Multiobjective economic model predictive control using utopia-tracking for the wet flue gas desulphurization system

Efficient control of the desulphurization system is challenging in maximizing the economic objective while reducing the SO_(2) emission concentration. The conventional optimization method is generally based on a hierarchical structure in which the upper optimization layer calculates the steady-state results and the lower control layer is responsible to drive the process to the target point. However, the conventional hierarchical structure does not take the economic performance of the dynamic tracking process into account. To this end, multi-objective economic model predictive control(MOEMPC) is introduced in this paper, which unifies the optimization and control layers in a single stage. The objective functions are formulated in terms of a dynamic horizon and to balance the stability and economic performance. In the MOEMPC scheme, economic performance and SO_(2) emission performance are guaranteed by tracking a set of utopia points during dynamic transitions. The terminal penalty function and stabilizing constraint conditions are designed to ensure the stability of the system. Finally, an optimized control method for the stable operation of the complex desulfurization system has been established. Simulation results demonstrate that MOEMPC is superior over another control strategy in terms of economic performance and emission reduction, especially when the desulphurization system suffers from frequent flue gas disturbances.

Fractional Order Environmental and Economic Model Investigations Using Artificial Neural Network

The motive of these investigations is to provide the importance and significance of the fractional order(FO)derivatives in the nonlinear environmental and economic(NEE)model,i.e.,FO-NEE model.The dynamics of the NEE model achieves more precise by using the form of the FO derivative.The investigations through the non-integer and nonlinear mathematical form to define the FO-NEE model are also provided in this study.The composition of the FO-NEEmodel is classified into three classes,execution cost of control,system competence of industrial elements and a new diagnostics technical exclusion cost.The mathematical FO-NEE system is numerically studied by using the artificial neural networks(ANNs)along with the Levenberg-Marquardt backpropagation method(ANNs-LMBM).Three different cases using the FO derivative have been examined to present the numerical performances of the FO-NEE model.The data is selected to solve the mathematical FO-NEE system is executed as 70%for training and 15%for both testing and certification.The exactness of the proposed ANNs-LMBM is observed through the comparison of the obtained and the Adams-Bashforth-Moulton database results.To ratify the aptitude,validity,constancy,exactness,and competence of the ANNs-LMBM,the numerical replications using the state transitions,regression,correlation,error histograms and mean square error are also described.

Finite-time economic model predictive control for optimal load dispatch and frequency regulation in interconnected power systems

This paper presents a finite-time economic model predictive control(MPC)algorithm that can be used for frequency regulation and optimal load dispatch in multi-area power systems.Economic MPC can be used in a power system to ensure frequency stability,real-time economic optimization,control of the system and optimal load dispatch from it.A generalized terminal penalty term was used,and the finite-time convergence of the system was guaranteed.The effectiveness of the proposed model predictive control algorithm was verified by simulating a power system,which had two areas connected by an AC tie line.The simulation results demonstrated the effectiveness of the algorithm.

Optimal dispatching method for integrated energy system based on robust economic model predictive control considering source-load power interval prediction

Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.

The Global Value Chains and the Evolution of Chinese Economic Model

According to the Word Bank,in the first 38 years of China,economic reform took 700 million people out poverty line in China at the same time benefiting the Global South economy due to the integration of the transnational enterprises global value chains with China.Chinese government understood the economic rational of global value chains,Flying Geese Model,and foreign direct investment theories and introduced policies to attract foreign capital,technology,production,and foreign buyers,placing China as the final stage of the production networks in Asia and also transforming China in the biggest buying market of many resources and energy suppliers from less developed countries in Asia,Africa,and South America.But a new model of Chinese economic development even more interconnected and interdependent with the world is now on move.Even quite before the world acknowledge the protectionist mindset of the US in Trump era,Chinese President Xi Jinping launched in 2013 a very ambitious initiative under the name of“One Road,One Belt,the 21st-Century Maritime Silk Road”to enhance a new stage of world globalization,which together with two complimentary initiatives:the“International Production Cooperation”and“Third-Country Market Cooperation”,and in complementarity with the“Made in China 2025”and“Internet Plus”plans will lead China to develop global value chains leaded by Chinese companies and integrating countries of Europe,Africa,Asia,and South America.

