A Process and Economic Model for the Real-Time Optimization of Operating Profit in a Citrus Feedmill

2007 ◽  
Author(s):  
Donald G. Gray
Keyword(s):  
Real Time ◽  
Economic Model ◽  
Product Market ◽  
Optimal Operation ◽  
Operating Conditions ◽  
Financial Loss ◽  
Performance Targets ◽  
Market Values ◽  
Operating Profit ◽  
Resource Cost

During the past 6 years, increases in energy costs have adversely impacted the profitability of feedmill operations. The market values of dried feed, molasses, and d-limonene have not sufficiently increased to offset this additional cost. Lacking alternatives to processing wet peel, many of the large citrus processors have operated feedmills at a financial loss. The optimal operation of a citrus feedmill requires that a combination of process, resource cost, and product market value data be analyzed and translated into actions that will maximize operating profit or minimize operational losses. In particular, variations in peel volume and moisture content, evaporation requirements, product market values, and resource costs require that a detailed process and economic analysis be routinely performed to achieve optimal financial performance. As a result, the complexity of achieving optimal performance on a day-to-day basis can be overwhelming to operators and managers. This paper discusses operational challenges that are common to many citrus feedmill operations, and proposed solutions. The basis for these solutions is a mathematical process and economic model that utilizes operational data to forecast production quantities and operational costs for a specified set of operating conditions. Equations are developed for optimizing energy usage, solids value, and operating profit in real-time. In addition to optimizing daily performance, the model can be used to determine optimal product yields, train operators and managers, determine the technical and financial merit of capital improvement projects, establish realistic performance targets, and devise accurate cost accounting drivers. Paper published with permission.

Power Test System Development and Dynamic Performance State Estimation Based on Hub Motor Vehicle

2020 ◽  
Vol 13 (2) ◽  
pp. 126-140
Author(s):  
Jing Gan ◽  
Xiaobin Fan ◽  
Zeng Song ◽  
Mingyue Zhang ◽  
Bin Zhao
Keyword(s):  
Real Time ◽  
Dynamic Performance ◽  
Test System ◽  
Operating Conditions ◽  
Motor Vehicles ◽  
Maximum Speed ◽  
Performance Parameters ◽  
Power Performance ◽  
Power Test ◽  
The Real

Background: The power performance of an electric vehicle is the basic parameter. Traditional test equipment, such as the expensive chassis dynamometer, not only increases the cost of testing but also makes it impossible to measure all the performance parameters of an electric vehicle. Objective: A set of convenient, efficient and sensitive power measurement system for electric vehicles is developed to obtain the real-time power changes of hub-motor vehicles under various operating conditions, and the dynamic performance parameters of hub-motor vehicles are obtained through the system. Methods: Firstly, a set of on-board power test system is developed by using virtual instrument (Lab- VIEW). This test system can obtain the power changes of hub-motor vehicles under various operating conditions in real-time and save data in real-time. Then, the driving resistance of hub-motor vehicles is analyzed, and the power performance of hub-motor vehicles is studied in depth. The power testing system is proposed to test the input power of both ends of the driving motor, and the chassis dynamometer is combined to test so that the output efficiency of the driving motor can be easily obtained without disassembly. Finally, this method is used to carry out the road test and obtain the vehicle dynamic performance parameters. Results: The real-time current, voltage and power, maximum power, acceleration time and maximum speed of the vehicle can be obtained accurately by using the power test system in the real road experiment. Conclusion: The maximum power required by the two motors reaches about 9KW, and it takes about 20 seconds to reach the maximum speed. The total power required to maintain the maximum speed is about 7.8kw, and the maximum speed is 62km/h. In this article, various patents have been discussed.

