摘要:

AbstractA decision‐analytic approach is taken to the problem of assessing the economic value of imperfect weather forecasts. Emphasis is placed on measures of the quality of such information and on the relationship between quality and economic value. The fallowing/planting problem for a spring wheat farmer is examined in detail as a specific application. It is assumed that the farmer's goal is to maximize the total expected discounted return over an infinite horizon, which places this problem within the general framework of Markov decision processes. By means of stochastic dynamic programming, the economic value to the farmer of currently available seasonal precipitation forecasts, as well as of hypothetical improvements in the quality of such forecasts, is estimated. Because the relationship between the quality and value of forecasts is highly nonlinear, the need to explicitly determine value‐of‐information estimates, rather than relying on quality as a surrogate for value, is made

ISSN:0277-6693    

DOI:10.1002/for.3980060202

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY

ISSN:0277-6693    

DOI:10.1002/for.3980060203

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY

ISSN:0277-6693    

DOI:10.1002/for.3980060204

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY

摘要:

AbstractThe potential use of state‐space modelling is evaluated through comparison with the existing multivariate ARMA models currently in use at Georgia Power Company for forecasting its residential sales, commercial sales and peak deman

ISSN:0277-6693    

DOI:10.1002/for.3980060205

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY

摘要:

AbstractAn important component of the New England Electric System Companies' (the 'System') total electricity sales is attributable to commercial customers. Commercial growth has recently been strong; moreover the System's peak demand is highly sensitive to commercial load. In a typical month this class represents 33 per cent of total System sales. Accurate short‐run forecasts of total kWh sales are important for rate making, budgeting, fuel cause proceedings, and corporate planning. In this study we use a variety of econometric and time‐series techniques to produce short‐run forecasts of commercial sales for two geographical areas served by two separate retail compa

ISSN:0277-6693    

DOI:10.1002/for.3980060206

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY

摘要:

AbstractThis paper presents the results of the Electric Power Research Institute Short Range Forecasting Project (EPRI‐SRF) performed by the Load Forecasts Department, Economics and Forecasts Division of Ontario Hydro, Ontario, Canada.In this study a variety of short‐range forecasting techniques are applied to Ontario Hydro monthly data on total system energy demand. These techniques are available in a software package (FORECAST MASTER) developed for EPRI by two consultants—Scientific Systems, Inc. (SSI) and Quantitativ Economic Research, Inc. (QUERI).The methods used for this study were the univariate Box‐Jenkins method, the multivariate state‐space method, Bayesian vector autoregression and autoregress ve econometric regression.A comparison of the models developed show that the econometric models perform the best overall. The state‐space models are more suitable for very short‐term (one‐step ahead) forecasts. Although the Box‐Jenkins method has the advantage of simplicity in terms of estimation and data requirement, its performance was not as good as that of the others. Bayesian vector autoregresson results indicate that this program needs some modification

ISSN:0277-6693    

DOI:10.1002/for.3980060207

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY

ISSN:0277-6693    

DOI:10.1002/for.3980060208

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY

ISSN:0277-6693    

DOI:10.1002/for.3980060201

出版商:John Wiley&Sons, Ltd.    

年代:1987

数据来源: WILEY