Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation indust...Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.展开更多
Micro-energy systems contribute significantly to environmental improvement by reducing dependence on power grids through the utilization of multiple renewable energy sources.This study quantified the environmental imp...Micro-energy systems contribute significantly to environmental improvement by reducing dependence on power grids through the utilization of multiple renewable energy sources.This study quantified the environmental impact of a micro-energy network system in an industrial park through a life cycle assessment using the operation of the micro-energy network over a year as the functional unit and“cradle-to-gate”as the system boundary.Based on the baseline scenario,a natural gas generator set was added to replace central heating,and the light pipes were expanded to constitute the optimized scenario.The results showed that the key impact categories for both scenarios were global warming,fine particulate matter formation,human carcinogenic toxicity,and human non-carcinogenic toxicity.The overall environmental impact of the optimized scenario was reduced by 68%compared to the baseline scenario.A sensitivity analysis of the key factors showed that electricity from the power grid was the key impact factor in both scenarios,followed by central heating and natural gas.Therefore,to reduce the environmental impact of network systems,it is necessary to further optimize the grid power structure.The research approach can be used to optimize micro-energy networks and evaluate the environmental impact of different energy systems.展开更多
Objective: This paper aims to explore the impact of optimizing details in the operating room on the level of knowledge, attitude, and practice of hospital infection prevention and control by surgeons, as well as the e...Objective: This paper aims to explore the impact of optimizing details in the operating room on the level of knowledge, attitude, and practice of hospital infection prevention and control by surgeons, as well as the effectiveness of infection control. Methods: From January 2022 to June 2023, a total of 120 patients were screened and randomly divided into a control group (routine care and hospital infection management) and a study group (optimizing details in the operating room). Results: Significant differences were found between the two groups in the data of surgeons’ level of knowledge, attitude, and practice in hospital infection prevention and control, infection rates, and nursing satisfaction, with the study group showing better results (P Conclusion: The use of optimizing details in the operating room among surgeons can effectively improve surgeons’ level of knowledge, attitude, and practice in hospital infection prevention and control, reduce infection occurrence, and is worth promoting.展开更多
An algorithm named InterOpt for optimizing operational parameters is proposed based on interpretable machine learning,and is demonstrated via optimization of shale gas development.InterOpt consists of three parts:a ne...An algorithm named InterOpt for optimizing operational parameters is proposed based on interpretable machine learning,and is demonstrated via optimization of shale gas development.InterOpt consists of three parts:a neural network is used to construct an emulator of the actual drilling and hydraulic fracturing process in the vector space(i.e.,virtual environment);:the Sharpley value method in inter-pretable machine learning is applied to analyzing the impact of geological and operational parameters in each well(i.e.,single well feature impact analysis):and ensemble randomized maximum likelihood(EnRML)is conducted to optimize the operational parameters to comprehensively improve the efficiency of shale gas development and reduce the average cost.In the experiment,InterOpt provides different drilling and fracturing plans for each well according to its specific geological conditions,and finally achieves an average cost reduction of 9.7%for a case study with 104 wells.展开更多
Building structures themselves are one of the key areas of urban energy consumption,therefore,are a major source of greenhouse gas emissions.With this understood,the carbon trading market is gradually expanding to the...Building structures themselves are one of the key areas of urban energy consumption,therefore,are a major source of greenhouse gas emissions.With this understood,the carbon trading market is gradually expanding to the building sector to control greenhouse gas emissions.Hence,to balance the interests of the environment and the building users,this paper proposes an optimal operation scheme for the photovoltaic,energy storage system,and flexible building power system(PEFB),considering the combined benefit of building.Based on the model of conventional photovoltaic(PV)and energy storage system(ESS),the mathematical optimization model of the system is proposed by taking the combined benefit of the building to the economy,society,and environment as the optimization objective,taking the near-zero energy consumption and carbon emission limitation of the building as the main constraints.The optimized operation strategy in this paper can give optimal results by making a trade-off between the users’costs and the combined benefits of the building.The efficiency and effectiveness of the proposed methods are verified by simulated experiments.展开更多
With the expansion and implementation of rural revitalization strategies,there is a constant need for new energy sources for the construction of new townships.Consequently,integrated energy systems with the interconne...With the expansion and implementation of rural revitalization strategies,there is a constant need for new energy sources for the construction of new townships.Consequently,integrated energy systems with the interconnection and interaction of multiple energy sources are developing rapidly.Biomass energy,a renewable green energy source with low pollution and wide distribution,has significant application potential in integrated energy systems.Considering the application of biomass energy in townships,this study established an integrated biomass energy system and proposed a model to optimize its operation.Lowest economic cost and highest clean energy utilization rate were considered as the objective functions.In addition,a plan was suggested to adjust the heat-electricity ratio based on the characteristics of the combined heat and power of the biomass.Finally,a simulation analysis conducted for a town in China was discussed,demonstrating that the construction of a township integrated-energy system and the use of biomass can significantly reduce operating costs and improve the energy utilization rate.Moreover,by adjusting the heat-electricity ratio,the economic cost was further reduced by 6.70%,whereas the clean energy utilization rate was increased by 5.14%.展开更多
