Optimal Flow Distribution Research Articles

Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm

The high variability and uncertainty introduced into modern electrical distribution systems due to decentralized renewable energy generators requires new solutions for grid management and power quality assurance. One of these possible solutions includes grid integrated energy storage. The appropriate size and placement of decentralized storage is highly dependent on purpose of the battery system and expected operational strategy. However, battery operational strategies are difficult to simulate simultaneously during a sizing and placement planning calculation. The motivation of this paper is to propose an algorithm that is capable of integrating sizing, placement and operational strategies of batteries into an Optimal Power Flow (OPF) distribution grid planning tool. The choice of the OPF approach permits to account for grid constraints which is more adapted for grid-connected storage devices compared to other approaches in the state of the art that are based only on an email balance analysis. This paper presents an alternating current (AC) multi-temporal OPF algorithm that uses a convex relaxation of the power flow equations to guarantee exact and optimal solutions with high algorithmic performance. The algorithm is unique and innovative due to the fact that it combines the simultaneous optimization of placement and sizing of storage devices taking into account load curves, photovoltaic (PV) production profiles, and distribution grid power quality constraints. The choice to invest in battery capacity is highly sensitive to the price of battery systems. The investment in battery systems solely for reducing losses an operational costs was proven not to be cost effective, however when battery systems are allowed to buy and sell electricity based on variable market prices they become cost effective. The assumptions used for this study shows that current battery system prices are too high to be cost effective even when allowing battery system market participation.

Concealment measurement and flow distribution of military supply transportation: A double-entropy model

To address the issues of military supply distribution and transportation under the restrictions of concealment during war preparation and warfare periods, this study proposes a double-entropy model to measure the degree of the comprehensive concealment of military supply transportation from the perspectives of transportation and detection. With respect to the real road conditions, we further develop this double-entropy model with consideration of the width and length of roads and introduction of the limitations of average transportation. The reasonability of this model and its related definitions are then demonstrated by theoretical analysis and mathematical proof. Subsequently, three distinctive properties of military supply transportation via a road or a road network, namely unordering, scalability, and directionality, are investigated. Based on the double-entropy model and the above properties, a flow distribution model of military supply is designed, which addresses a vital issue in the event of a military confrontation or regional war. Finally, we provide an example that calculates an optimal flow distribution schedule to carry out a regional military drill in the Jiangsu Province of China to demonstrate the proposed concepts and approaches.

Rule Minimization for Traffic Evolution in Software-Defined Networks

This letter addresses the problem of traffic evolution in software defined networks (SDNs). SDNs achieve optimal flow distribution by using flow optimization models, but as traffic evolves, the underlying optimization model changes. Applying the online model frequently can result in a flood of control messages to switches for deleting, modifying, or installing new rules, and the resulting traffic re-routing can cause transient loops and synchronization issues. In this letter, we present minimum rule application (MIRA), a mixed integer linear programming-based model, which re-calculates flow distribution dynamically while minimizing the number of rule installations. Since the proposed model is NP-hard, we also propose an efficient heuristic-based greedy algorithm. In addition, we also propose a rule-aggregation (RA) optimization for minimizing rule installation (MIRA-RA). Finally, we propose a multi-objective optimization model, which jointly minimizes the conflicting objectives of rule installation and link utilization (PARETO) and use the $\epsilon $ -constraint method to achieve pareto-optimality. We implement MIRA, MIRA-RA, Greedy, PARETO, and an existing solution in the area and present numerical results.

Multipath Routing Mathematical Model to Solve the Traffic Engineering in Multi-Protocol Label Switching Network

Multipath Protocol Label Switching (MPLS) is a routing mechanism (technology) used in modern telecommunication networks, which is built as a multi-service network with a certain Quality of Service (QoS). To maintain the required QoS in such complicated networks, the Traffic Engineering (TE) should be equipped with optimum traffic management, routing mechanism, and switching operations, which are what this paper tackles, where the TE is identified as the optimal distribution of flows in the existing network. In this paper, an effective multipath routing mathematical model is developed based on several previous mechanisms to ensure the guaranteed desired QoS and loading balance according to the Telecommunication Network Systems (TCS) resources, to achieve the optimum TE, and hence improving the network usage efficiency. Moreover, the obtained mathematical optimization algorithm results are provided through the relative equations. Indeed the developed routing mathematical model in this paper is suitable for the dynamic distribution of information flows, which is the main improvement in the TE achieved in this work.