Real-time Optimal Operation of Microgrid with Power-to-hydrogen

2020 ◽  
Author(s):  
Zhiyao Zhong ◽  
Danji Huang ◽  
Kewei Hu ◽  
Xiaomeng Ai ◽  
Jiakun Fang
Keyword(s):  
Real Time ◽  
Optimal Operation ◽  
Time Optimal

scholarly journals Dynamic Modelling and Simulation of a Multistage Flash Desalination System

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 522
Author(s):  
Qiu-Yun Huang ◽  
Ai-Peng Jiang ◽  
Han-Yu Zhang ◽  
Jian Wang ◽  
Yu-Dong Xia ◽  
...  
Keyword(s):  
Real Time ◽  
Mass Flow Rate ◽  
Mass Flow ◽  
Flow Rate ◽  
Dynamic Change ◽  
Seawater Temperature ◽  
Dynamic Modelling ◽  
Optimal Operation ◽  
Simultaneous Solution ◽  
Time Optimal

As the leading thermal desalination method, multistage flash (MSF) desalination plays an important role in obtaining freshwater. Its dynamic modeling and dynamic performance prediction are quite important for the optimal control, real-time optimal operation, maintenance, and fault diagnosis of MSF plants. In this study, a detailed mathematical model of the MSF system, based on the first principle and its treatment strategy, was established to obtain transient performance change quickly. Firstly, the whole MSF system was divided into four parts, which are brine heat exchanger, flashing stage room, mixed and split modulate, and physical parameter modulate. Secondly, based on mass, energy, and momentum conservation laws, the dynamic correlation equations were formulated and then put together for a simultaneous solution. Next, with the established model, the performance of a brine-recirculation (BR)-MSF plant with 16-stage flash chambers was simulated and compared for validation. Finally, with the validated model and the simultaneous solution method, dynamic simulation and analysis were carried out to respond to the dynamic change of feed seawater temperature, feed seawater concentration, recycle stream mass flow rate, and steam temperature. The dynamic response curves of TBT (top brine temperature), BBT (bottom brine temperature), the temperature of flashing brine at previous stages, and distillate mass flow rate at previous stages were obtained, which specifically reflect the dynamic characteristics of the system. The presented dynamic model and its treatment can provide better analysis for the real-time optimal operation and control of the MSF system to achieve lower operational cost and more stable freshwater quality.

scholarly journals DeepFogSim: A Toolbox for Execution and Performance Evaluation of the Inference Phase of Conditional Deep Neural Networks with Early Exits Atop Distributed Fog Platforms

2021 ◽  
Vol 11 (1) ◽  
pp. 377
Author(s):  
Michele Scarpiniti ◽  
Enzo Baccarelli ◽  
Alireza Momenzadeh ◽  
Sima Sarv Ahrabi
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Future Internet ◽  
Operating Conditions ◽  
Graphic User Interface ◽  
Energy Aware ◽  
Internet Applications ◽  
The Real ◽  
Delay Performance ◽  
Hard Constraints

The recent introduction of the so-called Conditional Neural Networks (CDNNs) with multiple early exits, executed atop virtualized multi-tier Fog platforms, makes feasible the real-time and energy-efficient execution of analytics required by future Internet applications. However, until now, toolkits for the evaluation of energy-vs.-delay performance of the inference phase of CDNNs executed on such platforms, have not been available. Motivated by these considerations, in this contribution, we present DeepFogSim. It is a MATLAB-supported software toolbox aiming at testing the performance of virtualized technological platforms for the real-time distributed execution of the inference phase of CDNNs with early exits under IoT realms. The main peculiar features of the proposed DeepFogSim toolbox are that: (i) it allows the joint dynamic energy-aware optimization of the Fog-hosted computing-networking resources under hard constraints on the tolerated inference delays; (ii) it allows the repeatable and customizable simulation of the resulting energy-delay performance of the overall Fog execution platform; (iii) it allows the dynamic tracking of the performed resource allocation under time-varying operating conditions and/or failure events; and (iv) it is equipped with a user-friendly Graphic User Interface (GUI) that supports a number of graphic formats for data rendering. Some numerical results give evidence for about the actual capabilities of the proposed DeepFogSim toolbox.

Long-term versus Real-time Optimal Operation for Gate Regulation during Flood in Urban Drainage Systems

2018 ◽  
Vol 15 (8) ◽  
pp. 750-759 ◽  
Author(s):  
Fatemeh Jafari ◽  
S. Jamshid Mousavi ◽  
Jafar Yazdi ◽  
Joong Hoon Kim
Keyword(s):  
Real Time ◽  
Optimal Operation ◽  
Urban Drainage ◽  
Drainage Systems ◽  
Urban Drainage Systems ◽  
Time Optimal

Real-Time Thermodynamic Performance Monitoring and Optimum Thermoeconomic Operation of Power Plants

