The power system,as an energy hub,plays a crucial role in the transformation of energy production and consumption.On July 19,2023,the International Energy Agency(IEA)released a Global Electricity Market Report for 202...The power system,as an energy hub,plays a crucial role in the transformation of energy production and consumption.On July 19,2023,the International Energy Agency(IEA)released a Global Electricity Market Report for 2023-2024.This report indicates that the development of the world’s energy production is rapidly moving towards the critical point where the proportion of electricity generated from renewable sources surpasses that from non-renewable sources.展开更多
With the development of green data centers,a large number of Uninterruptible Power Supply(UPS)resources in Internet Data Center(IDC)are becoming idle assets owing to their low utilization rate.The revitalization of th...With the development of green data centers,a large number of Uninterruptible Power Supply(UPS)resources in Internet Data Center(IDC)are becoming idle assets owing to their low utilization rate.The revitalization of these idle UPS resources is an urgent problem that must be addressed.Based on the energy storage type of the UPS(EUPS)and using renewable sources,a solution for IDCs is proposed in this study.Subsequently,an EUPS cluster classification method based on the concept of shared mechanism niche(CSMN)was proposed to effectively solve the EUPS control problem.Accordingly,the classified EUPS aggregation unit was used to determine the optimal operation of the IDC.An IDC cost minimization optimization model was established,and the Quantum Particle Swarm Optimization(QPSO)algorithm was adopted.Finally,the economy and effectiveness of the three-tier optimization framework and model were verified through three case studies.展开更多
Given the“double carbon”objective and the drive toward low-carbon power,investigating the integration and interaction within the carbon-electricity market can enhance renewable energy utilization and facilitate ener...Given the“double carbon”objective and the drive toward low-carbon power,investigating the integration and interaction within the carbon-electricity market can enhance renewable energy utilization and facilitate energy conservation and emission reduction endeavors.However,further research is necessary to explore operational optimization methods for establishing a regional energy system using Power-to-Hydrogen(P2H)technology,focusing on participating in combined carbon-electricity market transactions.This study introduces an innovative Electro-Hydrogen Regional Energy System(EHRES)in this context.This system integrates renewable energy sources,a P2H system,cogeneration units,and energy storage devices.The core purpose of this integration is to optimize renewable energy utilization and minimize carbon emissions.This study aims to formulate an optimal operational strategy for EHRES,enabling its dynamic engagement in carbon-electricity market transactions.The initial phase entails establishing the technological framework of the electricity-hydrogen coupling system integrated with P2H.Subsequently,an analysis is conducted to examine the operational mode of EHRES as it participates in carbon-electricity market transactions.Additionally,the system scheduling model includes a stepped carbon trading price mechanism,considering the combined heat and power generation characteristics of the Hydrogen Fuel Cell(HFC).This facilitates the establishment of an optimal operational model for EHRES,aiming to minimize the overall operating cost.The simulation example illustrates that the coordinated operation of EHRES in carbon-electricity market transactions holds the potential to improve renewable energy utilization and reduce the overall system cost.This result carries significant implications for attaining advantages in both low-carbon and economic aspects.展开更多
This study proposes a novel form of environmental reservoir operation through integrating environmental flow supply,drought analysis,and evolutionary optimization.This study demonstrates that simultaneous supply of do...This study proposes a novel form of environmental reservoir operation through integrating environmental flow supply,drought analysis,and evolutionary optimization.This study demonstrates that simultaneous supply of downstream environmental flow of reservoir as well as water demand is challenging in the semi-arid area especially in dry years.In this study,water supply and environmental flow supply were 40%and 30%in the droughts,respectively.Moreover,mean errors of supplying water demand as well as environmental flow in dry years were 6 and 9 m3/s,respectively.Hence,these results highlight that ecological stresses of the downstream aquatic habitats as well as water supply loss are considerably escalated in dry years,which implies even using environmental optimal operation is not able to protect downstream aquatic habitats properly in the severe droughts.Moreover,available storage in reservoir will be remarkably reduced(averagely more than 30×106 m3 compared with optimal storage equal to 70×106 m3),which implies strategic storage of reservoir might be threatened.Among used evolutionary algorithms,particle swarm optimization(PSO)was selected as the best algorithm for solving the novel proposed objective function.The significance of this study is to propose a novel objective function to optimize reservoir operation in which environmental flow supply is directly addressed and integrated with drought analysis.This novel form of optimization system can overcome uncertainties of the conventional objective function due to considering environmental flow in the objective function as well as drought analysis in the context of reservoir operation especially applicable in semi-arid areas.The results indicate that using either other water resources for water supply or reducing water demand is the only solution for managing downstream ecological impacts of the river ecosystem.In other words,the results highlighted that replanning of water resources in the study area is necessary.Replacing the conventional optimization system for reservoir operation in the semi-arid area with proposed optimization system is recommendable to minimize the negotiations between stakeholders and environmental managers.展开更多
