Dynamic Economic Emission Dispatch(DEED)aims to optimize control over fuel cost and pollution emission,two conflicting objectives,by scheduling the output power of various units at specific times.Although many methods...Dynamic Economic Emission Dispatch(DEED)aims to optimize control over fuel cost and pollution emission,two conflicting objectives,by scheduling the output power of various units at specific times.Although many methods well-performed on the DEED problem,most of them fail to achieve expected results in practice due to a lack of effective trade-off mechanisms between the convergence and diversity of non-dominated optimal dispatching solutions.To address this issue,a new multi-objective solver called Multi-Objective Golden Jackal Optimization(MOGJO)algorithm is proposed to cope with the DEED problem.The proposed algorithm first stores non-dominated optimal solutions found so far into an archive.Then,it chooses the best dispatching solution from the archive as the leader through a selection mechanism designed based on elite selection strategy and Euclidean distance index method.This mechanism can guide the algorithm to search for better dispatching solutions in the direction of reducing fuel costs and pollutant emissions.Moreover,the basic golden jackal optimization algorithm has the drawback of insufficient search,which hinders its ability to effectively discover more Pareto solutions.To this end,a non-linear control parameter based on the cosine function is introduced to enhance global exploration of the dispatching space,thus improving the efficiency of finding the optimal dispatching solutions.The proposed MOGJO is evaluated on the latest CEC benchmark test functions,and its superiority over the state-of-the-art multi-objective optimizers is highlighted by performance indicators.Also,empirical results on 5-unit,10-unit,IEEE 30-bus,and 30-unit systems show that the MOGJO can provide competitive compromise scheduling solutions compared to published DEED methods.Finally,in the analysis of the Pareto dominance relationship and the Euclidean distance index,the optimal dispatching solutions provided by MOGJO are the closest to the ideal solutions for minimizing fuel costs and pollution emissions simultaneously,compared to the latest published DEED solutions.展开更多
To get the movement mode and driving mechanism similar to human shoulder joint,a six degrees of freedom(DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators(PMAs)was designed.Howev...To get the movement mode and driving mechanism similar to human shoulder joint,a six degrees of freedom(DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators(PMAs)was designed.However,the structural parameters of the shoulder joint will affect various performances of the mechanism.To obtain the optimal structure parameters,the particle swarm optimization(PSO) was used.Besides,the mathematical expressions of indexes of rotation ranges,maximum bearing torque,discrete dexterity and muscle shrinkage of the bionic shoulder joint were established respectively to represent its many-sided characteristics.And the multi-objective optimization problem was transformed into a single-objective optimization problem by using the weighted-sum method.The normalization method and adaptive-weight method were used to determine each optimization index's weight coefficient;then the particle swarm optimization was used to optimize the integrated objective function of the bionic shoulder joint and the optimal solution was obtained.Compared with the average optimization generations and the optimal target values of many experiments,using adaptive-weight method to adjust weights of integrated objective function is better than using normalization method,which validates superiority of the adaptive-weight method.展开更多
The nonlinear dynamic modeling by combining the equivalent linear mechanics with the multi-objective optimization algorithm is proposed to describe the nonlinear behaviors of the joint interfaces.The joint interfaces ...The nonlinear dynamic modeling by combining the equivalent linear mechanics with the multi-objective optimization algorithm is proposed to describe the nonlinear behaviors of the joint interfaces.The joint interfaces are simplified as the equivalent virtual material or linear spring damper element.The genetic algorithm for multi-objective optimization is then used to identify the mechanical properties of the equivalent joint by minimizing the error between the simulated dynamic characteristics and the experimental results,including the modal frequencies of the bolted joint beam and the frequency response functions(FRFs)of the rubber isolation system.The FRFs are divided into several subsections with frequency-varied dynamic properties of the joint to consider the nonlinear dynamic behaviors,and the effects of subsection number and excitation amplitudes on the FRFs are also investigated.The results show that the simulated dynamic characteristics of modal frequencies and FRFs agree well with the experimental results.With the increase in the subsection number,the simulated FRFs agree better with the experimental results,indicating a good performance of modeling the nonlinear dynamic behaviors of the joint interfaces forced by different excitation amplitudes.Larger excitation amplitudes will decrease the joint stiffness.展开更多