2011 ◽  
Author(s):  
G. Hariharan ◽  
B. Kosanovic
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Real Time ◽  
Power Plants ◽  
Operating Conditions ◽  
Recursive Least Squares ◽  
Time Data ◽  
Real Time Data ◽  
One Step ◽  
Inputs And Outputs

The ability of modern power plant data acquisition systems to provide a continuous real-time data feed can be exploited to carry out interesting research studies. In the first part of this study, real-time data from a power plant is used to carry out a comprehensive heat balance calculation. The calculation involves application of the first law of thermodynamics to each powerhouse component. Stoichiometric combustion principles are applied to calculate emissions from fossil fuel consuming components. Exergy analysis is carried out for all components by the combined application of the first and second laws of thermodynamics. In the second part of this study, techniques from the field of System Identification and Linear Programming are brought together in finding thermoeconomically optimum plant operating conditions one step ahead in time. This is done by first using autoregressive models to make short-term predictions of plant inputs and outputs. Then, parameter estimation using recursive least squares is used to determine the relations between the predicted inputs and outputs. The estimated parameters are used in setting up a linear programming problem which is solved using the simplex method. The end result is knowledge of thermoeconomically optimum plant inputs and outputs one step ahead in time.

scholarly journals Data-driven Adaptive Thresholding Model for Real-time Valve Delay Estimation in Digital Pump/Motors

2020 ◽  
Author(s):  
Abdallah Chehade ◽  
Farid Breidi ◽  
Keith Scott Pate ◽  
John Lumkes
Keyword(s):  
High Pressure ◽  
Real Time ◽  
Domain Knowledge ◽  
Operating Conditions ◽  
Delay Model ◽  
Hydraulic Systems ◽  
Pressure Transducers ◽  
Statistical Behavior ◽  
Shift Detection ◽  
And Performance

Valve characteristics are an essential part of digital hydraulics. The on/off solenoid valves utilized on many of these systems can significantly affect the performance. Various factors can affect the speed of the valves causing them to experience various delays, which impact the overall performance of hydraulic systems. This work presents the development of an adaptive statistical based thresholding real-time valve delay model for digital Pump/Motors. The proposed method actively measures the valve delays in real-time and adapts the threshold of the system with the goal of improving the overall efficiency and performance of the system. This work builds on previous work by evaluating an alternative method used to detect valve delays in real-time. The method used here is a shift detection method for the pressure signals that utilizes domain knowledge and the system’s historical statistical behavior. This allows the model to be used over a large range of operating conditions, since the model can learn patterns and adapt to various operating conditions using domain knowledge and statistical behavior. A hydraulic circuit was built to measure the delay time experienced from the time the signal is sent to the valve to the time that the valve opens. Experiments were conducted on a three piston in-line digital pump/motor with 2 valves per cylinder, at low and high pressure ports, for a total of six valves. Two high frequency pressure transducers were used in this circuit to measure and analyze the differential pressure on the low and high pressure side of the on/off valves, as well as three in-cylinder pressure transducers. Data over 60 cycles was acquired to analyze the model against real time valve delays. The results show that the algorithm was successful in adapting the threshold for real time valve delays and accurately measuring the valve delays. 

scholarly journals New Approaches to the Interpretation of Balance in the Digital Economy

2020 ◽  
Vol 17 (3) ◽  
pp. 25-36
Author(s):  
M. I. Lugachev ◽  
N. V. Ulianova ◽  
K. G. Skripkin
Keyword(s):  
Real Time ◽  
Balance Sheet ◽  
Forecast Model ◽  
Financial Capital ◽  
Selling Price ◽  
The Past ◽  
Financial Condition ◽  
Operating Profit ◽  
The Impact ◽  
Operating Activities