The widespread penetration of distributed energy sources and the use of load response programs,especially in a microgrid,have caused many power system issues,such as control and operation of these networks,to be affec...The widespread penetration of distributed energy sources and the use of load response programs,especially in a microgrid,have caused many power system issues,such as control and operation of these networks,to be affected.The control and operation of many small-distributed generation units with different performance characteristics create another challenge for the safe and efficient operation of the microgrid.In this paper,the optimum operation of distributed generation resources and heat and power storage in a microgrid,was performed based on real-time pricing through the proposed gray wolf optimization(GWO)algorithm to reduce the energy supply cost with the microgrid.Distributed generation resources such as solar panels,diesel generators with battery storage,and boiler thermal resources with thermal storage were used in the studied microgrid.Also,a combined heat and power(CHP)unit was used to produce thermal and electrical energy simultaneously.In the simulations,in addition to the gray wolf algorithm,some optimization algorithms have also been used.Then the results of 20 runs for each algorithm confirmed the high accuracy of the proposed GWO algorithm.The results of the simulations indicated that the CHP energy resources must be managed to have a minimum cost of energy supply in the microgrid,considering the demand response program.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
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
The interest in distributed generation has been increasing in recent years, especially due to technical devel- opment on generation systems that meet environmental and energy policy concerns. One of the most impor- ta...The interest in distributed generation has been increasing in recent years, especially due to technical devel- opment on generation systems that meet environmental and energy policy concerns. One of the most impor- tant distributed energy technologies is Combined Cooling, Heat and Power (CCHP) systems. CCHP is a small and self-contained electric, heating and cooling generation plant that can provide power for households, commercial or industrial facilities. It can reduce power loss and enhance service reliability in distribution systems. The proposed method in this paper determines the optimal size and operation of CCHP, auxiliary boiler and also heat storage unit as elements of an energy hub, for users by an integrated view of electricity and natural gas network. Authors apply cost and benefit analysis in the optimization. To confirm the proposed method, the optimum sizes of these elements are determined for a hotel in Tehran as a case study.展开更多
Aiming at the problem that traditional optimal operation of hydropower reservoir pays little attention to ecology, an optimal operation model of multi-objective hydropower reservoir with ecology consideration is estab...Aiming at the problem that traditional optimal operation of hydropower reservoir pays little attention to ecology, an optimal operation model of multi-objective hydropower reservoir with ecology consideration is established which combines the ecology and power generation. The model takes the maximum annual power generation benefit, the maximum output of the minimal output stage in the year and the minimum shortage of ecological water demand as objectives, and water quantity balance of reservoir, reservoir storage, discharge flow, output and so on as constraints. Chaotic genetic arithmetic is developed to solve the optimal model. An example is studied, showing that the annual generation of the proposed model is 8 million kW?h less than that model without ecology consideration, which is about 0.28 percent. But the proposed model is in favor of river ecology protection, and can promote the sustainable utilization of water resources. So it is worthy and necessary for the optimal operation of hydropower reservoir with ecology consideration.展开更多
Traditional optimal operation of hydropower station usually has two problems. One is that the optimal algorithm hasn’t high efficiency, and the other is that the optimal operation model pays little attention to ecolo...Traditional optimal operation of hydropower station usually has two problems. One is that the optimal algorithm hasn’t high efficiency, and the other is that the optimal operation model pays little attention to ecology. And with the development of electric power market, the generated benefit is concerned instead of generated energy. Based on the analysis of time-varying electricity price policy, an optimal operation model of hydropower station reservoir with ecology consideration is established. The model takes the maximum annual power generation benefit, the maximum output of the minimal output stage in the year and the minimum shortage of eco-environment demand as the objectives, and reservoir water quantity balance, reservoir storage capacity, reservoir discharge flow and hydropower station output and nonnegative variable as the constraints. To solve the optimal model, a chaotic optimization genetic algorithm which combines the ergodicity of chaos and the inversion property of genetic algorithm is exploited. An example is given, which shows that the proposed model and algorithm are scientific and feasible to deal with the optimal operation of hydropower station.展开更多
