Storage Allocation Research Articles

Storage allocation and investment optimisation for transmission‐constrained networks considering losses and high renewable penetration

This study investigates the effects of transmission losses, constraints and increased renewable energy penetration on planning energy storage allocation and investment. By modifying a DC optimal power flow model using a linearised approximation for ohmic losses, the authors were able to understand which network characteristic or inhibitor drives the most change in expanding utility-scale storage. Four different storage technologies were explored: compressed air energy storage, pumped hydro storage, lithium-ion battery and fly wheel. Each had different charging, capacity and cost characteristics. The results of the storage allocation trials revealed that network congestion was a more influential network inhibitor than were line losses. Losses only had substantial effects on a free-flowing network but produced marginal changes in allocation in congested ones. The conclusion of the investment trials revealed two things: (i) storage investment is not significantly affected by transmission constraints so long as renewable generation stays constant and relatively low; (ii) more flexible technologies like flywheels are favoured at lower volumes of renewable penetration for their load balancing capabilities while cheaper technologies are best as the volume of renewable power generated increases.

Computational Model for Microgeneration Simulation, From Solar and Wind Renewable Sources, With Optimal Allocation of Loads, Electric Vehicle and Energy Storage, In a Residential Electrical Micro Network

Abstract The electrical sector is under constant evolution. One of the areas refers to the consumers that come to be generators, implementing distributed generation, interconnected to a smart grid. This article discusses the improvement of an algorithm, already presented in the literature, to make the best temporal allocation of loads, electric vehicle, storage and many sources of generation, aiming at the maximum financial performance, that is, the lowest value for the energy invoice The modeling consists of a Mixed Integer Linear Programming (MILP) algorithm, which considers each component of the system and weighs the maintenance and shelf life of storage devices, basically batteries, loads that can be reallocated and the concept of Vehicle-to-grid, performing a daily analysis. The simulation has considered the hypothetical case of a residence, in which are included storage, electric vehicle and redistribution of loads, as well as wind and solar generation. Several scenarios are simulated, with or without the presence of some of the components. The results indicate that the simplest model, only redistributing the loads, can provide a sensible monetary savings of approximately 60%, while with the application of all the components modeled, there can be a reduction in the invoice of 90%.

Joint Frequency Reuse and Cache Optimization in Backhaul-Limited Small-Cell Wireless Networks

Caching at base stations (BSs) is a promising approach for supporting the tremendous traffic growth of content delivery over future small-cell wireless networks with limited backhaul. This paper considers exploiting spatial caching diversity (i.e., caching different subsets of popular content files at neighboring BSs) that can greatly improve the cache hit probability, thereby leading to better overall system performance. A key issue in exploiting spatial caching diversity is that the cached content may not be located at the nearest BS, which means that to access such content, a user needs to overcome strong interference from the nearby BSs; this significantly limits the gain of spatial caching diversity. In this paper, we consider a joint design of frequency reuse and caching, such that the benefit of an improved cache hit probability induced by spatial caching diversity and the benefit of interference coordination induced by frequency reuse can be achieved simultaneously. We obtain a closed-form characterization of the approximate successful transmission probability for the proposed scheme and analyze the impact of key operating parameters on the performance. We design a low-complexity algorithm to optimize the frequency reuse factor and the cache storage allocation. Simulations show that the proposed scheme achieves a higher successful transmission probability than existing caching schemes.

Assignment Algorithm of Computer Storage Management Partition and Its Implementation

This paper is about the algorithm of computer storage management partition and its implementation. First, we introduced the background and significance of the project, as well as the principle of technology used by the author in this project. This includes the principles of storage management, partition allocation technology and recycling technology. Then, a detailed analysis of the operating system primary storage allocation of a simple algorithm and one of its implementation., which mainly is to achieve a variable partition of the storage management allocation and recycling technology. Variable partition management usually uses a variety of methods, and our design are the first adaptive algorithm and the use of the best adaptive algorithm. Then it is followed by the test results of the system and discussion of its advantages and disadvantages. The entire storage management partition allocation algorithm and its implementation is entirely in accordance with the primary storage management of the operating system and effective use, in order to achieve a certain level of economic and technical value.