The purpose of the article is to theoretically prove the possibility of generating forecast information in the balance-sheet regarding profit indicators, net inflow of operating money and financial capital. According to the authors, the system of these indicators is revealed in dynamics, thus reflecting the impact of profit on the financial condition of the organization. A logical and accounting balance-sheet relationship is established between actual and forecast indicators that characterize the financial condition in the past and future. By analyzing the processes in the operating cycle, the economic and financial feasibility of operating profit as a net cash flow from operating activities is theoretically proved. Based on the process approach and the induction method, the indicator of operating profit is included in the valuation of the asset and liability side of the balance-sheet, thereby developing the valuation method and forming a new forecast model of balance-sheet generalizations. The content of the forecast model of balance is described in the form of a balance equation. The obtained theoretical conclusions are verified experimentally.As a result, the asset of the balance-sheet reflects the process of transforming the value of operational resources into their selling price, and the forecast operating profit is generated in the liability side of the balance-sheet, which relates to assets and liabilities recognized in accounting at the current time. Cost parameter and value index are introduced, which characterize the indicators of income and expenses as the transformation of operational resources. Any change in the cost of resources used and the possible price (value) of their sale is reflected in the balance-sheet and affects the change in the estimate of forecast operating profit in real time. At the same time, due to the simultaneous recognition in the balance-sheet of actual and forecast estimates of assets and liabilities and the indicator of forecast operating profit, the indicator of financial capital receives a new interpretation. If we compare the value of assets and accounts payable, then financial capital characterizes the security of operating activities with own sources of financing in the past. If we compare the selling price of assets and account payable, then financial capital shows the forecast for repayment of account payable at the expense of own funds in the future. Consequently, the transition from actual to forecast estimates in the balance-sheet reveals the process of the circulation of operating capital and shows how much profit is provided by investments in working stocks made in the past. Due to the double recording method, any forecast estimates can be verified by the user, which increases the reliability of the forecast information in the balance-sheet.In fact, the balance-sheet is interpreted as a new method of analysis and forecasting of financial and economic indicators characterizing the activities of the organization. At the same time, it is not necessary to perform additional analytical calculations, forecast operating profit and analysis of its impact on financial capital can be carried out in real time as often as accounting entries are made that affect the change in working capital.

scholarly journals Digital Data Processing Methods for Estimating Tractive Force of Tractors

2021 ◽  
Vol 31 (1) ◽  
pp. 127-142
Author(s):  
Vyacheslav F. Fedorenko ◽  
Vitaly E. Tarkivskiy ◽  
Nikolay P. Mishurov ◽  
Nikolay V. Trubitsyn
Keyword(s):  
Real Time ◽  
Strain Gauge ◽  
Impulse Noise ◽  
Median Filter ◽  
Digital Processing ◽  
Operating Conditions ◽  
Measuring Instruments ◽  
Important Indicator ◽  
Tractive Effort ◽  
Useful Signal

Introduction. When carrying out an energy assessment of agricultural machines and traction tests of tractors, the most important indicator is the value of the tractive effort. The existing methods for determining the tractive effort of tractors imply the use of specialized measuring instruments, such as strain gauges and devices for processing and displaying information. The accuracy of determining the tractive effort is significantly influenced by the physical and mechanical properties of soil. To process the useful signal during the measurement of tractive effort, the data stream of the strain gauge sensor must be subjected to additional digital filtering taking into account the operating conditions of the agricultural unit. Materials and Methods. The functions of changing the tractive effort obtained on the K-744R2 tractor in various gears have been analyzed. An algorithm for digital processing of the signal of a strain gauge force meter based on a median filter has been developed that makes it possible to increase the measurement accuracy. The advantage of the proposed method is the ability to cut off sharp short-term impulse noise and sharp fluctuations in the amplitude of the measured value. Results. A method for determining the amount of tractive effort using median signal processing has been proposed. A device for determining the tractive effort during testing of agricultural tractors and units has been developed. The choice of the main components of the device for determining the magnitude of the tractive effort has been substantiated. As a result of the research, a device for measuring and digital processing of the signal of a force meter based on a microcontroller and specialized software for processing initial data in real time was designed and manufactured. Discussion and Conclusion. The developed method makes it possible to exclude the negative effect of impulse noise arising in the process of measuring the tractive effort of the tractor. The proposed device for measuring the tractive effort of tractors is compatible at the level of the exchange protocol with existing devices, has a high speed of operation in real time, multi-channel operation.

scholarly journals When Low Market Values are No Bad News: On the Coordination of Renewable Support and Real-Time Pricing

2015 ◽  
Author(s):  
Michael Pahle ◽  
Wolf-Peter Schill ◽  
Christian Gambardella ◽  
Oliver Tietjen
Keyword(s):  
Real Time ◽  
Bad News ◽  
Market Values ◽  
Real Time Pricing
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