Due to the intermittency and instability of Wind-Solar energy and easy compensation of hydropower, this study proposes a Wind-Solar-Hydro power optimal scheduling model. This model is aimed at maximizing the total sys...Due to the intermittency and instability of Wind-Solar energy and easy compensation of hydropower, this study proposes a Wind-Solar-Hydro power optimal scheduling model. This model is aimed at maximizing the total system power generation and the minimum ten-day joint output. To effectively optimize the multi-objective model, a new algorithm named non-dominated sorting culture differential evolution algorithm(NSCDE) is proposed. The feasibility of NSCDE was verified through several well-known benchmark problems. It was then applied to the Jinping Wind-Solar-Hydro complementary power generation system. The results demonstrate that NSCDE can provide decision makers a series of optimized scheduling schemes.展开更多
Combined heat and electricity operation with variable mass flow rates promotes flexibility,economy,and sustainability through synergies between electric power systems(EPSs)and district heating systems(DHSs).Such combi...Combined heat and electricity operation with variable mass flow rates promotes flexibility,economy,and sustainability through synergies between electric power systems(EPSs)and district heating systems(DHSs).Such combined operation presents a highly nonlinear and nonconvex optimization problem,mainly due to the bilinear terms in the heat flow model—that is,the product of the mass flow rate and the nodal temperature.Existing methods,such as nonlinear optimization,generalized Benders decomposition,and convex relaxation,still present challenges in achieving a satisfactory performance in terms of solution quality and computational efficiency.To resolve this problem,we herein first reformulate the district heating network model through an equivalent transformation and variable substitution.The reformulated model has only one set of nonconvex constraints with reduced bilinear terms,and the remaining constraints are linear.Such a reformulation not only ensures optimality,but also accelerates the solving process.To relax the remaining bilinear constraints,we then apply McCormick envelopes and obtain an objective lower bound of the reformulated model.To improve the quality of the McCormick relaxation,we employ a piecewise McCormick technique that partitions the domain of one of the variables of the bilinear terms into several disjoint regions in order to derive strengthened lower and upper bounds of the partitioned variables.We propose a heuristic tightening method to further constrict the strengthened bounds derived from the piecewise McCormick technique and recover a nearby feasible solution.Case studies show that,compared with the interior point method and the method implemented in a global bilinear solver,the proposed tightening McCormick method quickly solves the heat–electricity operation problem with an acceptable feasibility check and optimality.展开更多
In view of the poor water supply system’s network properties, the system’s complicated network hydraulic equations were replaced by macroscopic nodal pressure model and the model of relationship between supply flow ...In view of the poor water supply system’s network properties, the system’s complicated network hydraulic equations were replaced by macroscopic nodal pressure model and the model of relationship between supply flow and water source head. By using pump-station pressure head and initial tank water levels as decision variables, the model of optimal allocation of water supply between pump-sources was developed. Genetic algorithm was introduced to deal with the model of optimal allocation of water supply. Methods for handling each constraint condition were put forward, and overcome the shortcoming such as premature convergence of genetic algorithm; a solving method was brought forward in which genetic algorithm was combined with simulated annealing technology and self-adaptive crossover and mutation probabilities were adopted. An application example showed the feasibility of this algorithm.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
This paper includes an application of Differential Evolution (DE) for the optimal operation of multipurpose reservoir. The objective of the study is to maximize the hydropower production. The constraints for the optim...This paper includes an application of Differential Evolution (DE) for the optimal operation of multipurpose reservoir. The objective of the study is to maximize the hydropower production. The constraints for the optimization problem are reservoir capacity, turbine release capacity constraints, irrigation supply demand constraints and storage continuity. For initializing population, the upper and lower bounds of decision variables are fixed. The fitness of each vector is evaluated. The mutation and recombination is performed. The control parameters, i.e., population size, crossover constant and the weight are fixed according to their fitness value. This procedure is performed for the ten different strategies of DE. Sensitivity analysis performed for ten strategies of DE suggested that, De/best/1/bin is the best strategy which gives optimal solution. The DE algorithm application is presented through Jayakwadi project stage-I, Maharashtra State, India. Genetic algorithm is utilized as a comparative approach to assess the ability of DE. The results of GA and ten DE strategies for the given parameters indicated that both the results are comparable. The model is run for dependable inflows. Monthly maximized hydropower production and irrigation releases are presented. These values will be the basis for decision maker to take decisions regarding operation policy of the reservoir. Results of application of DE model indicate that the maximized hydropower production is 30.885 ×106 kwh and the cor-responding irrigation release is 928.44 Mm3.展开更多