Optimal capacity allocation of multiple energy storage considering microgrid cost

Proper capacity of energy storage is conducive to the promotion of the economy and flexibility of the microgrid system with distributed power supply. In order to determine the size of the energy storage capacity of the whole microgrid, a method for optimal allocation of multiple energy storage capacities is presented. Based on the spectrum analysis, the power demand is divided into different frequency components. According to the response time of each energy storage, the stabilizing frequency bands are attained. According to the economy of the micro grid, the optimal stabilizing frequency bands of each storage are got based on differential evolution algorithm, then the optimal capacity and power of hybrid energy storage are attained. The results show that system annual comprehensive cost of multiple-storage microgrid is lower than two or single energy storage. Capacity optimization considering the microgrid cost is better to improve the economic efficiency of microgrid.

Secure distributed adaptive bin packing algorithm for cloud storage

Cloud computing delivers highly scalable and flexible computing and storage resources on pay-per-use policy. Cloud Computing’s services for computation and storage are getting increasingly popular and many organizations are now moving their data from in-house data centers to the Cloud Storage Providers (CSPs). However, increasing user base and remote storage of data introduces challenges like inefficient usage of resources and insider threat to data at rest in the cloud storage. Time varying workload and data intensive applications are vulnerable to encounter such challenges while using cloud computing services. The consolidation of virtual machines to minimize the total number of active servers is a promising solution to conserve the energy but it requires efficient resource management strategies. Additionally, the encryption strategies and third party auditors to maintain data integrity are still in their developing stage and therefore the data at rest is still a concern for the cloud storage users. In this paper, we designed a distributed storage allocation architecture for fair utilization of storage resources and we also design an integrated end to end security framework for data at rest in cloud storage to eliminate insider threats.

A Stackelberg Game Approach to Proactive Caching in Large-Scale Mobile Edge Networks

Caching popular files in the storage of edge networks, namely edge caching, is a promising approach for service providers (SPs) to reduce redundant backhaul transmission to edge nodes (ENs). It is still an open problem to design an efficient incentive mechanism for edge caching in 5G networks with a large number of ENs and mobile users. In this paper, an edge network with one SP, a large number of ENs and mobile users with time-dependent requests is investigated. A convergent and scalable Stackelberg game for edge caching is designed. Specifically, the game is decomposed into two types of sub-games, a storage allocation game (SAG) and a number of user allocation games (UAGs). A Stackelberg game-based alternating direction method of multipliers (Stackelberg game-based ADMM) is proposed to solve either the SAG or each UAG in a distributed manner. Based on both analytical and simulation results, the convergence speed, the optimum of the entire game, and the amount of information exchange are linearly (or sublinearly) related to the network size, which indicates that this framework can potentially cope with large-scale caching problems. The proposed approach also requires less backhaul resource than the existed approaches.

A Hybrid Dynamical Approach for Allocating Materials in a Dry Bulk Terminal

This paper proposes a new modeling and control methodology for allocating materials in a dry bulk terminal with a finite storage capacity. The dynamical process of material storage allocation in the terminal is modeled using a hybrid system perspective that combines both discrete-event and continuous-time dynamics. The stockyard space is partitioned into a number of slots for exchanging incoming and outgoing material flows in the terminal, leading to a so-called mixed logical dynamical (MLD) model with the maximal storage capacity. Based on the MLD model, a model predictive controller is then proposed for maximizing the economic profit in a rolling horizon manner. A number of Monte Carlo simulations have been performed involving a real case study for analyzing the effects of different slot volumes on the economic performance and the computational performance of the controller. Simulations also demonstrate the potential of the proposed methodology. Note to Practitioners —This paper is motivated by the problem of allocating dry bulk materials in the stockyard of a small import terminal. In current approaches for allocating materials, the storage capacity cannot be considered, and this could lower the terminal profit resulting from delaying the vessel in the terminal when a finite storage capacity is considered. This paper suggests a new approach from a hybrid system perspective that captures the dry bulk terminal operation dynamics. In this paper, we mathematically describe the process of allocating materials into different slots in the stockyard using a hybrid dynamical model and propose a model predictive controller to maximize the terminal operation profit. We then show how the slot size influences the economic performance and analyze its associated computations by conducting simulation experiments involving a case study. Simulation experiments also suggest that this approach achieves significantly more economic benefits compared with current approaches. In future research, a large intermodal terminal will be investigated whereby incoming and outgoing materials of different transport modalities need to be coordinated properly.

