In a previous study [1] the authors had developed a methodology for predicting global oil production. Briefly, the model accounted for disruptions in production by utilising a series of Hubbert curves in combination w...In a previous study [1] the authors had developed a methodology for predicting global oil production. Briefly, the model accounted for disruptions in production by utilising a series of Hubbert curves in combination with a polynomial smoothing function. Whilst the model was able to produce predictions for future oil production, the methodology was complex in its implementation and not easily applied to future disruptions. In this study a Generalized Bass model approach is incorporated with the Hubbert linearization technique that overcomes these limitations and is consistent with our previous predictions.展开更多
With the large-scale promotion of distributed photovoltaics,new challenges have emerged in the photovoltaic consumptionwithin distribution networks.Traditional photovoltaic consumption schemes have primarily focused o...With the large-scale promotion of distributed photovoltaics,new challenges have emerged in the photovoltaic consumptionwithin distribution networks.Traditional photovoltaic consumption schemes have primarily focused on static analysis.However,as the scale of photovoltaic power generation devices grows and the methods of integration diversify,a single consumption scheme is no longer sufficient to meet the actual needs of current distribution networks.Therefore,this paper proposes an optimal evaluation method for photovoltaic consumption schemes based on BASS model predictions of installed capacity,aiming to provide an effective tool for generating and evaluating photovoltaic consumption schemes in distribution networks.First,the BASS diffusion model,combined with existing photovoltaic capacity data and roof area information,is used to predict the trends in photovoltaic installed capacity for each substation area,providing a scientific basis for consumption evaluation.Secondly,an improved random scenario simulation method is proposed for assessing the photovoltaic consumption capacity in distribution networks.This method generates photovoltaic integration schemes based on the diffusion probabilities of different regions and evaluates the consumption capacity of each scheme.Finally,the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)is used to comprehensively evaluate the generated schemes,ensuring that the selected scheme not only meets the consumption requirements but also offers high economic benefits and reliability.The effectiveness and feasibility of the proposedmethod are validated through simulations of the IEEE 33-node system,providing strong support for optimizing photovoltaic consumption schemes in distribution networks.展开更多
文摘In a previous study [1] the authors had developed a methodology for predicting global oil production. Briefly, the model accounted for disruptions in production by utilising a series of Hubbert curves in combination with a polynomial smoothing function. Whilst the model was able to produce predictions for future oil production, the methodology was complex in its implementation and not easily applied to future disruptions. In this study a Generalized Bass model approach is incorporated with the Hubbert linearization technique that overcomes these limitations and is consistent with our previous predictions.
基金supported in part by theThe Planning Subject Project of Guangdong Power Grid Co.,Ltd.(62273104).
文摘With the large-scale promotion of distributed photovoltaics,new challenges have emerged in the photovoltaic consumptionwithin distribution networks.Traditional photovoltaic consumption schemes have primarily focused on static analysis.However,as the scale of photovoltaic power generation devices grows and the methods of integration diversify,a single consumption scheme is no longer sufficient to meet the actual needs of current distribution networks.Therefore,this paper proposes an optimal evaluation method for photovoltaic consumption schemes based on BASS model predictions of installed capacity,aiming to provide an effective tool for generating and evaluating photovoltaic consumption schemes in distribution networks.First,the BASS diffusion model,combined with existing photovoltaic capacity data and roof area information,is used to predict the trends in photovoltaic installed capacity for each substation area,providing a scientific basis for consumption evaluation.Secondly,an improved random scenario simulation method is proposed for assessing the photovoltaic consumption capacity in distribution networks.This method generates photovoltaic integration schemes based on the diffusion probabilities of different regions and evaluates the consumption capacity of each scheme.Finally,the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)is used to comprehensively evaluate the generated schemes,ensuring that the selected scheme not only meets the consumption requirements but also offers high economic benefits and reliability.The effectiveness and feasibility of the proposedmethod are validated through simulations of the IEEE 33-node system,providing strong support for optimizing photovoltaic consumption schemes in distribution networks.
