Optimal Economic Performance Research Articles

Study on a novel reactive internally heat integrated distillation process for the synthesis of ethyl acetate and its column configuration

The production of ethyl acetate (EA) by reactive distillation (RD) has the disadvantage of high energy consumption. In order to solve this problem, the application of reactive internal heat integrated distillation was explored on the basis of RD process, and energy saving was further realized. The influence of different configurations of reactive internally heat integrated distillation column (RHIDiC) on the process were also studied. In this study, the symmetrical reaction internal heat integrated distillation column (S-RHIDiC), the upper aligned reaction internal heat integrated distillation column (UA-RHIDiC) and the lower aligned reaction internal heat integrated distillation column (LA-RHIDiC) were compared with RD in economic benefits, environmental protection, energy saving performance, and thermodynamic efficiency. In addition, all processes were optimized with TAC as the economic indicator. The results showed that S-RHIDiC process has the optimal economic benefits, environmental performance, energy consumption and thermodynamic efficiency. Compared with RD, the total annual cost (TAC) of S-RHIDiC was reduced by 32.56%, CO2 emissions were reduced by 52.79%, the TEC was reduced by 29.37%. The thermodynamic efficiency of RD, S-RHIDiC, UA-RHIDiC and LA-RHIDiC processes were 6.71%, 9.12%, 6.75% and 6.8%, respectively.

Economic optimization and dynamic control of pressure‐swing distillation for separating the ternary azeotrope of butanone/n‐heptane/isopropanol

AbstractBACKGROUNDEconomic optimization and dynamic control of the separation process for recovering the ternary mixture of butanone (MEK)/n‐heptane/isopropanol (IPA) from industrial wastewater is a significant topic. In this work, the optimal pressure‐swing distillation (PSD) sequence, heat integration and dynamic control for separating MEK/n‐heptane/IPA were investigated systematically. The optimal separation sequence was determined by combining the minimum total annual cost (TAC) with the residual curves map (RCM). Pressure‐swing distillation with non‐heat integration, partial heat integration or full heat integration was compared in terms of TAC. Dynamic control schemes were designed for optimal processes of two separation sequences with and without heat integration.RESULTSThe results demonstrate that the TAC of optimal PSD with non‐heat integration process can be reduced by 31.11%, whereas the TAC of optimal partial heat integration and full heat integration schemes can be reduced by 39.73% and 40.96%, respectively. The dynamic performance of all control schemes that can resist ±20% feed flow disturbances and composition disturbances are compared with the integral of squared error.CONCLUSIONIt is demonstrated that PSD with full integration process (FHIPSD) for separating MEK/n‐heptane/IPA has optimal economic performance, whereas PSD with non‐heat integration process (NTIPSD) has the optimal dynamic performance and robust stability. This work provides a significant reference for industrial separation of MEK/n‐heptane/IPA. © 2022 Society of Chemical Industry (SCI).

Carbon dioxide capture, transport and storage supply chains: Optimal economic and environmental performance of infrastructure rollout

This work presents a novel optimization framework for the optimal design of carbon capture, transport, and storage supply chains in terms of installation, sizing and operation of carbon dioxide (CO2) capture and transport technologies. The optimal design problem is formulated as a mixed-integer linear program that minimizes the total costs of the supply chains while complying with different emissions reduction pathways over a deployment time horizon of 25 years. All design decisions are time-dependent and are taken with a yearly resolution. Whereas the model is general, here its features are illustrated by designing optimal supply chains to decarbonize the Swiss waste-to-energy sector, for various emission reduction pathways, when up to two storage sites are considered, namely one in the North Sea assumed to be already available and a hypothetical one in Switzerland assumed to be possibly available in the future. Findings show that, unless a domestic storage site becomes available soon, the transport cost is the greatest contribution to the overall costs, followed by the capture cost, while the storage cost plays only a minor role. Pipelines are the most cost-effective mode of transport for large volumes of transported CO2, especially when considering multi-year time horizons for the planning of the supply chains. Ship and barge connections are competitive with pipeline connections, whereas rail and truck connections are cost-optimal only when considering shortsighted time horizons or small volumes of CO2 transported.

