This research proposes a more advanced way to address Combined Economic Emission Dispatch(CEED)concerns.Economic Load Dispatch(ELD)and Economic Emission Dispatch(EED)have been implemented to reduce generating unit fue...This research proposes a more advanced way to address Combined Economic Emission Dispatch(CEED)concerns.Economic Load Dispatch(ELD)and Economic Emission Dispatch(EED)have been implemented to reduce generating unit fuel costs and emissions.When both economics and emission tar-gets are taken into account,the dispatch of an aggregate cost-effective emission challenge emerges.This research affords a mathematical modeling-based analyti-cal technique for solving economic,emission,and collaborative economic and emission dispatch problems with only one goal.This study takes into account both the fuel cost target and the environmental impact of emissions.This bi-inten-tion CEED problem is converted to a solitary goal function using a price penalty factor technique.In this case,a metaheuristic and an environment-inspired,intel-ligent Spider Monkey Optimization technique(SMO)are used to address the CEED dilemma.By following the generator’s scheduling process,the SMO meth-od is used to regulate the output from the power generation system in terms of pollution and fuel cost.The Fission-Fusion social(FFS)structure of spider mon-keys promotes them to utilize a global optimization method known as SMO dur-ing foraging behaviour.The emphasis is mostly on lowering the cost of generation and pollution in order to improve the efficiency of the power system and han-dle dispatch problems with constraints.The economic dispatch has been reme-died,and the improved result demonstrates that the system’s performance is stable andflexible in real time.Finally,the system’s output demonstrates that the system has improved in resolving CEED difficulties.When compared to ear-lier investigations,the proposed model’sfindings have improved.As the gener-ating units,wind and solar are used to explore the CEED crisis in the IEEE 30 bus system.展开更多
Controlling voltage and active or reactive losses are one of the most important issues in each power grid.In this paper,the influence of wind farm and thyristors switched capacitors on the network are considered.TSSC ...Controlling voltage and active or reactive losses are one of the most important issues in each power grid.In this paper,the influence of wind farm and thyristors switched capacitors on the network are considered.TSSC and Wind turbines are one of the significant components of each network.These instruments are also one of the resources of producing active and reactive power.In this study,wind farm and TSSC are already located optimally by Genetic algorithm.This network studied when a fault considered in one of buses.So that,in first step none of wind farm and TSSC are in the power grid.In the second step,both wind farm and TSSC are connected while a short circuit accrues in one of the busses or lines of the network.At the end,it will be observed that using thyristor switched capacitors and wind farm influence the network.So that,the capacity of producing the reactive and active power will be increased and totally the loss of the system will be decreased.Furthermore,the voltage profile will be in a suitable range.展开更多
Dynamic Reactive Power Optimization(DRPO) is a large-scale, multi-period, and strongly coupled nonlinear mixed-integer programming problem that is difficult to solve directly. First, to handle discrete variables and s...Dynamic Reactive Power Optimization(DRPO) is a large-scale, multi-period, and strongly coupled nonlinear mixed-integer programming problem that is difficult to solve directly. First, to handle discrete variables and switching operation constraints, DRPO is formulated as a nonlinear constrained two-objective optimization problem in this paper. The first objective is to minimize the real power loss and the Total Voltage Deviations(TVDs), and the second objective is to minimize incremental system loss. Then a Filter Collaborative State Transition Algorithm(FCSTA) is presented for solving DRPO problems. Two populations corresponding to two different objectives are employed. Moreover, the filter technique is utilized to deal with constraints. Finally, the effectiveness of the proposed method is demonstrated through the results obtained for a 24-hour test on Ward & Hale 6 bus, IEEE 14 bus, and IEEE 30 bus test power systems. To substantiate the effectiveness of the proposed algorithms, the obtained results are compared with different approaches in the literature.展开更多
文摘This research proposes a more advanced way to address Combined Economic Emission Dispatch(CEED)concerns.Economic Load Dispatch(ELD)and Economic Emission Dispatch(EED)have been implemented to reduce generating unit fuel costs and emissions.When both economics and emission tar-gets are taken into account,the dispatch of an aggregate cost-effective emission challenge emerges.This research affords a mathematical modeling-based analyti-cal technique for solving economic,emission,and collaborative economic and emission dispatch problems with only one goal.This study takes into account both the fuel cost target and the environmental impact of emissions.This bi-inten-tion CEED problem is converted to a solitary goal function using a price penalty factor technique.In this case,a metaheuristic and an environment-inspired,intel-ligent Spider Monkey Optimization technique(SMO)are used to address the CEED dilemma.By following the generator’s scheduling process,the SMO meth-od is used to regulate the output from the power generation system in terms of pollution and fuel cost.The Fission-Fusion social(FFS)structure of spider mon-keys promotes them to utilize a global optimization method known as SMO dur-ing foraging behaviour.The emphasis is mostly on lowering the cost of generation and pollution in order to improve the efficiency of the power system and han-dle dispatch problems with constraints.The economic dispatch has been reme-died,and the improved result demonstrates that the system’s performance is stable andflexible in real time.Finally,the system’s output demonstrates that the system has improved in resolving CEED difficulties.When compared to ear-lier investigations,the proposed model’sfindings have improved.As the gener-ating units,wind and solar are used to explore the CEED crisis in the IEEE 30 bus system.
文摘Controlling voltage and active or reactive losses are one of the most important issues in each power grid.In this paper,the influence of wind farm and thyristors switched capacitors on the network are considered.TSSC and Wind turbines are one of the significant components of each network.These instruments are also one of the resources of producing active and reactive power.In this study,wind farm and TSSC are already located optimally by Genetic algorithm.This network studied when a fault considered in one of buses.So that,in first step none of wind farm and TSSC are in the power grid.In the second step,both wind farm and TSSC are connected while a short circuit accrues in one of the busses or lines of the network.At the end,it will be observed that using thyristor switched capacitors and wind farm influence the network.So that,the capacity of producing the reactive and active power will be increased and totally the loss of the system will be decreased.Furthermore,the voltage profile will be in a suitable range.
基金supported by the National Natural Science Foundation of China(Nos.51767022 and 51575469)
文摘Dynamic Reactive Power Optimization(DRPO) is a large-scale, multi-period, and strongly coupled nonlinear mixed-integer programming problem that is difficult to solve directly. First, to handle discrete variables and switching operation constraints, DRPO is formulated as a nonlinear constrained two-objective optimization problem in this paper. The first objective is to minimize the real power loss and the Total Voltage Deviations(TVDs), and the second objective is to minimize incremental system loss. Then a Filter Collaborative State Transition Algorithm(FCSTA) is presented for solving DRPO problems. Two populations corresponding to two different objectives are employed. Moreover, the filter technique is utilized to deal with constraints. Finally, the effectiveness of the proposed method is demonstrated through the results obtained for a 24-hour test on Ward & Hale 6 bus, IEEE 14 bus, and IEEE 30 bus test power systems. To substantiate the effectiveness of the proposed algorithms, the obtained results are compared with different approaches in the literature.
