Forecast error

In statistics, a forecast error is the difference between the actual or real and the predicted or forecast value of a time series or any other phenomenon of interest. Since the forecast error is derived from the same scale of data, comparisons between the forecast errors of different series can only be made when the series are on the same scale. In simple cases, a forecast is compared with an outcome at a single time-point and a summary of forecast errors is constructed over a collection of such time-points. Here the forecast may be assessed using the difference or using a proportional error. By convention, the error is defined using the value of the outcome minus the value of the forecast. In other cases, a forecast may consist of predicted values over a number of lead-times; in this case an assessment of forecast error may need to consider more general ways of assessing the match between the time-profiles of the forecast and the outcome. If a main application of the forecast is t

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On the use of inexact, pruned hardware in atmospheric modelling

Giovanni De Micheli, Jaime Joven Murillo, Avinash Lingamneni

Inexact hardware design, which advocates trading the accuracy of computations in exchange for significant savings in area, power and/or performance of computing hardware, has received increasing prominence in several error-tolerant application domains, particularly those involving perceptual or statistical end-users. In this paper, we evaluate inexact hardware for its applicability in weather and climate modelling. We expand previous studies on inexact techniques, in particular probabilistic pruning, to floating point arithmetic units and derive several simulated setups of pruned hardware with reasonable levels of error for applications in atmospheric modelling. The setup is tested on the Lorenz ‘96 model, a toy model for atmospheric dynamics, using software emulation for the proposed hardware. The results show that large parts of the computation tolerate the use of pruned hardware blocks without major changes in the quality of short- and long-time diagnostics, such as forecast errors and probability density functions. This could open the door to significant savings in computational cost and to higher resolution simulations with weather and climate models.

Royal Soc2014

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Characterizing the Reserve Provision Capability Area of Active Distribution Networks: A Linear Robust Optimization Method

Mokhtar Bozorg, Mohsen Kalantar Neyestanaki, Fabrizio Sossan

Distributed energy resources (DERs) installed in active distribution networks (ADNs) can be exploited to provide both active and reactive power reserves to the upper-layer grid (i.e., sub-transmission and transmission systems) at their connection point. This paper introduces a method to determine the capability area of an ADN for the provision of both active and reactive power reserves while considering the forecast errors of loads and stochastic generation, as well as the operational constraints of the grid and DERs. The method leverages a linearized load flow model and introduces a set of linear scenario-based robust optimization problems to estimate the reserve provision capability (RPC) area of the ADN. It is proved that, under certain assumptions, the RPC area is convex. The performance of the proposed method is tested on a modified version of the IEEE 33-bus distribution test system.

2021

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Allocation of Frequency Control Reserve from Aggregated Resources of Active Distribution Systems

Mokhtar Bozorg, Mohsen Kalantar Neyestanaki, Fabrizio Sossan

This paper addresses the allocation of frequency control services (FCSs) from aggregated resources of active distribution systems (ARADSs) for balancing the transmission system while considering credible contingencies as well as forecast error of loads and generations through scenarios. First the paper introduces a generic framework for modeling ARADS including distributed energy resources (DERs) as seen from the transmission system operator (TSO) perspective. Afterwards, based on the proposed modeling framework and relying on a DC power flow model, the problem is formulated as a linear optimization problem consisting in minimizing the cost of FCSs provision and deployment from all possible providers including ARADSs and GENCOs. Nodal and total Expected Load Not Served (ELNS) indices are used to measure the security of the transmission system for the different scenarios. Finally, a proof of-concept of the proposed planning strategy is proposed by considering the IEEE 24-bus system.

IEEE2018

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