With the rapid and large-scale development of renewable energy, the lack of new energy power transportation or consumption, and the shortage of grid peak-shifting ability have become increasingly serious. Aiming to th...With the rapid and large-scale development of renewable energy, the lack of new energy power transportation or consumption, and the shortage of grid peak-shifting ability have become increasingly serious. Aiming to the severe wind power curtailment issue, the characteristics of interactive load are studied upon the traditional day-ahead dispatch model to mitigate the influence of wind power fluctuation. A multi-objective optimal dispatch model with the minimum operating cost and power losses is built. Optimal power flow distribution is available when both generation and demand side participate in the resource allocation. The quantum particle swarm optimization (QPSO) algorithm is applied to convert multi-objective optimization problem into single objective optimization problem. The simulation results of IEEE 30-bus system verify that the proposed method can effectively reduce the operating cost and grid loss simultaneously enhancing the consumption of wind power.展开更多
A reference point based multi-objective optimization using a combination between trust region (TR) algorithm and particle swarm optimization (PSO) to solve the multi-objective environmental/economic dispatch (EED) pro...A reference point based multi-objective optimization using a combination between trust region (TR) algorithm and particle swarm optimization (PSO) to solve the multi-objective environmental/economic dispatch (EED) problem is presented in this paper. The EED problem is handled by Reference Point Interactive Approach. One of the main advantages of the proposed approach is integrating the merits of both TR and PSO, where TR has provided the initial set (close to the Pareto set as possible and the reference point of the decision maker) followed by PSO to improve the quality of the solutions and get all the points on the Pareto frontier. The performance of the proposed algorithm is tested on standard IEEE 30-bus 6-genrator test system and is compared with conventional methods. The results demonstrate the capabilities of the proposed approach to generate true and well-distributed Pareto-optimal non-dominated solutions in one single run. The comparison with the classical methods demonstrates the superiority of the proposed approach and confirms its potential to solve the multi-objective EED problem.展开更多
Confronted with the requirement of higher efficiency and higher quality of distribution network fault rush-repair, the subject addressed in this paper is the optimal resource dispatching issue of the distribution netw...Confronted with the requirement of higher efficiency and higher quality of distribution network fault rush-repair, the subject addressed in this paper is the optimal resource dispatching issue of the distribution network rush-repair when single resource center cannot meet the emergent resource demands. A multi-resource and multi-center dispatching model is established with the objective of “the shortest repair start-time” and “the least number of the repair centers”. The optimal and worst solutions of each objective are both obtained, and a “proximity degree method” is used to calculate the optimal resource dispatching plan. The feasibility of the proposed algorithm is illustrated by an example of a distribution network fault. The proposed method provides a practical technique for efficiency improvement of fault rush-repair work of distribution network, and thus mostly abbreviates power recovery time and improves the management level of the distribution network.展开更多
Automation advancements prompts the extensive integration of collaborative robot(cobot)across a range of industries.Compared to the commonly used design approach of increasing the payload-to-weight ratio of cobot to e...Automation advancements prompts the extensive integration of collaborative robot(cobot)across a range of industries.Compared to the commonly used design approach of increasing the payload-to-weight ratio of cobot to enhance load capacity,equal attention should be paid to the dynamic response characteristics of cobot during the design process to make the cobot more flexible.In this paper,a new method for designing the drive train parameters of cobot is proposed.Firstly,based on the analysis of factors influencing the load capacity and dynamic response characteristics,design criteria for both aspects are established for cobot with all optimization design criteria normalized within the design domain.Secondly,with the cobot in the horizontal pose,the motor design scheme is discretized and it takes the joint motor diameter and gearbox speed ratio as optimization design variables.Finally,all the discrete values of the optimization objectives are obtained through the enumeration method and the Pareto front is used to select the optimal solution through multi-objective optimization.Base on the cobot design method proposed in this paper,a six-axis cobot is designed and compared with the commercial cobot.The result shows that the load capacity of the designed cobot in this paper reaches 8.4 kg,surpassing the 5 kg load capacity commercial cobot which is used as a benchmark.The minimum resonance frequency of the joints is 42.70 Hz.展开更多