Design of Storage Allocation Using Interaction Frequency Heuristic-Order Oriented Slotting Approach to Reduce Delay Time on Traveling Searching Activities in Refinery Unit V Warehouse PT XYZ

<p><strong> </strong>Refinery Unit (RU) V is a processing company owned by PT XYZ located in Balikpapan. Refinery Unit V has twelve warehouses with four warehouses being the main focus in this research of RGM, RMS, RIN, and RSP used to store products for refinery maintenance processes. In the initial conditions, there is a delay in traveling searching activities. The occurrence of delay in traveling searching activity caused by the absence of details of the product location clearly. The proposed product allocation is using Interaction Frequency Heuristic-Order Oriented Slotting method. The last step is to create a new layout for each RU V warehouse.</p><p>The first step is to calculate the cycle time for each work order list by calculating the distance between the storage point with the point of I / O based on the aisle distance calculation. Next is to compare between the cycle time of each work order list with the standard time of the warehouse, so it will know the percentage of work order list that experienced delay for one year. Next, allocate product storage based on the popularity value of the product and the value of the interaction frequency between the products. The final step is to simulate using new work order list based on the proposed allocation layout to know the effect of change from the proposed layout. The result of this research is a new layout for each warehouse. All stock taking performance are better than the standard time while the exisiting condition violate the standard time.</p>

Storage allocation in a warehouse based on the forklifts fleet availability

Product allocation is one of the most important duties in warehousing operations. Based on the time and the number of products to put away and retrieve, storage allocation can directly affect the efficiency of a warehouse in terms of both response and operation time. Traditionally, the product storage allocation is done based on the less distance of shipment but focusing on distance may decrease the efficiency of a warehouse in terms of efficient utilization of resources such as warehouse inbound shipping fleet. This paper proposes a storage space allocation model that considers the availability of forklift fleet in a warehouse instead of product shipping distance. The numerical example shows that storing the products based on the proposed model can reduce the volume of forklift fleet idle hours on days with fewer volume of receiving and shipping outs. The proposed model also reduces the overtime working hours on days with higher volume of receiving and shipping out products.

Optimal Investment Planning of Bulk Energy Storage Systems

Many countries have the ambition to increase the share of renewable sources in electricity generation. However, continuously varying renewable sources, such as wind power or solar energy, require that the power system can manage the variability and uncertainty of the power generation. One solution to increase flexibility of the system is to use various forms of energy storage, which can provide flexibility to the system at different time ranges and smooth the effect of variability of the renewable generation. In this paper, we investigate three questions connected to investment planning of energy storage systems. First, how the existing flexibility in the system will affect the need for energy storage investments. Second, how presence of energy storage will affect renewable generation expansion and affect electricity prices. Third, who should be responsible for energy storage investments planning. This paper proposes to assess these questions through two different mathematical models. The first model is designed for centralized investment planning and the second model deals with a decentralized investment approach where a single independent profit maximizing utility is responsible for energy storage investments. The models have been applied in various case studies with different generation mixes and flexibility levels. The results show that energy storage system is beneficial for power system operation. However, additional regulation should be considered to achieve optimal investment and allocation of energy storage.

Logistics automation management based on the Internet of things

In order to enhance the logistics automation management, the radio frequency identification (RFI) is used as the key point of product identification and information collection, and the prototype system of logistics automation management software based on the Internet of things is developed. A hardware prototype platform of logistics warehouse is built, and the software of logistics automation management system based on the Internet of things is tested and run. According to the comparison of three kinds of anti-collision algorithms, the results showed that the backdrop binary anti-collision algorithm can well solve the problem of a large number of repeated test steps and invalid data. In addition, by running the logistics automatic management software system on the hardware platform, it proved that the system can accurately and efficiently obtain the information of goods, reduce the wrong storage allocation and storage, reduce duplication work in warehouse management and improve work efficiency. At the same time, the cost of logistics management is reduced, and the information management of all operation process of automatic identification and access to goods by warehouse management system is finally realized.