Against the realistic background of excess production capacity, product structure imbalance, and high material and energy consumption in steel enterprises, the implementation of operation optimization for the steel ma...Against the realistic background of excess production capacity, product structure imbalance, and high material and energy consumption in steel enterprises, the implementation of operation optimization for the steel manufacturing process is essential to reduce the production cost, increase the production or energy efficiency, and improve production management. In this study, the operation optimization problem of the steel manufacturing process, which needed to go through a complex production organization from customers' orders to workshop production, was analyzed. The existing research on the operation optimization techniques, including process simulation, production planning, production scheduling, interface scheduling, and scheduling of auxiliary equipment, was reviewed. The literature review reveals that, although considerable research has been conducted to optimize the operation of steel production, these techniques are usually independent and unsystematic.Therefore, the future work related to operation optimization of the steel manufacturing process based on the integration of multi technologies and the intersection of multi disciplines were summarized.展开更多
The rotary water jetting is one of the most important techniques for horizontal well cleanup.The jet flow is used to remove plugging particles from sand control screens to recover their permeability.Currently,the oper...The rotary water jetting is one of the most important techniques for horizontal well cleanup.The jet flow is used to remove plugging particles from sand control screens to recover their permeability.Currently,the operation optimization of this technique depends mainly on experience due to absence of applicable evaluation and design models for removing plugging materials.This paper presents an experimental setup to simulate the cleanup process of plugged screens by rotary water jetting on the surface and to evaluate the performance of a jetting tool.Using real plugged screens pulled from damaged wells,a series of tests were performed,and the qualitative relationships between the cleanup efficiency and various operational parameters,such as the type of fluids used,flow rate,mode of tool movement,etc.,were obtained.The test results indicated that the cleanup performance was much better when the rotary jetting tool moved and stopped periodically for a certain time than that when it reciprocated at a constant speed.To be exact,it was desirable for the rotary jetting tool to move for 1.5-2 m and stop for 2-4 min,which was called the "move-stop-move" mode.Good cleanup performance could be obtained at high flow rates,and the flow rate was recommended to be no lower than 550-600 L/min.The test results also indicated that complex mud acid was better than clean water in terms of cleanup performance.Good cleanup efficiency and high screen permeability recovery could be achieved for severely plugged screens.Rotary jetting is preferred for the cleanup of horizontal wells with severely plugged screens,and the screen permeability recovery ratio may reach 20% if optimized operation parameters were used.展开更多
The renewable portfolio standard has been promoted in parallel with the reform of the electricity market,and the flexibility requirement of the power system has rapidly increased.To promote renewable energy consumptio...The renewable portfolio standard has been promoted in parallel with the reform of the electricity market,and the flexibility requirement of the power system has rapidly increased.To promote renewable energy consumption and improve power system flexibility,a bi-level optimal operation model of the electricity market is proposed.A probabilistic model of the flexibility requirement is established,considering the correlation between wind power,photovoltaic power,and load.A bi-level optimization model is established for the multi-markets;the upper and lower models represent the intra-provincial market and inter-provincial market models,respectively.To efficiently solve the model,it is transformed into a mixed-integer linear programming model using the Karush–Kuhn–Tucker condition and Lagrangian duality theory.The economy and flexibility of the model are verified using a provincial power grid as an example.展开更多
Setting up a knowledge base is a helpful way to optimize the operation of the polyethylene process by improving the performance and the ef ciency of reuse of information and knowledge two critical ele- ments in polyet...Setting up a knowledge base is a helpful way to optimize the operation of the polyethylene process by improving the performance and the ef ciency of reuse of information and knowledge two critical ele- ments in polyethylene smart manufacturing. In this paper, we propose an overall structure for a knowl- edge base based on practical customer demand and the mechanism of the polyethylene process. First, an ontology of the polyethylene process constructed using the seven-step method is introduced as a carrier for knowledge representation and sharing. Next, a prediction method is presented for the molecular weight distribution (MWD) based on a back propagation (BP) neural network model, by analyzing the relationships between the operating conditions and the parameters of the MWD. Based on this network, a differential evolution algorithm is introduced to optimize the operating conditions by tuning the MWD. Finally, utilizing a MySQL database and the Java programming language, a knowledge base system for the operation optimization of the polyethylene process based on a browser/server framework is realized.展开更多
For oil company decision-makers,the principal concern is how to allocate their limited resources into the most valuable opportunities.Recently a new management philosophy,"Beyond NPV",has received more and more inte...For oil company decision-makers,the principal concern is how to allocate their limited resources into the most valuable opportunities.Recently a new management philosophy,"Beyond NPV",has received more and more international attention.Economists and senior executives are seeking effective alternative analysis approaches for traditional technical and economic evaluation methods.The improved portfolio optimization model presented in this article represents an applicable technique beyond NPV for doing capital budgeting.In this proposed model,not only can oil company executives achieve trade-offs between returns and risks to their risk tolerance,but they can also employ an "operational premium" to distinguish their ability to improve the performance of the underlying projects.A simulation study based on 19 overseas upstream assets owned by a large oil company in China is conducted to compare optimized utility with non-optimized utility.The simulation results show that the petroleum optimization model including "operational premium" is more in line with the rational investors' demand.展开更多
