Exchange Curve Research Articles

Smart Management of Energy Storage in Microgrid: Adapting the Control Algorithm to Specific Industrial Facility Conditions

The article introduces a method for optimizing energy storage system scheduling in industrial microgrids. It employs a PSO-based heuristic algorithm using daily generation and load forecasts. The objective is economic optimization, minimizing energy costs, and maximizing profits. Market energy prices and distributor tariffs are the base of the objective function. An algorithm maintains the plan by controlling storage power based on real-time microgrid measurements, aligning with the intended power exchange curve. Due to PSO’s ability to perform multidimensional optimization, it is possible to find the global optimum of the objective function. To validate the practical applicability of this approach, it is exemplified through its implementation within a real-world industrial microgrid setting. The presented results indicate the method’s effectiveness but also show its weaknesses. For the two considered cases, a decrease in operating costs of 6.7% and 10.8% was achieved, respectively. On the other hand, the best results are obtained for shorter forecasts, which is why the algorithm, despite long planning periods, revises the ESS operation plan whenever there are significant deviations between the forecast and the actual power.

OPTIMISATION OF PURCHASING STRATEGY OF TOOLS AND COMPONENTS BASED ON EXCHANGE CURVE THEORY

The optimal inventory control of tools and components in manufacturing systems plays an important role in the success of sustainable operation from financial and ecologic point of view. This study discusses an inventory control method, which is based on the transformation of investment of inventory into annual order cost or vice versa. The study presents the mathematical model of the exchange curve model for tools and components in the case of economic order quantity inventory strategy. The described methodology makes it possible to optimise available purchasing strategies for tools and components. The approach was tested with a scenario analysis, where different parameters of the purchasing process including inventory related constraints were taken into consideration. The computational results validated the exchange curve based inventory control methodology and showed that the inventory strategy can be improved with cost transformation Practical implications of the proposed model and method regard the possibility of finding optimal inventory policies that can affect the operation costs of manufacturing systems.

WITHDRAWN: A lightweight hybrid scheme for security of big data

The source of big data in the contemporary era led to the increased usage of cloud infrastructure. Plenty of Internet based applications are using cloud infrastructure to reap benefits like scalability, availability and fault tolerance. One of the sources of big data is Internet of Things (IoT) use case that exploits sensor networks and plethora of connected devices that are resource constrained. In such typical scenario, there is need for lightweight security schemes to deal with big data storage and dissemination. The traditional cryptography based schemes are not efficient to deal with big data in the aforementioned use case. Therefore, it is indispensable to have an efficient and lightweight scheme that leverages the state of the art in terms of security attributes such as data integrity and confidentiality. In this paper we proposed a security scheme known as Lightweight Hybrid Scheme (LHS) that is based on Diffie-Hellman key exchange and Elliptic Curve Cryptography. The LHS scheme works with any encryption technique and provide support for highly secure key exchange mechanism that results in smaller key sizes. The proposed scheme has optimized method for obtaining modulus of fractional number. LHS is evaluatedwithaprototype application and compared with start of the art algorithms like Diffie-Hellman (DH), Elliptic Curve-Diffie Hellman (ECDH) and RSA. The results revealed that LHS provides improvement in security besides reducing time complexity while dealing with big data operations.

WITHDRAWN: Hybrid cryptographic algorithm based key management scheme in MANET

Abstract In the recent networking era, Mobile Adhoc Network has been popular as it effectively solves the limitations that were pertaining with single path routers. Multi-path mobile adhoc networks (MANETs) have various advantages which include high throughput, lower time complexity and high energy efficiency. The major challenges here are the key management and secured way of routing. Secure routing ensures data integrity, confidentiality, authorization and authentication and non-repudiation. These requirements are satisfied only by cryptographic algorithms. Key management is the most essential one in cryptography. The management of keys which is integrated with the protocol start with trusted and network with more authentication. In order to ensure the secured broadcasting in MANET, here we proposed a secured multipath routing mechanism for reliable data transmission using cryptographic algorithms. In our proposed method, we are hybridizing the popular Diffie-Hellman method of key exchange and elliptic curve cryptography (HDHECC). First, the nodes are subjected to clustering using the LEACH protocol and the cluster head selection process will be carried out with the help of weight of each node. Here the trust mechanism will be done by using the AOMDV. For the management of keys, every head of the cluster is made to retain its public key of the corresponding member nodes and are made to act only as a router. The proposed technique solves the overhead of the centralized management of keys. Moreover, the requirement to store all the public keys. The propose method is tested for its performance by evaluating the end-end delay, Packet delivery ratio and packet losses. The implementation is carried out using the NS2 simulator.