The issues of uncertainty and frequency security become significantly serious in power systems with the high penetration of volatile inverter-based renewables(IBRs),which makes it necessary to consider the uncertainty...The issues of uncertainty and frequency security become significantly serious in power systems with the high penetration of volatile inverter-based renewables(IBRs),which makes it necessary to consider the uncertainty and frequency-related constraints in the economic dispatch(ED)programs.However,existing ED studies rarely proactively optimize the control parameters of inverter-based resources related to fast regulation(e.g.,virtual inertia and droop coefficients)in cooperation with other dispatchable resources to improve the system frequency security and dispatch reliability.This paper proposes a joint chance-constrained economic dispatch model that jointly optimizes the frequency-related inverter control,the system up/down reserves,and base-point power for the minimal total operational cost.In the proposed model,multiple dispatchable resources,including thermal units,dispatchable IBRs,and energy storage,are considered,and the(virtual)inertias,the regulation reserve allocations,and base-point power are coordinated.To ensure the system reliability,the joint chance-constraint formulation is also adopted.Additionally,since the traditional sample average approximation(SAA)method imposes a huge computational burden,a novel mix-SAA(MSAA)method is proposed to transform the original intractable model into a linear model that can be efficiently solved via commercial solvers.The case studies validate the satisfactory efficacy of the proposed ED model and demonstrate that the MSAA can save nearly 90%calculation time compared with the traditional SAA.展开更多
高比例新能源的接入对电力系统既是机遇也是挑战:新能源具有清洁低碳的环保优势,但其出力不确定性大、物理惯量低的特点也对系统的频率安全运行带来挑战。针对上述问题,提出一种考虑碳-绿证市场耦合的新能源与储能虚拟惯量-阻尼调度方...高比例新能源的接入对电力系统既是机遇也是挑战:新能源具有清洁低碳的环保优势,但其出力不确定性大、物理惯量低的特点也对系统的频率安全运行带来挑战。针对上述问题,提出一种考虑碳-绿证市场耦合的新能源与储能虚拟惯量-阻尼调度方法。首先,构建包含电力决策、碳交易市场和绿证交易市场三者耦合关系,并计及系统动态频率安全约束的虚拟惯量-阻尼调度优化模型;其次,为降低决策保守性,将不确定性约束建模为整体的联合机会约束形式;然后,采用改进的样本平均近似(modified sample average approximation, MSAA)方法对所提模型进行求解,有效规避常规样本平均近似(sample average approximation, SAA)方法中0-1指示变量导致的计算负担。在IEEE-39节点系统的仿真结果表明:与现有模型和机会约束建模方法相比,所提方法能够根据系统时变扰动需求自适应调整虚拟惯量和下垂阻尼,在满足风险概率5%的前提下,以比固定系数方法低6.03%的成本,确保系统频率偏差在0.5 Hz以内。展现出更好的经济性、低碳性和频率安全性;同时,改进的MSAA方法较传统SAA方法计算时间减少了约90%,可显著提升计算效率。展开更多
基金supported by the National Natural Science Foundation of China under Grant No.61802328,61972333,and 61771415.
文摘Dynamic Economic Emission Dispatch(DEED)aims to optimize control over fuel cost and pollution emission,two conflicting objectives,by scheduling the output power of various units at specific times.Although many methods well-performed on the DEED problem,most of them fail to achieve expected results in practice due to a lack of effective trade-off mechanisms between the convergence and diversity of non-dominated optimal dispatching solutions.To address this issue,a new multi-objective solver called Multi-Objective Golden Jackal Optimization(MOGJO)algorithm is proposed to cope with the DEED problem.The proposed algorithm first stores non-dominated optimal solutions found so far into an archive.Then,it chooses the best dispatching solution from the archive as the leader through a selection mechanism designed based on elite selection strategy and Euclidean distance index method.This mechanism can guide the algorithm to search for better dispatching solutions in the direction of reducing fuel costs and pollutant emissions.Moreover,the basic golden jackal optimization algorithm has the drawback of insufficient search,which hinders its ability to effectively discover more Pareto solutions.To this end,a non-linear control parameter based on the cosine function is introduced to enhance global exploration of the dispatching space,thus improving the efficiency of finding the optimal dispatching solutions.The proposed MOGJO is evaluated on the latest CEC benchmark test functions,and its superiority over the state-of-the-art multi-objective optimizers is highlighted by performance indicators.Also,empirical results on 5-unit,10-unit,IEEE 30-bus,and 30-unit systems show that the MOGJO can provide competitive compromise scheduling solutions compared to published DEED methods.Finally,in the analysis of the Pareto dominance relationship and the Euclidean distance index,the optimal dispatching solutions provided by MOGJO are the closest to the ideal solutions for minimizing fuel costs and pollution emissions simultaneously,compared to the latest published DEED solutions.