AN ECONOMIC MODEL-BASED MATCHING APPROACH BETWEEN BUYERS AND SELLERS THROUGH A BROKER IN AN OPEN E- MARKETPLACE

A broker in an open e-marketplace enables buyers and sellers to do business with each other. Although a broker plays an important role in e-marketplaces, theory and guidelines for matching between buyers and sellers in multi-attribute exchanges are limited. Therefore, a challenge for a broker＇s responsibility is how to maximize a buyer＇s total satisfaction degree as its goals under the consideration of trade-off between a buyer＇s buying quantity and price paid to a seller, and other attributes. To solve this challenge, this paper proposes an economic model-based matching approach between a buyer＇s requirements and a seller＇s offers. The major contributions of this paper are that （i） a broker can model a seller＇s price policy as per a buyer＇s buying quantity through communication between a broker and a seller; （ii） due to each buyer＇s different quantity demand, a broker models a buyer＇s satisfaction degree as per a buyer＇s buying quantity based on communication between a broker and a buyer; and （iii） to carry out a broker＇s matching processes, an objective function and a set of constraints are generated to help a broker to maximize a buyer＇s total satisfaction degree. Experimental results demonstrate the good performance of the proposed approach.

Economic modeling of mechanized and semi-mechanized rainfed wheat production systems using multiple linear regression model

Mathematical modeling of economic indices is a challenging topic in crop production systems.The present study aimed to model the economic indices of mechanized and semimechanized rainfed wheat production systems using various multiple linear regression models.The study area was Behshahr County located in the east of Mazandaran Province,Northern Iran.The statistical population included all wheat producers in Behshahr County in 2016/17 crop year.Five input variables were human labor,machinery,diesel fuel,chemical(chemical fertilizers and chemical pesticides)costs,and the income was considered to be the output.The results showed that the cost of wheat production in the semimechanized system was higher than that of the mechanized system.In both systems,the highest cost was related to agricultural machinery input.Moreover,seed cost was lower in the mechanized system than that of the semi-mechanized system.The net return indicator was 993.68$ha1 and 626.71$ha1 for the mechanized and semi-mechanized systems,respectively.The average benefit to cost ratio was 3.46 and 2.40 for the mechanized and semi-mechanized systems,respectively,demonstrating the greater profitability of the mechanized system.The results of the evaluation of five types of regression models including the Cobb-Douglas,linear,2FI,quadratic and pure-quadratic for the mechanized and semi-mechanized production systems indicated that in the developed Cobb-Douglas model,the R2-value was higher than that of the quadratic model while RMSE and MAPE of the quadratic model were determined to be smaller than that of the Cobb-Douglas model.Therefore,the best model to investigate the relationship between input costs and the income of wheat production in both mechanized and semi-mechanized systems was the quadratic model.

A Two-Sector Economic Growth Model with Labor Force

In this paper, a two\|sector growth model is given. The labor force transfer process from agricultural sector to industrial sector is exogenous determined. By introducing the labor force transferring function, a two\|dimension nonautonomous differential equation is obtained. The results of the model manifest that the labor force transfer delays industrial sector growth and accelerates the agricultural sector growth. It is proved that the solution of the model is asymptotic stable. By the numerical analysis, the economic growth and labor force transfer is presented under the specific parameters.