Optimal Sizing of Hydro-PV-Pumped Storage Integrated Generation System Considering Uncertainty of PV, Load and Price

Effectively using complementary property of various renewable energy sources by an integrated generation system is a concerned study. Considering the uncertainty of PV, spot price and load, the sizing of integrated generation system with combined market operation is a difficult problem. Based on the above uncertain factors, the sizing method of hydro-PV-pumped storage integrated generation system is proposed in this paper. The output characteristic model is established by utilizing the wide range of hydropower output and flexible schedulability of pumped storage. Then, the volatility ratio of the power exchange curve and load tracking coefficient are the evaluation index of the complementary effect, which ensures the stable and smooth output curve. Further, the uncertainty models of PV, spot price and load are established, considering that, the operation of the power generation system is optimized in the day-ahead market, and the predictive deviation of PV and load is balanced in a real-time market. Based on the above factors, the sizing model of the hydro-PV-pumped storage integrated energy system was proposed based on economics and complementary index. Finally, a case study was undertaken, the sensitivity analysis of the economy and complementarity indices was carried out, as the complementarity index is improved, the economy would be down. Further, the optimal sizing of hydro-PV-pumped storage integrated generation system was obtained, hydropower was a total of 165 MW, PV was 100 MW and pumped storage was 50 MW, that could ensure the economy while meeting the complementary index, the effectiveness of the model proposed was verified.

A multi-item inventory model for small business - a perspective from India

Micro, small and medium enterprises (MSMEs) in India are focused on improving their inventory management function as part of government's program to increase their contribution to the gross domestic product (GDP). A plethora of inventory models are available in literature; these models are either very complex, or need reliable inventory cost data, or are not applicable to all classes of items and are, therefore, rendered ineffective. In this paper we have developed and presented a simple, yet effective, model that combines the characteristics of selective inventory control (SIC) and an exchange curve (EC). Combination of these techniques not only allows determination of ordering policy for all items, but also involves managers in decision making, thus providing MSMEs with a solution that is robust and practical. We also describe application of this model to a sample of 30 items in an auto components manufacturing firm. The case study demonstrates ease of implementation of the proposed model as well as solution completeness.

Inventory reduction using the optimal policy curve approach: a case study

The current trends in Indian automotive manufacturing industry indicate a rapidly increasing socio-technical complexity of its manufacturing systems. The industry is striving to meet the ever-changing behaviour of the market demand. This has led to considerable increase in variety of products manufactured under one roof. Increasing variety requires high attention to control the high inventory levels of parts and aggregates. This paper focuses on understanding and analysing causes of high inventory levels of a leading tier-I automotive supplier and recommending the way forward using a structured methodology. The quality control (QC) tools, the economic order quantity (EOQ) and the optimal-policy curve (exchange curve) approach have been utilised effectively to funnel the key issues and finally optimise the inventory level of the key parts. The application of the QC tools and the optima-policy curve approach has resulted in a healthy 25% reduction of the high inventory in the industry under taken as a case study.

Study of microvia filling process based on multi-physical coupling

ABSTRACTThe microvia filling process used in the high-density interconnect printed circuit board manufacturing industry was investigated by multi-physical coupling technology. To achieve a perfect filling, SPS (bis-(sodium-sulphopropyl)-disulphide), EO/PO (ethylene oxide and propylene oxide block co-polymers) and PEOPI (polyethylene oxide-polyimide) were used. Furthermore, electrochemical behaviours of electrodeposition were investigated by cyclic voltammetry, galvanostatic potential transient measurement and dynamic potential polarisation technology. Through numerical simulation, the relationship between coverage of additive, concentration of additive, rotating speed of rotating disc electrode, exchange current density and curve slope was fitted. Based on multi-physical coupling to copper electrodeposition, a mathematical model of microvia filling was built to simulate the filling process by a finite element method, and a systematic analysis of the whole filling process was carried out. The void-free microvia filling and filling process with different shapes were finally achieved in acid copper electroplating solutions consisting of 0.3 M CuSO4·5H2O, 0.2 M H2SO4 and 80 mg L−1 Cl− (virgin make-up solution) plus additives SPS, EO/PO and PEOPI. Subsequently, from images of the microvia filling experiment at different times, shape evolution of the microvia filling and variation of electrodeposition rate at the bottom of the microvia and surface were analysed. The modelling result was compared with the measured data and showed good agreement with the experiment. The results showed that a process model was an excellent tool for quickly and cheaply studying the process behaviour greatly reduced need to execute time-consuming and costly experiments.

