In contrast to the overlapping-generations model, it is allowable to discount the future utility in a dynasty model without the ethical difficulty related to intergenerational conflicts. Much precedent research uses R...In contrast to the overlapping-generations model, it is allowable to discount the future utility in a dynasty model without the ethical difficulty related to intergenerational conflicts. Much precedent research uses Ramsey-type optimal growth theory in order to estimate the social discount rate. However, one must note that almost all the formulations neglect the existence of negative intertemporal externalities. This problem is vital when one analyzes the global warming problem mainly caused by the excess concentration of carbon dioxide (CO<sub>2</sub>). This is because an adjoining effect of capital accumulation exists besides the improvement of product capacity, which is reflected in the rate of interest (or equivalently, the marginal productivity of capital). That is, one cannot neglect a negative externality to the future productivity that originates from the excess emissions of CO<sub>2</sub>. Accordingly, following the optimal growth theory, the effective social discount rate should be heightened by a proportional carbon tax to suppress future excess consumption/ emissions than in the case of the existing analyses, which exclude such an intertemporal external diseconomy.展开更多
In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for n...In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.展开更多
文摘In contrast to the overlapping-generations model, it is allowable to discount the future utility in a dynasty model without the ethical difficulty related to intergenerational conflicts. Much precedent research uses Ramsey-type optimal growth theory in order to estimate the social discount rate. However, one must note that almost all the formulations neglect the existence of negative intertemporal externalities. This problem is vital when one analyzes the global warming problem mainly caused by the excess concentration of carbon dioxide (CO<sub>2</sub>). This is because an adjoining effect of capital accumulation exists besides the improvement of product capacity, which is reflected in the rate of interest (or equivalently, the marginal productivity of capital). That is, one cannot neglect a negative externality to the future productivity that originates from the excess emissions of CO<sub>2</sub>. Accordingly, following the optimal growth theory, the effective social discount rate should be heightened by a proportional carbon tax to suppress future excess consumption/ emissions than in the case of the existing analyses, which exclude such an intertemporal external diseconomy.
基金supported by the Deanship of Postgraduate Studies and Scientific Research at Majmaah University in Saudi Arabia under Project Number(ICR-2024-1002).
文摘In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.