Adding a reputation incentive system to peer-to-peer(P2P)energy transactions can encourage prosumers to regulate their trading behavior,which is important for ensuring the efficiency and reliability of P2P transaction...Adding a reputation incentive system to peer-to-peer(P2P)energy transactions can encourage prosumers to regulate their trading behavior,which is important for ensuring the efficiency and reliability of P2P transactions.This study proposed a P2P transaction mechanism and game optimization model for prosumers involved in distributed energy sources considering reputation-value incentives.First,the deviation of P2P transactions and the non-consumption rate of distributed renewable energy in P2P transactions were established as indicators to quantify the influencing factors of the reputation value,and a reputation incentive model of P2P transactions for prosumers was constructed.Then,the penalty coefficient was applied to the cost function of the prosumers,and a non-cooperative game model of P2P transactions based on the complete information of multi-prosumers was established.Furthermore,the Nash equilibrium problem was transformed into a nonlinear optimization problem by constructing the modified optimal reaction function,and the Nash equilibrium solution of the game was obtained via a relaxation algorithm.Finally,the modified IEEE 33-node test system based on electricity market P2P and an IEEE 123-node test system were used to analyze and verify the cost and P2P participation of prosumers considering the reputation value.The results show that the addition of the reputation incentive system can encourage prosumers to standardize their interactive transaction behavior and actively participate in P2P transactions.It can also improve the operation efficiency of the power grid and promote the perfection of the P2P transaction mechanism.展开更多
As new power systems and dual carbon policies develop,virtual power plant cluster(VPPC)provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems.To solve t...As new power systems and dual carbon policies develop,virtual power plant cluster(VPPC)provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems.To solve the coordinated optimal operation and low-carbon economic operation problem in multi-virtual power plant,a multi-virtual power plant(VPP)electricity-carbon interaction optimal scheduling model considering integrated demand response(IDR)is proposed.Firstly,a multi-VPP electricity-carbon interaction framework is established.The interaction of electric energy and carbon quotas can realize energy complementarity,reduce energy waste and promote low-carbon operation.Secondly,in order to coordinate the multiple types of energy and load in VPPC to further achieve low-carbon operation,the IDR mechanism based on the user comprehensive satisfaction(UCS)of electricity,heat as well as hydrogen is designed,which can effectively maintain the UCS in the cluster within a relatively high range.Finally,the unit output scheme is formulated to minimize the total cost of VPPC and the model is solved using theCPLEX solver.The simulation results showthat the proposed method effectively promotes the coordinated operation among multi-VPP,increases the consumption rate of renewable energy sources and the economics of VPPC and reduces carbon emissions.展开更多
Membrane technology has found wide applications in the petrochemical industry, mainly in the purification and recovery of the hydrogen resources. Accurate prediction of the membrane separation performance plays an imp...Membrane technology has found wide applications in the petrochemical industry, mainly in the purification and recovery of the hydrogen resources. Accurate prediction of the membrane separation performance plays an important role in carrying out advanced process control (APC). For the first time, a soft-sensor model for the membrane separation process has been established based on the radial basis function (RBF) neural networks. The main performance parameters, i.e, permeate hydrogen concentration, permeate gas flux, and residue hydrogen concentration, are estimated quantitatively by measuring the operating temperature, feed-side pressure, permeate-side pressure, residue-side pressure, feed-gas flux, and feed-hydrogen concentration excluding flow structure, membrane parameters, and other compositions. The predicted results can gain the desired effects. The effectiveness of this novel approach lays a foundation for integrating control technology and optimizing the operation of the gas membrane separation process.展开更多
Baoying pumping station is a part of source pumping stations in East Route Project of South-to-North Water Transfer in China. Aiming at the characteristics of head varying, and making use of the function of pump adjus...Baoying pumping station is a part of source pumping stations in East Route Project of South-to-North Water Transfer in China. Aiming at the characteristics of head varying, and making use of the function of pump adjustable blade, mathematical models of pumping station optimal operation are established and solved with genetic algorithm. For different total pumping discharge and total pumping volume of water per day, in order to minimize pumping station operation cost, the number and operation duties of running pump units are respectively determined at different periods of time in a day. The results indicate that the saving of electrical cost is significantly effected by the schemes of adjusting blade angles and time-varying electrical price when pumping certain water volume of water per day, and compared with conventional operation schemes (namely, the schemes of pumping station operation at design blade angles based on certain pumping discharge), the electrical cost is saved by 4.73%-31.27%. Also, compared with the electrical cost of conventional operation schemes, the electrical cost is saved by 2.03%-5.79% by the schemes of adjusting blade angles when pumping certain discharge.展开更多