基金the National Natural Science Foundation of China(NO.51405229)the Natural Science Foundation of Jiangsu Province of China(Nos.BK20151470 and BK20130796)
文摘To get the movement mode and driving mechanism similar to human shoulder joint,a six degrees of freedom(DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators(PMAs)was designed.However,the structural parameters of the shoulder joint will affect various performances of the mechanism.To obtain the optimal structure parameters,the particle swarm optimization(PSO) was used.Besides,the mathematical expressions of indexes of rotation ranges,maximum bearing torque,discrete dexterity and muscle shrinkage of the bionic shoulder joint were established respectively to represent its many-sided characteristics.And the multi-objective optimization problem was transformed into a single-objective optimization problem by using the weighted-sum method.The normalization method and adaptive-weight method were used to determine each optimization index's weight coefficient;then the particle swarm optimization was used to optimize the integrated objective function of the bionic shoulder joint and the optimal solution was obtained.Compared with the average optimization generations and the optimal target values of many experiments,using adaptive-weight method to adjust weights of integrated objective function is better than using normalization method,which validates superiority of the adaptive-weight method.
基金The work was supported by the Science Challenge Project(Grant No.TZ2018007)The authors also thank the National Natural Science Foundation of China(Grant Nos.11872059,11702279)National Defense Technology Foundation of China(Grant No.JSUS2018212C)for providing the financial support for this project.
文摘The nonlinear dynamic modeling by combining the equivalent linear mechanics with the multi-objective optimization algorithm is proposed to describe the nonlinear behaviors of the joint interfaces.The joint interfaces are simplified as the equivalent virtual material or linear spring damper element.The genetic algorithm for multi-objective optimization is then used to identify the mechanical properties of the equivalent joint by minimizing the error between the simulated dynamic characteristics and the experimental results,including the modal frequencies of the bolted joint beam and the frequency response functions(FRFs)of the rubber isolation system.The FRFs are divided into several subsections with frequency-varied dynamic properties of the joint to consider the nonlinear dynamic behaviors,and the effects of subsection number and excitation amplitudes on the FRFs are also investigated.The results show that the simulated dynamic characteristics of modal frequencies and FRFs agree well with the experimental results.With the increase in the subsection number,the simulated FRFs agree better with the experimental results,indicating a good performance of modeling the nonlinear dynamic behaviors of the joint interfaces forced by different excitation amplitudes.Larger excitation amplitudes will decrease the joint stiffness.
文摘With the rapid and large-scale development of renewable energy, the lack of new energy power transportation or consumption, and the shortage of grid peak-shifting ability have become increasingly serious. Aiming to the severe wind power curtailment issue, the characteristics of interactive load are studied upon the traditional day-ahead dispatch model to mitigate the influence of wind power fluctuation. A multi-objective optimal dispatch model with the minimum operating cost and power losses is built. Optimal power flow distribution is available when both generation and demand side participate in the resource allocation. The quantum particle swarm optimization (QPSO) algorithm is applied to convert multi-objective optimization problem into single objective optimization problem. The simulation results of IEEE 30-bus system verify that the proposed method can effectively reduce the operating cost and grid loss simultaneously enhancing the consumption of wind power.
文摘A reference point based multi-objective optimization using a combination between trust region (TR) algorithm and particle swarm optimization (PSO) to solve the multi-objective environmental/economic dispatch (EED) problem is presented in this paper. The EED problem is handled by Reference Point Interactive Approach. One of the main advantages of the proposed approach is integrating the merits of both TR and PSO, where TR has provided the initial set (close to the Pareto set as possible and the reference point of the decision maker) followed by PSO to improve the quality of the solutions and get all the points on the Pareto frontier. The performance of the proposed algorithm is tested on standard IEEE 30-bus 6-genrator test system and is compared with conventional methods. The results demonstrate the capabilities of the proposed approach to generate true and well-distributed Pareto-optimal non-dominated solutions in one single run. The comparison with the classical methods demonstrates the superiority of the proposed approach and confirms its potential to solve the multi-objective EED problem.