Assignment Algorithm of Computer Storage Management Partition and Its Implementation

This paper is about the algorithm of computer storage management partition and its implementation. First, we introduced the background and significance of the project, as well as the principle of technology used by the author in this project. This includes the principles of storage management, partition allocation technology and recycling technology. Then, a detailed analysis of the operating system primary storage allocation of a simple algorithm and one of its implementation., which mainly is to achieve a variable partition of the storage management allocation and recycling technology. Variable partition management usually uses a variety of methods, and our design are the first adaptive algorithm and the use of the best adaptive algorithm. Then it is followed by the test results of the system and discussion of its advantages and disadvantages. The entire storage management partition allocation algorithm and its implementation is entirely in accordance with the primary storage management of the operating system and effective use, in order to achieve a certain level of economic and technical value.

Submodular unsplittable flow on trees

We study the Unsplittable Flow problem (mathsf {UFP}) on trees with a submodular objective function. The input to this problem is a tree with edge capacities and a collection of tasks, each characterized by a source node, a sink node, and a demand. A subset of the tasks is feasible if the tasks can simultaneously send their demands from the source to the sink without violating the edge capacities. The goal is to select a feasible subset of the tasks that maximizes a submodular objective function. Our main result is an O(klog n)-approximation algorithm for Submodular UFP on trees where k denotes the pathwidth of the given tree. Since every tree has pathwidth O(log n), we obtain an O(log ^2 n) approximation for arbitrary trees. This is the first non-trivial approximation guarantee for the problem, matching the best known approximation ratio for UFP on trees with a linear objective function. Our main technical contribution is a new geometric relaxation for UFP on trees that builds on the recent work of Bonsma et al. (2014, FOCS), Anagnostopoulos et al. (Amazing 2+epsilon approximation for unsplittable flow on a path, SIAM, pp 26–41, 2014) for UFP on paths with a linear objective. Our relaxation is very structured, so it can be combined with the contention resolution framework of Chekuri et al. (2009, STOC). Our approach is robust and extends to several related problems, such as UFP with bag constraints and the Storage Allocation Problem. Additionally, we study the special case of UFP on trees with a linear objective and upward instances where, for each task, the source node is a descendant of the sink node. Such instances generalize UFP on paths. We build on the work of Bansal et al. (A quasi-PTAS for unsplittable flow on line graphs, ACM, pp 721–729, 2006) for UFP on paths and obtain a QPTAS for upward instances when the input data is quasi-polynomially bounded. We complement this result by showing that, unlike the path setting, upward instances are mathsf {APX}-hard if the input data is arbitrary.

The detrimental effects of CO2-driven chronic acidification on juvenile Pacific abalone (Haliotis discus hannai)

To test the effects of chronic stress caused by CO2-driven decreases in pH (NBS scale) on molluscs, juvenile Pacific abalone (Haliotis discus hannai), an economically important gastropod, were cultured at pH 8.1 (control), pH 7.9 or 7.7 for 3 months. Eroded shell surfaces, reduced growth rates, and altered biochemical composition and energy metabolism were found in abalone cultured in acidified conditions. Glycogen contents and crude lipid contents were significantly higher in the muscle of abalone from the control treatments than in those from the pH 7.7 treatment, indicating that allocation of tissue energy storage was altered by chronic acidification. The ratio of the oxygen consumption rate to the ammonia excretion rate (O:N ratio) of individuals cultured at two acidified treatments decreased significantly compared with the controls, suggesting a decreased use of body lipid and carbohydrates as a metabolic substrate under chronic acidified conditions. Chronic acidification had detrimental effects on the physiological activity of the Pacific abalone; however, the ability to acclimate varied among individuals. A minority of tested animals incubated at acidified conditions exhibited undiminished performance. The Pacific abalone may face severe challenges in the near future, but they may also hold considerable ability to acclimate to ocean acidification.