This paper focuses on the energy optimal operation problem of microgrids(MGs) under stochastic environment.The deterministic method of MGs operation is often uneconomical because it fails to consider the high randomne...This paper focuses on the energy optimal operation problem of microgrids(MGs) under stochastic environment.The deterministic method of MGs operation is often uneconomical because it fails to consider the high randomness of unconventional energy resources.Therefore,it is necessary to develop a novel operation approach combining the uncertainty in the physical world with modeling strategy in the cyber system.This paper proposes an energy scheduling optimization strategy based on stochastic programming model by considering the uncertainty in MGs.The goal is to minimize the expected operation cost of MGs.The uncertainties are modeled based on autoregressive moving average(ARMA) model to expose the effects of physical world on cyber world.Through the comparison of the simulation results with deterministic method,it is shown that the effectiveness and robustness of proposed stochastic energy scheduling optimization strategy for MGs are valid.展开更多
Methanol to olefin(MTO)technology provides the opportunity to produce olefins from nonpetroleum sources such as coal,biomass and natural gas.More than 20 commercial MTO plants have been put into operation.Till now,con...Methanol to olefin(MTO)technology provides the opportunity to produce olefins from nonpetroleum sources such as coal,biomass and natural gas.More than 20 commercial MTO plants have been put into operation.Till now,contributions on optimal operation of industrial MTO plants from a process systems engineering perspective are rare.Based on relevance vector machine(RVM),a data-driven framework for optimal operation of the industrial MTO process is established to fully utilize the plentiful industrial data sets.RVM correlates the yield distribution prediction of main products and the operation conditions.These correlations then serve as the constraints for the multi-objective optimization model to pursue the optimal operation of the plant.Nondominated sorting genetic algorithmⅡis used to solve the optimization problem.Comprehensive tests demonstrate that the ethylene yield is effectively improved based on the proposed framework.Since RVM does provide the distribution prediction instead of point estimation,the established model is expected to provide guidance for actual production operations under uncertainty.展开更多
The effects of optimized operation principles implemented at reservoirs on the Wujiang River in southwest China between September 2009 and April 2010 under drought conditions were analyzed based on operational data co...The effects of optimized operation principles implemented at reservoirs on the Wujiang River in southwest China between September 2009 and April 2010 under drought conditions were analyzed based on operational data collected from the Guizhou Wujiang Hydropower Development Co., Ltd. A set of linear regression equations was developed to identify the key factors impacting the electric power generation at reservoirs. A 59% reduction in the inflow discharge at the Hongjiadu Reservoir led to a decrease of only 38% in the total electric power generation at the Hongjiadu, Dongfeng, Suofengying, and Wujiangdu reservoirs on the Wujiang River, indicating that optimized operation can play an important role in drought management. The water level and the amount of other water inputs at the Hongjiadu Reservoir and the outflow discharge at all of the reservoirs except the Wujiangdu Reservoir were key factors affecting the total electric power generation at reservoirs on the Wujiang River under optimized operation.展开更多
Multi-objective optimal dispatching schemes with intelligent algorithms are recognized as effective measures to promote the economics and environmental friendliness of microgrid applications.However,the low accuracy a...Multi-objective optimal dispatching schemes with intelligent algorithms are recognized as effective measures to promote the economics and environmental friendliness of microgrid applications.However,the low accuracy and poor convergence of these algorithms have been challenging for system operators.The bird swarm algorithm(BSA),a new bio-heuristic cluster intelligent algorithm,can potentially address these challenges;however,its computational iterative process may fall into a local optimum and result in premature convergence when optimizing small portions of multi-extremum functions.To analyze the impact of a multi-objective economic-environmental dispatching of a microgrid and overcome the aforementioned problems of the BSA,a self-adaptive levy flight strategy-based BSA(LF-BSA)was proposed.It can solve the dispatching problems of microgrid and enhance its dispatching convergence accuracy,stability,and speed,thereby improving its optimization performance.Six typical test functions were used to compare the LF-BSA with three commonly accepted algorithms to verify its excellence.Finally,a typical summer-time daily microgrid scenario under grid-connected operational conditions was simulated.The results proved the feasibility of the proposed LF-BSA,effectiveness of the multi-objective optimization,and necessity of using renewable energy and energy storage in microgrid dispatching optimization.展开更多
In a multi-energy collaboration system, cooling, heating, electricity, and other energy components are coupled to complement each other. Through multi-energy coordination and cooperation, they can significantly improv...In a multi-energy collaboration system, cooling, heating, electricity, and other energy components are coupled to complement each other. Through multi-energy coordination and cooperation, they can significantly improve their individual operating efficiency and overall economic benefits. Demand response, as a multi-energy supply and demand balance method, can further improve system flexibility and economy. Therefore, a multi-energy cooperative system optimization model has been proposed, which is driven by price-based demand response to determine the impact of power-demand response on the optimal operating mode of a multi-energy cooperative system. The main components of the multi-energy collaborative system have been analyzed. The multi-energy coupling characteristics have been identified based on the energy hub model. Using market elasticity as a basis, a price-based demand response model has been built. The model has been optimized to minimize daily operating cost of the multi-energy collaborative system. Using data from an actual situation, the model has been verified, and we have shown that the adoption of price-based demand response measures can significantly improve the economy of multi-energy collaborative systems.展开更多
基金supported in part by the National Key Research and Development Program of China(2021YFC2902703)the National Natural Science Foundation of China(62173078,61773105,61533007,61873049,61873053,61703085,61374147)。
文摘Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.