A Novel 10-Parameter Motor Efficiency Model Based on I-SA and Its Comparative Application of Energy Utilization Efficiency in Different Driving Modes for Electric Tractor

To build a more accurate motor efficiency model with a strong generalization ability in order to evaluate and improve the efficiency characteristics of electric vehicles, this paper researches motor efficiency modeling based on the bench tests of two motor efficiencies with differently rated powers. This paper compares and analyzes three motor efficiency modeling methods and finds that, when the measured values in motor efficiency tests are insufficient, the bilinear interpolation method and radial basis kernel function neural networks have poor generalization abilities in full working conditions, and the precision of polynomial regression is limited. On this basis, this paper proposes a new modeling method combining correlation analysis, polynomial regression, and an improved simulated annealing (I-SA) algorithm. Using the mean and the standard deviation of the mean absolute percentage error of the 5-fold Cross Validation (CV) of 100 random tests as the evaluation indices of the precision of the motor efficiency model, and based on the motor efficiency models with verified precision, this paper makes a comparative analysis on the full vehicle efficiency of electric tractors of three types of drive in five working conditions. Research results show that the proposed novel method has a high modeling precision of motor efficiency; tractors with a dual motor coupling drive system have optimal economic performance.

Investigation of the potential of R717 blends as working fluids in the organic Rankine cycle (ORC) for ocean thermal energy conversion (OTEC)

Ammonia, R717, has been considered as a useful working fluid of the organic Rankine cycle (ORC) in the OTEC. The aim of this study is to investigate the potentials of R717 blends on thermodynamic and economic performances to surpass pure R717 used in an OTEC. The environmentally friendly refrigerants of R32 and R1234YF are considered and selected as the components of R717 blends. The effects of mass fraction ratios for R717 blends and four pinch points of conditions for the ORC are applied to evaluate the net power output and energy cost of the OTEC.The performances of OTEC system with R717/R32 and R717/R1234YF are evaluated and compared with pure R717. In thermodynamic improvement, the maximum net power outputs of R717/R32 and R717/R1234YF are higher than pure R717 by 18.9% and 12.23% with mass fraction ratios of 0.21/0.79 and 0.41/0.59, respectively. In addition, R717/R32 and R717/R1234YF blends with mass fraction ratios of 0.4/0.6 and 0.62/0.38 possess higher optimum economic performance than pure R717 by 3.45% and 2.1%, respectively. Furthermore, the optimum mass fraction ratios for economics are both higher than those for thermodynamics as R717/R32 and R717/R1234YF used in OTEC.

Two-stage stochastic programming of a hybrid SOFC-renewable integrated energy system considering time sequence correlation

ABSTRACT In the face of the ever-increasing pressure on climate change, recent decades witnessed booming interests in the integrated energy systems (IES) consisting of intermittent renewable energy and dispatchable power sources, such as reformed gas-fed solid oxide fuel cells (SOFC). However, optimization of system design and operation is challenging due to the system complexity, inevitable couplings, and various constraints. To this end, this paper proposes a comprehensive model to describe integrated energy systems with combined cooling, heating, and power (CCHP). Optimal economic performance is formulated as the objective function. Constraints are derived based on the safety and operation requirements. The problem is solved by developing a two-stage stochastic programming framework to achieve the optimized results in terms of both design and operation. The second stage concerns the operation scheduling given the operation plan and stochastic characteristics, based on which the first stage concerns the design planning to realize the prescribed CCHP capacity. Considering the computation complexity of the second stage, the stochastic characteristics are represented by selected scenarios. And to present the mutual influence of energy demands and climate conditions, the time sequence correlation among energy demands and renewable energy availability is considered in the clustering-based scenario selection technique. To solve the proposed two-stage framework, the real-coded genetic algorithm and mixed integer linear programming method are applied in the first and second stages, respectively. A case study in San Francisco is carried out to verify the effectiveness of the proposed method, providing some intuitive guidance for future IES operation and system planning.