Storage design using Fast moving, Slow moving and Non moving (FSN) analysis

Storage location assignment is related to the problem in warehousing management. The purpose of this paper is to gain storage allocations of goods in a warehouse based on the fast moving, slow moving and non moving (FSN) analysis as the determination of the allocation of storage based on items popularity that is stored in a warehouse. The method used for the research are fast moving, slow moving, non moving (FSN) and dedicated storage. The analysis can be used to determine the location for goods storage will allocated closer to loading area. Goods with fast moving categories allocated close to to loading area, slow moving items allocated next to fast moving items and nonmoving items allocated next to slow moving items which the farthest location from loading area. The concept of dedicated storage also applied to give a specific location for goods storage. The fast moving category items is 11,4% and requiring 86.31 m2 area. The slow moving category is 47,8% and requiring 34.86 m2 area. The non moving category is 40,8% and requiring 50.04 m2 area so that the total area needed is 171.21 m2.

Towards Distributed Data Management in Fog Computing

In the emerging area of the Internet of Things (IoT), the exponential growth of the number of smart devices leads to a growing need for efficient data storage mechanisms. Cloud Computing was an efficient solution so far to store and manipulate such huge amount of data. However, in the next years it is expected that Cloud Computing will be unable to handle the huge amount of the IoT devices efficiently due to bandwidth limitations. An arising technology which promises to overwhelm many drawbacks in large‐scale networks in IoT is Fog Computing. Fog Computing provides high‐quality Cloud services in the physical proximity of mobile users. Computational power and storage capacity could be offered from the Fog, with low latency and high bandwidth. This survey discusses the main features of Fog Computing, introduces representative simulators and tools, highlights the benefits of Fog Computing in line with the applications of large‐scale IoT networks, and identifies various aspects of issues we may encounter when designing and implementing social IoT systems in the context of the Fog Computing paradigm. The rationale behind this work lies in the data storage discussion which is performed by taking into account the importance of storage capabilities in modern Fog Computing systems. In addition, we provide a comprehensive comparison among previously developed distributed data storage systems which consist of a promising solution for data storage allocation in Fog Computing.

Conveyor Merges in Zone Picking Systems: A Tractable and Accurate Approximate Model

Sequential zone picking systems are popular conveyor-based picker-to-parts order picking systems that divide the order picking area in work zones. When designing a zone picking system, it is important to know whether the throughput capability of the system can meet customer demand. However, the performance and maximum throughput capability of a zone picking system is largely determined by congestion and blocking that occur at the various conveyor merges in the system. In this paper we develop an analytical model to study the impact of conveyor merges in sequential zone picking systems. Because of finite buffers, blocking, recirculation, and merging, the resulting queueing model does not have a product-form stationary queue-length distribution which makes exact analysis practically infeasible. Therefore, we develop an approximate solution by using an aggregation technique and matrix-geometric methods to study the throughput capability of the system. The model is suitable to support rapid design of complex zone picking systems, in terms of number and length of zones, input and output buffer capacities, and storage allocation of products to zones to meet prespecified performance targets. Comparison of the approximation results to simulation show that for a wide range of parameters the mean relative error in the system throughput is typically less than 5%. The model accurately predicts the loss in throughput due to congestion and blocking at the merges, and can be used to allocate input and output buffer spaces to maximize the throughput capability of the system.

