The selection of power transformer is very important to power sector. Most methods are utilized according to the initial cost and don’t consider the synthetical evaluation of economy and technology. Based on previous...The selection of power transformer is very important to power sector. Most methods are utilized according to the initial cost and don’t consider the synthetical evaluation of economy and technology. Based on previous research, this paper addresses a new practical probabilistic life cycle cost model. Then, in order to demonstrate the practicability of probabilistic life cycle cost for the power transformer, illustrative investment alternatives of actual power transformers are discussed. From the result of the numerical investigation, it may be positively stated that the optimum investment alternative for the power transformer based on the probabilistic life cycle cost model proposed in this study will lead to a more rational, economical and effective procedure compared with the conventional method only considering the initial cost.展开更多
The purpose of the Combined Economic Emission Dispatch(CEED)of electric power is to offer the most exceptional schedule for production units,which must run with both low fuel costs and emission levels concurrently,the...The purpose of the Combined Economic Emission Dispatch(CEED)of electric power is to offer the most exceptional schedule for production units,which must run with both low fuel costs and emission levels concurrently,thereby meeting the lack of system equality and inequality constraints.Economic and emissions dispatching has become a primary and significant concern in power system networks.Consequences of using non-renewable fuels as input to exhaust power systems with toxic gas emissions and depleted resources for future generations.The optimal power allocation to generators serves as a solution to this problem.Emission dispatch reduces emissions while ignoring economic considerations.A collective strategy known as Combined Economic and Emission Dispatch is utilized to resolve the above-mentioned problems and investigate the trade-off relationship between fuel cost and emissions.Consequently,this work manages the Substantial Augmented Transformative Algorithm(SATA)to take care of the Combined Economic Emission Dispatch Problem(CEEDP)of warm units while fulfilling imperatives,for example,confines on generator limit,diminish the fuel cost,lessen the emission and decrease the force misfortune.SATA is a stochastic streamlining process that relies upon the development and knowledge of swarms.The goal is to minimize the total fuel cost of fossil-based thermal power generation units that generate and cause environmental pollution.The algorithm searches for solutions in the search space from the smallest to the largest in the case of forwarding search.The simulation of the proposed system is developed using MATLAB Simulink software.Simulation results show the effectiveness and practicability of this method in terms of economic and emission dispatching issues.The performance of the proposed system is compared with existing Artificial Bee Colony-Particle Swarm Optimization(ABC-PSO),Simulated Annealing(SA),and Differential Evolution(DE)methods.The fuel cost and gas emission of the proposed system are 128904$/hr and 138094.4652$/hr.展开更多
文摘The selection of power transformer is very important to power sector. Most methods are utilized according to the initial cost and don’t consider the synthetical evaluation of economy and technology. Based on previous research, this paper addresses a new practical probabilistic life cycle cost model. Then, in order to demonstrate the practicability of probabilistic life cycle cost for the power transformer, illustrative investment alternatives of actual power transformers are discussed. From the result of the numerical investigation, it may be positively stated that the optimum investment alternative for the power transformer based on the probabilistic life cycle cost model proposed in this study will lead to a more rational, economical and effective procedure compared with the conventional method only considering the initial cost.
文摘The purpose of the Combined Economic Emission Dispatch(CEED)of electric power is to offer the most exceptional schedule for production units,which must run with both low fuel costs and emission levels concurrently,thereby meeting the lack of system equality and inequality constraints.Economic and emissions dispatching has become a primary and significant concern in power system networks.Consequences of using non-renewable fuels as input to exhaust power systems with toxic gas emissions and depleted resources for future generations.The optimal power allocation to generators serves as a solution to this problem.Emission dispatch reduces emissions while ignoring economic considerations.A collective strategy known as Combined Economic and Emission Dispatch is utilized to resolve the above-mentioned problems and investigate the trade-off relationship between fuel cost and emissions.Consequently,this work manages the Substantial Augmented Transformative Algorithm(SATA)to take care of the Combined Economic Emission Dispatch Problem(CEEDP)of warm units while fulfilling imperatives,for example,confines on generator limit,diminish the fuel cost,lessen the emission and decrease the force misfortune.SATA is a stochastic streamlining process that relies upon the development and knowledge of swarms.The goal is to minimize the total fuel cost of fossil-based thermal power generation units that generate and cause environmental pollution.The algorithm searches for solutions in the search space from the smallest to the largest in the case of forwarding search.The simulation of the proposed system is developed using MATLAB Simulink software.Simulation results show the effectiveness and practicability of this method in terms of economic and emission dispatching issues.The performance of the proposed system is compared with existing Artificial Bee Colony-Particle Swarm Optimization(ABC-PSO),Simulated Annealing(SA),and Differential Evolution(DE)methods.The fuel cost and gas emission of the proposed system are 128904$/hr and 138094.4652$/hr.