FourQ on embedded devices with strong countermeasures against side-channel attacks

This work deals with the energy-efficient, high-speed and high-security implementation of elliptic curve scalar multiplication, elliptic curve Diffie-Hellman (ECDH) key exchange and elliptic curve digital signatures on embedded devices using Four $\mathbb {Q}$ Q and incorporating strong countermeasures to thwart a wide variety of side-channel attacks. First, we set new speed records for constant-time curve-based scalar multiplication, DH key exchange and digital signatures at the 128-bit security level with implementations targeting 8, 16 and 32-bit microcontrollers. For example, our software computes a static ECDH shared secret in $\sim$ ∼ 6.9 million cycles (or 0.86 seconds @8 MHz) on a low-power 8-bit AVR microcontroller which, compared to the fastest Curve25519 and genus-2 Kummer implementations on the same platform, offers 2x and 1.4x speedups, respectively. Similarly, it computes the same operation in $\sim$ ∼ 495 thousand cycles on a 32-bit ARM Cortex-M4 microcontroller, achieving a factor-1.9 speedup when compared to the fastest Curve25519 implementation targeting another Cortex-M4 platform. A similar speed performance is observed in the case of digital signatures. Second, we engineer a set of side-channel countermeasures taking advantage of Four $\mathbb {Q}$ Q 's rich arithmetic and propose a secure implementation that offers protection against a wide range of sophisticated side-channel attacks, including differential power analysis (DPA). Despite the use of strong countermeasures, the experimental results show that our Four $\mathbb {Q}$ Q software is still efficient enough to outperform implementations of Curve25519 that only protect against timing attacks. Finally, we perform a differential power analysis evaluation of our software running on an ARM Cortex-M4, and report that no leakage was detected with up to 10 million traces. These results demonstrate the potential of deploying Four $\mathbb {Q}$ Q on low-power applications such as protocols for the Internet of Things.

The Area Between Exchange Curves as a Measure of Conformational Differences in Hydrogen-Deuterium Exchange Mass Spectrometry Studies

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) provides information about protein conformational mobility under native conditions. The area between exchange curves, A bec , a functional data analysis concept, was adapted to the interpretation of HDX-MS data and provides a useful measure of exchange curve dissimilarity for tests of significance. Importantly, for most globular proteins under native conditions, A bec values provide an estimate of the log ratio of exchange-competent fractions in the two states, and thus are related to differences in the free energy of microdomain unfolding. Graphical Abstract ᅟ.

Highly tunable exchange in donor qubits in silicon

AbstractIn this article we have investigated the electrical control of the exchange coupling (J) between donor-bound electrons in silicon with a detuning gate bias, crucial for the implementation of the two-qubit gate in a silicon quantum computer. We found that the asymmetric 2P–1P system provides a highly tunable exchange curve with mitigated J-oscillation, in which 5 orders of magnitude change in the exchange coupling can be achieved using a modest range of electric field (3 MV/m) for ~15-nm qubit separation. Compared with the barrier gate control of exchange in the Kane qubit, the detuning gate design reduces the gate density by a factor of ~2. By combining large-scale atomistic tight-binding method with a full configuration interaction technique, we captured the full two-electron spectrum of gated donors, providing state-of-the-art calculations of exchange energy in 1P–1P and 2P–1P qubits.

Using Spreadsheet Modeling to Teach Exchange Curves (Optimal Policy Curves) in Inventory Management

ABSTRACTInventory management is widely researched and the topic is taught in business programs across the spectrum of operations and supply chain management. However, the concepts are notoriously difficult for students to practice once they finish school and become managers responsible for inventory control. This article explains the structure and details of an inventory management class module designed to bridge the gap between learning inventory management theory and applying the learning to practice. Through an active learning exercise, groups of logistics management graduate students in two sections of an introductory inventory management class (in‐residence and online) are taught the exchange curve concept, introduced to its use in practice, and given a tool for implementing this learning in a variety of practical scenarios. The exercise is valuable as it is well suited for students with a limited math background because it allows the exchange curve concept to be taught and demonstrated without presenting complicated mathematics. A three‐tiered assessment of the exercise reveals its effectiveness in meeting the goals of providing an engaging and interesting use of learning time and giving the students an in‐depth practical understanding of the exchange curve concept. The exercise is designed to be equally useful for application in an undergraduate class.