基金funded by the National Key R&D Project[Grant No.2019YFC1903900]Key R&D Province[Grant No.2023SFGC0101]Taishan Scholar Project[Grant No.tsqn202103010].
文摘Micro-energy systems contribute significantly to environmental improvement by reducing dependence on power grids through the utilization of multiple renewable energy sources.This study quantified the environmental impact of a micro-energy network system in an industrial park through a life cycle assessment using the operation of the micro-energy network over a year as the functional unit and“cradle-to-gate”as the system boundary.Based on the baseline scenario,a natural gas generator set was added to replace central heating,and the light pipes were expanded to constitute the optimized scenario.The results showed that the key impact categories for both scenarios were global warming,fine particulate matter formation,human carcinogenic toxicity,and human non-carcinogenic toxicity.The overall environmental impact of the optimized scenario was reduced by 68%compared to the baseline scenario.A sensitivity analysis of the key factors showed that electricity from the power grid was the key impact factor in both scenarios,followed by central heating and natural gas.Therefore,to reduce the environmental impact of network systems,it is necessary to further optimize the grid power structure.The research approach can be used to optimize micro-energy networks and evaluate the environmental impact of different energy systems.
文摘Objective: This paper aims to explore the impact of optimizing details in the operating room on the level of knowledge, attitude, and practice of hospital infection prevention and control by surgeons, as well as the effectiveness of infection control. Methods: From January 2022 to June 2023, a total of 120 patients were screened and randomly divided into a control group (routine care and hospital infection management) and a study group (optimizing details in the operating room). Results: Significant differences were found between the two groups in the data of surgeons’ level of knowledge, attitude, and practice in hospital infection prevention and control, infection rates, and nursing satisfaction, with the study group showing better results (P Conclusion: The use of optimizing details in the operating room among surgeons can effectively improve surgeons’ level of knowledge, attitude, and practice in hospital infection prevention and control, reduce infection occurrence, and is worth promoting.
文摘An algorithm named InterOpt for optimizing operational parameters is proposed based on interpretable machine learning,and is demonstrated via optimization of shale gas development.InterOpt consists of three parts:a neural network is used to construct an emulator of the actual drilling and hydraulic fracturing process in the vector space(i.e.,virtual environment);:the Sharpley value method in inter-pretable machine learning is applied to analyzing the impact of geological and operational parameters in each well(i.e.,single well feature impact analysis):and ensemble randomized maximum likelihood(EnRML)is conducted to optimize the operational parameters to comprehensively improve the efficiency of shale gas development and reduce the average cost.In the experiment,InterOpt provides different drilling and fracturing plans for each well according to its specific geological conditions,and finally achieves an average cost reduction of 9.7%for a case study with 104 wells.
基金support by Ministry of Housing and Urban-Rural Development’s Science and Technology Plan Project 2022(Hubei Province).
文摘Building structures themselves are one of the key areas of urban energy consumption,therefore,are a major source of greenhouse gas emissions.With this understood,the carbon trading market is gradually expanding to the building sector to control greenhouse gas emissions.Hence,to balance the interests of the environment and the building users,this paper proposes an optimal operation scheme for the photovoltaic,energy storage system,and flexible building power system(PEFB),considering the combined benefit of building.Based on the model of conventional photovoltaic(PV)and energy storage system(ESS),the mathematical optimization model of the system is proposed by taking the combined benefit of the building to the economy,society,and environment as the optimization objective,taking the near-zero energy consumption and carbon emission limitation of the building as the main constraints.The optimized operation strategy in this paper can give optimal results by making a trade-off between the users’costs and the combined benefits of the building.The efficiency and effectiveness of the proposed methods are verified by simulated experiments.
基金supported by the National Natural Science Foundation of China(U2066211)。
文摘With the expansion and implementation of rural revitalization strategies,there is a constant need for new energy sources for the construction of new townships.Consequently,integrated energy systems with the interconnection and interaction of multiple energy sources are developing rapidly.Biomass energy,a renewable green energy source with low pollution and wide distribution,has significant application potential in integrated energy systems.Considering the application of biomass energy in townships,this study established an integrated biomass energy system and proposed a model to optimize its operation.Lowest economic cost and highest clean energy utilization rate were considered as the objective functions.In addition,a plan was suggested to adjust the heat-electricity ratio based on the characteristics of the combined heat and power of the biomass.Finally,a simulation analysis conducted for a town in China was discussed,demonstrating that the construction of a township integrated-energy system and the use of biomass can significantly reduce operating costs and improve the energy utilization rate.Moreover,by adjusting the heat-electricity ratio,the economic cost was further reduced by 6.70%,whereas the clean energy utilization rate was increased by 5.14%.