Analysis of the Secondary Network Flow Distribution in Absorption Heat Exchange Unit

An absorption heat-exchanger consists of an absorption heat pump driven by hot water and a conventional water-water heat exchanger. The return water of the secondary network is divided into two units: one part is sent into the water-water heat exchanger, heated by the primary network, and the other is heated in the absorption heat pump. Finally, the water of the two parts is mixed and transmitted to the end consumers. The flow distribution of the secondary network will affect the return water temperature of the primary network. The flow proportion of the secondary network and primary network in the water-water heat exchanger is selected 1:1~2:1, according to the experience in practice. However, the actual operation effect may not be optimal. The flow distribution principle of the secondary network is proposed in this paper through simulation calculation. The optimal flow distribution principle is obtained by calculating the minimum value of the return water temperature of the primary network. The results provide the reference for the optimized design and operation of the ab-sorption heat exchanger.

Experimental investigation of combined transpiration and film cooling for sintered metal porous struts

A combined transpiration and film cooling method was evaluated experimentally for protecting struts made of sintered stainless steel porous media with film holes on the leading edge in a supersonic wind tunnel. The combined cooling results were compared to standard transpiration cooling of the strut. Schlieren figures show that the film cooling and transpiration cooling had little effect on the flow field stability and the shock wave profiles around the struts for the present conditions. Standard transpiration cooling can protect most of the strut but cannot effectively cool the leading edge even with increased coolant injection pressures. The combined film and transpiration cooling effectively cools both the leading edge and other parts of the strut. Non-uniform coolant injection with higher injection pressures in the front cavity and lower injection pressures in the back cavity more effectively utilized the limited coolant flow. The average cooling efficiency of the front part of the strut increased from 25.7% for standard transpiration cooling to 37.9% for combined transpiration and film cooling with the same coolant consumption using the optimal non-uniform coolant flow distribution.

Numerical and experimental investigation on the realization of target flow distribution among parallel mini-channels

Fluid flow maldistribution is considered as one of the main causes of performance deterioration in various energy and process systems, especially when parallel micro- or mini-channel fluidic networks are involved. For a specific purpose, the optimal flow distribution is not necessarily uniform. However, specific non-uniform distributions are somewhat more difficult to achieve than uniform ones. The insertion of a geometrically optimized baffle has been numerically confirmed as an effective solution to this issue, but experimental validation is still lacking which is indispensable for bridging the gap between theory and practice.This paper presents a numerical and experimental investigation on the realization of target flow distribution among parallel mini-channels, using the optimized baffle insertion method. A 15-channel fluidic network integrated with the distributor and the collector is fabricated and tested. Various perforated baffles are optimized and fabricated corresponding to different target distributions (uniform, ascending and descending). PIV technique is used for the flow distribution measurement while CFD simulations are also performed for comparison. CFD results and PIV data show that different target distributions could be successfully achieved by the optimized baffle insertion method. The robustness of the optimized baffle for uniform distribution is also evaluated and discussed to provide some guidelines for future applications.

Design and optimization of baffled fluid distributor for realizing target flow distribution in a tubular solar receiver

This paper presents an original study on the design and optimization of baffled fluid distributor for the realization of optimal fluid flow distribution in a tubular solar receiver. The basic idea is to install a perforated baffle in the inlet fluid distributor and to optimize the configuration of orifices on the baffle so as to approach the target flow distribution among downstream parallel tubes. A pressurized-air solar receiver comprising of 45 parallel tubes is used for study, with copper or Inconel 600 used as the filling material.Results show that the final fluid flow distributions realized by the geometrically optimized baffles are in good agreement with the target curves. The peak temperature of the receiver wall can be minimized accordingly with moderate increase in total pressure drop of the receiver system. It is shown that the insertion of a geometrically optimized baffle is generally a practical solution with various features: capable of realizing non-uniform target distribution; small pressure drop increase; compact geometry; flexible and adaptive; easy fabrication with a reasonable cost, etc.