Energy Efficient Thermal Comfort Control for Residential Building Based on Nonlinear EMPC

For purpose of achieving the desired thermal comfort level and reducing the economic cost of maintaining the thermal comfort of green residential building, an energy efficient thermal comfort control strategy based on economic model predictive control (EMPC) for green residential buildings which adopts household heat metering is presented. Firstly, the nonlinear thermal comfort model of heating room is analyzed and obtained. A practical nonlinear thermal comfort prediction model is obtained by using an approximation method. Then, the economic cost function and optimization problem of energy-saving under the necessary thermal comfort requirements are constructed to realize the optimal economic performance of the dynamic process. The energy efficient thermal comfort MPC (EETCMPC) is designed. Finally, the comparison and analysis between EETCMPC and Double-layer Model Predictive Control (DMPC) is simulated. The simulation results reveal that when the clothing insulation is typical, the energy efficiency of EETCMPC is 8.9% and 11.6%, respectively, in the two simulation scenarios. When the clothing insulation varies with temperature, the energy efficiency of EETCMPC is 7.29% and 9.15%, respectively, and the total energy consumption is reduced by about 1.65% and 14.6%, respectively, compared with the typical clothing insulation. The economic performance is improved in the thermal comfort dynamic process of heating room.

Fast Stochastic Dual Dynamic Programming for Economic Dispatch in Distribution Systems

The multistage economic dispatch solution is of paramount importance for achieving the optimal unit commitment and the optimal decentralized decision-making in smart grid operations. Through the approximations of the optimal expected cost-to-go functions, the stochastic dual dynamic programming (SDDP) has been shown effective to obtain the optimum for the multistage stochastic programming (SP) problem, while without finite termination guarantee. Thus, we propose a fast stochastic dual dynamic programming (FSDDP) method to accelerate the convergence rate of the SDDP, including updating the candidate points based on the case with the maximum difference between the upper and lower bounds of the optimal value functions, adding a backward-forward-backward inner scheme in the backward pass, and initializing the bounds with finite constant values. We can verify that the FSDDP method enjoys a nice property with a finite convergence guarantee for the multistage SP problems. Numerical tests on 4-, 33-, 34-, 69-, 118- and 123-bus distribution systems have demonstrated that FSDDP can approach the optimal economic performance at significantly improved computational efficiency.

Формування системи маркетингового менеджменту підприємства

The purpose of the article is to study the essence of the marketing management of the enterprise and the formation of its management system in order to ensure the sustainable functioning of the enterprise in the market. It is noted that the successful functioning of the enterprise in the modern market in the conditions of growing competition, the development of technologies depends on the use of marketing tools in activities that will contribute to the development and adaptation of the enterprise to volatile market conditions. Marketing management is considered as an innovative approach to enterprise management, allowing to achieve optimal economic performance and positive social effect at the same time, coordinating the different interests of owners, managers, employees, partners, consumers, and society. The application of an integrated approach to marketing management is substantiated, namely: the need to form a marketing management system in an enterprise with a significant number of interrelated structural components that differ in their goals, act autonomously, while integrating management functions and aiming at achieving a single goal – ensuring the stability of all areas of the enterprise in modern market conditions and transforming consumer needs into enterprise revenues. It is proposed, taking into account the provisions of the general theory of systems and management theory, to consider the marketing management system as a cybernetic system capable of transforming information. It is further noted that the marketing management system of an enterprise is an open system that is subject to the influence of the marketing environment, where the components are macro- and microenvironment. It is proved that the factors of the external (macro-) environment form the impact on marketing programs and on the marketing activities of enterprise, and the factors of the internal (micro) environment determine the marketing activity of the enterprise. Objective tendencies in the development of the marketing environment are defined. The model of the marketing management system as a logical-structural scheme is proposed, on the basis of which the algorithm for optimization and management of marketing activities is provided, where the interrelations and relationships of elements (in accordance with the functions of marketing management) are presented.