基金financially supported by the National Natural Science Foundation of China (No.51734004)the National Key Research and Development Program of China (No.2017YFB0304005)the National Natural Science Foundation of China (No.51474044)。
文摘Against the realistic background of excess production capacity, product structure imbalance, and high material and energy consumption in steel enterprises, the implementation of operation optimization for the steel manufacturing process is essential to reduce the production cost, increase the production or energy efficiency, and improve production management. In this study, the operation optimization problem of the steel manufacturing process, which needed to go through a complex production organization from customers' orders to workshop production, was analyzed. The existing research on the operation optimization techniques, including process simulation, production planning, production scheduling, interface scheduling, and scheduling of auxiliary equipment, was reviewed. The literature review reveals that, although considerable research has been conducted to optimize the operation of steel production, these techniques are usually independent and unsystematic.Therefore, the future work related to operation optimization of the steel manufacturing process based on the integration of multi technologies and the intersection of multi disciplines were summarized.
文摘The rotary water jetting is one of the most important techniques for horizontal well cleanup.The jet flow is used to remove plugging particles from sand control screens to recover their permeability.Currently,the operation optimization of this technique depends mainly on experience due to absence of applicable evaluation and design models for removing plugging materials.This paper presents an experimental setup to simulate the cleanup process of plugged screens by rotary water jetting on the surface and to evaluate the performance of a jetting tool.Using real plugged screens pulled from damaged wells,a series of tests were performed,and the qualitative relationships between the cleanup efficiency and various operational parameters,such as the type of fluids used,flow rate,mode of tool movement,etc.,were obtained.The test results indicated that the cleanup performance was much better when the rotary jetting tool moved and stopped periodically for a certain time than that when it reciprocated at a constant speed.To be exact,it was desirable for the rotary jetting tool to move for 1.5-2 m and stop for 2-4 min,which was called the "move-stop-move" mode.Good cleanup performance could be obtained at high flow rates,and the flow rate was recommended to be no lower than 550-600 L/min.The test results also indicated that complex mud acid was better than clean water in terms of cleanup performance.Good cleanup efficiency and high screen permeability recovery could be achieved for severely plugged screens.Rotary jetting is preferred for the cleanup of horizontal wells with severely plugged screens,and the screen permeability recovery ratio may reach 20% if optimized operation parameters were used.
基金supported by the National Key R&D Program of China(2018YFA0702200)Science and Technology Project of State Grid Shandong Electric Power Corporation(52062518000Q)。
文摘The renewable portfolio standard has been promoted in parallel with the reform of the electricity market,and the flexibility requirement of the power system has rapidly increased.To promote renewable energy consumption and improve power system flexibility,a bi-level optimal operation model of the electricity market is proposed.A probabilistic model of the flexibility requirement is established,considering the correlation between wind power,photovoltaic power,and load.A bi-level optimization model is established for the multi-markets;the upper and lower models represent the intra-provincial market and inter-provincial market models,respectively.To efficiently solve the model,it is transformed into a mixed-integer linear programming model using the Karush–Kuhn–Tucker condition and Lagrangian duality theory.The economy and flexibility of the model are verified using a provincial power grid as an example.
文摘Setting up a knowledge base is a helpful way to optimize the operation of the polyethylene process by improving the performance and the ef ciency of reuse of information and knowledge two critical ele- ments in polyethylene smart manufacturing. In this paper, we propose an overall structure for a knowl- edge base based on practical customer demand and the mechanism of the polyethylene process. First, an ontology of the polyethylene process constructed using the seven-step method is introduced as a carrier for knowledge representation and sharing. Next, a prediction method is presented for the molecular weight distribution (MWD) based on a back propagation (BP) neural network model, by analyzing the relationships between the operating conditions and the parameters of the MWD. Based on this network, a differential evolution algorithm is introduced to optimize the operating conditions by tuning the MWD. Finally, utilizing a MySQL database and the Java programming language, a knowledge base system for the operation optimization of the polyethylene process based on a browser/server framework is realized.
基金financial support from National Science and Technology Major Project of the Ministry of Science and Technology of China"Research on Investment estimation tools and economic appraisal system integration and development"(2011ZX05030-006-04)
文摘For oil company decision-makers,the principal concern is how to allocate their limited resources into the most valuable opportunities.Recently a new management philosophy,"Beyond NPV",has received more and more international attention.Economists and senior executives are seeking effective alternative analysis approaches for traditional technical and economic evaluation methods.The improved portfolio optimization model presented in this article represents an applicable technique beyond NPV for doing capital budgeting.In this proposed model,not only can oil company executives achieve trade-offs between returns and risks to their risk tolerance,but they can also employ an "operational premium" to distinguish their ability to improve the performance of the underlying projects.A simulation study based on 19 overseas upstream assets owned by a large oil company in China is conducted to compare optimized utility with non-optimized utility.The simulation results show that the petroleum optimization model including "operational premium" is more in line with the rational investors' demand.