Influence of Anode Configuration on Flow Distribution and Performance in Tubular Microbial Fuel Cells

A microbial fuel cell (MFC) is a device that utilizes bacteria to oxidize organic and inorganic matter, and through the process of extracellular electron transfer, generate electricity. When the electron transfer at the bacteria-electrode interface is rapid, the efficiency of a MFC is dependent on the flow distribution and mass transport in the anode, which controls the delivery of reactants and removal of waste products. It has been predicted that diffusion of soluble substrates is fast over the length scale of bacterium, but gets significantly slower over millimeter-scale distances and at the scale of centimeters, advection is required. Electrolyte advection along with optimal flow distribution will bring substrates to anode respiring bacteria and enable substrate utilization at high rates. Therefore, in this study we explored the influence of the anode configuration on flow distribution and MFC performance. The efficiency of the system was determined on the basis of chemical oxygen demand (COD) removal and Columbic Efficiency (CE). The MFC used for these studies was a membrane based tubular MFC with a submerged oxygen-reducing cathode. Three anode configurations were explored and included: 1) packed graphite granules (MFC 1); 2) bundles of stacked graphite granules (MFC 2); and 3) a small polypropylene mesh cylinder filled with packed graphite granules, wrapped with pleated carbon cloth (MFC 3). The volume of the anode compartment of each reactor was 1L. The reactors were operated under MFC, semi-batch mode with a downstream flow. The reactors were first inoculated with swine waste and lagoon sediment and subsequently fed with swine waste only 1,300 mg-COD/L. Key parameters were measured on a weekly basis including COD, pH, dissolved oxygen (DO) and turbidity. Samples for 16S rRNA analysis were also collected on a weekly basis from the effluents of each reactor for the classification and identification of bacterial species present. Voltage data was recorded continuously and polarization curves and cyclic voltammetry were periodically performed to monitor biofilm development and MFCs operation. The preliminary results indicate that due to the advanced flow distribution, MFC 3 demonstrated the highest performance. It showed a startup time of approximately 4 days and achieved a voltage of 0.40 V. MFC 2 also had a startup time of approximately 4 days and achieved a voltage of 0.15 V. MFC 1 had the slowest startup time of about 11 days with a voltage of ≈ 0.10 V. All MFCs were operated under 560 Ω resistors. Future work will include a comprehensive analysis of microbial dynamics and system performance to determine which anode structure was most correlated to improved wastewater treatment and energy recovery activities.

A Novel Traffic Control Scheme for Multi-Layered Satellite Network Based on Chain Reaction Model

Multi-Layered Satellite Network (MLSN) is a kind of delay tolerant network with characters of intermittent connection, long packet queuing time, complex and uncertain delay time, etc. The call congestion rate of new business is higher in delay tolerant network which leads to the reduction of communication quality and the high packet loss rate. The existing traffic control scheme is hard to meet the individual requirements of new business. It becomes more and more important to study the most effective traffic control scheme so as to increase the satellite bandwidth utilization. According to the nuclear chain reaction of atomic physics, a novel traffic control method based on chain reaction model (TCCR) is presented in this paper to realize dynamic data transmission and control for MLSN. The optimal flow distribution scheme will be obtained by analyzing the network transmission information in this algorithm. Simulation by OPENT is done which proves that TCCR can obviously improve the network total throughput, shorten link transmission delay, and reduce packet loss rate of MLSN.

Integrating Optimal Simulation Budget Allocation and Genetic Algorithm to Find the Approximate Pareto Patient Flow Distribution

The imbalanced development among different levels of healthcare facilities has become a major social issue in China’s urban healthcare system, which has raised the irrational patient flow distribution on the levels of both intra-hospital and inter-healthcare facilities. In this research, we develop a methodology to find the optimal macrolevel patient flow distribution in terms of multidimension inputs and outputs for the two-level healthcare system. The proposed method integrates the discrete-event simulation (DES), the multiobjective optimization and the simulation budget allocation together to comprehensively improve the overall system performances by finding the approximate Pareto patient flow distribution in the hierarchical healthcare system. The multiobjective optimal computing budget allocation (MOCBA) is applied to improve the efficiency, where the nondominated probability is functioned as the fitness measurement to each design. A case study based on the real data is carried out to validate and implement the proposed method. The results of the case study show the recommended Pareto optimal patient flow distribution can improve the overall hierarchical system performances and our methodology are qualified as a quantitative decision tool for decision makers.