Column leaching of uranium ore with fungal metabolic products and uranium recovery by ion exchange

To verifying the feasibility of uranium recovery with fungal metabolic products in large-scale applications, column leaching and ion exchange of uranium was carried out. The uranium recovery reached 81.76 % in 14 days. The ion exchange curve for the leach solution obtained with the metabolic products of Aspergillus niger was in the shape of a wave. The elution curve was similar to that of leaching with H2SO4. The results indicate that leaching with the metabolic products of A. niger is a promising and environmentally friendly method for exploitation of low grade uranium ores in large-scale applications.

Enhanced Security Algorithm using Hybrid Encryption and ECC

The AES and ECC are the best two algorithms of symmetric encryption technology and asymmetric encryption technology. The paper presents a hybrid model which uses a combination of two symmetric algorithms enhanced AES and Blowfish for data confidentiality, Message Digest-5 for data integrity, Elliptic Curve Diffie Hellman algorithm-ECDHA for key exchange and Elliptic Curve Digital signature algorithmECDSA is used for digital signature. AES is enhanced by modifying the S-boxes columns, and then combination of enhanced AES and blowfish is used for data confidentiality. Performance of this system is evaluated on different configurations on the basis of encryption/decryption time, throughput and memory usage for different data formats like text file, image file, audio file and video file.

Saudi Arabian White Silica as a Good Adsorbent for Pollutants

ABSTRACTThe Saudi Arabian white silica is used as a starting material for preparation of adsorbent for heavy metals and some organic dyes. Hydrothermal treatment of white silica with aluminum source resulted in an amorphous phase of microporous materials with large enhancement of ion exchange properties in addition to adsorption of some organic dyes. In this research we examine the modified white silica towards ion exchange of Cu2+, Co2+, and Ni2+ ions. The ion exchange curve was elucidated. Cu2+ has higher affinity for ion exchange while Co2+ and Ni2+ nearly the same affinity. Adsorption of methylene blue and methyl red was examined and a simulation study was performed.

Estimating exchange curve for inventory management through evolutionary multi-objective optimization

Inventory management involves trade-offs between conflicting objectives such as cost minimization and service level maximization. The trade-off analysis of cycle stock investment and workload, so called the exchange curve, possibly dates back to several decades ago. These analyses seldom formulated inventory trade-offs as a multi-objective optimization problem and their solution procedures were all based on single objective optimization. To our best knowledge, there do exist some studies that propose non-classical approach to multi-objective inventory management. However, some of the objectives in earlier studies are not conflicted each other such that the multi-objective models were not properly justified. In this paper, a bi-objective inventory management model without redundancy is discussed first. Then a solution procedure based on evolutionary multi-objective optimization is introduced to effectively solve the fixed order model. The results show that the intrinsic multi-objective approach can find efficient policies of order size and safety factor simultaneously without estimating shortage cost or service level. Moreover, a fitted exchange curve of cost and service is useful in determining the best customer service possible for the given investment in inventory management. The cost-service trade-off can be observed in a single run of an iterative computation, so that it is more appropriate for the practice of inventory management. Key words: inventory management, exchange curve, multi-objective optimization, particle swarm optimization.

Evolutionary Pareto optimizers for continuous review stochastic inventory systems

Multi-objective inventory control has been studied for a long time. The trade-off analysis of cycle stock investment and workload, so called the exchange curve concept, possibly dates back to several decades ago. A classical way to such trade-off analysis is to utilize the Lagrangian relaxation technique or interactive method to search for the optimum in a sequence of single objective optimization problems. However, the field of optimization has been changed over the last few decades since the concept of evolutionary computation was introduced. In this paper, a continuous review stochastic inventory system with three objectives about cost and shortage is resolved by evolutionary computation in order to plan for the control policies under backordering and lost sales. Two evolutionary optimizers, multi-objective electromagnetism-like optimization (MOEMO) and multi-objective particle swarm optimization (MOPSO), are employed to well and fast approximate the non-dominated policies in term of lot size and safety stock. Trade-offs are observed in a non-dominated set that no one excels the others in all objectives. Computational results show that the evolutionary Pareto optimizers could generate trade-off solutions potentially ignored by the well-known simultaneous method. Comparisons between the results of backordering and lost sales indicate that decision makers will make more deliberate choices about lot sizing and safety stocking when unsatisfied demand is completely lost.