Establishing Surrogate Model to Predict the Optimal Thermodynamic and Economic Performance of a Packed Bed Humidifier via Multi-Objective Optimization

In this paper, to optimize the thermodynamic and economic performance of a packed bed humidifier, a multi-objective optimization combined response surface method with a genetic algorithm is employed. The critical parameters, including geometric and thermodynamic parameters, are designated as the impact factors, and the objective functions contain unit humidification capacity of volume and unit humidification capacity of cost in a Box–Behnken design. The results of the analysis of variance demonstrated that the quadratic regression models of objectives are reliable and robust. It is found that the liquid–gas ratio, the interaction of the liquid–gas ratio, and inlet water temperature are simultaneously the strongest influence factors for the thermodynamic and economic indicators among the independent and interactive parameters. In addition, the optimal parameter group is found out through a genetic algorithm, and the actual optimal results are obtained as 0.11 kgs−1m−3 for thermodynamic performance and 15.86 kg$−1 for economic performance. Furthermore, it is shown that the thermodynamic performance improves by 56% and the economic performance increases by 6.55%, compared with optimum experimental design points. During the optimization design process, the computational time to find the optimal values reduces from 69,000 s with previous mathematical models to 10 s with established regression models. Additionally, a series of Pareto-optimal points for possible best thermodynamic and economic performance give the reference for the designers of packed bed humidifiers.

Sustainable supply chain design considering indicators of value creation

The growing concern about environmental and social impacts resulting from industrial activities has rethought the problem of supply chain design, in which the environmental and social pillars must be considered in the design process. Although the optimization of economic performance has been the main objective on the design of supply chains, the integration of financial indicators into design models has not been widely developed. This article proposes a mathematical programming model for the design of a sustainable supply chain. The objective function of the proposed model is the maximization of the market value added as a measure of the accumulated economic performance. The formulation includes the application of weighted raw material, transportation, and production costs to correctly calculate the cost of goods sold, a feature widely ignored in the literature. Regarding the social dimension, the installation of plants and distribution centers in regions with low human development index is promoted, and in the environmental dimension, the equivalent tons of carbon dioxide emitted by the land transportation of goods are restricted. An optimization-based primal heuristic is used as a solution strategy for the resulting mixed integer non-linear programming model. Finally, the proposed model is applied to a case study, which demonstrates the importance of considering sustainability for supply chain configuration.

Analyzing the mediating effect of economic performance on the relationship between green construction practices and health and safety performance in Nigeria.

The adoption of green construction practices (GCP) has been on the increase in recent years as a means of reducing the negative effects of construction on the natural environment. However, GCP have been discovered to expose the construction workers to numerous health and safety (HS) risks, resulting from a decline in safety investment due to the economic burden associated with its adoption. This study explores the means through which GCP influence the HS performance of construction projects through economic performance. To obtain the views of contractors, a survey questionnaire was developed, and data was collected from project managers and site managers of "class A" contractors, with a response rate of 81.55%. The partial least squares structural equation modeling (PLS-SEM) technique was adopted to analyze the data. The results show that the effect of GCP on HS performance is fully mediated by economic performance. The study concludes that for projects that adopt GCP to have high levels of HS performance, they are required to have an optimal economic performance. Efforts should be intensified by the government in providing subsidies, tax waivers, and other incentives for adopters of GCP to ensure the economic performance of their projects since it guarantees high HS performance.

Insights from Circular Economy Literature: A Review of Extant Definitions and Unravelling Paths to Future Research