Quantitative and qualitative analysis of the flow field development through T99 draft tube caused by optimized inlet velocity profiles

The effect of the inlet swirling flow in a hydraulic turbine draft tube is a very complex phenomenon, which has been extensively investigated both theoretically and experimentally. In fact, the finding of the optimal flow distribution at the draft tube inlet in order to get the best performance has remained a challenge. Thus, attempting to answer this question, it was assumed that through an automatic optimization process a Genetic Algorithm would be able to manage a parameterized inlet velocity profile in order to achieve the best flow field for a particular draft tube. As a result of the optimization process, it was possible to obtain different draft-tube flow structures generated by the automatic manipulation of parameterized inlet velocity profiles. Thus, this work develops a qualitative and quantitative analysis of these new draft tube flow field structures provoked by the redesigned inlet velocity profiles. The comparisons among the different flow fields obtained clearly illustrate the importance of the flow uniformity at the end of the conduit. Another important aspect has been the elimination of the re-circulating flow area which used to promote an adverse pressure gradient in the cone, deteriorating the pressure recovery effect. Thanks to the evolutionary optimization strategy, it has been possible to demonstrate that the optimized inlet velocity profile can suppress or mitigate, at least numerically, the undesirable draft tube flow characteristics. Finally, since there is only a single swirl number for which the objective function has been minimized, the energy loss factor might be slightly affected by the flow rate if the same relation of the axial-tangential velocity components is maintained, which makes it possible to scale the inlet velocity field to different operating points.

ICONE23-1841 THERMAL HYDRAULIC ANALYSIS OF WATER COOLED BREEDER BLANKET DESIGNED FOR CFETR

CFETR (Chinese Fusion Engineering Testing Reactor) is a superconducting Tokamak device. The simulation was performed on the cooling circuit inside water cooled breeder blanket which is one of the breeding blanket candidates for CFETR to compare the thermal hydraulic characteristics based on superheated steam and PWR (pressurized water reactor) water conditions. The work is carried out using MELCOR code. As a result, under the optimal flow distribution, it turns out that the thermal hydraulic characteristics meet the design requirements and the nuclear heat inside blanket module as well as heat flux from plasma could be removed completely by the cooling circuits on both conditions. It's also found that the temperature of first wall (FW) is higher on PWR condition than superheated steam. But due to the generation of superheated steam, the wall temperature would grow significantly in the backward zone of cooling circuit. Based on the steady state, LOFA (loss of flow accident) was simulated. It was predicted that FW will melt anyway due to the high nuclear heat without considering thermal radiation. As for different ways of FPSS, a 100s delay is invalid and a 3s delay could buy us time to take measures.

Optimal electrolyte flow distribution in hydrodynamic circuit of vanadium redox flow battery

This article presents the results of studies of the electrolyte flow configuration in a vanadium redox flow battery (VRFB). The flow structure is formed by a system of inlet and outlet channels and of porous collectors of the battery. This configuration is considered as a hydrodynamic circuit. The theoretical models, which were used to simulate the flow behaviour, are based on conservation laws of mass and of electric charge. The electrolyte flow was analysed on the basis of three theoretical models: total flow, depending on the electric current; flow distribution in the inlet/outlet channel system; flow distribution in a half-cell. For the test battery a capacity availability was calculated and measured in a wide range of the flow rate and of the electric current. The flow distribution in the porous collector was calculated and the efficiency by the different flow configurations in the half-cells was measured. The parameters and the configuration of the electrolyte inlet/outlet channels were optimized to obtain the uniform distribution of the electrolyte flow to each half-cell.