文摘Confronted with the requirement of higher efficiency and higher quality of distribution network fault rush-repair, the subject addressed in this paper is the optimal resource dispatching issue of the distribution network rush-repair when single resource center cannot meet the emergent resource demands. A multi-resource and multi-center dispatching model is established with the objective of “the shortest repair start-time” and “the least number of the repair centers”. The optimal and worst solutions of each objective are both obtained, and a “proximity degree method” is used to calculate the optimal resource dispatching plan. The feasibility of the proposed algorithm is illustrated by an example of a distribution network fault. The proposed method provides a practical technique for efficiency improvement of fault rush-repair work of distribution network, and thus mostly abbreviates power recovery time and improves the management level of the distribution network.
基金Supported by National Key Research and Development Program of China (Grant Nos.2022YFB4703000,2019YFB1309900)。
文摘Automation advancements prompts the extensive integration of collaborative robot(cobot)across a range of industries.Compared to the commonly used design approach of increasing the payload-to-weight ratio of cobot to enhance load capacity,equal attention should be paid to the dynamic response characteristics of cobot during the design process to make the cobot more flexible.In this paper,a new method for designing the drive train parameters of cobot is proposed.Firstly,based on the analysis of factors influencing the load capacity and dynamic response characteristics,design criteria for both aspects are established for cobot with all optimization design criteria normalized within the design domain.Secondly,with the cobot in the horizontal pose,the motor design scheme is discretized and it takes the joint motor diameter and gearbox speed ratio as optimization design variables.Finally,all the discrete values of the optimization objectives are obtained through the enumeration method and the Pareto front is used to select the optimal solution through multi-objective optimization.Base on the cobot design method proposed in this paper,a six-axis cobot is designed and compared with the commercial cobot.The result shows that the load capacity of the designed cobot in this paper reaches 8.4 kg,surpassing the 5 kg load capacity commercial cobot which is used as a benchmark.The minimum resonance frequency of the joints is 42.70 Hz.
基金supported by the National Natural Science Foundation of China under Grant 52377107.
文摘The issues of uncertainty and frequency security become significantly serious in power systems with the high penetration of volatile inverter-based renewables(IBRs),which makes it necessary to consider the uncertainty and frequency-related constraints in the economic dispatch(ED)programs.However,existing ED studies rarely proactively optimize the control parameters of inverter-based resources related to fast regulation(e.g.,virtual inertia and droop coefficients)in cooperation with other dispatchable resources to improve the system frequency security and dispatch reliability.This paper proposes a joint chance-constrained economic dispatch model that jointly optimizes the frequency-related inverter control,the system up/down reserves,and base-point power for the minimal total operational cost.In the proposed model,multiple dispatchable resources,including thermal units,dispatchable IBRs,and energy storage,are considered,and the(virtual)inertias,the regulation reserve allocations,and base-point power are coordinated.To ensure the system reliability,the joint chance-constraint formulation is also adopted.Additionally,since the traditional sample average approximation(SAA)method imposes a huge computational burden,a novel mix-SAA(MSAA)method is proposed to transform the original intractable model into a linear model that can be efficiently solved via commercial solvers.The case studies validate the satisfactory efficacy of the proposed ED model and demonstrate that the MSAA can save nearly 90%calculation time compared with the traditional SAA.
文摘高比例新能源的接入对电力系统既是机遇也是挑战:新能源具有清洁低碳的环保优势,但其出力不确定性大、物理惯量低的特点也对系统的频率安全运行带来挑战。针对上述问题,提出一种考虑碳-绿证市场耦合的新能源与储能虚拟惯量-阻尼调度方法。首先,构建包含电力决策、碳交易市场和绿证交易市场三者耦合关系,并计及系统动态频率安全约束的虚拟惯量-阻尼调度优化模型;其次,为降低决策保守性,将不确定性约束建模为整体的联合机会约束形式;然后,采用改进的样本平均近似(modified sample average approximation, MSAA)方法对所提模型进行求解,有效规避常规样本平均近似(sample average approximation, SAA)方法中0-1指示变量导致的计算负担。在IEEE-39节点系统的仿真结果表明:与现有模型和机会约束建模方法相比,所提方法能够根据系统时变扰动需求自适应调整虚拟惯量和下垂阻尼,在满足风险概率5%的前提下,以比固定系数方法低6.03%的成本,确保系统频率偏差在0.5 Hz以内。展现出更好的经济性、低碳性和频率安全性;同时,改进的MSAA方法较传统SAA方法计算时间减少了约90%,可显著提升计算效率。