In the present study, a Linear Programming (LP) model is developed for the conjunctive use of surface water and ground water to obtain the optimal operating policy for a multipurpose single reservoir. The objective of...In the present study, a Linear Programming (LP) model is developed for the conjunctive use of surface water and ground water to obtain the optimal operating policy for a multipurpose single reservoir. The objective of the present study is to maximize the net benefit from the command area under consideration. The constraints imposed on the objective function are maximum and minimum irrigation demands, reservoir storages and canal capacity. The model takes into account the continuity constraint which includes inflows in to the reservoir, releases for irrigation, releases for hydro-power generation, evaporation losses, feeder canal releases, initial and final storages in the reservoir in each time period. The developed model is applied to the case study of Jayakwadi reservoir stage-I, built across river Godavari, Maharashtra, India. Initially the model is solved for the availability of surface water which results in net benefit of 3373.45 million rupees with irrigation intensity is 57.07%. Next the model solved by considering the availability of surface water and available potential of groundwater in the area, which results in net benefits of 3590.02 million rupees with an intensity of irrigation 58.48%. The present model takes in to account the socio-economic requirement of growing the essential crops to meet the requirement of the society. The model has also generated the canal wise optimal releases for irrigation and power, monthly utilization of groundwater, storages in the reservoir at the end of every month and corresponding head over the turbine.展开更多
The optimal operation of water distribution networks under local pipe failures, such as water main breaks, was proposed. Based on a hydraulic analysis and a simulation of water distribution networks, a macroscopic mod...The optimal operation of water distribution networks under local pipe failures, such as water main breaks, was proposed. Based on a hydraulic analysis and a simulation of water distribution networks, a macroscopic model for a network under a local pipe failure was established by the statistical regression. After the operation objectives under a local pipe failure were determined, the optimal operation model was developed and solved by the genetic algorithm. The program was developed and examined by a city distribution network. The optimal operation alternative shows that the electricity cost is saved approximately 11%, the income of the water corporation is increased approximately 5%, and the pressure in the water distribution network is distributed evenly to ensure the network safe operation. Therefore, the proposed method for optimal operation under local pipe failure is feasible and cost-effective.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 adjust...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
In semiconductor and electronics factories, large multi-chiller systems are needed to satisfy strict cooling load requirements. In order to save energy, it is worthwhile to design the chilled water system operation. I...In semiconductor and electronics factories, large multi-chiller systems are needed to satisfy strict cooling load requirements. In order to save energy, it is worthwhile to design the chilled water system operation. In this paper, an optimal flexible operation scheme is developed based on a two-dimensional time-series model to forecast the cooling load of multi-chiller systems with chiller units of different cooling capacities running in parallel. The optimal integrity scheme can be obtained using the Mixed Integer Nonlinear Programming method, which minimizes the energy consumption of the system within a future time period. In order to better adapt the change of cooling load, the operation strategy of regulating the chilled water flowrates is employed. The chilled water flowrates are set as a design variable. When the chillers are running, their chilled water flowrates can vary within limits, whereas the flowrates are zero when the chillers are unloaded. This forecasting method provides integral optimization within a future time period and offers the operating reference for operators. The power and advantages of the proposed method are presented using an industrial case to help readers delve into this matter.展开更多
This paper proposes an improved optimal operation planning method for residential PEFC-CGS (Polymer Electrolyte Fuel CellCo-Generation System). Residential PEFC-CGS has recently been gathering attention as one of the ...This paper proposes an improved optimal operation planning method for residential PEFC-CGS (Polymer Electrolyte Fuel CellCo-Generation System). Residential PEFC-CGS has recently been gathering attention as one of the distributed power sources with high efficiency and low environmental impacts. Previous research pointed out that the output variations of PEFC adversely affect the durability. It can be surmised that smaller output variations will be desired to extend durability years. However, in this field, ramping rate have not been sufficiently considered. For local search and tabu search, ramping rate constraint makes our operation planning difficult because it restricts the search for feasible neighborhood solutions. Therefore, the authors proposed a method to deal with typical and harsher ramping rate constraints in comparison with conventional methods. There are two key points for the improvement. One is the reinforcement of the search along the output power axis;the other is to make use of the strategy of tabu search which avoids the local optimal solutions. The simulation results show the effectiveness of the proposed method in the daily operation planning. Furthermore, in the case using typical ramping rate parameter, it is confirmed that tabu search doesn’t contribute the reduction of daily operational cost due to the above stated restriction of the search area.展开更多
文摘The power system,as an energy hub,plays a crucial role in the transformation of energy production and consumption.On July 19,2023,the International Energy Agency(IEA)released a Global Electricity Market Report for 2023-2024.This report indicates that the development of the world’s energy production is rapidly moving towards the critical point where the proportion of electricity generated from renewable sources surpasses that from non-renewable sources.