基金supported by the National Natural Science Foundation of China(U2066211,52177124,52107134)the Institute of Electrical Engineering,CAS(E155610101)+1 种基金the DNL Cooperation Fund,CAS(DNL202023)the Youth Innovation Promotion Association of CAS(2019143).
文摘Adding a reputation incentive system to peer-to-peer(P2P)energy transactions can encourage prosumers to regulate their trading behavior,which is important for ensuring the efficiency and reliability of P2P transactions.This study proposed a P2P transaction mechanism and game optimization model for prosumers involved in distributed energy sources considering reputation-value incentives.First,the deviation of P2P transactions and the non-consumption rate of distributed renewable energy in P2P transactions were established as indicators to quantify the influencing factors of the reputation value,and a reputation incentive model of P2P transactions for prosumers was constructed.Then,the penalty coefficient was applied to the cost function of the prosumers,and a non-cooperative game model of P2P transactions based on the complete information of multi-prosumers was established.Furthermore,the Nash equilibrium problem was transformed into a nonlinear optimization problem by constructing the modified optimal reaction function,and the Nash equilibrium solution of the game was obtained via a relaxation algorithm.Finally,the modified IEEE 33-node test system based on electricity market P2P and an IEEE 123-node test system were used to analyze and verify the cost and P2P participation of prosumers considering the reputation value.The results show that the addition of the reputation incentive system can encourage prosumers to standardize their interactive transaction behavior and actively participate in P2P transactions.It can also improve the operation efficiency of the power grid and promote the perfection of the P2P transaction mechanism.
基金supported by the National Natural Science Foundation of China (NSFC) (Grant No.52107107).
文摘As new power systems and dual carbon policies develop,virtual power plant cluster(VPPC)provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems.To solve the coordinated optimal operation and low-carbon economic operation problem in multi-virtual power plant,a multi-virtual power plant(VPP)electricity-carbon interaction optimal scheduling model considering integrated demand response(IDR)is proposed.Firstly,a multi-VPP electricity-carbon interaction framework is established.The interaction of electric energy and carbon quotas can realize energy complementarity,reduce energy waste and promote low-carbon operation.Secondly,in order to coordinate the multiple types of energy and load in VPPC to further achieve low-carbon operation,the IDR mechanism based on the user comprehensive satisfaction(UCS)of electricity,heat as well as hydrogen is designed,which can effectively maintain the UCS in the cluster within a relatively high range.Finally,the unit output scheme is formulated to minimize the total cost of VPPC and the model is solved using theCPLEX solver.The simulation results showthat the proposed method effectively promotes the coordinated operation among multi-VPP,increases the consumption rate of renewable energy sources and the economics of VPPC and reduces carbon emissions.
文摘Membrane technology has found wide applications in the petrochemical industry, mainly in the purification and recovery of the hydrogen resources. Accurate prediction of the membrane separation performance plays an important role in carrying out advanced process control (APC). For the first time, a soft-sensor model for the membrane separation process has been established based on the radial basis function (RBF) neural networks. The main performance parameters, i.e, permeate hydrogen concentration, permeate gas flux, and residue hydrogen concentration, are estimated quantitatively by measuring the operating temperature, feed-side pressure, permeate-side pressure, residue-side pressure, feed-gas flux, and feed-hydrogen concentration excluding flow structure, membrane parameters, and other compositions. The predicted results can gain the desired effects. The effectiveness of this novel approach lays a foundation for integrating control technology and optimizing the operation of the gas membrane separation process.
基金supported by Author Special Foundation of National Excellent Doctoral Dissertation of China (Grant No. 2007B41)Jiangsu Provincial Foundation of "333 Talents Engineering" of ChinaJiangsu Provincial Academic Header Foundation of Qinglan Engineering of China
文摘Baoying pumping station is a part of source pumping stations in East Route Project of South-to-North Water Transfer in China. Aiming at the characteristics of head varying, and making use of the function of pump adjustable blade, mathematical models of pumping station optimal operation are established and solved with genetic algorithm. For different total pumping discharge and total pumping volume of water per day, in order to minimize pumping station operation cost, the number and operation duties of running pump units are respectively determined at different periods of time in a day. The results indicate that the saving of electrical cost is significantly effected by the schemes of adjusting blade angles and time-varying electrical price when pumping certain water volume of water per day, and compared with conventional operation schemes (namely, the schemes of pumping station operation at design blade angles based on certain pumping discharge), the electrical cost is saved by 4.73%-31.27%. Also, compared with the electrical cost of conventional operation schemes, the electrical cost is saved by 2.03%-5.79% by the schemes of adjusting blade angles when pumping certain discharge.