Construction of Regional Economic Vitality Model

Regional economic vitality reflects the scale and development potential of a region’s economy.It largely determines the development of the city,and is also affected by many factors such as population competitiveness,corporate competitiveness,market vitality,innovation vitality,and environmental vitality.A pilot model was constructed with Hebei Province as the inspection area.Quantitative measurement of regional economic vitality was made by finding 21 indicators that indirectly or indirectly affect the economic vitality of Hebei Province.By analyzing the data of 21 indicators for nearly 10 years,the time series clustering is used to achieve the dimensionality reduction of the indicators.After the dimension reduction,it is divided into four categories:overall scale,development potential,market vitality,and innovation vitality.Construct the economic vitality structure model of Hebei Province,and determine the four types of contribution to economic vitality and compare them.On this basis,more accurately grasp the indicators that affect economic vitality and work out reasonable and effective action plans.From the perspective of human resources and corporate vitality,analyze how the action plan accurately affects the economic vitality of Hebei Province[1].The 11 cities in Hebei Province are the target of regional economic vitality.The economic vitality structure model constructed uses the required contribution value to select priority indicators.Finally,the six indicators of GPD,GPD growth rate,fiscal revenue,fiscal revenue growth rate,number of industrial enterprises above designated size,and total profit of industrial enterprises above designated size were established for eleven cities in Hebei Province to construct a TOPSIS scoring model,and calculation rankings were conducted through MATLAB.Results The top three cities were Shijiazhuang,Tangshan and Cangzhou.

What Competition Model for Economic Development Should China Adopt at the Present Stage?

As a major developing country,China has attracted significant attention as to whichpathitshouldfol owfortechnologicalprogress.Accordingtotheauthorofthispaper,Chinashouldcontinueto pursue the international division of labor and competition strategy based on comparative advantages.Meanwhile,China should,through reform and adjustment,build a national innovation system capable ofplaying an e ective role in the future.However,laying too much emphasis on proprietary innovation atthe present stage wil bring about undesirable consequences.The timing for China to embark on a path oftechnologicaldevelopmentthroughproprietaryinnovationissubjecttothechangesbothintradeconditionsandin income distribution e ects arising from proprietary innovation.

Information Models for Forecasting Nonlinear Economic Dynamics in the Digital Era

The aim of this study was to develop an adequate mathematical model for long-term forecasting of technological progress and economic growth in the digital age (2020-2050). In addition, the task was to develop a model for forecast calculations of labor productivity in the symbiosis of “man + intelligent machine”, where an intelligent machine (IM) is understood as a computer or robot equipped with elements of artificial intelligence (AI), as well as in the digital economy as a whole. In the course of the study, it was shown that in order to implement its goals the Schumpeter-Kondratiev innovation and cycle theory on forming long waves (LW) of economic development influenced by a powerful cluster of economic technologies engendered by industrial revolutions is most appropriate for a long-term forecasting of technological progress and economic growth. The Solow neoclassical model of economic growth, synchronized with LW, gives the opportunity to forecast economic dynamics of technologically advanced countries with a greater precision up to 30 years, the time which correlates with the continuation of LW. In the information and digital age, the key role among the main factors of growth (capital, labour and technological progress) is played by the latter. The authors have developed an information model which allows for forecasting technological progress basing on growth rates of endogenous technological information in economics. The main regimes of producing technological information, corresponding to the eras of information and digital economies, are given in the article, as well as the Lagrangians that engender them. The model is verified on the example of the 5th information LW for the US economy (1982-2018) and it has had highly accurate approximation for both technological progress and economic growth. A number of new results were obtained using the developed information models for forecasting technological progress. The forecasting trajectory of economic growth of developed countries (on the example of the USA) on the upward stage of the 6th LW (2018-2042), engendered by the digital technologies of the 4th Industrial Revolution is given. It is also demonstrated that the symbiosis of human and intelligent machine (IM) is the driving force in the digital economy, where man plays the leading role organizing effective and efficient mutual work. Authors suggest a mathematical model for calculating labour productivity in the digital economy, where the symbiosis of “human + IM” is widely used. The calculations carried out with the help of the model show: 1) the symbiosis of “human + IM” from the very beginning lets to realize the possibilities of increasing work performance in the economy with the help of digital technologies;2) the largest labour productivity is achieved in the symbiosis of “human + IM”, where man labour prevails, and the lowest labour productivity is seen where the largest part of the work is performed by IM;3) developed countries may achieve labour productivity of 3% per year by the mid-2020s, which has all the chances to stay up to the 2040s.

Resource Schedule in Grid Based on Market Models

A new modern resource management method based on economic model is proposed. Giving mathematic description about economic model; analysis different resource scheduling methods based on deadline and budget constrained which present by Buyya, point out shortcoming of Buyya's schedule method. Considerate integrate factor of time and budget, by import a weight coefficient named a , puts forward a new resource schedule method named STPP based on economic models of Buyya. Contrast to old schedule strategy of Buyya through analysis and experiments, STPP policy is more flexible, and is easy to import other new QoS parameters.