The circular economy (CE) has become one of the prominent topics in both natural science and management literature over the last few decades. CE is a dual-loop regenerative system that focuses on the effective and efficient utilization of resources in the ecosystem, which is beneficial to environmental and economic performance optimization. Dual CE initiatives allow firms to increased resource eco-efficiency, as well as resource effectiveness. CE has profound consequences for economic and operational advantage. This reinforces the need for reflection on the definition that may provide guidelines to assess and advance the depth and diversity of the field. We aim to provide a definitional analysis of the CE and suggest future research streams to advance the existing literature. For this purpose, we employed a systematic literature review to collect related publications in the CE. As a result of this, a total of 91 papers were selected, studied, and analyzed. We proposed a sound definition of a circular economy that includes the main identified elements, organizational planning processes, customers and society, utilization of the ecosystem, and economic resource flows. Moreover, future direction agenda, in CE research, is suggested considering three research streams: (1) circular design as value creation and capture, (2) antecedents of key activities, and (3) consequences of key processes. There is limited empirical research conducted on CE, and much of the existing research focuses on theoretical, conceptual, and normative. A few empirical research studies are mainly cross-sectional in their focus and are confined to developing and emerging economies. We hope this study’s findings will extend the field of CE, in which some of the most influential information regarding CE literature is provided. This study suggests that the development of CE initiatives plays an important role in the growing digital transformation in the value chain. There have been limited research studies in the interface of circular economy and Industry 4.0. Future research studies may investigate the extent to which digital transformation can increase the implementation of CE, and their influence on digital performance management.

ПЛАНУВАННЯ ЛОГІСТИЧНИХ ПРОЦЕСІВ У ПОВСЯКДЕННІЙ ДІЯЛЬНОСТІ ВІЙСЬКОВИХ ПІДРОЗДІЛІВ НАЦІОНАЛЬНОЇ ГВАРДІЇ УКРАЇНИ

This article presents an analysis of the planning of logistics processes in the daily activities of military units of the National Guard of Ukraine. The article systematizes the specific features of logistics functions in contrast to similar functions of the traditional approach to resource management. Particular attention is paid to the fact that the distinctive features of the system of logistics functions are the deep systemic relationship of logistics functions with each other, as well as the focus on the management of material and related flows. In this article, the methodological basis of the logistical approach to resource management is to ensure the relationship between all types of resources, as well as structural units of the stakeholder organization in making strategic and operational decisions and ensuring their focus on achieving optimal economic performance of military units. The paper proposes a scheme of operational and functional nature of planning the logistics activities of military units of the National Guard of Ukraine. The article develops a system of requirements for planning logistics processes in the daily activities of military units. The scheme of the logistics system of military units as a part of managing and managed subsystems is offered. The article considers the subject of management of the logistics system of military units, which is the organizational structure of resource management, its structural components and specialists with the necessary knowledge, skills to manage the movement of all types of flows. The role and functions of each type of logistics in the daily activities of military units of the National Guard of Ukraine are separated. The article proposes the main directions of planning the logistics approach, which should be implemented for the military units of the National Guard of Ukraine in the process of solving everyday tasks. The article emphasizes that as a result of effective planning of logistics processes of the army should ensure the acceleration of the physical distribution and minimization of the total cost of supply of products and achieve the required quality of products or services. The practical result of the scientific research of the article is the system of recommendations of military units of the National Guard of Ukraine regarding the planning of logistics processes.

Application of machine learning methods for optimizing the technical and economic performance of generating systems

The paper is on the technical and economic performance optimization technique for thermal and power generating system using machine learning methods. The possibility of using regression analysis for parameter influence evaluation when calculating technical and economic performance in order to reach better generating unit efficiency is described. The approach to evaluate the parameter influence of a large distributed control system is presented.

Synthesis of wastewater treatment plant based on minimal waste generation cost: A material flow cost accounting (MFCA) approach

Wastewater treatment (WWT) is a mandatory process to ensure wastewater quality meets legislation requirements and to reduce environmental impacts. Many established WWT technologies are available in the market and the selection of such technologies is usually based on heuristics. However, technologies selected using heuristics may not be able to guarantee optimal economic performance. In this respect, it is important for manufacturing companies to synthesise a WWT process with minimum investment cost while meeting legislation requirements. Most manufacturing companies face issues to achieve this goal. Among these issues, is the fact that part of the investment invested into a WWT process will be lost to waste (sludge cake) generation. The generated waste (sludge cake) will require additional high waste disposal costs. Therefore, to reduce the loss of investment in a WWT process, the waste generation cost and waste disposal cost must be minimised. This can be addressed via Material Flow Cost Accounting (MFCA), a management tool that quantifies material flows across physical and monetary values in a production process. Previous works had adapted the concept of MFCA for prioritisation of waste streams for waste recovery and minimisation of investment cost in processes with revenue streams. Thus, the objective of this paper is to extend the use of MFCA as a preliminary decision-making tool in the selection of WWT technologies with minimum waste generation cost. To illustrate the developed approach, a case study on sago-based WWT process is solved in this work. Based on the results, the synthesised WWT process from the developed model is capable of recovering as much as 93.3 % of the total operating cost back into the manufacturing process while minimising the waste generation cost to 6.7 % of the operating investment cost.