Go Beyond Conventional Hydraulic Tools for Optimized Flow Distribution in Your Wastewater Plant

Go Beyond Conventional Hydraulic Tools for Optimized Flow Distribution in Your Wastewater Plant

A dynamic evacuation model for pedestrian–vehicle mixed-flow networks

In urban emergency evacuation, a potentially large number of evacuees may depend either on transit or other modes, or need to walk a long distance, to access their passenger cars. In the process of approaching the designated pick-up points or parking areas for evacuation, the massive number of pedestrians may cause tremendous burden to vehicles in the roadway network. Responsible agencies often need to contend with congestion incurred by massive vehicles emanating from parking garages, evacuation buses generated from bus stops, and the conflicts between evacuees and vehicles at intersections. Hence, an effective plan for such evacuation needs to concurrently address both the multi-modal traffic route assignment and the optimization of network signal controls for mixed traffic flows. This paper presents an integrated model to produce the optimal distribution of vehicle and pedestrian flows, and the responsive network signal plan for massive mixed pedestrian–vehicle flows within the evacuation zone. The proposed model features its effectiveness in accounting for multiple types of evacuation vehicles, the interdependent relations between pedestrian and vehicle flows via some conversion locations, and the inevitable conflicts between intersection turning vehicle and pedestrian flows. An illustrating example concerning an evacuation around the M&T stadium area has been presented, and the results indicate the promising properties of our proposed model, especially on reflecting the complex interactions between vehicle and pedestrian flows and the favorable use of high-occupancy vehicles for evacuation operations.

Optimized Flow Distribution for Enhancing Temperature Uniformity Across An Open Cathode PEM Fuel Cell Stack

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Optimized Flow Distribution for Enhancing Temperature Uniformity across an Open Cathode PEM Fuel Cell Stack

The objective of this work is to develop a stable energy source based on renewable energy for powering an in-house developed unmanned robot. The major challenges are firstly to design a power source with higher energy density and secondly to develop a compact design (low volume and light weight stack) suitable for integrating with the in house robot platform. To overcome the aforementioned challenges, the study aims at designing an open cathode low temperature polymer electrolyte membrane fuel cell (PEMFC) system to be coupled with a battery to serves as an efficient power source. The major part of the work involves the design of compact fuel cell system. In a fuel cell the serpentine flow channel is considered to optimal because it has the advantage of uniform flow distribution, but with higher pressure drop. Because of the higher pressure drop a pump is required to supply the oxidant for chemical reaction. But with lower pressure drop and fairly uniform flow distribution open cathode stack design is developed, that facilitates the use of blower which consumes less power. Also the overall system volume can be reduced with higher efficiency.

Optimization methodology assessment for the inlet velocity profile of a hydraulic turbine draft tube: part I—computer optimization techniques

In recent years, numerical and experimental investigations on the draft tube performance have confirmed the importance of the inlet swirling flow created by the runner vanes. The results indicate that it is still a challenge to get the optimal flow distribution at the draft tube inlet which gives the best machine performance over a range of operation points. Consequently, there is a need to adjust the runner-draft tube coupling to minimize the losses arising from the inlet flow distribution. This paper focus on establishing an optimization methodology for maximizing the draft tube performance as a function of the inlet velocity profile. The overall work is divides into two parts: The part one establish the inlet velocity parametrization, the numerical optimization set-up and the objective function definition. The part two validate the numerical CFD draft tube model. These steps are represented by the coupling of the commercial softwares MATLAB, FLUENT and iSIGHT. It is considered that this proved methodology will help to find a inlet velocity profile shape which will be able to suppress or mitigate the undesirable draft tube flow characteristics.

Application of genetic algorithms for joint optimization of signal setting parameters and dynamic traffic assignment for the real network data

This paper presents the joint optimization of signal setting parameters and dynamic user equilibrium (DUE) traffic assignment for the congested urban road network. The simulation-based approach is employed to obtain the DUE condition for the case of multiple-origin multiple-destination traffic flows. The dynamic traffic assignment simulation program (DTASP), developed in C language is used to assign the traffic dynamically on the road network, whereas method of successive averages (MSA) is modified and used to arrive at the DUE condition. The artificial intelligence technique of genetic algorithms (GAs) is applied to obtain the optimal signal setting parameters and path flow distribution factor for DUE condition. The methodology developed in such a way that joint optimization of signal setting parameters with DUE is obtained. The proposed method is applied to the real network data of Fort Area of Mumbai city comprising of 17 nodes and 56 unidirectional links with 72 Origin–Destination pairs, where all the 17 nodes are signalized intersections. The traffic flow condition for the optimized signal setting parameters is considerably improved compared to the existing signal settings. The results prove that the GA is an effective technique to solve the joint optimization problem for the real network data.