基金supported by the Key Technology Projects of the China Southern Power Grid Corporation(STKJXM20200059)the Key Support Project of the Joint Fund of the National Natural Science Foundation of China(U22B20123)。
文摘With the development of green data centers,a large number of Uninterruptible Power Supply(UPS)resources in Internet Data Center(IDC)are becoming idle assets owing to their low utilization rate.The revitalization of these idle UPS resources is an urgent problem that must be addressed.Based on the energy storage type of the UPS(EUPS)and using renewable sources,a solution for IDCs is proposed in this study.Subsequently,an EUPS cluster classification method based on the concept of shared mechanism niche(CSMN)was proposed to effectively solve the EUPS control problem.Accordingly,the classified EUPS aggregation unit was used to determine the optimal operation of the IDC.An IDC cost minimization optimization model was established,and the Quantum Particle Swarm Optimization(QPSO)algorithm was adopted.Finally,the economy and effectiveness of the three-tier optimization framework and model were verified through three case studies.
基金supported financially by InnerMongoliaKey Lab of Electrical Power Conversion,Transmission,and Control under Grant IMEECTC2022001the S&TMajor Project of Inner Mongolia Autonomous Region in China(2021ZD0040).
文摘Given the“double carbon”objective and the drive toward low-carbon power,investigating the integration and interaction within the carbon-electricity market can enhance renewable energy utilization and facilitate energy conservation and emission reduction endeavors.However,further research is necessary to explore operational optimization methods for establishing a regional energy system using Power-to-Hydrogen(P2H)technology,focusing on participating in combined carbon-electricity market transactions.This study introduces an innovative Electro-Hydrogen Regional Energy System(EHRES)in this context.This system integrates renewable energy sources,a P2H system,cogeneration units,and energy storage devices.The core purpose of this integration is to optimize renewable energy utilization and minimize carbon emissions.This study aims to formulate an optimal operational strategy for EHRES,enabling its dynamic engagement in carbon-electricity market transactions.The initial phase entails establishing the technological framework of the electricity-hydrogen coupling system integrated with P2H.Subsequently,an analysis is conducted to examine the operational mode of EHRES as it participates in carbon-electricity market transactions.Additionally,the system scheduling model includes a stepped carbon trading price mechanism,considering the combined heat and power generation characteristics of the Hydrogen Fuel Cell(HFC).This facilitates the establishment of an optimal operational model for EHRES,aiming to minimize the overall operating cost.The simulation example illustrates that the coordinated operation of EHRES in carbon-electricity market transactions holds the potential to improve renewable energy utilization and reduce the overall system cost.This result carries significant implications for attaining advantages in both low-carbon and economic aspects.