基金supported by National Natural Science Foundation of China(61100159,61233007)National High Technology Research and Development Program of China(863 Program)(2011AA040103)+2 种基金Foundation of Chinese Academy of Sciences(KGCX2-EW-104)Financial Support of the Strategic Priority Research Program of Chinese Academy of Sciences(XDA06021100)the Cross-disciplinary Collaborative Teams Program for Science,Technology and Innovation,of Chinese Academy of Sciences-Network and System Technologies for Security Monitoring and Information Interaction in Smart Grid Energy Management System for Micro-smart Grid
文摘This paper focuses on the energy optimal operation problem of microgrids(MGs) under stochastic environment.The deterministic method of MGs operation is often uneconomical because it fails to consider the high randomness of unconventional energy resources.Therefore,it is necessary to develop a novel operation approach combining the uncertainty in the physical world with modeling strategy in the cyber system.This paper proposes an energy scheduling optimization strategy based on stochastic programming model by considering the uncertainty in MGs.The goal is to minimize the expected operation cost of MGs.The uncertainties are modeled based on autoregressive moving average(ARMA) model to expose the effects of physical world on cyber world.Through the comparison of the simulation results with deterministic method,it is shown that the effectiveness and robustness of proposed stochastic energy scheduling optimization strategy for MGs are valid.
基金financial support for this work from National Natural Science Foundation of China(21978150,21706143)。
文摘Methanol to olefin(MTO)technology provides the opportunity to produce olefins from nonpetroleum sources such as coal,biomass and natural gas.More than 20 commercial MTO plants have been put into operation.Till now,contributions on optimal operation of industrial MTO plants from a process systems engineering perspective are rare.Based on relevance vector machine(RVM),a data-driven framework for optimal operation of the industrial MTO process is established to fully utilize the plentiful industrial data sets.RVM correlates the yield distribution prediction of main products and the operation conditions.These correlations then serve as the constraints for the multi-objective optimization model to pursue the optimal operation of the plant.Nondominated sorting genetic algorithmⅡis used to solve the optimization problem.Comprehensive tests demonstrate that the ethylene yield is effectively improved based on the proposed framework.Since RVM does provide the distribution prediction instead of point estimation,the established model is expected to provide guidance for actual production operations under uncertainty.
基金supported by the National Natural Science Foundation of China (Grant No. 51109229)
文摘The effects of optimized operation principles implemented at reservoirs on the Wujiang River in southwest China between September 2009 and April 2010 under drought conditions were analyzed based on operational data collected from the Guizhou Wujiang Hydropower Development Co., Ltd. A set of linear regression equations was developed to identify the key factors impacting the electric power generation at reservoirs. A 59% reduction in the inflow discharge at the Hongjiadu Reservoir led to a decrease of only 38% in the total electric power generation at the Hongjiadu, Dongfeng, Suofengying, and Wujiangdu reservoirs on the Wujiang River, indicating that optimized operation can play an important role in drought management. The water level and the amount of other water inputs at the Hongjiadu Reservoir and the outflow discharge at all of the reservoirs except the Wujiangdu Reservoir were key factors affecting the total electric power generation at reservoirs on the Wujiang River under optimized operation.
基金supported by the National Natural Science Foundation of China (No. 52061635103)
文摘Multi-objective optimal dispatching schemes with intelligent algorithms are recognized as effective measures to promote the economics and environmental friendliness of microgrid applications.However,the low accuracy and poor convergence of these algorithms have been challenging for system operators.The bird swarm algorithm(BSA),a new bio-heuristic cluster intelligent algorithm,can potentially address these challenges;however,its computational iterative process may fall into a local optimum and result in premature convergence when optimizing small portions of multi-extremum functions.To analyze the impact of a multi-objective economic-environmental dispatching of a microgrid and overcome the aforementioned problems of the BSA,a self-adaptive levy flight strategy-based BSA(LF-BSA)was proposed.It can solve the dispatching problems of microgrid and enhance its dispatching convergence accuracy,stability,and speed,thereby improving its optimization performance.Six typical test functions were used to compare the LF-BSA with three commonly accepted algorithms to verify its excellence.Finally,a typical summer-time daily microgrid scenario under grid-connected operational conditions was simulated.The results proved the feasibility of the proposed LF-BSA,effectiveness of the multi-objective optimization,and necessity of using renewable energy and energy storage in microgrid dispatching optimization.
基金supported by State Grid Corporation Technology Project (5400-201956447A-0-0-00)。
文摘In a multi-energy collaboration system, cooling, heating, electricity, and other energy components are coupled to complement each other. Through multi-energy coordination and cooperation, they can significantly improve their individual operating efficiency and overall economic benefits. Demand response, as a multi-energy supply and demand balance method, can further improve system flexibility and economy. Therefore, a multi-energy cooperative system optimization model has been proposed, which is driven by price-based demand response to determine the impact of power-demand response on the optimal operating mode of a multi-energy cooperative system. The main components of the multi-energy collaborative system have been analyzed. The multi-energy coupling characteristics have been identified based on the energy hub model. Using market elasticity as a basis, a price-based demand response model has been built. The model has been optimized to minimize daily operating cost of the multi-energy collaborative system. Using data from an actual situation, the model has been verified, and we have shown that the adoption of price-based demand response measures can significantly improve the economy of multi-energy collaborative systems.