The NMR Structures of the Major Intermediates of the Two-domain Tick Carboxypeptidase Inhibitor Reveal Symmetry in Its Folding and Unfolding Pathways

There is a lack of experimental structural information about folding intermediates of multidomain proteins. Tick carboxypeptidase inhibitor (TCI) is a small, disulfide-rich protein consisting of two domains that fold and unfold autonomously through the formation of two major intermediates, IIIa and IIIb. Each intermediate contains three native disulfide bonds in one domain and six free cysteines in the other domain. Here we have determined the NMR structures of these two intermediates trapped and isolated at acidic pH in which they are stable and compared their structures with that of the native protein analyzed under the same conditions. Both IIIa and IIIb were found to contain a folded region that corresponds to the N- and C-terminal domains of TCI, respectively, with structures very similar to the corresponding regions of the native protein. The remainder of the polypeptide chains of the intermediates was shown to be unfolded in a random coil conformation. Solvent exchange measurements further indicated that the two protein domains are not completely independent, but affect each other in terms of dynamics and stability, in agreement with reported inhibitory activity data. The derived results provide structural evidence for symmetric TCI folding and unfolding mechanisms that converge in IIIa and IIIb and reveal the structural basis that accounts for the strong and simultaneous accumulation of both intermediates. Altogether, this work has important implications for a better understanding of the folding mechanisms of multidomain, disulfide-rich proteins.

An estimation of CO2 fixation capacity in mangrove forest using two methods of CO2 gas exchange and growth curve analysis

In many coastal areas of South-East Asia, attempts have been made to revive coastal ecosystem by initiating projects that encourage planting of mangrove trees. Compared to the terrestrial trees, mangrove trees possess a higher carbon fixation capacity. It becomes a very significant option for clean development mechanism (CDM) program. However, a reliable method to estimate CO2 fixation capacity of mangrove trees has not been established. Acknowledging the above fact, we decided to set up an estimation method for the CDM program, using gas exchange analysis to estimate mangrove productivity, we put into consideration the net CO2 fixation of reforested Kandelia candel (5-, 10-, and 15-year-old stand). This was estimated by gas exchange analysis and growth curve analysis. In growth curve analysis, we drew a growth curve of a single stand using data of above- and below-ground biomass. In the gas exchange analysis, we calculated CO2 fixation capacity by (1) measuring respiration rate of each organ of stand and calculating respiratory CO2 emission from above- to below-ground biomass. (2) Measuring the single-leaf photosynthetic rate in response to light intensity and calculating the photosynthetic CO2 absorption. (3) We also developed a model for the diurnal changes in temperature, and monthly averages based on one-day estimation of CO2 absorption and emission, which we corrected by this model in order to estimate the net CO2 fixation capacity in response to temperature. Comparing the biomass accumulation of the two methods constructed for the same forest, the above-ground biomass accumulation of 10-year-old forest (34.3 ton ha−1 yr−1) estimated by gas exchange analysis was closely compared to those of growth curve analysis (26.6 ton ha−1 yr−1), suggesting that the gas exchange analysis was capable of estimating mangrove productivity. The validity of the estimated CO2 fixation capacity by the gas exchange analysis and the growth curve analysis was also discussed.

Synthesis of LiAlTiO4 and its selectivity to Li+ exchange

The ion-exchanger LiAlTiO4 of spinel type was prepared by the common precipitation/hydrothermal crystallization method, and was acid-modified. Its ion-exchange properties for alkali ions such as saturation capacity of exchange, distribution coefficient and pH titration curve were determined. LiAlTiO4 was characterized by the X-ray diffraction method. The acid treatment of LiAlTiO4 caused Li+ extraction ratio to change from 28% to 72%, while the dissolution of Al is less than 6.8%. This inorganic ion-exchanger (LiAlTiO4-700) has a higher saturation capacity of exchange for Li than for other alkali ions, the saturation capacity of exchange for Li+ reaches 4.29 mmol/g (30.03 mg/g); LiAlTiO4-700(H) has a higher selectivity of ion exchange for Li+ than for other alkali ions. These results show LiAlTiO4-700(H) has better memory and selectivity of ion exchange, and higher capacity of ion exchange for Li+. It is a kind of prospective ionic sieve for Li+.