文摘This study proposes a novel form of environmental reservoir operation through integrating environmental flow supply,drought analysis,and evolutionary optimization.This study demonstrates that simultaneous supply of downstream environmental flow of reservoir as well as water demand is challenging in the semi-arid area especially in dry years.In this study,water supply and environmental flow supply were 40%and 30%in the droughts,respectively.Moreover,mean errors of supplying water demand as well as environmental flow in dry years were 6 and 9 m3/s,respectively.Hence,these results highlight that ecological stresses of the downstream aquatic habitats as well as water supply loss are considerably escalated in dry years,which implies even using environmental optimal operation is not able to protect downstream aquatic habitats properly in the severe droughts.Moreover,available storage in reservoir will be remarkably reduced(averagely more than 30×106 m3 compared with optimal storage equal to 70×106 m3),which implies strategic storage of reservoir might be threatened.Among used evolutionary algorithms,particle swarm optimization(PSO)was selected as the best algorithm for solving the novel proposed objective function.The significance of this study is to propose a novel objective function to optimize reservoir operation in which environmental flow supply is directly addressed and integrated with drought analysis.This novel form of optimization system can overcome uncertainties of the conventional objective function due to considering environmental flow in the objective function as well as drought analysis in the context of reservoir operation especially applicable in semi-arid areas.The results indicate that using either other water resources for water supply or reducing water demand is the only solution for managing downstream ecological impacts of the river ecosystem.In other words,the results highlighted that replanning of water resources in the study area is necessary.Replacing the conventional optimization system for reservoir operation in the semi-arid area with proposed optimization system is recommendable to minimize the negotiations between stakeholders and environmental managers.
基金This work was supported in part by an International Research Partnership“Electrical Engineering—Thai French Research Center(EE-TFRC)”under the project framework of the Lorraine Universitéd’Excellence(LUE)in cooperation between Universitéde Lorraine and King Mongkut’s University of Technology North Bangkok and in part by the National Research Council of Thailand(NRCT)under Senior Research Scholar Program under Grant No.N42A640328.
文摘The widespread penetration of distributed energy sources and the use of load response programs,especially in a microgrid,have caused many power system issues,such as control and operation of these networks,to be affected.The control and operation of many small-distributed generation units with different performance characteristics create another challenge for the safe and efficient operation of the microgrid.In this paper,the optimum operation of distributed generation resources and heat and power storage in a microgrid,was performed based on real-time pricing through the proposed gray wolf optimization(GWO)algorithm to reduce the energy supply cost with the microgrid.Distributed generation resources such as solar panels,diesel generators with battery storage,and boiler thermal resources with thermal storage were used in the studied microgrid.Also,a combined heat and power(CHP)unit was used to produce thermal and electrical energy simultaneously.In the simulations,in addition to the gray wolf algorithm,some optimization algorithms have also been used.Then the results of 20 runs for each algorithm confirmed the high accuracy of the proposed GWO algorithm.The results of the simulations indicated that the CHP energy resources must be managed to have a minimum cost of energy supply in the microgrid,considering the demand response program.
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.
文摘The interest in distributed generation has been increasing in recent years, especially due to technical devel- opment on generation systems that meet environmental and energy policy concerns. One of the most impor- tant distributed energy technologies is Combined Cooling, Heat and Power (CCHP) systems. CCHP is a small and self-contained electric, heating and cooling generation plant that can provide power for households, commercial or industrial facilities. It can reduce power loss and enhance service reliability in distribution systems. The proposed method in this paper determines the optimal size and operation of CCHP, auxiliary boiler and also heat storage unit as elements of an energy hub, for users by an integrated view of electricity and natural gas network. Authors apply cost and benefit analysis in the optimization. To confirm the proposed method, the optimum sizes of these elements are determined for a hotel in Tehran as a case study.
文摘Aiming at the problem that traditional optimal operation of hydropower reservoir pays little attention to ecology, an optimal operation model of multi-objective hydropower reservoir with ecology consideration is established which combines the ecology and power generation. The model takes the maximum annual power generation benefit, the maximum output of the minimal output stage in the year and the minimum shortage of ecological water demand as objectives, and water quantity balance of reservoir, reservoir storage, discharge flow, output and so on as constraints. Chaotic genetic arithmetic is developed to solve the optimal model. An example is studied, showing that the annual generation of the proposed model is 8 million kW?h less than that model without ecology consideration, which is about 0.28 percent. But the proposed model is in favor of river ecology protection, and can promote the sustainable utilization of water resources. So it is worthy and necessary for the optimal operation of hydropower reservoir with ecology consideration.