The Economic Profitability of Cereal Production Systems in the Context of Adaptation to Climate Change:the Case of Millet

This article studies the economic profitability of the millet production in a context of adaptation to climatic changes by considering the techniques of adaptation to soil protection,namely,low wall girdles tree and halfmoon in order to determine their impact on the economic profitability of the production of this cereal.

Memory-Type Control Charts Through the Lens of Cost Parameters

A memory-type control chart utilizes previous information for chart construction.An example of a memory-type chart is an exponentially-weighted moving average(EWMA)control chart.The EWMA control chart is well-known and widely employed by practitioners for monitoring small and moderate process mean shifts.Meanwhile,the EWMA median chart is robust against outliers.In light of this,the economic model of the EWMA and EWMA median control charts are commonly considered.This study aims to investigate the effect of cost parameters on the out-of-control average run lengthðARL_(1)Þin implementing EWMA and EWMA median control charts.The economic model was used to compute the ARL_(1) parameter.The 14 input parameters were identified and the analysis was carried out based on the one-parameter-at-a-time basis.When the input parameters change based on a predetermined percentage,the ARL_(1) is affected.According to the results of the EWMA chart,nine input parameters had an effect andfive input parameters had no effect on the ARL_(1) parameter.Further,only seven of the 14 input parameters had an effect on the ARL_(1) of the EWMA median chart.However,the effect of each input parameter on the ARL_(1) was different.Moreover,the ARL_(1) for the EWMA median chart was smaller than the EWMA chart.This analysis is crucial to observe and determine the input parameters that have a significant impact on the ARL_(1) of the EMWA and EWMA median control charts.Hence,practitioners can obtain an overview of the influence of the input parameters on the ARL_(1) when implementing the EWMA and EWMA median control charts.

Some Suggested Future Directions ofQuantitative Resource Assessments

Future quantitative assessments will be expected to estimate quantities, values, and locations of undiscovered mineral resources in a form that conveys both economic viability and uncertainty associated with the resources. Historically, declining metal prices point to the need for larger deposits over time. Sensitivity analysis demonstrates that the greatest opportunity for reducing uncertainty in assessments lies in lowering uncertainty associated with tonnage estimates. Of all errors possible in assessments, these affecting tonnage estimates are by far the most important. Selecting the correct deposit model is the most important way of controlling errors because of the dominance of tonnage-deposit models are the best known predictors of tonnage. Much of the surface is covered with apparently barren rocks and sediments in many large regions. Because many exposed mineral deposits are believed to have been found, a prime concern is the presence of possible mineralized rock under cover. Assessments of areas with resources under cover must rely on extrapolation from surrounding areas, new geologic maps of rocks under cover, or analogy with other well-explored areas that can be considered training tracts. Cover has a profound effect on uncertainty and on methods and procedures of assessments because geology is seldom known and geophysical methods typically have attenuated responses. Many earlier assessment methods were based on relationships of geochemical and geophysical variables to deposits learned from deposits exposed on the surface-these will need to be relearned based on covered deposits. Mineral-deposit models are important in quantitative resource assessments for two reasons: (1) grades and tonnages of most deposit types are significantly different, and (2) deposit types are present in different geologic settings that can be identified from geologic maps. Mineral-deposit models are the keystone in combining the diverse geoscience information on geology, mineral occurrences, geophysics, and geochemistry used in resource assessments and mineral exploration. Grade and tonnage models and development of quantitative descriptive, economic, and deposit density models will help reduce the uncertainty of these new assessments.