Reaction-Separation Process Integration and Working Fluid Optimization for Organic Rankine Cycles Recovering Waste Heat in Cumene Synthesis

Reaction and distillation separation processes are two significantly energy-intensive unit operations in the chemical industry. Due to the high-temperature reaction and separation conditions, a large amount of waste heat with multiple grades is produced, which should be effectively utilized. In the article, the organic Rankine cycle (ORC) system is adopted to recover the waste heat in the reaction-separation process of cumene synthesis to generate electricity. The design parameters of the ORC system with eight working fluids including R113, R601, R123, R601a, R245ca, R245fa, R600 and R600a are optimized, aiming to maximize annual net economic revenues (NER) through the sequential quadratic programming (SQP). Simultaneously, the thermal efficiency (?ORC) of ORC system with optimal economic performance is calculated for eight working fluids. The results illustrate that R113 performs better than other working fluids in terms of NER and ?ORC. The corresponding annual net electricity generation (NEG), annual NER of ORC system (NERORC) and overall process (NERoverall) and ?ORC can reach 620.83 kW, 0.75 × 105 $/y, 2.11 × 105 $/y and 21.79 %.

Economic Performance Optimization by Set Point and Weighting Parameter Tuning based on LQG Controller Design

Several researches have formulated economic performance optimization problems taking account of a trade-off relation between process input and output variance. The present work introduces theoretical formulations that relate the weighting parameter with each input and output variance on the condition that the Linear Quadratic Gaussian (LQG) controllers are implemented as lower layer controllers. The proposed approach is applied to a two-input, two-output separation process model, and solves optimal weighting parameter based on LQG control. The numerical example also shows that the obtained optimal weighting parameter is effective for a MPC based learning algorithm.

A knowledge-based method for eco-efficiency upgrading of remanufacturing process planning

Eco-efficiency has been proved as one of the powerful indicators in link with environment management and economic output. As a core procedure of remanufacturing activities, upgrading the eco-efficiency of remanufacturing process planning is of great significance for maximizing the circular economic advantages of remanufacturing. With the increasing of individual differences in used parts, the remanufacturing process planning is becoming more complicated. In this paper, a knowledge-based method for remanufacturing process planning is proposed as part of the efforts in upgrading eco-efficiency which also aims to improve the efficiency of process planning and realize the inheritance and evolvability of the process planning knowledge. Based on the identification of basic attribute characteristics and damage characteristics of used parts, a similarity calculation method is presented to match the most relevant historical remanufacturing process planning knowledge from the existing knowledge base, so as to design the feasible initial process plan set. For eco-efficiency upgrading, a remanufacturing process planning model is proposed to obtain the process plan with the optimal economic and environmental performance, and then the knowledge base can be updated and expanded. Finally, a case study of remanufacturing a used worm gear is demonstrated to validate the proposed method.

Production of ethanol fuel via syngas fermentation: Optimization of economic performance and energy efficiency

In this work, a model was developed to predict the performance of a bubble column reactor for syngas fermentation and the subsequent recovery of anhydrous ethanol. The model was embedded in an optimization framework which employs surrogate models (artificial neural networks) and multi-objective genetic algorithm to optimize different process conditions and design variables with objectives related to investment, minimum selling price, energy efficiency and bioreactor productivity. The results indicate the optimal trade-offs between these objectives while providing a range of solutions such that, if desired, a single solution can be picked, depending on the priority conferred to different process targets. The Pareto-optimal values of the decision variables were discussed for different case studies with and without the recovery unit. It was shown that enhancing the gas-liquid mass transfer coefficient is a key strategy toward sustainability improvement.