文摘Traditional optimal operation of hydropower station usually has two problems. One is that the optimal algorithm hasn’t high efficiency, and the other is that the optimal operation model pays little attention to ecology. And with the development of electric power market, the generated benefit is concerned instead of generated energy. Based on the analysis of time-varying electricity price policy, an optimal operation model of hydropower station reservoir with ecology consideration is established. The model takes the maximum annual power generation benefit, the maximum output of the minimal output stage in the year and the minimum shortage of eco-environment demand as the objectives, and reservoir water quantity balance, reservoir storage capacity, reservoir discharge flow and hydropower station output and nonnegative variable as the constraints. To solve the optimal model, a chaotic optimization genetic algorithm which combines the ergodicity of chaos and the inversion property of genetic algorithm is exploited. An example is given, which shows that the proposed model and algorithm are scientific and feasible to deal with the optimal operation of hydropower station.
基金supported by the National Key R&D Program of China (2016YFC0402209)the Major Research Plan of the National Natural Science Foundation of China (No. 91647114)
文摘Due to the intermittency and instability of Wind-Solar energy and easy compensation of hydropower, this study proposes a Wind-Solar-Hydro power optimal scheduling model. This model is aimed at maximizing the total system power generation and the minimum ten-day joint output. To effectively optimize the multi-objective model, a new algorithm named non-dominated sorting culture differential evolution algorithm(NSCDE) is proposed. The feasibility of NSCDE was verified through several well-known benchmark problems. It was then applied to the Jinping Wind-Solar-Hydro complementary power generation system. The results demonstrate that NSCDE can provide decision makers a series of optimized scheduling schemes.
基金This work was supported by the Science and Technology Program of State Grid Corporation of China(522300190008).
文摘Combined heat and electricity operation with variable mass flow rates promotes flexibility,economy,and sustainability through synergies between electric power systems(EPSs)and district heating systems(DHSs).Such combined operation presents a highly nonlinear and nonconvex optimization problem,mainly due to the bilinear terms in the heat flow model—that is,the product of the mass flow rate and the nodal temperature.Existing methods,such as nonlinear optimization,generalized Benders decomposition,and convex relaxation,still present challenges in achieving a satisfactory performance in terms of solution quality and computational efficiency.To resolve this problem,we herein first reformulate the district heating network model through an equivalent transformation and variable substitution.The reformulated model has only one set of nonconvex constraints with reduced bilinear terms,and the remaining constraints are linear.Such a reformulation not only ensures optimality,but also accelerates the solving process.To relax the remaining bilinear constraints,we then apply McCormick envelopes and obtain an objective lower bound of the reformulated model.To improve the quality of the McCormick relaxation,we employ a piecewise McCormick technique that partitions the domain of one of the variables of the bilinear terms into several disjoint regions in order to derive strengthened lower and upper bounds of the partitioned variables.We propose a heuristic tightening method to further constrict the strengthened bounds derived from the piecewise McCormick technique and recover a nearby feasible solution.Case studies show that,compared with the interior point method and the method implemented in a global bilinear solver,the proposed tightening McCormick method quickly solves the heat–electricity operation problem with an acceptable feasibility check and optimality.
基金Project (No. 50078048) supported by the National Natural Science Foundation of China
文摘In view of the poor water supply system’s network properties, the system’s complicated network hydraulic equations were replaced by macroscopic nodal pressure model and the model of relationship between supply flow and water source head. By using pump-station pressure head and initial tank water levels as decision variables, the model of optimal allocation of water supply between pump-sources was developed. Genetic algorithm was introduced to deal with the model of optimal allocation of water supply. Methods for handling each constraint condition were put forward, and overcome the shortcoming such as premature convergence of genetic algorithm; a solving method was brought forward in which genetic algorithm was combined with simulated annealing technology and self-adaptive crossover and mutation probabilities were adopted. An application example showed the feasibility of this algorithm.
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.
文摘This paper includes an application of Differential Evolution (DE) for the optimal operation of multipurpose reservoir. The objective of the study is to maximize the hydropower production. The constraints for the optimization problem are reservoir capacity, turbine release capacity constraints, irrigation supply demand constraints and storage continuity. For initializing population, the upper and lower bounds of decision variables are fixed. The fitness of each vector is evaluated. The mutation and recombination is performed. The control parameters, i.e., population size, crossover constant and the weight are fixed according to their fitness value. This procedure is performed for the ten different strategies of DE. Sensitivity analysis performed for ten strategies of DE suggested that, De/best/1/bin is the best strategy which gives optimal solution. The DE algorithm application is presented through Jayakwadi project stage-I, Maharashtra State, India. Genetic algorithm is utilized as a comparative approach to assess the ability of DE. The results of GA and ten DE strategies for the given parameters indicated that both the results are comparable. The model is run for dependable inflows. Monthly maximized hydropower production and irrigation releases are presented. These values will be the basis for decision maker to take decisions regarding operation policy of the reservoir. Results of application of DE model indicate that the maximized hydropower production is 30.885 ×106 kwh and the cor-responding irrigation release is 928.44 Mm3.