A Brief Introduction to BNU-HESM1.0 and Its Earth Surface Temperature Simulations

Integrated assessment models and coupled earth system models both have their limitations in understanding the interactions between human activity and the physical earth system. In this paper, a new human--earth system model, BNU- HESM1.0, constructed by combining the economic and climate damage components of the Dynamic Integrated Model of Climate Change and Economy to the BNU-ESM model, is introduced. The ability of BNU-HESM1.0 in simulating the global CO2 concentration and surface temperature is also evaluated. We find that, compared to observation, BNU-HESM1.0 underestimates the global CO2 concentration and its rising trend during 1965-2005, due to the uncertainty in the economic components. However, the surface temperature simulated by BNU-HESM1.0 is much closer to observation, resulting from the overestimates of surface temperature by the original BNU-ESM model. The uncertainty of BNU-ESM falls within the range of present earth system uncertainty, so it is the economic and climate damage component of BNU-HESM 1.0 that needs to be improved through further study. However, the main purpose of this paper is to introduce a new approach to investigate the complex relationship between human activity and the earth system. It is hoped that it will inspire further ideas that prove valuable in guiding human activities appropriate for a sustainable future climate.

Multiyear Discrete Stochastic Programming with a Fuzzy Semi-Markov Process

Drought conditions at a given location evolve randomly through time and are typically characterized by severity and duration. Researchers interested in modeling the economic effects of drought on agriculture or other water users often capture the stochastic nature of drought and its conditions via multiyear, stochastic economic models. Three major sources of uncertainty in application of a multiyear discrete stochastic model to evaluate user preparedness and response to drought are: (1) the assumption of independence of yearly weather conditions, (2) linguistic vagueness in the definition of drought itself, and (3) the duration of drought. One means of addressing these uncertainties is to re-cast drought as a stochastic, multiyear process using a “fuzzy” semi-Markov process. In this paper, we review “crisp” versus “fuzzy” representations of drought and show how fuzzy semi-Markov processes can aid researchers in developing more robust multiyear, discrete stochastic models.

A Research on Business Information System and Informatization

Based on the analysis of commercial economic informatization,this paper puts forward the abstract model of commercial information system,which comprises of the environmental system,business system,monitoring system,and emergency system.In addition,it also involves the strain cycle,monitoring cycle,and business cycle.In order to promote a better development in the business economic model under the background of informatization,commercial enterprises should improve their understanding,develop and continuously optimize business economic informatization,as well as create an efficient and safe network security environment for the future.

Economic Life Assessment of Power Transformers Using an Improved Model

The electric power enterprise devotes considerable attention to the reliability of power transformers particularly when it decides to either maintain these transformers or decommission them altogether from operation.Although this process has reduced the risk of transformer faults,the attendant dilemma is of excessive maintenance of transformers,or retiring them prematurely,leading to high economic waste.This paper is inspired by real-time engineering applications,and proposes an improved model to assess the economic life of power transformers.The new model offers a more efficient approach than previous methods of assessment,with a specific focus of using the annual net income as separate criteria for determining the economic indices of continuous operation,overhaul,and retirement strategies of transformers.The economic life of power transformers is divided into three sections according to different strategies to better resolve the quantification problem in this field.A case study is provided to prove the feasibility and validity of the proposed economic life model.The case study achieves the fine management goal when the electric power enterprise is required to make the maintenance and retirement strategy decision.

An Economic Optimization Method for Demand-side Energy-storage Accident Backup Assisted Deep Peaking of Thermal Power Units

With the large-scale penetration of new energy such as wind power,its anti-modulation peak characteristics have increased challenges in power systems.Therefore,an economic optimization method for depth peak regulation and the depth of the emergency of the Energy storage(ES)accident on the demand side is proposed.First,a quantitative model of unplanned disconnection risk caused by weather state,load level,and fault type is constructed to obtain the spare and available ES capacity.Therefore,a deep peak regulation(DPR)economic optimization model is established to minimize the fuel injection cost of thermal power units,including ES accident standby,unit damage,and fuel demand.The particle swarm optimization algorithm is used to simulate the modified IEEE 30-node system.Based on the results,the DPR of ES accident standby can reduce the wind abandonment rate by 1.1%and the total peak adjustment cost by 33.5%under class-A weather.In class-C weather,the wind abandonment ratio can be reduced by 4.19%,reducing the cost of the total adjustment peak by 31.4%.The multiple purposes of improving the power grid modulation,wind power,and the standby utilization of ES accidents can be achieved.