太行山东坡不同林龄杏树林碳储量及其分配特征

PDF HTML阅读 XML下载 导出引用 引用提醒 太行山东坡不同林龄杏树林碳储量及其分配特征 DOI: 10.5846/stxb201803290634 作者: 作者单位: 河北省科学院地理科学研究所,河北省科学院地理科学研究所,河北省科学院,河北省科学院地理科学研究所,河北省科学院地理科学研究所,中国科学院遗传与发育生物学研究所农业资源研究中心,河北省科学院地理科学研究所,河北省科学院地理科学研究所 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（3150048）；河北省科学院科技攻关项目（18111）；河北省青年拔尖人才项目；河北省科学院青年拔尖人才项目 Carbon storage and its allocation pattern in Armeniaca vulgaris plantations at different ages on the eastern slope of Taihang Mountain Author: Affiliation: Institute of Geographical Sciences,Hebei Academy of Sciences,Institute of Geographical Sciences,Hebei Academy of Sciences,Hebei Academy of Sciences,Institute of Geographical Sciences,Hebei Academy of Sciences,Institute of Geographical Sciences,Hebei Academy of Sciences,Center for Agricultural Resources Research,Institute of Genetics and Developmental Biology,Chinese Academy of Sciences,Institute of Geographical Sciences,Hebei Academy of Sciences,Institute of Geographical Sciences,Hebei Academy of Sciences Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:在生物量调查的基础上，对太行山东坡4、8、12年生和16年生杏树林生态系统碳储量及其分配特征进行了研究。结果表明：杏树各器官碳含量在447.3-488.1 g/kg；树干碳含量随林龄的增长而显著降低（P < 0.05），不同林龄间树根、树枝和树叶碳含量无显著差异；土壤层（0-100 cm）碳含量随林龄的增长而增大；随土层深度的增加而降低。林龄对杏树林乔木层、土壤层和生态系统碳储量均有显著影响。4、8、12年生和16年生杏树林生态系统碳储量分别为27.810、72.647、82.450 Mg/hm2和102.336 Mg/hm2；土壤层碳储量占总碳储量的90.1%-99.6%，且主要集中于0-40 cm。乔木层碳储量分配随着林龄的增长而增加，土壤碳储量分配则减小。结果揭示了土壤层是杏树林生态系统的主要碳库；杏树人工林生态系统在生长过程中能显著地积累有机碳。研究结果可为经济林经营管理及碳汇功能评价提供参考。 Abstract:Carbon storage and its allocation of 4-, 8-, 12-, and 16-year-old Armeniaca vulgaris plantation ecosystems on the eastern slope of Taihang Mountain were studied based on a biomass survey. The results showed that the carbon contents in different organs of apricots ranged from to 447.3 to 488.1 g/kg. The carbon content of stems decreased significantly with stand age, whereas no significant differences in carbon content were observed among the roots, branches, and leaves of the apricot plantations with different ages. The carbon content in the soil layer (0-100 cm) increased significantly with increasing stand age, but decreased with increasing soil depth (P < 0.05). The carbon storage in the arbor layer, soil layer, and whole ecosystem of the apricot plantations was obviously age dependent. The values of total carbon storage in the 4-, 8-, 12-, and 16-year-old apricot plantation ecosystems were 27.810, 72.647, 82.450 Mg/hm2 and 102.336 Mg/hm2, respectively. The carbon storage in the soil layer accounted for >90.1%of the carbon storage in the apricot plantation ecosystem, which was accumulated at higher levels in the 0-40 cm soil layer. The carbon storage and distribution patterns in the apricot plantations varied obviously with the stand age. In addition, carbon storage allocation increased in the arbor layer but decreased in the soil layer with increasing stand age. Our results suggested that the soil layer was the major carbon pool, and also impliedthat the plantation ecosystems at these stand ages could accumulate organic carbon continuously. Quantifying carbon storage and distribution patterns of apricot plantationscould help design sustainable forest management strategies for achieving its potential in mitigating climate change. 参考文献 相似文献 引证文献

Minimizing Power Consumption in Video Servers by the Combined Use of Solid-State Disks and Multi-Speed Disks

Disks use a considerable portion of the total energy consumed by a video server. Solid-state disks (SSDs) can be used as a cache to reduce disk speeds, thereby decreasing the power consumed by disks. However, effective SSD bandwidth management is essential to cope with the high request rates for popular video files stored on SSDs. To address this problem, we propose a new SSD cache management scheme for a video server that uses multi-speed disks. First, we introduce a storage allocation scheme to examine how the presence of an SSD cache affects disk bandwidth consumption. We then propose an SSD bandwidth allocation algorithm to minimize energy consumption by allowing disks to run at lower speeds while achieving jitter-free disk speed transitions and by limiting the number of transitions to ensure disk reliability. Our experimental results demonstrate that our proposed bandwidth allocation algorithm achieves appreciable power savings under various workloads while limiting the number of disk speed changes.