文摘In the present study, a Linear Programming (LP) model is developed for the conjunctive use of surface water and ground water to obtain the optimal operating policy for a multipurpose single reservoir. The objective of the present study is to maximize the net benefit from the command area under consideration. The constraints imposed on the objective function are maximum and minimum irrigation demands, reservoir storages and canal capacity. The model takes into account the continuity constraint which includes inflows in to the reservoir, releases for irrigation, releases for hydro-power generation, evaporation losses, feeder canal releases, initial and final storages in the reservoir in each time period. The developed model is applied to the case study of Jayakwadi reservoir stage-I, built across river Godavari, Maharashtra, India. Initially the model is solved for the availability of surface water which results in net benefit of 3373.45 million rupees with irrigation intensity is 57.07%. Next the model solved by considering the availability of surface water and available potential of groundwater in the area, which results in net benefits of 3590.02 million rupees with an intensity of irrigation 58.48%. The present model takes in to account the socio-economic requirement of growing the essential crops to meet the requirement of the society. The model has also generated the canal wise optimal releases for irrigation and power, monthly utilization of groundwater, storages in the reservoir at the end of every month and corresponding head over the turbine.
基金Project(50278062) supported by the National Natural Science Foundation of ChinaProject(003611611)supported by the Natural Science Foundation of Tianjin, China
文摘The optimal operation of water distribution networks under local pipe failures, such as water main breaks, was proposed. Based on a hydraulic analysis and a simulation of water distribution networks, a macroscopic model for a network under a local pipe failure was established by the statistical regression. After the operation objectives under a local pipe failure were determined, the optimal operation model was developed and solved by the genetic algorithm. The program was developed and examined by a city distribution network. The optimal operation alternative shows that the electricity cost is saved approximately 11%, the income of the water corporation is increased approximately 5%, and the pressure in the water distribution network is distributed evenly to ensure the network safe operation. Therefore, the proposed method for optimal operation under local pipe failure is feasible and cost-effective.
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.
文摘In semiconductor and electronics factories, large multi-chiller systems are needed to satisfy strict cooling load requirements. In order to save energy, it is worthwhile to design the chilled water system operation. In this paper, an optimal flexible operation scheme is developed based on a two-dimensional time-series model to forecast the cooling load of multi-chiller systems with chiller units of different cooling capacities running in parallel. The optimal integrity scheme can be obtained using the Mixed Integer Nonlinear Programming method, which minimizes the energy consumption of the system within a future time period. In order to better adapt the change of cooling load, the operation strategy of regulating the chilled water flowrates is employed. The chilled water flowrates are set as a design variable. When the chillers are running, their chilled water flowrates can vary within limits, whereas the flowrates are zero when the chillers are unloaded. This forecasting method provides integral optimization within a future time period and offers the operating reference for operators. The power and advantages of the proposed method are presented using an industrial case to help readers delve into this matter.
文摘This paper proposes an improved optimal operation planning method for residential PEFC-CGS (Polymer Electrolyte Fuel CellCo-Generation System). Residential PEFC-CGS has recently been gathering attention as one of the distributed power sources with high efficiency and low environmental impacts. Previous research pointed out that the output variations of PEFC adversely affect the durability. It can be surmised that smaller output variations will be desired to extend durability years. However, in this field, ramping rate have not been sufficiently considered. For local search and tabu search, ramping rate constraint makes our operation planning difficult because it restricts the search for feasible neighborhood solutions. Therefore, the authors proposed a method to deal with typical and harsher ramping rate constraints in comparison with conventional methods. There are two key points for the improvement. One is the reinforcement of the search along the output power axis;the other is to make use of the strategy of tabu search which avoids the local optimal solutions. The simulation results show the effectiveness of the proposed method in the daily operation planning. Furthermore, in the case using typical ramping rate parameter, it is confirmed that tabu search doesn’t contribute the reduction of daily operational cost due to the above stated restriction of the search area.
