Probabilistic forecasting is becoming increasingly important for a wide range of applications,especially for en-ergy systems such as forecasting wind power production.A need for proper evaluation of probabilistic fore...Probabilistic forecasting is becoming increasingly important for a wide range of applications,especially for en-ergy systems such as forecasting wind power production.A need for proper evaluation of probabilistic forecasts follows naturally with this,because evaluation is the key to improving the forecasts.Although plenty of excellent reviews and research papers on probabilistic forecast evaluation already exist,we find that there is a need for an introduction with some practical application.In particular,many forecast scenarios in energy systems are inher-ently multivariate,and while univariate evaluation methods are well understood and documented,only limited and scattered work has been done on their multivariate counterparts.This paper therefore contains a review of a selected set of probabilistic forecast evaluation methods,primarily scoring rules,as well as practical sections that explain how these methods can be calculated and estimated.In three case studies featuring simple autore-gressive models,stochastic differential equations and real wind power data,we implement,apply and discuss the logarithmic score,the continuous ranked probability score and the variogram score for forecasting problems of varying dimension.Finally,the advantages and disadvantages of the three scoring rules are highlighted,and this provides a significant step towards deciding on an evaluation method for a given multivariate forecast scenario including forecast scenarios relevant for energy systems.展开更多
The reliability plays a significant role in power systems and it is an important objective or constraint in transmission expansion planning.Firstly,a DC optimization model was proposed to calculate the maximum arrival...The reliability plays a significant role in power systems and it is an important objective or constraint in transmission expansion planning.Firstly,a DC optimization model was proposed to calculate the maximum arrival power at each load point.Compared to the network flow method,DC model is closer to the actual power flow and it is able to obtain more realistic reliability assessment results.Furthermore,a novel sensitivity index(SI)was also proposed to choose the most effective line so as to enhance the nodal and/or system reliability.The Monte Carlo simulation is used to simulate the system components state.This improved reliability evaluation method and SI can be used for transmission expansion planning or maintenance scheduling.Tests are performed using 6-bus system derived from the Garver’s system and the IEEE 10-machine 39-bus system.The results show the effectiveness of the method.展开更多
文摘Probabilistic forecasting is becoming increasingly important for a wide range of applications,especially for en-ergy systems such as forecasting wind power production.A need for proper evaluation of probabilistic forecasts follows naturally with this,because evaluation is the key to improving the forecasts.Although plenty of excellent reviews and research papers on probabilistic forecast evaluation already exist,we find that there is a need for an introduction with some practical application.In particular,many forecast scenarios in energy systems are inher-ently multivariate,and while univariate evaluation methods are well understood and documented,only limited and scattered work has been done on their multivariate counterparts.This paper therefore contains a review of a selected set of probabilistic forecast evaluation methods,primarily scoring rules,as well as practical sections that explain how these methods can be calculated and estimated.In three case studies featuring simple autore-gressive models,stochastic differential equations and real wind power data,we implement,apply and discuss the logarithmic score,the continuous ranked probability score and the variogram score for forecasting problems of varying dimension.Finally,the advantages and disadvantages of the three scoring rules are highlighted,and this provides a significant step towards deciding on an evaluation method for a given multivariate forecast scenario including forecast scenarios relevant for energy systems.
基金This work is supported by China Scholarship Council,as well as Young Teacher Scientific Research Foundation of Sichuan University(No.2012SCU11003).
文摘The reliability plays a significant role in power systems and it is an important objective or constraint in transmission expansion planning.Firstly,a DC optimization model was proposed to calculate the maximum arrival power at each load point.Compared to the network flow method,DC model is closer to the actual power flow and it is able to obtain more realistic reliability assessment results.Furthermore,a novel sensitivity index(SI)was also proposed to choose the most effective line so as to enhance the nodal and/or system reliability.The Monte Carlo simulation is used to simulate the system components state.This improved reliability evaluation method and SI can be used for transmission expansion planning or maintenance scheduling.Tests are performed using 6-bus system derived from the Garver’s system and the IEEE 10-machine 39-bus system.The results show the effectiveness of the method.
