manner based on one-day ahead solar energy generation prediction. In the second stage, all SMGs share their energy exchange information with directly connected neighboring SMGs to cooperatively optimize the global operation cost. The proposed DCEMS is deployed in our distributed SMGs emulation platform and its performance is compared with other approaches. The results show that the proposed DCEMS outperforms heuristic rule-based EMS by more than 30%. It can also protect customers’ privacy and avoid single point of failure without degrading performance too much compared to centralized EMS.
关键词： Information prediction,Microgrid emulation platform,Distributed algorithms,Energy management system,Demand-side management
更新于2025-09-23 15:22:29
-
Global Solar Radiation Prediction Using Hybrid Online Sequential Extreme Learning Machine Model
摘要： Accurate global solar radiation prediction is highly essential for related research on renewable energy sources. The cost implication and measurement expertise of global solar radiation emphasize that intelligence prediction models need to be applied. On the basis of long-term measured daily solar radiation data, this study uses a novel regularized online sequential extreme learning machine, integrated with variable forgetting factor (FOS-ELM), to predict global solar radiation at Bur Dedougou, in the Burkina Faso region. Bayesian Information Criterion (BIC) is applied to build the seven input combinations based on speed (Wspeed), maximum and minimum temperature (Tmax and Tmin), maximum and minimum humidity (Hmax and Hmin), evaporation (Eo) and vapor pressure deficiency (VPD). For the difference input parameters magnitudes, seven models were developed and evaluated for the optimal input combination. Various statistical indicators were computed for the prediction accuracy examination. The experimental results of the applied FOS-ELM model demonstrated a reliable prediction accuracy against the classical extreme learning machine (ELM) model for daily global solar radiation simulation. In fact, compared to classical ELM, the FOS-ELM model reported an enhancement in the root mean square error (RMSE) and mean absolute error (MAE) by (68.8–79.8%). In summary, the results clearly confirm the effectiveness of the FOS-ELM model, owing to the fixed internal tuning parameters.
关键词： global solar radiation,West Africa region,energy harvesting,FOS-ELM model,input optimization
更新于2025-09-23 15:22:29
-
Scaling up electrodes for photoelectrochemical water splitting: fabrication process and performance of 40 cm2 LaTiO2N photoanodes
摘要： A scalable process for particle-based photoanodes is developed. The electrodes are versatilely made of photocatalytically active semiconductor particles, here LaTiO2N, and optionally coated with co-catalysts and protecting components, all immobilized on a conducting substrate. The involved fabrication steps are restricted to scalable processes like electrophoretic deposition, annealing in air and dip coating. Special care is taken to ensure charge transport in between particles and to the substrate by adding conducting connectors. Adapting the fabrication steps, the geometrical electrode dimension is increased from the size of a typical lab electrode of 1 cm2 to 40 cm2. The quality of the scale up process is characterized by comparing the photoanodes in terms of thickness, light absorption properties and morphology. For several compositions, the electrochemical performance of both electrode sizes is assessed by measuring photocurrents and Faraday efficiencies. The comparison revealed a complex upscaling behavior and showed that photoelectrode size affected performance already on the 0.1 m scale.
关键词： photoelectrodes,energy conversion,LaTiO2N,electrode size,water splitting
更新于2025-09-23 15:22:29
-
A distributed parametric model of Brinson shape memory alloy based resonant frequency tunable cantilevered PZT energy harvester
摘要： This paper presents, an analytical model of piezoelectric vibration energy harvester consists of Brinson shape memory alloy (SMA) plate which can tune the resonant frequency. As the energy harvester should be tuned to excitation frequency in order to drive the maximum power, the temperature of SMA is varied to tune the natural frequency of the composite beam. In addition to SMA it also consists of piezoelectric layer and substructure layer. Using Euler–Bernoulli beam assumption, the expressions for frequency response of voltage, current and power outputs with temperature are obtained. From parametric study, it is observed that the tuning of natural frequency is 25–26%, for first three modes of vibration in short and open circuit conditions.
关键词： PZT,Energy harvester,Shape memory alloy,Tunable,Cantilever
更新于2025-09-23 15:22:29